Sample records for brazil droughts modeling

  1. On the dynamics of droughts in northeast Brazil - Observations, theory and numerical experiments with a general circulation model

    Moura, A. D.; Shukla, J.


    The establishment of a thermally direct local circulation which has its ascending branch at about 10 deg N and its descending branch over northeast Brazil and the adjoining oceanic region is proposed as a possible mechanism for the occurrence of severe droughts over this Brazilian region. The driving for this anomalous circulation is provided by enhanced moist convection due to the effect of warmer sea surface anomalies over the northern tropical Atlantic and cooling associated with colder sea surface temperature anomalies in the southern tropical Atlantic. A simple primitive equation model is used to calculate the frictionally-controlled and thermally-driven circulation due to a prescribed heating function in a resting atmosphere, and a series of numerical experiments are carried out to test the sensitivity of the Goddard Laboratory's model to prescribed sea surface temperature anomalies over the tropical Atlantic.

  2. The influence of oceanic basins on drought and ecosystem dynamics in Northeast Brazil

    Pereira, Marcos Paulo Santos; Justino, Flavio; Malhado, Ana Claudia Mendes; Barbosa, Humberto; Marengo, José


    The 2012 drought in Northeast Brazil was the harshest in decades, with potentially significant impacts on the vegetation of the unique semi-arid caatinga biome and on local livelihoods. Here, we use a coupled climate–vegetation model (CCM3-IBIS) to: (1) investigate the role of the Pacific and Atlantic oceans in the 2012 drought, and; (2) evaluate the response of the caatinga vegetation to the 2012 climate extreme. Our results indicate that anomalous sea surface temperatures (SSTs) in the Atlantic Ocean were the primary factor forcing the 2012 drought, with Pacific Ocean SST having a larger role in sustaining typical climatic conditions in the region. The drought strongly influenced net primary production in the caatinga, causing a reduction in annual net ecosystem exchange indicating a reduction in amount of CO 2 released to the atmosphere. (letter)

  3. Managing the Health Impacts of Drought in Brazil

    Sena, Aderita; Barcellos, Christovam; Freitas, Carlos; Corvalan, Carlos


    Drought is often a hidden risk with the potential to become a silent public health disaster. It is difficult to define precisely when it starts or when it is over, and although it is a climatological event, its impacts depend on other human activities, and are intensified by social vulnerability. In Brazil, half of all natural disaster events are drought related, and they cause half of the impacts in number of affected persons. One large affected area is the semiarid region of Brazil’s Northeast, which has historically been affected by drought. Many health and well-being indicators in this region are worse than the rest of the country, based on an analysis of 5565 municipalities using available census data for 1991, 2000 and 2010, which allowed separating the 1133 municipalities affected by drought in order to compare them with the rest of the country. Although great progress has been made in reducing social and economic vulnerability, climate change and the expected changes in the semiarid region in the next few decades call for a review of current programs, particularly in public health, and the planning of new interventions with local communities. This study reviews the literature, analyzes available data and identifies possible actions and actors. The aim is to ensure there will be sufficient and sustainable local adaptive capacity and resilience, for a population already living within the limits of environmental vulnerability. PMID:25325358

  4. Managing the Health Impacts of Drought in Brazil

    Aderita Sena


    Full Text Available Drought is often a hidden risk with the potential to become a silent public health disaster. It is difficult to define precisely when it starts or when it is over, and although it is a climatological event, its impacts depend on other human activities, and are intensified by social vulnerability. In Brazil, half of all natural disaster events are drought related, and they cause half of the impacts in number of affected persons. One large affected area is the semiarid region of Brazil’s Northeast, which has historically been affected by drought. Many health and well-being indicators in this region are worse than the rest of the country, based on an analysis of 5565 municipalities using available census data for 1991, 2000 and 2010, which allowed separating the 1133 municipalities affected by drought in order to compare them with the rest of the country. Although great progress has been made in reducing social and economic vulnerability, climate change and the expected changes in the semiarid region in the next few decades call for a review of current programs, particularly in public health, and the planning of new interventions with local communities. This study reviews the literature, analyzes available data and identifies possible actions and actors. The aim is to ensure there will be sufficient and sustainable local adaptive capacity and resilience, for a population already living within the limits of environmental vulnerability.

  5. Water: Drought, Crisis and Governance in Australia and Brazil

    Wilson Sousa Júnior


    Full Text Available Despite huge differences in population, household income and development levels, Australia and Brazil have some temporal convergences in their water governance systems. Over the last 20 years, both countries have significantly reformed their water policies and practices by introducing a legal foundation for more integrated and participatory catchment/basin management based on the best information available. A critical test of any water reform is how effective it is in meeting the challenges of extreme and unpredictable conditions of drought and floods, which are expected to increase under climate changes scenarios. This paper compared the contemporary water governance frameworks of Australia and Brazil in relation to three elements of Integrated Water Resources Management (IWRM: integration, participation, and information/knowledge. We focused on insights from Brazil’s recent drought and Australia’s fluctuating water crises to derive lessons and recommendations for future changes. Among the main recommendations, we stress the need for both systems to improve effective participation and to embrace a more comprehensive approach to cope with water scarcity in future scenarios. Furthermore, water related decisions should be based on a transparent and well informed process, and take into account the lessons from similar situations worldwide in order to avoid unnecessary or ineffective measures. As demonstrated in the Australian case during the Millennium Drought, the most effective initiatives were those involving government, the private sector and society to achieve a more sustainable consumption pattern in all sectors. There is much to learn from the Brazilian and Australia experiences in water reforms and crises, but it is imperative to understand the social, economic and environmental context within which these took place. Continuing to develop the capacity and willingness of researchers and policy makers to work together can make an

  6. Circulation and teleconnection mechanisms of Northeast Brazil droughts

    Hastenrath, Stefan


    The Northern Nordeste of Brazil has its short rainy season narrowly concentrated around March-April, when the interhemispheric southward gradient of sea surface temperature (SST) is weakest and the Intertropical Convergence Zone (ITCZ), which is the main rainbearing system for the Nordeste, reaches its southernmost position in the course of the year. The recurrent Secas (droughts) have a severe socio-economic impact in this semi-arid region. In drought years, the pre-season (October-January) rainfall is scarce, the interhemispheric SST gradient weakened and the basin-wide southerly (northerly) wind component enhanced (reduced), all manifestations of an anomalously far northward ITCZ position. Apart from this ensemble of Atlantic indicators, the Secas also tend to be preceded by anomalously warm equatorial Pacific waters in January. During El Niño years, an upper-tropospheric wave train extends from the equatorial eastern Pacific to the northern tropical Atlantic, affecting the patterns of upper-tropospheric topography and divergence, and hence of vertical motion over the Atlantic. The altered vertical motion leads to a weaker meridional pressure gradient on the equatorward flank of the North Atlantic subtropical high, and thus weaker North Atlantic tradewinds. The concomitant reduction of evaporation and wind stirring allows for warmer surface waters in the tropical North Atlantic and thus steeper interhemispheric meridional thermal gradient. Consequently, the ITCZ stays anomalously far North and the Nordeste rainy season becomes deficient.

  7. Drought Persistence Errors in Global Climate Models

    Moon, H.; Gudmundsson, L.; Seneviratne, S. I.


    The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.

  8. Drought Duration Biases in Current Global Climate Models

    Moon, Heewon; Gudmundsson, Lukas; Seneviratne, Sonia


    Several droughts in the recent past are characterized by their increased duration and intensity. In particular, substantially prolonged droughts have brought major societal and economic losses in certain regions, yet climate change projections of such droughts in terms of duration is subject to large uncertainties. This study analyzes the biases of drought duration in state-of-the-art global climate model (GCM) simulations from the 5th phase of Coupled Model Intercomparison Project (CMIP5). Drought durations are defined as negative precipitation anomalies and evaluated with three observation-based datasets in the period of 1901-2010. Large spread in biases of GCMs is commonly found in all regions, with particular strong biases in North East Brazil, Africa, Northern Australia, Central America, Central and Northern Europe, Sahel and Asia. Also in most regions, the interquartile range of bias lies below 0, meaning that the GCMs tend to underestimate drought durations. Meanwhile in some regions such as Western South America, the Amazon, Sahel, West and South Africa, and Asia, considerable inconsistency among the three observation-based datasets were found. These results indicate substantial uncertainties and errors in current GCMs for simulating drought durations as well as a large spread in observation-based datasets, both of which are found to be particularly strong in those regions that are often considered to be hot spots of projected future drying. The underlying sources of these uncertainties need to be identified in further study and will be applied to constrain GCM-based drought projections under climate change.

  9. Spatiotemporal drought forecasting using nonlinear models

    Vasiliades, Lampros; Loukas, Athanasios


    Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

  10. Accounting for dynamics of mean precipitation in drought projections: A case study of Brazil for the 2050 and 2070 periods.

    Mpelasoka, Freddie; Awange, Joseph L; Goncalves, Rodrigo Mikosz


    Changes in drought around the globe are among the most daunting potential effects of climate change. However, changes in droughts are often not well distinguished from changes in aridity levels. As drought constitutes conditions of aridity, the projected declines in mean precipitation tend to override changes in drought. This results in projections of more dire changes in drought than ever. The overestimate of changes can be attributed to the use of 'static' normal precipitation in the derivation of drought events. The failure in distinguishing drought from aridity is a conceptual problem of concern, particularly to drought policymakers. Given that the key objective of drought policies is to determine drought conditions, which are rare and so protracted that they are beyond the scope of normal risk management, for interventions. The main objective of this Case Study of Brazil is to demonstrate the differences between projections of changes in drought based on 'static' and '30-year dynamic' precipitation normal conditions. First we demonstrate that the 'static' based projections suggest 4-fold changes in the probability of drought-year occurrences against changes by the dynamic normal precipitation. The 'static-normal mean precipitation' based projections tend to be monotonically increasing in magnitude, and were arguably considered unrealistic. Based on the '30-year dynamic' normal precipitation conditions, the 13-member GCM ensemble median projection estimates of changes for 2050 under rcp4.5 1 and rcp8.5 2 suggest: (i) Significant differences between changes associated with rcp4.5 and rcp8.5, and are more noticeable for droughts at long than short timescales in the 2070; (ii) Overall, the results demonstrate more realistic projections of changes in drought characteristics over Brazil than previous projections based on 'static' normal precipitation conditions. However, the uncertainty of response of droughts to climate change in CMIP5 simulations is still large

  11. Flood model for Brazil

    Palán, Ladislav; Punčochář, Petr


    Looking on the impact of flooding from the World-wide perspective, in last 50 years flooding has caused over 460,000 fatalities and caused serious material damage. Combining economic loss from ten costliest flood events (from the same period) returns a loss (in the present value) exceeding 300bn USD. Locally, in Brazil, flood is the most damaging natural peril with alarming increase of events frequencies as 5 out of the 10 biggest flood losses ever recorded have occurred after 2009. The amount of economic and insured losses particularly caused by various flood types was the key driver of the local probabilistic flood model development. Considering the area of Brazil (being 5th biggest country in the World) and the scattered distribution of insured exposure, a domain covered by the model was limited to the entire state of Sao Paolo and 53 additional regions. The model quantifies losses on approx. 90 % of exposure (for regular property lines) of key insurers. Based on detailed exposure analysis, Impact Forecasting has developed this tool using long term local hydrological data series (Agencia Nacional de Aguas) from riverine gauge stations and digital elevation model (Instituto Brasileiro de Geografia e Estatística). To provide most accurate representation of local hydrological behaviour needed for the nature of probabilistic simulation, a hydrological data processing focused on frequency analyses of seasonal peak flows - done by fitting appropriate extreme value statistical distribution and stochastic event set generation consisting of synthetically derived flood events respecting realistic spatial and frequency patterns visible in entire period of hydrological observation. Data were tested for homogeneity, consistency and for any significant breakpoint occurrence in time series so the entire observation or only its subparts were used for further analysis. The realistic spatial patterns of stochastic events are reproduced through the innovative use of d-vine copula

  12. Drought

    Quevauviller, P.; Lanen, Van Henny A.J.


    Drought is one of the most extreme weather-related natural hazards. It differs from other hydrometeorological extremes in several ways. It develops gradually and usually over large areas (transnational), mostly resulting from a prolonged period (from months to years) of below-normal

  13. Characterizing Drought Events from a Hydrological Model Ensemble

    Smith, Katie; Parry, Simon; Prudhomme, Christel; Hannaford, Jamie; Tanguy, Maliko; Barker, Lucy; Svensson, Cecilia


    Hydrological droughts are a slow onset natural hazard that can affect large areas. Within the United Kingdom there have been eight major drought events over the last 50 years, with several events acting at the continental scale, and covering the entire nation. Many of these events have lasted several years and had significant impacts on agriculture, the environment and the economy. Generally in the UK, due to a northwest-southeast gradient in rainfall and relief, as well as varying underlying geology, droughts tend to be most severe in the southeast, which can threaten water supplies to the capital in London. With the impacts of climate change likely to increase the severity and duration of drought events worldwide, it is crucial that we gain an understanding of the characteristics of some of the longer and more extreme droughts of the 19th and 20th centuries, so we may utilize this information in planning for the future. Hydrological models are essential both for reconstructing such events that predate streamflow records, and for use in drought forecasting. However, whilst the uncertainties involved in modelling hydrological extremes on the flooding end of the flow regime have been studied in depth over the past few decades, the uncertainties in simulating droughts and low flow events have not yet received such rigorous academic attention. The "Cascade of Uncertainty" approach has been applied to explore uncertainty and coherence across simulations of notable drought events from the past 50 years using the airGR family of daily lumped catchment models. Parameter uncertainty has been addressed using a Latin Hypercube sampled experiment of 500,000 parameter sets per model (GR4J, GR5J and GR6J), over more than 200 catchments across the UK. The best performing model parameterisations, determined using a multi-objective function approach, have then been taken forward for use in the assessment of the impact of model parameters and model structure on drought event

  14. Socioeconomic Drought in a Changing Climate: Modeling and Management

    AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid


    Drought is typically defined based on meteorological, hydrological and land surface conditions. However, in many parts of the world, anthropogenic changes and water management practices have significantly altered local water availability. Socioeconomic drought refers to conditions whereby the available water supply cannot satisfy the human and environmental water needs. Surface water reservoirs provide resilience against local climate variability (e.g., droughts), and play a major role in regional water management. This presentation focuses on a framework for describing socioeconomic drought based on both water supply and demand information. We present a multivariate approach as a measure of socioeconomic drought, termed Multivariate Standardized Reliability and Resilience Index (MSRRI; Mehran et al., 2015). This model links the information on inflow and surface reservoir storage to water demand. MSRRI integrates a "top-down" and a "bottom-up" approach for describing socioeconomic drought. The "top-down" component describes processes that cannot be simply controlled or altered by local decision-makers and managers (e.g., precipitation, climate variability, climate change), whereas the "bottom-up" component focuses on the local resilience, and societal capacity to respond to droughts. The two components (termed, Inflow-Demand Reliability (IDR) indicator and Water Storage Resilience (WSR) indicator) are integrated using a nonparametric multivariate approach. We use this framework to assess the socioeconomic drought during the Australian Millennium Drought (1998-2010) and the 2011-2014 California Droughts. MSRRI provides additional information on socioeconomic drought onset, development and termination based on local resilience and human demand that cannot be obtained from the commonly used drought indicators. We show that MSRRI can be used for water management scenario analysis (e.g., local water availability based on different human water demands scenarios). Finally

  15. Modelling crop yield in Iberia under drought conditions

    Ribeiro, Andreia; Páscoa, Patrícia; Russo, Ana; Gouveia, Célia


    The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining

  16. A hybrid spatiotemporal drought forecasting model for operational use

    Vasiliades, L.; Loukas, A.


    Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

  17. Using SIMGRO for drought analysis – as demonstrated for the Taquari Basin, Brazil

    Querner, E.P.; Lanen, van H.A.J.


    Tools were developed and tested to quantify space–time development of droughts at the river basin scale. The spatial development of a hydrological drought in river basins brings different challenges to describe drought characteristics, such as: area in a drought and areal expressions for onset,

  18. Comparative metabolomics of drought acclimation in model and forage legumes.

    Sanchez, Diego H; Schwabe, Franziska; Erban, Alexander; Udvardi, Michael K; Kopka, Joachim


    Water limitation has become a major concern for agriculture. Such constraints reinforce the urgent need to understand mechanisms by which plants cope with water deprivation. We used a non-targeted metabolomic approach to explore plastic systems responses to non-lethal drought in model and forage legume species of the Lotus genus. In the model legume Lotus. japonicus, increased water stress caused gradual increases of most of the soluble small molecules profiled, reflecting a global and progressive reprogramming of metabolic pathways. The comparative metabolomic approach between Lotus species revealed conserved and unique metabolic responses to drought stress. Importantly, only few drought-responsive metabolites were conserved among all species. Thus we highlight a potential impediment to translational approaches that aim to engineer traits linked to the accumulation of compatible solutes. Finally, a broad comparison of the metabolic changes elicited by drought and salt acclimation revealed partial conservation of these metabolic stress responses within each of the Lotus species, but only few salt- and drought-responsive metabolites were shared between all. The implications of these results are discussed with regard to the current insights into legume water stress physiology. © 2011 Blackwell Publishing Ltd.

  19. Drought Patterns Forecasting using an Auto-Regressive Logistic Model

    del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.


    Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

  20. Drought propagation in the Paraná Basin, Brazil: from rainfall deficits to impacts on reservoir storage

    Melo, D. D.; Wendland, E.


    The sensibility and resilience of hydrologic systems to climate changes are crucial for estimating potential impacts of droughts, responsible for major economic and human losses globally. Understanding how droughts propagate is a key element to develop a predictive understanding for future management and mitigation strategies. In this context, this study investigated the drought propagation in the Paraná Basin (PB), Southeast Brazil, a major hydroelectricity producing region with 32 % (60 million people) of the country's population. Reservoir storage (RESS), river discharge (Q) and rainfall (P) data were used to assess the linkages between meteorological and hydrological droughts, characterized by the Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI), respectively. The data are from 37 sub-basins within the PB, consisting of contributing areas of 37 reservoirs (250 km3 of stored water) within the PB for the period between 1995 and 2015. The response time (RT) of the hydrologic system to droughts, given as the time lag between P, Q and RESS, was quantified using a non-parametric statistical method that combines cumulative sums and Bootstrap resampling technique. Based on our results, the RTs of the hydrologic system of the PB varies from 0 to 6 months, depending on a number of aspects: lithology, topography, dam operation, etc. Linkages between SPI and SDI indicated that the anthropogenic control (dam operation) plays an important role in buffering drought impacts to downstream sub-basins: SDI decreased from upstream to downstream despite similar SPI values over the whole area. Comparisons between sub-basins, with variable drainage sizes (5,000 - 50,000 km2), confirmed the benefice of upstream reservoirs in reducing hydrological droughts. For example, the RT for a 4,800 km2 basin was 6 months between P and Q and 9 months between Q and RESS, under anthropogenic control. Conversely, the RT to precipitation for a reservoir subjected to natural

  1. The North American Drought Atlas: Tree-Ring Reconstructions of Drought Variability for Climate Modeling and Assessment

    Cook, E. R.


    The North American Drought Atlas describes a detailed reconstruction of drought variability from tree rings over most of North America for the past 500-1000 years. The first version of it, produced over three years ago, was based on a network of 835 tree-ring chronologies and a 286-point grid of instrumental Palmer Drought Severity Indices (PDSI). These gridded PDSI reconstructions have been used in numerous published studies now that range from modeling fire in the American West, to the impact of drought on palaeo-Indian societies, and to the determination of the primary causes of drought over North America through climate modeling experiments. Some examples of these applications will be described to illustrate the scientific value of these large-scale reconstructions of drought. Since the development and free public release of Version 1 of the North American Drought Atlas (see, great improvements have been made in the critical tree-ring network used to reconstruct PDSI at each grid point. This network has now been enlarged to 1743 annual tree-ring chronologies, which greatly improves the density of tree-ring records in certain parts of the grid, especially in Canada and Mexico. In addition, the number of tree-ring records that extend back before AD 1400 has been substantially increased. These developments justify the creation of Version 2 of the North American Drought Atlas. In this talk I will describe this new version of the drought atlas and some of its properties that make it a significant improvement over the previous version. The new product provides enhanced resolution of the spatial and temporal variability of prolonged drought such as the late 16th century event that impacted regions of both Mexico and the United States. I will also argue for the North American Drought Atlas being used as a template for the development of large-scale drought reconstructions in other land areas of

  2. Nonparametric Integrated Agrometeorological Drought Monitoring: Model Development and Application

    Zhang, Qiang; Li, Qin; Singh, Vijay P.; Shi, Peijun; Huang, Qingzhong; Sun, Peng


    Drought is a major natural hazard that has massive impacts on the society. How to monitor drought is critical for its mitigation and early warning. This study proposed a modified version of the multivariate standardized drought index (MSDI) based on precipitation, evapotranspiration, and soil moisture, i.e., modified multivariate standardized drought index (MMSDI). This study also used nonparametric joint probability distribution analysis. Comparisons were done between standardized precipitation evapotranspiration index (SPEI), standardized soil moisture index (SSMI), MSDI, and MMSDI, and real-world observed drought regimes. Results indicated that MMSDI detected droughts that SPEI and/or SSMI failed to do. Also, MMSDI detected almost all droughts that were identified by SPEI and SSMI. Further, droughts detected by MMSDI were similar to real-world observed droughts in terms of drought intensity and drought-affected area. When compared to MMSDI, MSDI has the potential to overestimate drought intensity and drought-affected area across China, which should be attributed to exclusion of the evapotranspiration components from estimation of drought intensity. Therefore, MMSDI is proposed for drought monitoring that can detect agrometeorological droughts. Results of this study provide a framework for integrated drought monitoring in other regions of the world and can help to develop drought mitigation.

  3. Modeling drought impact occurrence based on climatological drought indices for four European countries

    Stagge, James H.; Kohn, Irene; Tallaksen, Lena M.; Stahl, Kerstin


    The relationship between atmospheric conditions and the likelihood of a significant drought impact has, in the past, been difficult to quantify, particularly in Europe where political boundaries and language have made acquiring comprehensive drought impact information difficult. As such, the majority of studies linking meteorological drought with the occurrence or severity of drought impacts have previously focused on specific regions, very detailed impact types, or both. This study describes a new methodology to link the likelihood of drought impact occurrence with climatological drought indices across different European climatic regions and impact sectors using the newly developed European Drought Impact report Inventory (EDII), a collaborative database of drought impact information ( The Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) are used as predictor variables to quantify meteorological drought severity over prior time periods (here 1, 2, 3, 6, 9, 12, and 24 months are used). The indices are derived using the gridded WATCH Forcing Datasets, covering the period 1958-2012. Analysis was performed using logistic regression to identify the climatological drought index and accumulation period, or linear combination of drought indices, that best predicts the likelihood of a documented drought impact, defined by monthly presence/absence. The analysis was carried out for a subset of four European countries (Germany, UK, Norway, Slovenia) and four of the best documented impact sectors: Public Water Supply, Agriculture and Livestock Farming, Energy and Industry, and Environmental Quality. Preliminary results show that drought impacts in these countries occur most frequently due to a combination of short-term (2-6 month) precipitation deficits and long-term (12-24 month) potential evapotranspiration anomaly, likely associated with increased temperatures. Agricultural drought impacts

  4. Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

    A. F. Van Loon


    Full Text Available Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP. For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity, drought propagation features (pooling, attenuation, lag, lengthening, and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought.

    Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an

  5. Short-term droughts forecast using Markov chain model in Victoria, Australia

    Rahmat, Siti Nazahiyah; Jayasuriya, Niranjali; Bhuiyan, Muhammed A.


    A comprehensive risk management strategy for dealing with drought should include both short-term and long-term planning. The objective of this paper is to present an early warning method to forecast drought using the Standardised Precipitation Index (SPI) and a non-homogeneous Markov chain model. A model such as this is useful for short-term planning. The developed method has been used to forecast droughts at a number of meteorological monitoring stations that have been regionalised into six (6) homogenous clusters with similar drought characteristics based on SPI. The non-homogeneous Markov chain model was used to estimate drought probabilities and drought predictions up to 3 months ahead. The drought severity classes defined using the SPI were computed at a 12-month time scale. The drought probabilities and the predictions were computed for six clusters that depict similar drought characteristics in Victoria, Australia. Overall, the drought severity class predicted was quite similar for all the clusters, with the non-drought class probabilities ranging from 49 to 57 %. For all clusters, the near normal class had a probability of occurrence varying from 27 to 38 %. For the more moderate and severe classes, the probabilities ranged from 2 to 13 % and 3 to 1 %, respectively. The developed model predicted drought situations 1 month ahead reasonably well. However, 2 and 3 months ahead predictions should be used with caution until the models are developed further.

  6. Regional drought assessment using a distributed hydrological model coupled with Standardized Runoff Index

    H. Shen


    Full Text Available Drought assessment is essential for coping with frequent droughts nowadays. Owing to the large spatio-temporal variations in hydrometeorology in most regions in China, it is very necessary to use a physically-based hydrological model to produce rational spatial and temporal distributions of hydro-meteorological variables for drought assessment. In this study, the large-scale distributed hydrological model Variable Infiltration Capacity (VIC was coupled with a modified standardized runoff index (SRI for drought assessment in the Weihe River basin, northwest China. The result indicates that the coupled model is capable of reasonably reproducing the spatial distribution of drought occurrence. It reflected the spatial heterogeneity of regional drought and improved the physical mechanism of SRI. This model also has potential for drought forecasting, early warning and mitigation, given that accurate meteorological forcing data are available.

  7. A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

    Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian


    Reliable drought prediction is fundamental for water resource managers to develop and implement drought mitigation measures. Considering that drought development is closely related to the spatial-temporal evolution of large-scale circulation patterns, we developed a conceptual prediction model of seasonal drought processes based on atmospheric and oceanic standardized anomalies (SAs). Empirical orthogonal function (EOF) analysis is first applied to drought-related SAs at 200 and 500 hPa geopotential height (HGT) and sea surface temperature (SST). Subsequently, SA-based predictors are built based on the spatial pattern of the first EOF modes. This drought prediction model is essentially the synchronous statistical relationship between 90-day-accumulated atmospheric-oceanic SA-based predictors and SPI3 (3-month standardized precipitation index), calibrated using a simple stepwise regression method. Predictor computation is based on forecast atmospheric-oceanic products retrieved from the NCEP Climate Forecast System Version 2 (CFSv2), indicating the lead time of the model depends on that of CFSv2. The model can make seamless drought predictions for operational use after a year-to-year calibration. Model application to four recent severe regional drought processes in China indicates its good performance in predicting seasonal drought development, despite its weakness in predicting drought severity. Overall, the model can be a worthy reference for seasonal water resource management in China.

  8. Approaches to modeling landscape-scale drought-induced forest mortality

    Gustafson, Eric J.; Shinneman, Douglas


    Drought stress is an important cause of tree mortality in forests, and drought-induced disturbance events are projected to become more common in the future due to climate change. Landscape Disturbance and Succession Models (LDSM) are becoming widely used to project climate change impacts on forests, including potential interactions with natural and anthropogenic disturbances, and to explore the efficacy of alternative management actions to mitigate negative consequences of global changes on forests and ecosystem services. Recent studies incorporating drought-mortality effects into LDSMs have projected significant potential changes in forest composition and carbon storage, largely due to differential impacts of drought on tree species and interactions with other disturbance agents. In this chapter, we review how drought affects forest ecosystems and the different ways drought effects have been modeled (both spatially and aspatially) in the past. Building on those efforts, we describe several approaches to modeling drought effects in LDSMs, discuss advantages and shortcomings of each, and include two case studies for illustration. The first approach features the use of empirically derived relationships between measures of drought and the loss of tree biomass to drought-induced mortality. The second uses deterministic rules of species mortality for given drought events to project changes in species composition and forest distribution. A third approach is more mechanistic, simulating growth reductions and death caused by water stress. Because modeling of drought effects in LDSMs is still in its infancy, and because drought is expected to play an increasingly important role in forest health, further development of modeling drought-forest dynamics is urgently needed.

  9. Reconstruction of droughts in India using multiple land-surface models (1951-2015)

    Mishra, Vimal; Shah, Reepal; Azhar, Syed; Shah, Harsh; Modi, Parth; Kumar, Rohini


    India has witnessed some of the most severe historical droughts in the current decade, and severity, frequency, and areal extent of droughts have been increasing. As a large part of the population of India is dependent on agriculture, soil moisture drought affecting agricultural activities (crop yields) has significant impacts on socio-economic conditions. Due to limited observations, soil moisture is generally simulated using land-surface hydrological models (LSMs); however, these LSM outputs have uncertainty due to many factors, including errors in forcing data and model parameterization. Here we reconstruct agricultural drought events over India during the period of 1951-2015 based on simulated soil moisture from three LSMs, the Variable Infiltration Capacity (VIC), the Noah, and the Community Land Model (CLM). Based on simulations from the three LSMs, we find that major drought events occurred in 1987, 2002, and 2015 during the monsoon season (June through September). During the Rabi season (November through February), major soil moisture droughts occurred in 1966, 1973, 2001, and 2003. Soil moisture droughts estimated from the three LSMs are comparable in terms of their spatial coverage; however, differences are found in drought severity. Moreover, we find a higher uncertainty in simulated drought characteristics over a large part of India during the major crop-growing season (Rabi season, November to February: NDJF) compared to those of the monsoon season (June to September: JJAS). Furthermore, uncertainty in drought estimates is higher for severe and localized droughts. Higher uncertainty in the soil moisture droughts is largely due to the difference in model parameterizations (especially soil depth), resulting in different persistence of soil moisture simulated by the three LSMs. Our study highlights the importance of accounting for the LSMs' uncertainty and consideration of the multi-model ensemble system for the real-time monitoring and prediction of

  10. Multi-basin, Multi-sector Drought Economic Impact Model in Python: Development and Applications

    Gutenson, J. L.; Zhu, L.; Ernest, A. N. S.; Oubeidillah, A.; Bearden, B.; Johnson, T. G.


    Drought is one of the most economically disastrous natural hazards, one whose impacts are exacerbated by the lack of abrupt onset and offset that define tornados and hurricanes. In the United States, about 30 billion dollars losses is caused by drought in 2012, resulting in widespread economic impacts for societies, industries, agriculture, and recreation. And in California, the drought cost statewide economic losses about 2.2 billion, with a total loss of 17,100 seasonal and part-time jobs. Driven by a variety of factors including climate change, population growth, increased water demands, alteration to land cover, drought occurs widely all over the world. Drought economic consequence assessment tool are greatly needed to allow decision makers and stakeholders to anticipate and manage effectively. In this study, current drought economic impact modeling methods were reviewed. Most of these models only deal with the impact in the agricultural sector with a focus on a single basin; few of these models analyze long term impact. However, drought impacts are rarely restricted to basin boundaries, and cascading economic impacts are likely to be significant. A holistic approach to multi-basin, multi-sector drought economic impact assessment is needed.In this work, we developed a new model for drought economic impact assessment, Drought Economic Impact Model in Python (PyDEM). This model classified all business establishments into thirteen categories based on NAICS, and using a continuous dynamic social accounting matrix approach, coupled with calculation of the indirect consequences for the local and regional economies and the various resilience. In addition, Environmental Policy Integrated Climate model was combined for analyzing drought caused soil erosion together with agriculture production, and then the long term impacts of drought were achieved. A visible output of this model was presented in GIS. In this presentation, Choctawhatchee-Pea-Yellow River Basins, Alabama

  11. Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

    Loon, van A.F.; Huijgevoort, van M.H.J.; Lanen, van H.A.J.


    Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological

  12. Drought-associated changes in climate and their relevance for ecosystem experiments and models

    H. J. De Boeck


    Full Text Available Drought periods can have important impacts on plant productivity and ecosystem functioning, but climatic conditions other than the lack of precipitation during droughts have never been quantified and have therefore not been considered explicitly in both experimental and modeling studies. Here, we identify which climatic characteristics deviate from normal during droughts and how these deviations could affect plant responses. Analysis of 609 years of daily data from nine Western European meteorological stations reveals that droughts in the studied region are consistently associated with more sunshine (+45 %, increased mean (+1.6 °C and maximum (+2.8 °C air temperatures and vapour pressure deficits that were 51 % higher than under normal conditions. These deviations from normal increase significantly as droughts progress. Using the process-model ORCHIDEE, we simulated droughts consistent with the results of the dataset analysis and compared water and carbon exchange of three different vegetation types during such natural droughts and droughts in which only the precipitation was affected. The comparison revealed contrasting responses: carbon loss was higher under natural drought in grasslands, while increased carbon uptake was found especially in decidious forests. This difference was attributed to better access to water reserves in forest ecosystems which prevented drought stress. This demonstrates that the warmer and sunnier conditions naturally associated with droughts can either improve growth or aggravate drought-related stress, depending on water reserves. As the impacts of including or excluding climatic parameters that correlate with drought are substantial, we propose that both experimental and modeling efforts should take into account other environmental factors than merely precipitation.

  13. A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies and its application to four recent severe regional drought events in China

    Liu, Z.; LU, G.; He, H.; Wu, Z.; He, J.


    Reliable drought prediction is fundamental for seasonal water management. Considering that drought development is closely related to the spatio-temporal evolution of large-scale circulation patterns, we develop a conceptual prediction model of seasonal drought processes based on atmospheric/oceanic Standardized Anomalies (SA). It is essentially the synchronous stepwise regression relationship between 90-day-accumulated atmospheric/oceanic SA-based predictors and 3-month SPI updated daily (SPI3). It is forced with forecasted atmospheric and oceanic variables retrieved from seasonal climate forecast systems, and it can make seamless drought prediction for operational use after a year-to-year calibration. Simulation and prediction of four severe seasonal regional drought processes in China were forced with the NCEP/NCAR reanalysis datasets and the NCEP Climate Forecast System Version 2 (CFSv2) operationally forecasted datasets, respectively. With the help of real-time correction for operational application, model application during four recent severe regional drought events in China revealed that the model is good at development prediction but weak in severity prediction. In addition to weakness in prediction of drought peak, the prediction of drought relief is possible to be predicted as drought recession. This weak performance may be associated with precipitation-causing weather patterns during drought relief. Based on initial virtual analysis on predicted 90-day prospective SPI3 curves, it shows that the 2009/2010 drought in Southwest China and 2014 drought in North China can be predicted and simulated well even for the prospective 1-75 day. In comparison, the prospective 1-45 day may be a feasible and acceptable lead time for simulation and prediction of the 2011 droughts in Southwest China and East China, after which the simulated and predicted developments clearly change.

  14. A geospatial suitability model for drought-tolerant switchgrass

    Lewis, S. M.; Kelly, M.


    A perennial grass native to the North America, switchgrass (Panicum virgatum) has been targeted by the USDA as a model mass bioenergy crop to replace petroleum energy products and meet policy demands. Although highly water use efficient, as a warm-season crop, switchgrass requires a significant amount of water during the growing season (April -September). However, locations that have highly reliable water availability are also ideal for profitable food crops (e.g. corn and soy growing regions) and food competition is a significant concern in regards to biofuel crops being grown on productive agricultural lands. Drier, marginal lands (lands on which normal agricultural crops are difficult to cultivate) are therefore potentially ideal locations to grow biofuel crops to ensure that food competition is not an issue. Genetics scientists at UC Davis are in the process of developing a modified variety of switchgrass that can withstand extended periods of drought while not substantially affecting overall yield. As this product is being developed, it is important to identify the potential geographical niche for this new drought-tolerant variety of switchgrass. This project introduces a geospatial approach that utilizes both physical and economic variables to identify ideal geographic locations for this innovative crop.

  15. Risk, Innovation and Development in a Changing Climate: The Role of Drought Preparedness Policies and Disaster Risk Management in Ceara, Brazil.

    Carlos Germano Ferreira Costa


    Full Text Available Droughts are among the most common type of disasters, generating enormous socioeconomic impacts in the world, especially when considering the silent character they have. These phenomena are becoming more frequent, intense and longer lasting, which gives us an idea of ​​what may happen with the accentuation of climate change. This article seeks to provide and overview of the measures and policies addressing drought prevention and preparedness, facing the impacts of climate change, in the State of Ceará, Brazil. This study addresses issues of public policies concerning drought risk management in order to allow a greater understanding of policies and programs, experiences and perspectives by the analysis of the process of elaboration of the Integrated Disaster Risk Management Plan of the State of Ceara, Brazil (PIGRD-CE, as well as of the development of the Early Warning System - Drought Monitor -, while addressing the political coordination, which led to the creation of the Drought Commission (Comitê das Secas. As a result, we understand this strategy, concerning drought preparedness, as a tool able to increase the adaptability and resilience of the political process. In this regard, we present the experiences accumulated by the State of Ceara in drought management processes showing a promising potential for replicability in other Latin American countries also subjected to threats that the changing climate may impose, in combination with the analysis of related risks - political/institutional/cultural -, in the development of public policies to draw together the main conclusions, lessons learned and recommendations.

  16. Significance of Bias Correction in Drought Frequency and Scenario Analysis Based on Climate Models

    Aryal, Y.; Zhu, J.


    Assessment of future drought characteristics is difficult as climate models usually have bias in simulating precipitation frequency and intensity. To overcome this limitation, output from climate models need to be bias corrected based on the specific purpose of applications. In this study, we examine the significance of bias correction in the context of drought frequency and scenario analysis using output from climate models. In particular, we investigate the performance of three widely used bias correction techniques: (1) monthly bias correction (MBC), (2) nested bias correction (NBC), and (3) equidistance quantile mapping (EQM) The effect of bias correction in future scenario of drought frequency is also analyzed. The characteristics of drought are investigated in terms of frequency and severity in nine representative locations in different climatic regions across the United States using regional climate model (RCM) output from the North American Regional Climate Change Assessment Program (NARCCAP). The Standardized Precipitation Index (SPI) is used as the means to compare and forecast drought characteristics at different timescales. Systematic biases in the RCM precipitation output are corrected against the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data. The results demonstrate that bias correction significantly decreases the RCM errors in reproducing drought frequency derived from the NARR data. Preserving mean and standard deviation is essential for climate models in drought frequency analysis. RCM biases both have regional and timescale dependence. Different timescale of input precipitation in the bias corrections show similar results. Drought frequency obtained from the RCM future (2040-2070) scenarios is compared with that from the historical simulations. The changes in drought characteristics occur in all climatic regions. The relative changes in drought frequency in future scenario in relation to

  17. Analysis of future drought characteristics in China using the regional climate model CCLM

    Huang, Jinlong; Zhai, Jianqing; Jiang, Tong; Wang, Yanjun; Li, Xiucang; Wang, Run; Xiong, Ming; Su, Buda; Fischer, Thomas


    In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016-2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016-2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at

  18. Incorporation of GRACE Data into a Bayesian Model for Groundwater Drought Monitoring

    Slinski, K.; Hogue, T. S.; McCray, J. E.; Porter, A.


    Groundwater drought, defined as the sustained occurrence of below average availability of groundwater, is marked by below average water levels in aquifers and reduced flows to groundwater-fed rivers and wetlands. The impact of groundwater drought on ecosystems, agriculture, municipal water supply, and the energy sector is an increasingly important global issue. However, current drought monitors heavily rely on precipitation and vegetative stress indices to characterize the timing, duration, and severity of drought events. The paucity of in situ observations of aquifer levels is a substantial obstacle to the development of systems to monitor groundwater drought in drought-prone areas, particularly in developing countries. Observations from the NASA/German Space Agency's Gravity Recovery and Climate Experiment (GRACE) have been used to estimate changes in groundwater storage over areas with sparse point measurements. This study incorporates GRACE total water storage observations into a Bayesian framework to assess the performance of a probabilistic model for monitoring groundwater drought based on remote sensing data. Overall, it is hoped that these methods will improve global drought preparedness and risk reduction by providing information on groundwater drought necessary to manage its impacts on ecosystems, as well as on the agricultural, municipal, and energy sectors.

  19. Model based climate information on drought risk in Africa

    Calmanti, S.; Syroka, J.; Jones, C.; Carfagna, F.; Dell'Aquila, A.; Hoefsloot, P.; Kaffaf, S.; Nikulin, G.


    The United Nations World Food Programme (WFP) has embarked upon the endeavor of creating a sustainable Africa-wide natural disaster risk management system. A fundamental building block of this initiative is the setup of a drought impact modeling platform called Africa Risk-View that aims to quantify and monitor weather-related food security risk in Africa. The modeling approach is based the Water Requirement Satisfaction Index (WRSI), as the fundamental indicator of the performances of agriculture and uses historical records of food assistance operation to project future potential needs for livelihood protection. By using climate change scenarios as an input to Africa Risk-View it is possible, in principles, to evaluate the future impact of climate variability on critical issues such as food security and the overall performance of the envisaged risk management system. A necessary preliminary step to this challenging task is the exploration of the sources of uncertainties affecting the assessment based on modeled climate change scenarios. For this purpose, a limited set of climate models have been selected in order verify the relevance of using climate model output data with Africa Risk-View and to explore a minimal range of possible sources of uncertainty. This first evaluation exercise started before the setup of the CORDEX framework and has relied on model output available at the time. In particular only one regional downscaling was available for the entire African continent from the ENSEMBLES project. The analysis shows that current coarse resolution global climate models can not directly feed into the Africa RiskView risk-analysis tool. However, regional downscaling may help correcting the inherent biases observed in the datasets. Further analysis is performed by using the first data available under the CORDEX framework. In particular, we consider a set of simulation driven with boundary conditions from the reanalysis ERA-Interim to evaluate the skill drought

  20. Probabilistic modelling of drought events in China via 2-dimensional joint copula

    Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Javed, Tehseen; Yao, Ning


    Probabilistic modelling of drought events is a significant aspect of water resources management and planning. In this study, popularly applied and several relatively new bivariate Archimedean copulas were employed to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013. Drought duration (Dd), severity (Ds), and peak (Dp), as indicated by Standardized Precipitation Evapotranspiration Index (SPEI), were extracted according to the run theory and fitted with suitable marginal distributions. The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas. Drought probabilities and return periods were analysed based on appropriate bivariate copula in sub-region I-VII and entire mainland China. The goodness-of-fit tests as indicated by the CFM showed that copula NN19 in sub-regions III, IV, V, VI and mainland China, NN20 in sub-region I and NN13 in sub-region VII are the best for modeling drought variables. Bivariate drought probability across mainland China is relatively high, and the highest drought probabilities are found mainly in the Northwestern and Southwestern China. Besides, the result also showed that different sub-regions might suffer varying drought risks. The drought risks as observed in Sub-region III, VI and VII, are significantly greater than other sub-regions. Higher probability of droughts of longer durations in the sub-regions also corresponds to shorter return periods with greater drought severity. These results may imply tremendous challenges for the water resources management in different sub-regions, particularly the Northwestern and Southwestern China.

  1. Identification of drought in Dhalai river watershed using MCDM and ANN models

    Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy


    An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

  2. Non-linear effects of drought under shade: reconciling physiological and ecological models in plant communities.

    Holmgren, Milena; Gómez-Aparicio, Lorena; Quero, José Luis; Valladares, Fernando


    The combined effects of shade and drought on plant performance and the implications for species interactions are highly debated in plant ecology. Empirical evidence for positive and negative effects of shade on the performance of plants under dry conditions supports two contrasting theoretical models about the role of shade under dry conditions: the trade-off and the facilitation hypotheses. We performed a meta-analysis of field and greenhouse studies evaluating the effects of drought at two or more irradiance levels on nine response variables describing plant physiological condition, growth, and survival. We explored differences in plant response across plant functional types, ecosystem types and methodological approaches. The data were best fit using quadratic models indicating a humped-back shape response to drought along an irradiance gradient for survival, whole plant biomass, maximum photosynthetic capacity, stomatal conductance and maximal photochemical efficiency. Drought effects were ameliorated at intermediate irradiance, becoming more severe at higher or lower light levels. This general pattern was maintained when controlling for potential variations in the strength of the drought treatment among light levels. Our quantitative meta-analysis indicates that dense shade ameliorates drought especially among drought-intolerant and shade-tolerant species. Wet tropical species showed larger negative effects of drought with increasing irradiance than semiarid and cold temperate species. Non-linear responses to irradiance were stronger under field conditions than under controlled greenhouse conditions. Non-linear responses to drought along the irradiance gradient reconciliate opposing views in plant ecology, indicating that facilitation is more likely within certain range of environmental conditions, fading under deep shade, especially for drought-tolerant species.

  3. Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study

    Mishra, Ashok K.; Ines, Amor V. M.; Das, Narendra N.; Prakash Khedun, C.; Singh, Vijay P.; Sivakumar, Bellie; Hansen, James W.


    Drought is of global concern for society but it originates as a local problem. It has a significant impact on water quantity and quality and influences food, water, and energy security. The consequences of drought vary in space and time, from the local scale (e.g. county level) to regional scale (e.g. state or country level) to global scale. Within the regional scale, there are multiple socio-economic impacts (i.e., agriculture, drinking water supply, and stream health) occurring individually or in combination at local scales, either in clusters or scattered. Even though the application of aggregated drought information at the regional level has been useful in drought management, the latter can be further improved by evaluating the structure and evolution of a drought at the local scale. This study addresses a local-scale agricultural drought anatomy in Story County in Iowa, USA. This complex problem was evaluated using assimilated AMSR-E soil moisture and MODIS-LAI data into a crop model to generate surface and sub-surface drought indices to explore the anatomy of an agricultural drought. Quantification of moisture supply in the root zone remains a gray area in research community, this challenge can be partly overcome by incorporating assimilation of soil moisture and leaf area index into crop modeling framework for agricultural drought quantification, as it performs better in simulating crop yield. It was noted that the persistence of subsurface droughts is in general higher than surface droughts, which can potentially improve forecast accuracy. It was found that both surface and subsurface droughts have an impact on crop yields, albeit with different magnitudes, however, the total water available in the soil profile seemed to have a greater impact on the yield. Further, agricultural drought should not be treated equal for all crops, and it should be calculated based on the root zone depth rather than a fixed soil layer depth. We envisaged that the results of

  4. Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

    Wanders, N.; Van Lanen, H. A. J.


    Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study a conceptual hydrological model was forced by downscaled and bias-corrected outcome from three general circulation models for the SRES A2 emission scenario (GCM forced models), and the WATCH Forcing Data set (reference model). The threshold level method was applied to investigate drought occurrence, duration and severity. Results for the control period (1971-2000) show that the drought characteristics of each GCM forced model reasonably agree with the reference model for most of the climate types, suggesting that the climate models' results after post-processing produce realistic outcomes for global drought analyses. For the near future (2021-2050) and far future (2071-2100) the GCM forced models show a decrease in drought occurrence for all major climates around the world and increase of both average drought duration and deficit volume of the remaining drought events. The largest decrease in hydrological drought occurrence is expected in cold (D) climates where global warming results in a decreased length of the snow season and an increased precipitation. In the dry (B) climates the smallest decrease in drought occurrence is expected to occur, which probably will lead to even more severe water scarcity. However, in the extreme climate regions (desert and polar), the drought analysis for the control period showed that projections of hydrological drought characteristics are most uncertain. On a global scale the increase in hydrological drought duration and severity in multiple regions will lead to a higher impact of drought events, which should motivate water resource managers to timely anticipate the increased risk of more severe drought in groundwater and streamflow

  5. Impacts of climate change on drought: changes to drier conditions at the beginning of the crop growing season in southern Brazil

    Vânia Rosa Pereira


    Full Text Available ABSTRACT The intensification of drought incidence is one of the most important threats of the 21st century with significant effects on food security. Accordingly, there is a need to improve the understanding of the regional impacts of climate change on this hazard. This study assessed long-term trends in probability-based drought indices (Standardized Precipitation Index and Standardized Evapotranspiration Index in the State of São Paulo, Brazil. Owing to the multi-scalar nature of both indices, the analyses were performed at 1 to 12-month time scales. The indices were calculated by means of a relativist approach that allowed us to compare drought conditions from different periods. The years 1961-1990 were used as the referential period. To the authors’ best knowledge, this is the first time that such relativist approach is used in historical trend analysis. The results suggest that the evapotranspiration rates have intensified the regional drought conditions. The time scale used to calculate the indices significantly affected the outcomes of drought trend assessments. The reason behind this feature is that the significant changes in the monthly regional patterns are limited to a specific period of the year. More specifically, virtually all significant changes have been observed during the first trimester of the rainy season (October, November and December. Considering that this period corresponds to critical plant growth stages (flowering/regrowth/sprouting of several major crops (e.g. Sugarcane and Citrus, we may conclude that these significant changes have increased the risk of crop yield reductions due to agricultural drought.

  6. Dynamic Stackelberg game model for water rationalization in drought emergency

    Kicsiny, R.; Piscopo, V.; Scarelli, A.; Varga, Z.


    In water resource management, in case of a limited resource, there is a conflict situation between different consumers. In this paper, a dynamic game-theoretical model is suggested for the solution of such conflict. Let us suppose that in a region, water supply is based on a given aquifer, from which a quantity of effective reserve can be used without damaging the aquifer, and a long drought is foreseen. The use of water is divided between the social sector represented by the local authority, and the production sector, in our case, simplified to a single agricultural producer using water for irrigation; they are the players in the game. For a fixed time period, every day, a given amount is available, from which first the authority, then the producer takes a proportion, which corresponds to the strategy choices of the players. A price function is given, which depends on the total available reserve, the payoffs of both players are quantified as their net incomes for the whole period: for the producer: profit from selling the product minus price of water and tax paid, for the authority: tax received plus the gain for the authority from selling the water bought to the social sector minus price of water purchased. A solution (equilibrium) of the game consists of such strategy choices of both players, with which each player maximizes her/his total payoff (over the whole time horizon of the game) provided that the other player also maximizes her/his own payoff. In the paper, in a mathematical model for the above conflict situation, a deterministic continuum-strategy two-player discrete-time dynamic Stackelberg game with fixed finite time duration and closed-loop information structure is proposed, where the authority is “leader” and the producer is “follower”. The algorithms for the solution of the game are based on recent theoretical results of the authors. Illustrative numerical examples are also given.

  7. Drought Forecasting with Vegetation Temperature Condition Index Using ARIMA Models in the Guanzhong Plain

    Miao Tian


    Full Text Available This paper works on the agricultural drought forecasting in the Guanzhong Plain of China using Autoregressive Integrated Moving Average (ARIMA models based on the time series of drought monitoring results of Vegetation Temperature Condition Index (VTCI. About 90 VTCI images derived from Advanced Very High Resolution Radiometer (AVHRR data were selected to develop the ARIMA models from the erecting stage to the maturity stage of winter wheat (early March to late May in each year at a ten-day interval of the years from 2000 to 2009. We take the study area overlying on the administration map around the study area, and divide the study area into 17 parts where at least one weather station is located in each part. The pixels where the 17 weather stations are located are firstly chosen and studied for their fitting models, and then the best models for all pixels of the whole area are determined. According to the procedures for the models’ development, the selected best models for the 17 pixels are identified and the forecast is done with three steps. The forecasting results of the ARIMA models were compared with the monitoring ones. The results show that with reference to the categorized VTCI drought monitoring results, the categorized forecasting results of the ARIMA models are in good agreement with the monitoring ones. The categorized drought forecasting results of the ARIMA models are more severity in the northeast of the Plain in April 2009, which are in good agreements with the monitoring ones. The absolute errors of the AR(1 models are lower than the SARIMA models, both in the frequency distributions and in the statistic results. However, the ability of SARIMA models to detect the changes of the drought situation is better than the AR(1 models. These results indicate that the ARIMA models can better forecast the category and extent of droughts and can be applied to forecast droughts in the Plain.

  8. Combined statistical and spatially distributed hydrological model for evaluating future drought indices in Virginia

    Hyunwoo Kang


    New hydrological insights for the region: The results of the ensemble mean of SSI indicated that there was an overall increase in agricultural drought occurrences projected in the New (>1.3 times and Rappahannock (>1.13 times river basins due to increases in evapotranspiration and surface and groundwater flow. However, MSDI and MPDSI exhibited a decrease in projected future drought, despite increases in precipitation, which suggests that it is essential to use hybrid-modeling approaches and to interpret application-specific drought indices that consider both precipitation and temperature changes.

  9. Modeling the Effects of Drought Events on Forest Ecosystem Functioning Historically and Under Scenarios of Climate Change

    Ren, J.; Hanan, E. J.; Kolden, C.; Abatzoglou, J. T.; Tague, C.; Liu, M.; Adam, J. C.


    Drought events have been increasing across the western United States in recent years. Many studies have shown that, in the context of climate change, droughts will continue to be stronger, more frequent, and prolonged in the future. However, the response of forest ecosystems to droughts, particularly multi-year droughts, is not well understood. The objectives of this study are to examine how drought events of varying characteristics (e.g. intensity, duration, frequency, etc.) have affected the functioning of forest ecosystems historically, and how changing drought characteristics (including multi-year droughts) may affect forest functioning in a future climate. We utilize the Regional Hydro-Ecological Simulation System (RHESSys) to simulate impacts of both historical droughts and scenarios of future droughts on forest ecosystems. RHESSys is a spatially-distributed and process-based model that captures the interactions between coupled biogeochemical and hydrologic cycles at catchment scales. Here our case study is the Trail Creek catchment of the Big Wood River basin in Idaho, the Northwestern USA. For historical simulations, we use the gridded meteorological data of 1979 to 2016; for future climate scenarios, we utilize downscaled data from GCMs that have been demonstrated to capture drought events in the Northwest of the USA. From these climate projections, we identify various types of drought in intensity and duration, including multi-year drought events. We evaluate the following responses of ecosystems to these events: 1) evapotranspiration and streamflow; 2) gross primary productivity; 3) the post-drought recovery of plant biomass; and 4) the forest functioning and recovery after multi-year droughts. This research is part of an integration project to examine the roles of drought, insect outbreak, and forest management activities on wildfire activity and its impacts. This project will provide improved information for forest managers and communities in the wild

  10. Genotype-specific physiological and transcriptomic responses to drought stress in Setaria italica (an emerging model for Panicoideae grasses).

    Tang, Sha; Li, Lin; Wang, Yongqiang; Chen, Qiannan; Zhang, Wenying; Jia, Guanqing; Zhi, Hui; Zhao, Baohua; Diao, Xianmin


    Understanding drought-tolerance mechanisms and identifying genetic dominance are important for crop improvement. Setaria italica, which is extremely drought-tolerant, has been regarded as a model plant for studying stress biology. Moreover, different genotypes of S. italica have evolved various drought-tolerance/avoidance mechanisms that should be elucidated. Physiological and transcriptomic comparisons between drought-tolerant S. italica cultivar 'Yugu1' and drought-sensitive 'An04' were conducted. 'An04' had higher yields and more efficient photosystem activities than 'Yugu1' under well-watered conditions, and this was accompanied by positive brassinosteroid regulatory actions. However, 'An04's growth advantage was severely repressed by drought, while 'Yugu1' maintained normal growth under a water deficiency. High-throughput sequencing suggested that the S. italica transcriptome was severely remodelled by genotype × environment interactions. Expression profiles of genes related to phytohormone metabolism and signalling, transcription factors, detoxification, and other stress-related proteins were characterised, revealing genotype-dependent and -independent drought responses in different S. italica genotypes. Combining our data with drought-tolerance-related QTLs, we identified 20 candidate genes that contributed to germination and early seedling' drought tolerance in S. italica. Our analysis provides a comprehensive picture of how different S. italica genotypes respond to drought, and may be used for the genetic improvement of drought tolerance in Poaceae crops.

  11. The Gaussian copula model for the joint deficit index for droughts

    Van de Vyver, H.; Van den Bergh, J.


    The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation.

  12. Assessing Agricultural Drought Vulnerability by a VSD Model: A Case Study in Yunnan Province, China

    Jiansheng Wu


    Full Text Available Drought vulnerability of agriculture is significant to economic development and sustainable food production. In this paper, we proposed a framework to evaluate the regional agricultural-eco environment in the face of drought caused by climate change. Based on a vulnerability scoping diagram (VSD model, we built up a comprehensive system to evaluate the agricultural drought vulnerability of Yunnan Province in China. The model highlights the human-land relationship by considering both natural conditions and human activities. Twelve indicators were generated to construct three components of the model: exposure, sensitivity, and adaptive capacity. During the construction of the VSD model, the entropy and the analytic hierarchy process (AHP comprehensive analysis method were adopted to generate the weights and to compute the composite index for each section. Furthermore, the factor analysis method was used to determine the dominant factors of different cities and the main indicators driving the system. The results indicated a spatial pattern that the vulnerability value was high on the eastern and western sides, but low in the middle of Yunnan Province. Most of the vulnerable regions were concentrated in remote areas. Indicators such as population density, irrigation level, annual average precipitation, cultivation land ratio, and difficulty of water supply were the main driving factors. This means that there is a deep connection between agricultural drought vulnerability and urbanization. The evaluation system developed during this research will provide guidance for drought mitigation in regions of complex terrain.

  13. Modeling Flood & Drought Scenario for Water Management in Porali River Basin, Balochistan

    Shoaib Ahmed


    Full Text Available Recent history shows that floods have become a frequently occurring disaster in Balochistan, especially during monsoon season. Two rivers, river Porali and river Kud overflows, inundating its banks and causing destruction to cultivated land and property. This study is an attempt to identify flood prone areas of Porali river basin for future flood scenario and propose possible reservoir locations for excess flood water storage. Computer-based models Hydrological Simulation Program-FORTRAN (HSPF and HEC-river analysis system (HEC-RAS are used as tools to simulate existing and future flood and drought scenarios. Models are calibrated and validated using data from 3 weather stations, namely Wadh, Bela, and Uthal and stream flow data from two gauging stations. The highest and the lowest 10 years of precipitation data are extracted, from historic dataset of all stations, to attain future flooding and drought scenarios, respectively. Flood inundation map is generated highlighting agricultural prone land and settlements of the watershed. Using Digital Elevation Model (DEM and volume of water calculated from the flood scenario, possible locations for reservoirs are marked that can store excess water for the use in drought years. Flow and volume of water has also been simulated for drought scenario. Analyses show that 3 × 109 m3 of water available due to immense flooding that is sufficient for the survival for one drought year, as the volume of water for latter scenario is 2.9 × 108m3.

  14. Adaptation of the HBV model for the study of drought propagation in European catchments

    van Loon, A. F.; van Lanen, H. A. J.; Seibert, J.; Torfs, P. J. J. F.


    Drought propagation is the conversion of a meteorological drought signal into a hydrological drought (e.g. groundwater and streamflow) as it moves through the subsurface part of the hydrological cycle. The lag, attenuation and possibly pooling of parts of the signal are dependent on climate and catchment characteristics. The understanding of processes underlying drought propagation is still very limited. Our aim is to study these processes in small catchments across Europe with different climate conditions and physical structures (e.g. hard rock, porous rock, flat areas, steep slopes, snow, lakes). As measurements of soil moisture and groundwater storage are normally scarce, simulation of these variables using a lumped hydrological model is needed. However, although a simple model is preferable, many conceptual rainfall-runoff models are not suitable for this purpose because of their focus on fast reactions and therefore unrealistic black box approach of the soil moisture and groundwater system. We studied the applicability of the well-known semi-distributed rainfall-runoff model HBV for drought propagation research. The results show that HBV reproduces observed discharges fairly well. However, in simulating groundwater storage in dry periods, HBV has some conceptual weaknesses: 1) surface runoff is approximated by a quick flow component through the upper groundwater box; 2) the storage in the upper groundwater box has no upper limit; 3) lakes are simulated as part of the lower groundwater box; 4) the percolation from the upper to the lower groundwater box is not continuous, but either zero or constant. So, adaptation of the HBV model structure was needed to be able to simulate realistic groundwater storage in dry periods. The HBV Light model (Seibert et al., 2000) was used as basis for this work. As the snow and soil routines of this model have proven their value in previous (drought) studies, these routines are left unchanged. The lower part of HBV Light, the

  15. Reconstructing and analyzing China's fifty-nine year (1951–2009 drought history using hydrological model simulation

    Z. Y. Wu


    Full Text Available The 1951–2009 drought history of China is reconstructed using daily soil moisture values generated by the Variable Infiltration Capacity (VIC land surface macroscale hydrology model. VIC is applied over a grid of 10 458 points with a spatial resolution of 30 km × 30 km, and is driven by observed daily maximum and minimum air temperature and precipitation from 624 long-term meteorological stations. The VIC soil moisture is used to calculate the Soil Moisture Anomaly Percentage Index (SMAPI, which can be used as a measure of the severity of agricultural drought on a global basis. We have developed a SMAPI-based drought identification procedure for practical uses in the identification of both grid point and regional drought events. As a result, a total of 325 regional drought events varying in time and strength are identified from China's nine drought study regions. These drought events can thus be assessed quantitatively at different spatial and temporal scales. The result shows that the severe drought events of 1978, 2000 and 2006 are well reconstructed, which indicates that the SMAPI is capable of identifying the onset of a drought event, its progression, as well as its termination. Spatial and temporal variations of droughts in China's nine drought study regions are studied. Our result shows that on average, up to 30% of the total area of China is prone to drought. Regionally, an upward trend in drought-affected areas has been detected in three regions (Inner Mongolia, Northeast and North from 1951–2009. However, the decadal variability of droughts has been weak in the rest of the five regions (South, Southwest, East, Northwest, and Tibet. Xinjiang has even been showing steadily wetter since the 1950s. Two regional dry centres are discovered in China as the result of a combined analysis on the occurrence of drought events from both grid points and drought study regions. The first centre is located in the area partially covered by the North

  16. River water quality modelling under drought situations – the Turia River case

    J. Paredes-Arquiola


    Full Text Available Drought and water shortage effects are normally exacerbated due to collateral impacts on water quality, since low streamflow affects water quality in rivers and water uses depend on it. One of the most common problems during drought conditions is maintaining a good water quality while securing the water supply to demands. This research analyses the case of the Turia River Water Resource System located in Eastern Spain. Its main water demand comes as urban demand from Valencia City, which intake is located in the final stretch of the river, where streamflow may become very low during droughts. As a result, during drought conditions concentrations of pathogens and other contaminants increase, compromising the water supply to Valencia City. In order to define possible solutions for the above-mentioned problem, we have developed an integrated model for simulating water management and water quality in the Turia River Basin to propose solutions for water quality problems under water scarcity. For this purpose, the Decision Support System Shell AQUATOOL has been used. The results demonstrate the importance of applying environmental flows as a measure of reducing pollutant's concentration depending on the evolution of a drought event and the state of the water resources system.

  17. Droughts and floods monitoring in Poland with SMOS, SEVIRI and model data

    Kotarba, A. Z.; Stankiewicz, K.; Słomiński, J.; Słomińska, E.; Marczewski, W.


    Droughts and floods represent the extreme cases of hydrological regime. Both significantly influence ecological processes in the environment as well as socio-economic situation of human activity. Measurements of soil moisture and rainfall is being recognized as fundamental for droughts and floods monitoring. We used Soil Moisture and Ocean Salinity (SMOS) L2 soil moisture data and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) rain rate approximation to evaluate the intensity and extend of droughts/floods events in Poland in 2010 and 2011. SEVIRI Multi-Sensor Precipitation Estimate rain rates were used for calculation of monthly rain accumulation (24 SEVIRI L2 datasets per day), then projected to match SMOS spatial reference. Based on SEVIRI data, monthly sum of precipitation was estimated for each SMOS DGG cell within area of interest (the ROI covers Poland and the closest neighborhood). At the DGG level, SMOS SM and SEVIRI precipitation data were compared for each month since May 2010. Nearly two year series provided a background for droughts and floods events. Final L3 products of SMOS SM and SEVIRI precipitation were compared with operational, traditionally-developed drought risk maps, in order to evaluate the degree of agreement between remotely sensed products and models calculated with surface-based measurements only.

  18. Market Anatomy of a Drought: Modeling Barge and Corn Market Adaptation to Reduced Rainfall and Low Mississippi River Water Levels During the 2012 Midwestern U.S. Drought

    Foster, B.; Characklis, G. W.; Thurman, W. N.


    In mid 2012, a severe drought swept across the Midwest, the heartland of corn production in the U.S. When the drought persisted into late Fall, corn markets were affected in two distinct ways: (1) reduced rainfall led to projected and actual corn yields that were lower than expected and (2) navigation restrictions, a result of low water levels on the Mississippi River, disrupted barge transportation, the most common and inexpensive mode for moving corn to many markets. Both (1) and (2) led to significant financial losses, but due to the complexity of the economic system and the coincidence of two different market impacts, the size of the role that low water levels played wass unclear. This is important, as losses related to low water levels are used to justify substantial investments in dredging activities on the Mississippi River. An "engineering" model of the system, suggests that low water levels should drive large increases in barge and corn prices, while some econometric models suggest that water levels explain very little of the changes in barge rates and corn prices. Employing a model that integrates both the engineering and economic elements of the system indicates that corn prices and barge rates during the drought display spatial and temporal behavior that is difficult to explain using either the engineering or econometric models alone. This integrated model accounts for geographic and temporal variations in drought impacts and identifies unique market responses to four different sets of conditions over the drought's length. Results illustrate that corn and barge price responses during the drought were a product of comingled, but distinct, reactions to both supply changes and navigation disruptions. Results also provide a more structured description of how the economic system that governs corn allocation interacts with the Mississippi River system during drought. As both public and private parties discuss potential managerial or infrastructural methods

  19. Groundwater Withdrawals under Drought: Reconciling GRACE and Models in the United States High Plains Aquifer

    Nie, W.; Zaitchik, B. F.; Kumar, S.; Rodell, M.


    Advanced Land Surface Models (LSM) offer a powerful tool for studying and monitoring hydrological variability. Highly managed systems, however, present a challenge for these models, which typically have simplified or incomplete representations of human water use, if the process is represented at all. GRACE, meanwhile, detects the total change in water storage, including change due to human activities, but does not resolve the source of these changes. Here we examine recent groundwater declines in the US High Plains Aquifer (HPA), a region that is heavily utilized for irrigation and that is also affected by episodic drought. To understand observed decline in groundwater (well observation) and terrestrial water storage (GRACE) during a recent multi-year drought, we modify the Noah-MP LSM to include a groundwater pumping irrigation scheme. To account for seasonal and interannual variability in active irrigated area we apply a monthly time-varying greenness vegetation fraction (GVF) dataset to the model. A set of five experiments were performed to study the impact of irrigation with groundwater withdrawal on the simulated hydrological cycle of the HPA and to assess the importance of time-varying GVF when simulating drought conditions. The results show that including the groundwater pumping irrigation scheme in Noah-MP improves model agreement with GRACE mascon solutions for TWS and well observations of groundwater anomaly in the southern HPA, including Texas and Kansas, and that accounting for time-varying GVF is important for model realism under drought. Results for the HPA in Nebraska are mixed, likely due to misrepresentation of the recharge process. This presentation will highlight the value of the GRACE constraint for model development, present estimates of the relative contribution of climate variability and irrigation to declining TWS in the HPA under drought, and identify opportunities to integrate GRACE-FO with models for water resource monitoring in heavily

  20. Urban adaptation to mega-drought: Anticipatory water modeling, policy, and planning in Phoenix

    Gober, P.; Sampson, D. A.; Quay, R.; White, D. D.; Chow, W.


    There is increasing interest in using the results of water models for long-term planning and policy analysis. Achieving this goal requires more effective integration of human dimensions into water modeling and a paradigm shift in the way models are developed and used. A user-defined focus argues in favor of models that are designed to foster public debate and engagement about the difficult trade-offs that are inevitable in managing complex water systems. These models also emphasize decision making under uncertainty and anticipatory planning, and are developed through a collaborative and iterative process. This paper demonstrates the use of anticipatory modeling for long-term drought planning in Phoenix, one of the largest and fastest growing urban areas in the southwestern USA. WaterSim 5, an anticipatory water policy and planning model, was used to explore groundwater sustainability outcomes for mega-drought conditions across a range of policies, including population growth management, water conservation, water banking, direct reuse of RO reclaimed water, and water augmentation. Results revealed that business-as-usual population growth, per capita use trends, and management strategies may not be sustainable over the long term, even without mega-drought conditions as years of available groundwater supply decline over the simulation period from 2000 to 2060. Adding mega-drought increases the decline in aquifer levels and increases the variability in flows and uncertainty about future groundwater supplies. Simulations that combine drought management policies can return the region to sustainable. Results demonstrate the value of long-term planning and policy analysis for anticipating and adapting to environmental change.

  1. Drought, Fire and Insects in Western US Forests: Observations to Improve Regional Land System Modeling

    Law, B. E.; Yang, Z.; Berner, L. T.; Hicke, J. A.; Buotte, P.; Hudiburg, T. W.


    Drought, fire and insects are major disturbances in the western US, and conditions are expected to get warmer and drier in the future. We combine multi-scale observations and modeling with CLM4.5 to examine the effects of these disturbances on forests in the western US. We modified the Community Land Model, CLM4.5, to improve simulated drought-related mortality in forests, and prediction of insect outbreaks under future climate conditions. We examined differences in plant traits that represent species variation in sensitivity to drought, and redefined plant groupings in PFTs. Plant traits, including sapwood area: leaf area ratio and stemwood density were strongly correlated with water availability during the ecohydrologic year. Our database of co-located observations of traits for 30 tree species was used to produce parameterization of the model by species groupings according to similar traits. Burn area predicted by the new fire model in CLM4.5 compares well with recent years of GFED data, but has a positive bias compared with Landsat-based MTBS. Biomass mortality over recent decades increased, and was captured well by the model in general, but missed mortality trends of some species. Comparisons with AmeriFlux data showed that the model with dynamic tree mortality only (no species trait improvements) overestimated GPP in dry years compared with flux data at semi-arid sites, and underestimated GPP at more mesic sites that experience dry summers. Simulations with both dynamic tree mortality and species trait parameters improved estimates of GPP by 17-22%; differences between predicted and observed NEE were larger. Future projections show higher productivity from increased atmospheric CO2 and warming that somewhat offsets drought and fire effects over the next few decades. Challenges include representation of hydraulic failure in models, and availability of species trait and carbon/water process data in disturbance- and drought-impacted regions.

  2. Methods and Model Dependency of Extreme Event Attribution: The 2015 European Drought

    Hauser, Mathias; Gudmundsson, Lukas; Orth, René; Jézéquel, Aglaé; Haustein, Karsten; Vautard, Robert; van Oldenborgh, Geert J.; Wilcox, Laura; Seneviratne, Sonia I.


    Science on the role of anthropogenic influence on extreme weather events, such as heatwaves or droughts, has evolved rapidly in the past years. The approach of "event attribution" compares the occurrence-probability of an event in the present, factual climate with its probability in a hypothetical, counterfactual climate without human-induced climate change. Several methods can be used for event attribution, based on climate model simulations and observations, and usually researchers only assess a subset of methods and data sources. Here, we explore the role of methodological choices for the attribution of the 2015 meteorological summer drought in Europe. We present contradicting conclusions on the relevance of human influence as a function of the chosen data source and event attribution methodology. Assessments using the maximum number of models and counterfactual climates with pre-industrial greenhouse gas concentrations point to an enhanced drought risk in Europe. However, other evaluations show contradictory evidence. These results highlight the need for a multi-model and multi-method framework in event attribution research, especially for events with a low signal-to-noise ratio and high model dependency such as regional droughts.

  3. Predicting forest dieback in Maine, USA: a simple model based on soil frost and drought

    Allan N.D. Auclair; Warren E. Heilman; Blondel. Brinkman


    Tree roots of northern hardwoods are shallow rooted, winter active, and minimally frost hardened; dieback is a winter freezing injury to roots incited by frost penetration in the absence of adequate snow cover and exacerbated by drought in summer. High soil water content greatly increases conductivity of frost. We develop a model based on the sum of z-scores of soil...

  4. Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models

    W. R. L. Anderegg; C. Schwalm; F. Biondi; J. J. Camarero; G. Koch; M. Litvak; K. Ogle; J. D. Shaw; E. Shevliakova; A. P. Williams; A. Wolf; E. Ziaco; S. Pacala


    The impacts of climate extremes on terrestrial ecosystems are poorly understood but important for predicting carbon cycle feedbacks to climate change. Coupled climate-carbon cycle models typically assume that vegetation recovery from extreme drought is immediate and complete, which conflicts with the understanding of basic plant physiology. We examined the recovery of...

  5. Multi-environment QTL mixed models for drought stress adaptation in wheat

    Mathews, K.L.; Malosetti, M.; Chapman, S.; McIntyre, L.; Reynolds, M.; Shorter, R.; Eeuwijk, van F.A.


    Many quantitative trait loci (QTL) detection methods ignore QTL-by-environment interaction (QEI) and are limited in accommodation of error and environment-specific variance. This paper outlines a mixed model approach using a recombinant inbred spring wheat population grown in six drought stress

  6. Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

    Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.


    One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

  7. Modeling water scarcity and droughts for policy adaptation to climate change in arid and semiarid regions

    Kahil, Mohamed Taher; Dinar, Ariel; Albiac, Jose


    Growing water extractions combined with emerging demands for environment protection increase competition for scarce water resources worldwide, especially in arid and semiarid regions. In those regions, climate change is projected to exacerbate water scarcity and increase the recurrence and intensity of droughts. These circumstances call for methodologies that can support the design of sustainable water management. This paper presents a hydro-economic model that links a reduced form hydrological component, with economic and environmental components. The model is applied to an arid and semiarid basin in Southeastern Spain to analyze the effects of droughts and to assess alternative adaptation policies. Results indicate that drought events have large impacts on social welfare, with the main adjustments sustained by irrigation and the environment. The water market policy seems to be a suitable option to overcome the negative economic effects of droughts, although the environmental effects may weaken its advantages for society. The environmental water market policy, where water is acquired for the environment, is an appealing policy to reap the private benefits of markets while protecting ecosystems. The current water management approach in Spain, based on stakeholders' cooperation, achieves almost the same economic outcomes and better environmental outcomes compared to a pure water market. These findings call for a reconsideration of the current management in arid and semiarid basins around the world. The paper illustrates the potential of hydro-economic modeling for integrating the multiple dimensions of water resources, becoming a valuable tool in the advancement of sustainable water management policies.

  8. Integrated Modeling of Drought-Impacted Areas using Remote Sensing and Microenvironmental Data in California

    Rao, M.; Silber-coats, Z.; Lawrence, F.


    California's ongoing drought condition shriveled not just the agricultural sector, but also the natural resources sector including forestry, wildlife, and fisheries. As future predictions of drought and fire severity become more real in California, there is an increased awareness to pursue innovative and cost-effective solutions that are based on silvicultural treatments and controlled burns to improve forest health and reduce the risk of high-severity wildfires. The main goal of this study is to develop a GIS map of the drought-impacted region of northern and central California using remote sensing data for the summer period of 2014. Specifically, Landsat/NAIP imagery will be analyzed using a combination of object-oriented classification and spectral indices such as the Modified Perpendicular Drought Index (MPDI). This spectral index basically scales the line perpendicular to the soil line defined in the Red-NIR feature space in conjunction with added information about vegetative fraction derived using NDVI. The resulting output will be correlated with USGS-produced estimates of climatic water deficit (CWD) data to characterize the severity of the drought. The CWD is simulated based on hydrological tool, Basin Characterization Model (BCM) that ingests historical climate data in conjunction with soils, topography, and geological data to predict other monthly hydrological outputs including runoff, recharge, and snowpack. In addition to field data, data collected by state agencies including USFS, will be used in the classification and accuracy assessment procedures. Visual assessment using high-resolution imagery such as NAIP will be used to further refine the spatial maps. The drought severity maps produced will greatly facilitate site-specific planning efforts aimed at implementing resource management decisions.

  9. Experimental evidence and modelling of drought induced alternative stable soil moisture states

    Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget


    The theory of alternative stable states in ecosystems is well established in ecology; however, evidence from manipulation experiments supporting the theory is limited. Developing the evidence base is important because it has profound implications for ecosystem management. Here we show evidence of the existence of alternative stable soil moisture states induced by drought in an upland wet heath. We used a long-term (15 yrs) climate change manipulation experiment with moderate sustained drought, which reduced the ability of the soil to retain soil moisture by degrading the soil structure, reducing moisture retention. Moreover, natural intense droughts superimposed themselves on the experiment, causing an unexpected additional alternative soil moisture state to develop, both for the drought manipulation and control plots; this impaired the soil from rewetting in winter. Our results show the coexistence of three stable states. Using modelling with the Hydrus 1D software package we are able to show the circumstances under which shifts in soil moisture states are likely to occur. Given the new understanding it presents a challenge of how to incorporate feedbacks, particularly related to soil structure, into soil flow and transport models?

  10. Quantitative comparisons of three modeling approaches for characterizing drought response of a highly variable, widely grown crop species

    Pleban, J. R.; Mackay, D. S.; Aston, T.; Ewers, B. E.; Wienig, C.


    Quantifying the drought tolerance of crop species and genotypes is essential in order to predict how water stress may impact agricultural productivity. As climate models predict an increase in both frequency and severity of drought corresponding plant hydraulic and biochemical models are needed to accurately predict crop drought tolerance. Drought can result in cavitation of xylem conduits and related loss of plant hydraulic conductivity. This study tested the hypothesis that a model incorporating a plants vulnerability to cavitation would best assess drought tolerance in Brassica rapa. Four Brassica genotypes were subjected to drought conditions at a field site in Laramie, WY. Concurrent leaf gas exchange, volumetric soil moisture content and xylem pressure measurements were made during the drought period. Three models were used to access genotype specific drought tolerance. All 3 models rely on the Farquhar biochemical/biophysical model of leaf level photosynthesis, which is integrated into the Terrestrial Regional Ecosystem Exchange Simulator (TREES). The models differ in how TREES applies the environmental driving data and plant physiological mechanisms; specifically how water availability at the site of photosynthesis is derived. Model 1 established leaf water availability from a modeled soil moisture content; Model 2 input soil moisture measurements directly to establish leaf water availability; Model 3 incorporated the Sperry soil-plant transport model, which calculates flows and pressure along the soil-plant water transport pathway to establish leaf water availability. This third model incorporated measured xylem pressures thus constraining leaf water availability via genotype specific vulnerability curves. A multi-model intercomparison was made using a Bayesian approach, which assessed the interaction between uncertainty in model results and data. The three models were further evaluated by assessing model accuracy and complexity via deviance information

  11. Large-scale hydrological modelling in the semi-arid north-east of Brazil

    Guentner, A


    Semi-arid areas are characterized by small water resources. An increasing water demand due to population growth and economic development as well as a possible decreasing water availability in the course of climate change may aggravate water scarcity in future in these areas. The quantitative assessment of the water resources is a prerequisite for the development of sustainable measures of water management. For this task, hydrological models within a dynamic integrated framework are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability over a large geographic domain of semi-arid environments. The study area is the Federal State of Ceara in the semi-arid north-east of Brazil. Surface water from reservoirs provides the largest part of water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. (orig.)

  12. The Added Utility of Hydrological Model and Satellite Based Datasets in Agricultural Drought Analysis over Turkey

    Bulut, B.; Hüsami Afşar, M.; Yilmaz, M. T.


    Analysis of agricultural drought, which causes substantial socioeconomically costs in Turkey and in the world, is critical in terms of understanding this natural disaster's characteristics (intensity, duration, influence area) and research on possible precautions. Soil moisture is one of the most important parameters which is used to observe agricultural drought, can be obtained using different methods. The most common, consistent and reliable soil moisture datasets used for large scale analysis are obtained from hydrologic models and remote sensing retrievals. On the other hand, Normalized difference vegetation index (NDVI) and gauge based precipitation observations are also commonly used for drought analysis. In this study, soil moisture products obtained from different platforms, NDVI and precipitation datasets over several different agricultural regions under various climate conditions in Turkey are obtained in growth season period. These datasets are later used to investigate agricultural drought by the help of annual crop yield data of selected agricultural lands. The type of vegetation over these regions are obtained using CORINE Land Cover (CLC 2012) data. The crop yield data were taken from the record of related district's statistics which is provided by Turkish Statistical Institute (TÜİK). This project is supported by TÜBİTAK project number 114Y676.

  13. Integrating an agent-based model into a large-scale hydrological model for evaluating drought management in California

    Sheffield, J.; He, X.; Wada, Y.; Burek, P.; Kahil, M.; Wood, E. F.; Oppenheimer, M.


    California has endured record-breaking drought since winter 2011 and will likely experience more severe and persistent drought in the coming decades under changing climate. At the same time, human water management practices can also affect drought frequency and intensity, which underscores the importance of human behaviour in effective drought adaptation and mitigation. Currently, although a few large-scale hydrological and water resources models (e.g., PCR-GLOBWB) consider human water use and management practices (e.g., irrigation, reservoir operation, groundwater pumping), none of them includes the dynamic feedback between local human behaviors/decisions and the natural hydrological system. It is, therefore, vital to integrate social and behavioral dimensions into current hydrological modeling frameworks. This study applies the agent-based modeling (ABM) approach and couples it with a large-scale hydrological model (i.e., Community Water Model, CWatM) in order to have a balanced representation of social, environmental and economic factors and a more realistic representation of the bi-directional interactions and feedbacks in coupled human and natural systems. In this study, we focus on drought management in California and considers two types of agents, which are (groups of) farmers and state management authorities, and assumed that their corresponding objectives are to maximize the net crop profit and to maintain sufficient water supply, respectively. Farmers' behaviors are linked with local agricultural practices such as cropping patterns and deficit irrigation. More precisely, farmers' decisions are incorporated into CWatM across different time scales in terms of daily irrigation amount, seasonal/annual decisions on crop types and irrigated area as well as the long-term investment of irrigation infrastructure. This simulation-based optimization framework is further applied by performing different sets of scenarios to investigate and evaluate the effectiveness

  14. The Prediction of Drought-Related Tree Mortality in Vegetation Models

    Schwinning, S.; Jensen, J.; Lomas, M. R.; Schwartz, B.; Woodward, F. I.


    Drought-related tree die-off events at regional scales have been reported from all wooded continents and it has been suggested that their frequency may be increasing. The prediction of these drought-related die-off events from regional to global scales has been recognized as a critical need for the conservation of forest resources and improving the prediction of climate-vegetation interactions. However, there is no conceptual consensus on how to best approach the quantitative prediction of tree mortality. Current models use a variety of mechanisms to represent demographic events. Mortality is modeled to represent a number of different processes, including death by fire, wind throw, extreme temperatures, and self-thinning, and each vegetation model differs in the emphasis they place on specific mechanisms. Dynamic global vegetation models generally operate on the assumption of incremental vegetation shift due to changes in the carbon economy of plant functional types and proportional effects on recruitment, growth, competition and mortality, but this may not capture sudden and sweeping tree death caused by extreme weather conditions. We tested several different approaches to predicting tree mortality within the framework of the Sheffield Dynamic Global Vegetation Model. We applied the model to the state of Texas, USA, which in 2011 experienced extreme drought conditions, causing the death of an estimated 300 million trees statewide. We then compared predicted to actual mortality to determine which algorithms most accurately predicted geographical variation in tree mortality. We discuss implications regarding the ongoing debate on the causes of tree death.

  15. Assessing Drought Impacts on Water Storage using GRACE Satellites and Regional Groundwater Modeling in the Central Valley of California

    Scanlon, B. R.; Zhang, Z.; Save, H.; Faunt, C. C.; Dettinger, M. D.


    Increasing concerns about drought impacts on water resources in California underscores the need to better understand effects of drought on water storage and coping strategies. Here we use a new GRACE mascons solution with high spatial resolution (1 degree) developed at the Univ. of Texas Center for Space Research (CSR) and output from the most recent regional groundwater model developed by the U.S. Geological Survey to evaluate changes in water storage in response to recent droughts. We also extend the analysis of drought impacts on water storage back to the 1980s using modeling and monitoring data. The drought has been intensifying since 2012 with almost 50% of the state and 100% of the Central Valley under exceptional drought in 2015. Total water storage from GRACE data declined sharply during the current drought, similar to the rate of depletion during the previous drought in 2007 - 2009. However, only 45% average recovery between the two droughts results in a much greater cumulative impact of both droughts. The CSR GRACE Mascons data offer unprecedented spatial resolution with no leakage to the oceans and no requirement for signal restoration. Snow and reservoir storage declines contribute to the total water storage depletion estimated by GRACE with the residuals attributed to groundwater storage. Rates of groundwater storage depletion are consistent with the results of regional groundwater modeling in the Central Valley. Traditional approaches to coping with these climate extremes has focused on surface water reservoir storage; however, increasing conjunctive use of surface water and groundwater and storing excess water from wet periods in depleted aquifers is increasing in the Central Valley.

  16. Application of Multiple Evaluation Models in Brazil

    Rafael Victal Saliba


    Full Text Available Based on two different samples, this article tests the performance of a number of Value Drivers commonly used for evaluating companies by finance practitioners, through simple regression models of cross-section type which estimate the parameters associated to each Value Driver, denominated Market Multiples. We are able to diagnose the behavior of several multiples in the period 1994-2004, with an outlook also on the particularities of the economic activities performed by the sample companies (and their impacts on the performance through a subsequent analysis with segregation of companies in the sample by sectors. Extrapolating simple multiples evaluation standards from analysts of the main financial institutions in Brazil, we find that adjusting the ratio formulation to allow for an intercept does not provide satisfactory results in terms of pricing errors reduction. Results found, in spite of evidencing certain relative and absolute superiority among the multiples, may not be generically representative, given samples limitation.

  17. Linking definitions, mechanisms, and modeling of drought-induced tree death.

    Anderegg, William R L; Berry, Joseph A; Field, Christopher B


    Tree death from drought and heat stress is a critical and uncertain component in forest ecosystem responses to a changing climate. Recent research has illuminated how tree mortality is a complex cascade of changes involving interconnected plant systems over multiple timescales. Explicit consideration of the definitions, dynamics, and temporal and biological scales of tree mortality research can guide experimental and modeling approaches. In this review, we draw on the medical literature concerning human death to propose a water resource-based approach to tree mortality that considers the tree as a complex organism with a distinct growth strategy. This approach provides insight into mortality mechanisms at the tree and landscape scales and presents promising avenues into modeling tree death from drought and temperature stress. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Drought resilience across ecologically dominant species: An experiment-model integration approach

    Felton, A. J.; Warren, J.; Ricciuto, D. M.; Smith, M. D.


    Poorly understood are the mechanisms contributing to variability in ecosystem recovery following drought. Grasslands of the central U.S. are ecologically and economically important ecosystems, yet are also highly sensitive to drought. Although characteristics of these ecosystems change across gradients of temperature and precipitation, a consistent feature among these systems is the presence of highly abundant, dominant grass species that control biomass production. As a result, the incorporation of these species' traits into terrestrial biosphere models may constrain predictions amid increases in climatic variability. Here we report the results of a modeling-experiment (MODEX) research approach. We investigated the physiological, morphological and growth responses of the dominant grass species from each of the four major grasslands of the central U.S. (ranging from tallgrass prairie to desert grassland) following severe drought. Despite significant differences in baseline values, full recovery in leaf physiological function was evident across species, of which was consistently driven by the production of new leaves. Further, recovery in whole-plant carbon uptake tended to be driven by shifts in allocation from belowground to aboveground structures. However, there was clear variability among species in the magnitude of this dynamic as well as the relative allocation to stem versus leaf production. As a result, all species harbored the physiological capacity to recover from drought, yet we posit that variability in the recovery of whole-plant carbon uptake to be more strongly driven by variability in the sensitivity of species' morphology to soil moisture increases. The next step of this project will be to incorporate these and other existing data on these species and ecosystems into the community land model in an effort to test the sensitivity of this model to these data.

  19. Modelling drought-induced dieback of Aleppo pine at the arid timberline

    Wingate, Lisa; Preisler, Yakir; Bert, Didier; Rotenberg, Eyal; Yakir, Dan; Maseyk, Kadmiel; Ogee, Jerome


    During the mid 1960's an ambitious afforestation programme was initiated in the Negev desert of Israel. After five decades enduring harsh growing conditions, the Aleppo pine forest of Yatir is now exhibiting signs of 'drought-induced' dieback. Since 2010, 5-10% of the entire Yatir population have died, however the pattern of mortality is extremely patchy with some areas exhibiting >80% mortality whilst others display none. In this presentation, we reflect on historic climatic and edaphic conditions that have triggered this landscape mosaic of survival and mortality and how physiological and hydraulic traits vary within this patchwork. In addition, we explore how these pine trees have responded physiologically over recent years (1996-2010) to a series of severe drought events using a combined approach that brings together micrometeorological, dendro-isotopic and dendro-climatological datasets alongside process-based modelling. In particular the dataset trends were investigated with the isotope-enabled ecosystem model MuSICA to explore the consequences of subsequent droughts and embolism on modelled carbohydrate and water pool dynamics and their impact on carbon allocation and ecosystem function.

  20. Predicting drought propagation within peat layers using a three dimensionally explicit voxel based model

    Condro, A. A.; Pawitan, H.; Risdiyanto, I.


    Peatlands are very vulnerable to widespread fires during dry seasons, due to availability of aboveground fuel biomass on the surface and belowground fuel biomass on the sub-surface. Hence, understanding drought propagation occurring within peat layers is crucial with regards to disaster mitigation activities on peatlands. Using a three dimensionally explicit voxel-based model of peatland hydrology, this study predicted drought propagation time lags into sub-surface peat layers after drought events occurrence on the surface of about 1 month during La-Nina and 2.5 months during El-Nino. The study was carried out on a high-conservation-value area of oil palm plantation in West Kalimantan. Validity of the model was evaluated and its applicability for disaster mitigation was discussed. The animations of simulated voxels are available at: (El-Nino 2015 episode) and (La-Nina 2016 episode). The model is available at:

  1. Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

    Sheffield, J.; Lobell, D. B.; Wood, E. F.


    Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart ( The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including

  2. A case for multi-model and multi-approach based event attribution: The 2015 European drought

    Hauser, Mathias; Gudmundsson, Lukas; Orth, René; Jézéquel, Aglaé; Haustein, Karsten; Seneviratne, Sonia Isabelle


    Science on the role of anthropogenic influence on extreme weather events such as heat waves or droughts has evolved rapidly over the past years. The approach of "event attribution" compares the occurrence probability of an event in the present, factual world with the probability of the same event in a hypothetical, counterfactual world without human-induced climate change. Every such analysis necessarily faces multiple methodological choices including, but not limited to: the event definition, climate model configuration, and the design of the counterfactual world. Here, we explore the role of such choices for an attribution analysis of the 2015 European summer drought (Hauser et al., in preparation). While some GCMs suggest that anthropogenic forcing made the 2015 drought more likely, others suggest no impact, or even a decrease in the event probability. These results additionally differ for single GCMs, depending on the reference used for the counterfactual world. Observational results do not suggest a historical tendency towards more drying, but the record may be too short to provide robust assessments because of the large interannual variability of drought occurrence. These results highlight the need for a multi-model and multi-approach framework in event attribution research. This is especially important for events with low signal to noise ratio and high model dependency such as regional droughts. Hauser, M., L. Gudmundsson, R. Orth, A. Jézéquel, K. Haustein, S.I. Seneviratne, in preparation. A case for multi-model and multi-approach based event attribution: The 2015 European drought.

  3. Simulating the 2012 High Plains Drought Using Three Single Column Models (SCM)

    Medina, I. D.; Baker, I. T.; Denning, S.; Dazlich, D. A.


    The impact of changes in the frequency and severity of drought on fresh water sustainability is a great concern for many regions of the world. One such location is the High Plains, where the local economy is primarily driven by fresh water withdrawals from the Ogallala Aquifer, which accounts for approximately 30% of total irrigation withdrawals from all U.S. aquifers combined. Modeling studies that focus on the feedback mechanisms that control the climate and eco-hydrology during times of drought are limited, and have used conventional General Circulation Models (GCMs) with grid length scales ranging from one hundred to several hundred kilometers. Additionally, these models utilize crude statistical parameterizations of cloud processes for estimating sub-grid fluxes of heat and moisture and have a poor representation of land surface heterogeneity. For this research, we focus on the 2012 High Plains drought and perform numerical simulations using three single column model (SCM) versions of BUGS5 (Colorado State University (CSU) GCM coupled to the Simple Biosphere Model (SiB3)). In the first version of BUGS5, the model is used in its standard bulk setting (single atmospheric column coupled to a single instance of SiB3), secondly, the Super-Parameterized Community Atmospheric Model (SP-CAM), a cloud resolving model (CRM) (CRM consists of 32 atmospheric columns), replaces the single CSU GCM atmospheric parameterization and is coupled to a single instance of SiB3, and for the third version of BUGS5, an instance of SiB3 is coupled to each CRM column of the SP-CAM (32 CRM columns coupled to 32 instances of SiB3). To assess the physical realism of the land-atmosphere feedbacks simulated by all three versions of BUGS5, differences in simulated energy and moisture fluxes are computed between the 2011 and 2012 period and are compared to those calculated using observational data from the AmeriFlux Tower Network for the same period at the ARM Site in Lamont, OK. This research

  4. Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches.

    Jin, Zhenong; Zhuang, Qianlai; Tan, Zeli; Dukes, Jeffrey S; Zheng, Bangyou; Melillo, Jerry M


    Stresses from heat and drought are expected to increasingly suppress crop yields, but the degree to which current models can represent these effects is uncertain. Here we evaluate the algorithms that determine impacts of heat and drought stress on maize in 16 major maize models by incorporating these algorithms into a standard model, the Agricultural Production Systems sIMulator (APSIM), and running an ensemble of simulations. Although both daily mean temperature and daylight temperature are common choice of forcing heat stress algorithms, current parameterizations in most models favor the use of daylight temperature even though the algorithm was designed for daily mean temperature. Different drought algorithms (i.e., a function of soil water content, of soil water supply to demand ratio, and of actual to potential transpiration ratio) simulated considerably different patterns of water shortage over the growing season, but nonetheless predicted similar decreases in annual yield. Using the selected combination of algorithms, our simulations show that maize yield reduction was more sensitive to drought stress than to heat stress for the US Midwest since the 1980s, and this pattern will continue under future scenarios; the influence of excessive heat will become increasingly prominent by the late 21st century. Our review of algorithms in 16 crop models suggests that the impacts of heat and drought stress on plant yield can be best described by crop models that: (i) incorporate event-based descriptions of heat and drought stress, (ii) consider the effects of nighttime warming, and (iii) coordinate the interactions among multiple stresses. Our study identifies the proficiency with which different model formulations capture the impacts of heat and drought stress on maize biomass and yield production. The framework presented here can be applied to other modeled processes and used to improve yield predictions of other crops with a wide variety of crop models. © 2016 John

  5. Drought occurence

    John W. Coulston


    Why Is Drought Important? Drought is an important forest disturbance that occurs regularly in the Western United States and irregularly in the Eastern United States (Dale and others 2001). Moderate drought stress tends to slow plant growth while severedrought stress can also reduce photosynthesis (Kareiva and others 1993). Drought can also interact with...

  6. 2-D Model Test Study of the Suape Breakwater, Brazil

    Andersen, Thomas Lykke; Burcharth, Hans F.; Sopavicius, A.

    This report deals with a two-dimensional model test study of the extension of the breakwater in Suape, Brazil. One cross-section was tested for stability and overtopping in various sea conditions. The length scale used for the model tests was 1:35. Unless otherwise specified all values given...

  7. Modelling soil water content variations under drought stress on soil column cropped with winter wheat

    Csorba Szilveszter


    Full Text Available Mathematical models are effective tools for evaluating the impact of predicted climate change on agricultural production, but it is difficult to test their applicability to future weather conditions. We applied the SWAP model to assess its applicability to climate conditions, differing from those, for which the model was developed. We used a database obtained from a winter wheat drought stress experiment. Winter wheat was grown in six soil columns, three having optimal water supply (NS, while three were kept under drought-stressed conditions (S. The SWAP model was successfully calibrated against measured values of potential evapotranspiration (PET, potential evaporation (PE and total amount of water (TSW in the soil columns. The Nash-Sutcliffe model efficiency coefficient (N-S for TWS for the stressed columns was 0.92. For the NS treatment, we applied temporally variable soil hydraulic properties because of soil consolidation caused by regular irrigation. This approach improved the N-S values for the wetting-drying cycle from -1.77 to 0.54. We concluded that the model could be used for assessing the effects of climate change on soil water regime. Our results indicate that soil water balance studies should put more focus on the time variability of structuredependent soil properties.

  8. Use of Drought Index and Crop Modelling for Drought Impacts Analysis on Maize (Zea mays L.) Yield Loss in Bandung District

    Kurniasih, E.; Impron; Perdinan


    Drought impacts on crop yield loss depend on drought magnitude and duration and on plant genotype at every plant growth stages when droughts occur. This research aims to assess the difference calculation results of 2 drought index methods and to study the maize yield loss variability impacted by drought magnitude and duration during maize growth stages in Bandung district, province of West Java, Indonesia. Droughts were quantified by the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at 1- to 3-month lags for the January1986-December 2015 period data. Maize yield responses to droughts were simulated by AquaCrop for the January 1986-May 2016 period of growing season. The analysis showed that the SPI and SPEI methods provided similar results in quantifying drought event. Droughts during maize reproductive stages caused the highest maize yield loss.

  9. a Probability Model for Drought Prediction Using Fusion of Markov Chain and SAX Methods

    Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.


    Drought is one of the most powerful natural disasters which are affected on different aspects of the environment. Most of the time this phenomenon is immense in the arid and semi-arid area. Monitoring and prediction the severity of the drought can be useful in the management of the natural disaster caused by drought. Many indices were used in predicting droughts such as SPI, VCI, and TVX. In this paper, based on three data sets (rainfall, NDVI, and land surface temperature) which are acquired from MODIS satellite imagery, time series of SPI, VCI, and TVX in time limited between winters 2000 to summer 2015 for the east region of Isfahan province were created. Using these indices and fusion of symbolic aggregation approximation and hidden Markov chain drought was predicted for fall 2015. For this purpose, at first, each time series was transformed into the set of quality data based on the state of drought (5 group) by using SAX algorithm then the probability matrix for the future state was created by using Markov hidden chain. The fall drought severity was predicted by fusion the probability matrix and state of drought severity in summer 2015. The prediction based on the likelihood for each state of drought includes severe drought, middle drought, normal drought, severe wet and middle wet. The analysis and experimental result from proposed algorithm show that the product of this algorithm is acceptable and the proposed algorithm is appropriate and efficient for predicting drought using remote sensor data.

  10. Drought Forecasting by SPI Index and ANFIS Model Using Fuzzy C-mean Clustering

    mehdi Komasi


    Full Text Available Drought is the interaction between environment and water cycle in the world and affects natural environment of an area when it persists for a longer period. So, developing a suitable index to forecast the spatial and temporal distribution of drought plays an important role in the planning and management of natural resources and water resource systems. In this article, firstly, the drought concept and drought indexes were introduced and then the fuzzy neural networks and fuzzy C-mean clustering were applied to forecast drought via standardized precipitation index (SPI. The results of this research indicate that the SPI index is more capable than the other indexes such as PDSI (Palmer Drought Severity Index, PAI (Palfai Aridity Index and etc. in drought forecasting process. Moreover, application of adaptive nero-fuzzy network accomplished by C-mean clustering has high efficiency in the drought forecasting.

  11. Application of Physically based landslide susceptibility models in Brazil

    Carvalho Vieira, Bianca; Martins, Tiago D.


    Shallow landslides and floods are the processes responsible for most material and environmental damages in Brazil. In the last decades, some landslides events induce a high number of deaths (e.g. Over 1000 deaths in one event) and incalculable social and economic losses. Therefore, the prediction of those processes is considered an important tool for land use planning tools. Among different methods the physically based landslide susceptibility models having been widely used in many countries, but in Brazil it is still incipient when compared to other ones, like statistical tools and frequency analyses. Thus, the main objective of this research was to assess the application of some Physically based landslide susceptibility models in Brazil, identifying their main results, the efficiency of susceptibility mapping, parameters used and limitations of the tropical humid environment. In order to achieve that, it was evaluated SHALSTAB, SINMAP and TRIGRS models in some studies in Brazil along with the Geotechnical values, scales, DEM grid resolution and the results based on the analysis of the agreement between predicted susceptibility and the landslide scar's map. Most of the studies in Brazil applied SHALSTAB, SINMAP and to a lesser extent the TRIGRS model. The majority researches are concentrated in the Serra do Mar mountain range, that is a system of escarpments and rugged mountains that extends more than 1,500 km along the southern and southeastern Brazilian coast, and regularly affected by heavy rainfall that generates widespread mass movements. Most part of these studies used conventional topographic maps with scales ranging from 1:2000 to 1:50000 and DEM-grid resolution between 2 and 20m. Regarding the Geotechnical and hydrological values, a few studies use field collected data which could produce more efficient results, as indicated by international literature. Therefore, even though they have enormous potential in the susceptibility mapping, even for comparison

  12. Capturing flood-to-drought transitions in regional climate model simulations

    Anders, Ivonne; Haslinger, Klaus; Hofstätter, Michael; Salzmann, Manuela; Resch, Gernot


    In previous studies atmospheric cyclones have been investigated in terms of related precipitation extremes in Central Europe. Mediterranean (Vb-like) cyclones are of special relevance as they are frequently related to high atmospheric moisture fluxes leading to floods and landslides in the Alpine region. Another focus in this area is on droughts, affecting soil moisture and surface and sub-surface runoff as well. Such events develop differently depending on available pre-saturation of water in the soil. In a first step we investigated two time periods which encompass a flood event and a subsequent drought on very different time scales, one long lasting transition (2002/2003) and a rather short one between May and August 2013. In a second step we extended the investigation to the long time period 1950-2016. We focused on high spatial and temporal scales and assessed the currently achievable accuracy in the simulation of the Vb-events on one hand and following drought events on the other hand. The state-of-the-art regional climate model CCLM is applied in hindcast-mode simulating the single events described above, but also the time from 1948 to 2016 to evaluate the results from the short runs to be valid for the long time period. Besides the conventional forcing of the regional climate model at its lateral boundaries, a spectral nudging technique is applied. The simulations covering the European domain have been varied systematically different model parameters. The resulting precipitation amounts have been compared to E-OBS gridded European precipitation data set and a recent high spatially resolved precipitation data set for Austria (GPARD-6). For the drought events the Standardized Precipitation Evapotranspiration Index (SPEI), soil moisture and runoff has been investigated. Varying the spectral nudging setup helps us to understand the 3D-processes during these events, but also to identify model deficiencies. To improve the simulation of such events in the past

  13. The role of extreme drought events in modelling the distribution of beech at its xeric limit

    Rasztovits, Ervin; Berki, Imre; Eredics, Attila; Móricz, Norbert


    Context: Projections of species distribution models (SDMs) for future climate conditions are based on long term mean climate data. For management and conservation issues SDMs have been extensively used, but it is not tested whether models that are successful in predicting current distributions are equally powerful in predicting distributions under future climates. Methods: Observations after 2003 confirms that extreme drought events played an important role in driving beech mortality at low-elevation xeric limits. The objective of this study was (1) to set up a simple extreme drought event based vitality model (EDM) using sanitary logging information as a proxy of vitality response of beech and (2) to compare the spatial pattern of the predicted vitality loss provided by the EDM with the distribution limits of the SDMs for three terms (2025, 2050 and 2100) in Hungary to assess model performance. Results: Prediction for vitality loss for 2025 obtained from the EDM was in agreement with those of the SDM, but for the end of the century the EDM predicted a more serious decline in almost all regions of Hungary. Conclusion: The result of the comparison suggests that the increasing frequency and severity of extremes might play a more important role in limiting the distribution of beech in the future near to the xeric limit than long-term means.

  14. Exploring the Causes of Mid-Holocene Drought in the Rocky Mountains Using Hydrologic Forward Models

    Meador, E.; Morrill, C.


    We present a quantitative model-data comparison for mid-Holocene (6 ka) lake levels in the Rocky Mountains, with the goals of assessing the skill coupled climate models and hydrologic forward models in simulating climate change and improving our understanding of the factors causing past changes in water resources. The mid-Holocene climate in this area may in some ways be similar to expected future climate, thus improved understanding of the factors causing past changes in water resources have the potential to aid in the process of water allocation for large areas that share a relatively small water source. This project focuses on Little Windy Hill Pond in the Medicine Bow Forest in the Rocky Mountains in southern Wyoming. We first calibrated the Variable Infiltration Capacity (VIC) catchment hydrologic model and the one-dimensional Hostetler Bartlein lake energy-balance model to modern observations, using U.S. Geological Survey stream discharge data and Snow Telemetry (SNOTEL) data to ensure appropriate selection of model parameters. Once the models were calibrated to modern conditions, we forced them with output from eight mid-Holocene coupled climate model simulations completed as part of the Coupled Model Intercomparison Project, Phase 5. Forcing from nearly all of the CMIP5 models generates intense, short-lived droughts for the mid-Holocene that are more severe than any we modeled for the past six decades. The severity of the mid-Holocene droughts could be sufficient, depending on sediment processes in the lake, to account for low lake levels recorded by loss-on-ignition in sediment cores. Our preliminary analysis of model output indicates that the combined effects of decreased snowmelt runoff and increased summer lake evaporation cause low mid-Holocene lake levels. These factors are also expected to be important in the future under anthropogenic climate change.

  15. Growth and yield of southwest pinyon-juniper woodlands: Modeling growth and drought effects

    John D. Shaw


    A complex of drought, insects, and disease caused widespread mortality in the pinyon-juniper forest types of the American Southwest in recent years. Most public and scientific attention has been given to the extent of drought-related mortality and causal factors. At the same time, there has been relatively little attention given to non-lethal drought effects. As part...

  16. Representation of physiological drought at ecosystem level based on model and eddy covariance measurements

    Zhang, Y.; Novick, K. A.; Song, C.; Zhang, Q.; Hwang, T.


    Drought and heat waves are expected to increase both in frequency and amplitude, exhibiting a major disturbance to global carbon and water cycles under future climate change. However, how these climate anomalies translate into physiological drought, or ecosystem moisture stress are still not clear, especially under the co-limitations from soil moisture supply and atmospheric demand for water. In this study, we characterized the ecosystem-level moisture stress in a deciduous forest in the southeastern United States using the Coupled Carbon and Water (CCW) model and in-situ eddy covariance measurements. Physiologically, vapor pressure deficit (VPD) as an atmospheric water demand indicator largely controls the openness of leaf stomata, and regulates atmospheric carbon and water exchanges during periods of hydrological stress. Here, we tested three forms of VPD-related moisture scalars, i.e. exponent (K2), hyperbola (K3), and logarithm (K4) to quantify the sensitivity of light-use efficiency to VPD along different soil moisture conditions. The sensitivity indicators of K values were calibrated based on the framework of CCW using Monte Carlo simulations on the hourly scale, in which VPD and soil water content (SWC) are largely decoupled and the full carbon and water exchanging information are held. We found that three K values show similar performances in the predictions of ecosystem-level photosynthesis and transpiration after calibration. However, all K values show consistent gradient changes along SWC, indicating that this deciduous forest is less responsive to VPD as soil moisture decreases, a phenomena of isohydricity in which plants tend to close stomata to keep the leaf water potential constant and reduce the risk of hydraulic failure. Our study suggests that accounting for such isohydric information, or spectrum of moisture stress along different soil moisture conditions in models can significantly improve our ability to predict ecosystem responses to future

  17. Global Climate Model Simulated Hydrologic Droughts and Floods in the Nelson-Churchill Watershed

    Vieira, M. J. F.; Stadnyk, T. A.; Koenig, K. A.


    There is uncertainty surrounding the duration, magnitude and frequency of historical hydroclimatic extremes such as hydrologic droughts and floods prior to the observed record. In regions where paleoclimatic studies are less reliable, Global Climate Models (GCMs) can provide useful information about past hydroclimatic conditions. This study evaluates the use of Coupled Model Intercomparison Project 5 (CMIP5) GCMs to enhance the understanding of historical droughts and floods across the Canadian Prairie region in the Nelson-Churchill Watershed (NCW). The NCW is approximately 1.4 million km2 in size and drains into Hudson Bay in Northern Manitoba, Canada. One hundred years of observed hydrologic records show extended dry and wet periods in this region; however paleoclimatic studies suggest that longer, more severe droughts have occurred in the past. In Manitoba, where hydropower is the primary source of electricity, droughts are of particular interest as they are important for future resource planning. Twenty-three GCMs with daily runoff are evaluated using 16 metrics for skill in reproducing historic annual runoff patterns. A common 56-year historic period of 1950-2005 is used for this evaluation to capture wet and dry periods. GCM runoff is then routed at a grid resolution of 0.25° using the WATFLOOD hydrological model storage-routing algorithm to develop streamflow scenarios. Reservoir operation is naturalized and a consistent temperature scenario is used to determine ice-on and ice-off conditions. These streamflow simulations are compared with the historic record to remove bias using quantile mapping of empirical distribution functions. GCM runoff data from pre-industrial and future projection experiments are also bias corrected to obtain extended streamflow simulations. GCM streamflow simulations of more than 650 years include a stationary (pre-industrial) period and future periods forced by radiative forcing scenarios. Quantile mapping adjusts for magnitude

  18. Estimating carbon and showing impacts of drought using satellite data in regression-tree models

    Boyte, Stephen; Wylie, Bruce K.; Howard, Danny; Dahal, Devendra; Gilmanov, Tagir G.


    Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training data over large geographic spaces, allowing a better understanding of broad-scale ecosystem processes. The current study presents annual gross primary production (GPP) and annual ecosystem respiration (RE) for 2000–2013 in several short-statured vegetation types using carbon flux data from towers that are located strategically across the conterminous United States (CONUS). We calculate carbon fluxes (annual net ecosystem production [NEP]) for each year in our study period, which includes 2012 when drought and higher-than-normal temperatures influence vegetation productivity in large parts of the study area. We present and analyse carbon flux dynamics in the CONUS to better understand how drought affects GPP, RE, and NEP. Model accuracy metrics show strong correlation coefficients (r) (r ≥ 94%) between training and estimated data for both GPP and RE. Overall, average annual GPP, RE, and NEP are relatively constant throughout the study period except during 2012 when almost 60% less carbon is sequestered than normal. These results allow us to conclude that this modelling method effectively estimates carbon dynamics through time and allows the exploration of impacts of meteorological anomalies and vegetation types on carbon dynamics.

  19. Development and Evaluation of an Integrated Hydrological Modeling Framework for Monitoring and Understanding Floods and Droughts

    Yang, Z. L.; Wu, W. Y.; Lin, P.; Maidment, D. R.


    Extreme water events such as catastrophic floods and severe droughts have increased in recent decades. Mitigating the risk to lives, food security, infrastructure, energy supplies, as well as numerous other industries posed by these extreme events requires informed decision-making and planning based on sound science. We are developing a global water modeling capability by building models that will provide total operational water predictions (evapotranspiration, soil moisture, groundwater, channel flow, inundation, snow) at unprecedented spatial resolutions and updated frequencies. Toward this goal, this talk presents an integrated global hydrological modeling framework that takes advantage of gridded meteorological forcing, land surface modeling, channeled flow modeling, ground observations, and satellite remote sensing. Launched in August 2016, the National Water Model successfully incorporates weather forecasts to predict river flows for more than 2.7 million rivers across the continental United States, which transfers a "synoptic weather map" to a "synoptic river flow map" operationally. In this study, we apply a similar framework to a high-resolution global river network database, which is developed from a hierarchical Dominant River Tracing (DRT) algorithm, and runoff output from the Global Land Data Assimilation System (GLDAS) to a vector-based river routing model (The Routing Application for Parallel Computation of Discharge, RAPID) to produce river flows from 2001 to 2016 using Message Passing Interface (MPI) on Texas Advanced Computer Center's Stampede system. In this simulation, global river discharges for more than 177,000 rivers are computed every 30 minutes. The modeling framework's performance is evaluated with various observations including river flows at more than 400 gauge stations globally. Overall, the model exhibits a reasonably good performance in simulating the averaged patterns of terrestrial water storage, evapotranspiration and runoff. The

  20. Using plant growth modeling to analyse C source-sink relations under drought: inter and intra specific comparison

    Benoit ePallas


    Full Text Available The ability to assimilate C and allocate NSC (non structural carbohydrates to the most appropriate organs is crucial to maximize plant ecological or agronomic performance. Such C source and sink activities are differentially affected by environmental constraints. Under drought, plant growth is generally more sink than source limited as organ expansion or appearance rate is earlier and stronger affected than C assimilation. This favors plant survival and recovery but not always agronomic performance as NSC are stored rather than used for growth due to a modified metabolism in source and sink leaves. Such interactions between plant C and water balance are complex and plant modeling can help analyzing their impact on plant phenotype. This paper addresses the impact of trade-offs between C sink and source activities and plant production under drought, combining experimental and modeling approaches. Two contrasted monocotyledonous species (rice, oil palm were studied. Experimentally, the sink limitation of plant growth under moderate drought was confirmed as well as the modifications in NSC metabolism in source and sink organs. Under severe stress, when C source became limiting, plant NSC concentration decreased. Two plant models dedicated to oil palm and rice morphogenesis were used to perform a sensitivity analysis and further explore how to optimize C sink and source drought sensitivity to maximize plant growth. Modeling results highlighted that optimal drought sensitivity depends both on drought type and species and that modeling is a great opportunity to analyse such complex processes. Further modeling needs and more generally the challenge of using models to support complex trait breeding are discussed.

  1. Assessment of groundwater response to droughts in a complex runoff-dominated watershed by using an integrated hydrologic model

    Woolfenden, L. R.; Hevesi, J. A.; Nishikawa, T.


    Groundwater is an important component of the water supply, especially during droughts, within the Santa Rosa Plain watershed (SRPW), California, USA. The SRPW is 680 km2 and includes a network of natural and engineered stream channels. Streamflow is strongly seasonal, with high winter flows, predominantly intermittent summer flows, and comparatively rapid response time to larger storms. Groundwater flow is influenced primarily by complex geology, spatial and temporal variation in recharge, and pumping for urban, agricultural, and rural demands. Results from an integrated hydrologic model (GSFLOW) for the SRPW were analyzed to assess the effect of droughts on groundwater resources during water years 1976-2010. Model results indicate that, in general, below-average precipitation during historical drought periods reduced groundwater recharge (focused within stream channels and diffuse outside of channels on alluvial plains), groundwater evapotranspiration (ET), and groundwater discharge to streams (baseflow). In addition, recharge during wet periods was not sufficient to replenish groundwater-storage losses caused by drought and groundwater pumping, resulting in an overall 150 gigaliter loss in groundwater storage for water years 1976-2010. During drought periods, lower groundwater levels from reduced recharge broadly increased the number and length of losing-stream reaches, and seepage losses in streams became a higher percentage of recharge relative to the diffuse recharge outside of stream channels (for example, seepage losses in streams were 36% of recharge in 2006 and 57% at the end of the 2007-09 drought). Reductions in groundwater storage during drought periods resulted in decreased groundwater ET (loss of riparian habitat) and baseflow, especially during the warmer and dryer months (May through September) when groundwater is the dominant component of streamflow.

  2. Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change.

    Gustafson, Eric J; De Bruijn, Arjan M G; Pangle, Robert E; Limousin, Jean-Marc; McDowell, Nate G; Pockman, William T; Sturtevant, Brian R; Muss, Jordan D; Kubiske, Mark E


    Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS-II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short-term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon-juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought-induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

  3. Why Brazil Needed a New Market Model

    Pereira, Mario Veiga; Rosenblatt, Jose; Barroso, Luiz Augusto


    This paper discusses how the issue of supply adequacy is treated in the Brazilian power market, analyzing lessons learned from past experiences and describing the solutions that are being implemented to reconcile competition in generation with an adequate supply. The primary goal of the initial reform process is Brazil was to ensure sufficient capacity and investment to serve reliably the country's growing economy. This work discusses the difficulties that were identified in its design in terms of supply reliability and the proposals and reforms introduced by two governments to correct them and to implement a design that reconciles competition in generation with a guarantee of adequate supply. It is shown that, due to the high influence of hydroelectric power, Brazilian spot prices do not provide clear economic signals for system expansion, which in turn make bilateral contracts a key element in the market design. Another difficulty that must be addressed is the need to provide adequate expansion in an environment where there is high uncertainty on demand growth levels

  4. 2011 spring drought in France : Evaluation of the SURFEX land surface model.

    Lafont, S.; Barbu, A.; Szczypta, C.; Carrer, D.; Delire, C.; Calvet, J.-C.


    The spring of the year 2011 has been exceptionally dry in Western Europe. Over France, May 2011 has been one of the driest over the last 50 years. This event had a marked impact on vegetation development leading to very low value of the Leaf Area Index (LAI) during the growing season . In contrast, July 2011 has been in general wet and cold allowing a new vegetation development. This extreme event, followed by higher than normal rainfall is an excellent case-study to evaluate the capacity of a land surface model to simulate the drought impact on vegetation, and vegetation recovery after a drought. In this study, we used the SURFEX land surface model, in its ISBA-CC (CC stands for Carbon Cycle) configuration. The ISBA-CC version simulates the vegetation carbon cycle, interactive LAI and the carbon accumulation in wood and in the soil organic matter. This model is used by the GEOLAND2 Land Carbon Core Information Service. We performed 20-years simulations of SURFEX at high resolution (8 km) with atmospheric forcing from the SAFRAN dataset, an operational product over France. The vegetation map is provided by the ECOCLIMAP2 database. Following previous work that have confirmed a good simulation of the LAI inter-annual variability, this study investigates the ability of the model of reproducing the observed anomalies of LAI in 2011, in terms of timing and spatial patterns. We compare the simulated LAI with long time series (10 yr) of LAI derived from Earth Observation product within GEOLAND2 BIOPAR project. We quantify the anomalies of energy, water and carbon fluxes. We investigate the robustness of these results and the impact of modifying several important sub-modules of the model: soil texture, photosynthesis, and rainfall interception.

  5. Preparing the Dutch delta for future droughts: model based support in the national Delta Programme

    ter Maat, Judith; Haasnoot, Marjolijn; van der Vat, Marnix; Hunink, Joachim; Prinsen, Geert; Visser, Martijn


    Keywords: uncertainty, policymaking, adaptive policies, fresh water management, droughts, Netherlands, Dutch Deltaprogramme, physically-based complex model, theory-motivated meta-model To prepare the Dutch Delta for future droughts and water scarcity, a nation-wide 4-year project, called Delta Programme, is established to assess impacts of climate scenarios and socio-economic developments and to explore policy options. The results should contribute to a national adaptive plan that is able to adapt to future uncertain conditions, if necessary. For this purpose, we followed a model-based step-wise approach, wherein both physically-based complex models and theory-motivated meta-models were used. First step (2010-2011) was to make a quantitative problem description. This involved a sensitivity analysis of the water system for drought situations under current and future conditions. The comprehensive Dutch national hydrological instrument was used for this purpose and further developed. Secondly (2011-2012) our main focus was on making an inventory of potential actions together with stakeholders. We assessed efficacy, sell-by date of actions, and reassessed vulnerabilities and opportunities for the future water supply system if actions were (not) taken. A rapid assessment meta-model was made based on the complex model. The effects of all potential measures were included in the tool. Thirdly (2012-2013), with support of the rapid assessment model, we assessed the efficacy of policy actions over time for an ensemble of possible futures including sea level rise and climate and land use change. Last step (2013-2014) involves the selection of preferred actions from a set of promising actions that meet the defined objectives. These actions are all modeled and evaluated using the complex model. The outcome of the process will be an adaptive management plan. The adaptive plan describes a set of preferred policy pathways - sequences of policy actions - to achieve targets under

  6. Droughts in the US: Modeling and Forecasting for Agriculture-Water Management and Adaptation

    Perveen, S.; Devineni, N.; Lall, U.


    More than half of all US counties are currently mired in a drought that is considered the worst in decades. A persistent drought can not only lead to widespread impacts on water access with interstate implications (as has been shown in the Southeast US and Texas), chronic scarcity can emerge as a risk in regions where fossil aquifers have become the primary source of supply and are being depleted at rates much faster than recharge (e.g., Midwestern US). The standardized drought indices on which the drought declarations are made in the US so far consider only the static decision frameworks—where only the supply is the control variable and not the water consumption. If a location has low demands, drought as manifest in the usual indices does not really have "proportionate" social impact. Conversely, a modest drought as indicated by the traditional measures may have significant impacts where demand is close to the climatological mean value of precipitation. This may also lead to drought being declared too late or too soon. Against this fact, the importance of improved drought forecasting and preparedness for different sectors of the economy becomes increasingly important. The central issue we propose to address through this paper is the construction and testing of a drought index that considers regional water demands for specific purposes (e.g., crops, municipal use) and their temporal distribution over the year for continental US. Here, we have highlighted the use of the proposed index for three main sectors: (i) water management organizations, (ii) optimizing agricultural water use, and (iii) supply chain water risk. The drought index will consider day-to-day climate variability and sectoral demands to develop aggregate regional conditions or disaggregated indices for water users. For the daily temperature and precipitation data, we are using NLDAS dataset that is available from 1949 onwards. The national agricultural statistics services (NASS) online database has

  7. Impact of drought on morphological, physiological and nutrient use efficiency of elite cacao genotypes from Bahia-Brazil, Tarapoto-Peru and Puerto Rico-USA

    Worldwide, drought is considered one of the most limiting abiotic stress factors for cacao growth, development and production. A series of greenhouse and growth chamber experiments were undertaken to assess drought effects on early cacao morphological and physiological traits and nutrient use effici...

  8. A Drought Early Warning System Using System Dynamics Model and Seasonal Climate Forecasts: a case study in Hsinchu, Taiwan.

    Tien, Yu-Chuan; Tung, Ching-Ping; Liu, Tzu-Ming; Lin, Chia-Yu


    In the last twenty years, Hsinchu, a county of Taiwan, has experienced a tremendous growth in water demand due to the development of Hsinchu Science Park. In order to fulfill the water demand, the government has built the new reservoir, Baoshan second reservoir. However, short term droughts still happen. One of the reasons is that the water level of the reservoirs in Hsinchu cannot be reasonably forecasted, which sometimes even underestimates the severity of drought. The purpose of this study is to build a drought early warning system that projects the water levels of two important reservoirs, Baoshan and Baoshan second reservoir, and also the spatial distribution of water shortagewith the lead time of three months. Furthermore, this study also attempts to assist the government to improve water resources management. Hence, a system dynamics model of Touchien River, which is the most important river for public water supply in Hsinchu, is developed. The model consists of several important subsystems, including two reservoirs, water treatment plants and agricultural irrigation districts. Using the upstream flow generated by seasonal weather forecasting data, the model is able to simulate the storage of the two reservoirs and the distribution of water shortage. Moreover, the model can also provide the information under certain emergency scenarios, such as the accident or failure of a water treatment plant. At last, the performance of the proposed method and the original water resource management method that the government used were also compared. Keyword: Water Resource Management, Hydrology, Seasonal Climate Forecast, Reservoir, Early Warning, Drought

  9. The Future of Drought in the Southeastern U.S.: Projections from downscaled CMIP5 models

    Keellings, D.; Engstrom, J.


    The Southeastern U.S. has been repeatedly impacted by severe droughts that have affected the environment and economy of the region. In this study the ability of 32 downscaled CMIP5 models, bias corrected using localized constructed analogs (LOCA), to simulate historical observations of dry spells from 1950-2005 are assessed using Perkins skill scores and significance tests. The models generally simulate the distribution of dry days well but there are significant differences between the ability of the best and worst performing models, particularly when it comes to the upper tail of the distribution. The best and worst performing models are then projected through 2099, using RCP 4.5 and 8.5, and estimates of 20 year return periods are compared. Only the higher skill models provide a good estimate of extreme dry spell lengths with simulations of 20 year return values within ± 5 days of observed values across the region. Projected return values differ by model grouping, but all models exhibit significant increases.

  10. Mexican drought: an observational modeling and tree ring study of variability and climate change

    Seager, R.; Ting, M. [Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY (United States)]. E-mail:; Davis, M. [Department of History, University of California at Irvine, CA (United States); Cane, M.; Naik, N.; Nakamura, J.; Li, C.; Cook, E. [Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY (United States); Stahle, D.W. [Tree Ring Laboratory, University of Arkansas, Fayetteville, Arkansas (United States)


    Variability of Mexican hydroclimate, with special attention to persistent drought, is examined using observations, model simulations forced by historical sea surface temperature (SST), tree ring reconstructions of past climate and model simulations and projections of naturally and anthropogenically forced climate change. During the winter half year, hydroclimate across Mexico is influenced by the state of the tropical Pacific Ocean with the Atlantic playing little role. Mexican winters tend to be wetter during El Nino conditions. In the summer half year northern Mexico is also wetter when El Nino conditions prevail, but southern Mexico is drier. A warm tropical North Atlantic Ocean makes northern Mexico dry and southern Mexico wet. These relationships are reasonably well reproduced in ensembles of atmosphere model simulations forced by historical SST for the period from 1856 to 2002. Large ensembles of 100 day long integrations are used to examine the day to day evolution of the atmospheric circulation and precipitation in response to a sudden imposition of a El Nino SST anomaly in the summer half year. Kelvin waves propagate east and immediately cause increased column-integrated moisture divergence and reduced precipitation over the tropical Americas and Intra-America Seas. Within a few days a low level high pressure anomaly develops over the Gulf of Mexico. A forced nonlinear model is used to demonstrate that this low is forced by the reduced atmospheric heating over the tropical Atlantic-Intra-America Seas area. Tree ring reconstructions that extend back before the period of instrumental precipitation data coverage are used to verify long model simulations forced by historical SST. The early to mid 1950s drought in northern Mexico appears to have been the most severe since the mid nineteenth century and likely arose as a response to both a multiyear La Nina and a warm tropical North Atlantic. A drought in the 1890s was also severe and appears driven by a

  11. can tepary bean be a model for improvement of drought resistance ...

    Prof. Adipala Ekwamu

    levels of water supply (irrigated and rainfed). Results showed that two accessions of tepary bean, P. acutifolius. (G 40159 and G 40068) and two elite lines (RAB 650, SEA 23) of common bean were outstanding in their adaptation to terminal drought stress. The superior performance of these genotypes under drought stress ...

  12. Development of an agricultural drought assessment system : integration of agrohydrological modelling, remote sensing and geographical information

    Vazifedoust, M.


    Iran faces widespread droughts regularly, causing large economical and social damages. The agricultural sector is with 80-90 % by far the largest user of water in Iran and is often the first sector to be affected by drought. Unfortunately, water management in agriculture is also rather poor and

  13. Modeling forest mortality caused by drought stress: implications for climate change

    Eric J Gustafson; Brian R. Sturtevant


    Climate change is expected to affect forest landscape dynamics in many ways, but it is possible that the most important direct impact of climate change will be drought stress. We combined data from weather stations and forest inventory plots (FIA) across the upper Great Lakes region (USA) to study the relationship between measures of drought stress and mortality for...

  14. Analysis of agricultural drought in Iiuni, Eastern Kenya: Application of a Markov model

    Biamah, E.K.; Sterk, G.; Sharma, T.C.


    In semi-arid Kenya, episodes of agricultural droughts of varying severity and duration occur. The occurrence of these agricultural droughts is associated with seasonal rainfall variability and can be reflected by seasonal soil moisture deficits that significantly affect crop performance and yield.

  15. Measured and modelled leaf and stand-scale productivity across a soil moisture gradient and a severe drought.

    Wright, J K; Williams, M; Starr, G; McGee, J; Mitchell, R J


    Environmental controls on carbon dynamics operate at a range of interacting scales from the leaf to landscape. The key questions of this study addressed the influence of water and nitrogen (N) availability on Pinus palustris (Mill.) physiology and primary productivity across leaf and canopy scales, linking the soil-plant-atmosphere (SPA) model to leaf and stand-scale flux and leaf trait/canopy data. We present previously unreported ecophysiological parameters (e.g. V(cmax) and J(max)) for P. palustris and the first modelled estimates of its annual gross primary productivity (GPP) across xeric and mesic sites and under extreme drought. Annual mesic site P. palustris GPP was ∼23% greater than at the xeric site. However, at the leaf level, xeric trees had higher net photosynthetic rates, and water and light use efficiency. At the canopy scale, GPP was limited by light interception (canopy level), but co-limited by nitrogen and water at the leaf level. Contrary to expectations, the impacts of an intense growing season drought were greater at the mesic site. Modelling indicated a 10% greater decrease in mesic GPP compared with the xeric site. Xeric P. palustris trees exhibited drought-tolerant behaviour that contrasted with mesic trees' drought-avoidance behaviour. © 2012 Blackwell Publishing Ltd.

  16. Accelerated Growth Rate and Increased Drought Stress Resilience of the Model Grass Brachypodium distachyon Colonized by Bacillus subtilis B26.

    François Gagné-Bourque

    Full Text Available Plant growth-promoting bacteria (PGB induce positive effects in plants, for instance, increased growth and reduced abiotic stresses susceptibility. The mechanisms by which these bacteria impact the host plant are numerous, diverse and often specific. Here, we studied the agronomical, molecular and biochemical effects of the endophytic PGB Bacillus subtilis B26 on the full life cycle of Brachypodium distachyon Bd21, an established model species for functional genomics in cereal crops and temperate grasses. Inoculation of Brachypodium with B. subtilis strain B26 increased root and shoot weights, accelerated growth rate and seed yield as compared to control plants. B. subtilis strain B26 efficiently colonized the plant and was recovered from roots, stems and blades as well as seeds of Brachypodium, indicating that the bacterium is able to migrate, spread systemically inside the plant, establish itself in the aerial plant tissues and organs, and is vertically transmitted to seeds. The presence of B. subtilis strain B26 in the seed led to systemic colonization of the next generation of Brachypodium plants. Inoculated Brachypodium seedlings and mature plants exposed to acute and chronic drought stress minimized the phenotypic effect of drought compared to plants not harbouring the bacterium. Protection from the inhibitory effects of drought by the bacterium was linked to upregulation of the drought-response genes, DREB2B-like, DHN3-like and LEA-14-A-like and modulation of the DNA methylation genes, MET1B-like, CMT3-like and DRM2-like, that regulate the process. Additionally, total soluble sugars and starch contents increased in stressed inoculated plants, a biochemical indication of drought tolerance. In conclusion, we show a single inoculation of Brachypodium with a PGB affected the whole growth cycle of the plant, accelerating its growth rates, shortening its vegetative period, and alleviating drought stress effects. These effects are relevant to

  17. On the utility of land surface models for agricultural drought monitoring

    W. T. Crow


    Full Text Available The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (< 5% in relative terms in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5–15% in relative terms can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

  18. Quantifying human impacts on hydrological drought using a combined modelling approach in a tropical river basin in central Vietnam

    A. B. M. Firoz


    Full Text Available Hydrological droughts are one of the most damaging disasters in terms of economic loss in central Vietnam and other regions of South-east Asia, severely affecting agricultural production and drinking water supply. Their increasing frequency and severity can be attributed to extended dry spells and increasing water abstractions for e.g. irrigation and hydropower development to meet the demand of dynamic socioeconomic development. Based on hydro-climatic data for the period from 1980 to 2013 and reservoir operation data, the impacts of recent hydropower development and other alterations of the hydrological network on downstream streamflow and drought risk were assessed for a mesoscale basin of steep topography in central Vietnam, the Vu Gia Thu Bon (VGTB River basin. The Just Another Modelling System (JAMS/J2000 was calibrated for the VGTB River basin to simulate reservoir inflow and the naturalized discharge time series for the downstream gauging stations. The HEC-ResSim reservoir operation model simulated reservoir outflow from eight major hydropower stations as well as the reconstructed streamflow for the main river branches Vu Gia and Thu Bon. Drought duration, severity, and frequency were analysed for different timescales for the naturalized and reconstructed streamflow by applying the daily varying threshold method. Efficiency statistics for both models show good results. A strong impact of reservoir operation on downstream discharge at the daily, monthly, seasonal, and annual scales was detected for four discharge stations relevant for downstream water allocation. We found a stronger hydrological drought risk for the Vu Gia river supplying water to the city of Da Nang and large irrigation systems especially in the dry season. We conclude that the calibrated model set-up provides a valuable tool to quantify the different origins of drought to support cross-sectorial water management and planning in a suitable way to be transferred to similar

  19. Quantifying human impacts on hydrological drought using a combined modelling approach in a tropical river basin in central Vietnam

    Firoz, A. B. M.; Nauditt, Alexandra; Fink, Manfred; Ribbe, Lars


    Hydrological droughts are one of the most damaging disasters in terms of economic loss in central Vietnam and other regions of South-east Asia, severely affecting agricultural production and drinking water supply. Their increasing frequency and severity can be attributed to extended dry spells and increasing water abstractions for e.g. irrigation and hydropower development to meet the demand of dynamic socioeconomic development. Based on hydro-climatic data for the period from 1980 to 2013 and reservoir operation data, the impacts of recent hydropower development and other alterations of the hydrological network on downstream streamflow and drought risk were assessed for a mesoscale basin of steep topography in central Vietnam, the Vu Gia Thu Bon (VGTB) River basin. The Just Another Modelling System (JAMS)/J2000 was calibrated for the VGTB River basin to simulate reservoir inflow and the naturalized discharge time series for the downstream gauging stations. The HEC-ResSim reservoir operation model simulated reservoir outflow from eight major hydropower stations as well as the reconstructed streamflow for the main river branches Vu Gia and Thu Bon. Drought duration, severity, and frequency were analysed for different timescales for the naturalized and reconstructed streamflow by applying the daily varying threshold method. Efficiency statistics for both models show good results. A strong impact of reservoir operation on downstream discharge at the daily, monthly, seasonal, and annual scales was detected for four discharge stations relevant for downstream water allocation. We found a stronger hydrological drought risk for the Vu Gia river supplying water to the city of Da Nang and large irrigation systems especially in the dry season. We conclude that the calibrated model set-up provides a valuable tool to quantify the different origins of drought to support cross-sectorial water management and planning in a suitable way to be transferred to similar river basins.

  20. Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

    Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.


    Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

  1. Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors

    Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; De Stefano, Lucia; Vogt, Jürgen


    Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction

  2. Integration of Satellite, Global Reanalysis Data and Macroscale Hydrological Model for Drought Assessment in Sub-Tropical Region of India

    Pandey, V.; Srivastava, P. K.


    Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80 %) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.


    V. Pandey


    Full Text Available Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI. A macroscale hydrological model Variable Infiltration Capacity (VIC was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP and ESA's Climate Change Initiative soil moisture (CCI-SM data respectively. The analysis of results demonstrates that most of the study regions (> 80 % especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.

  4. Evidence-based modelling of diverse plant water use strategies on stomatal and non-stomatal components under drought

    zhou, S.; Prentice, C.; Medlyn, B. E.; Sabaté, S.


    Models disagree on how to represent effects of drought stress on plant gas exchange. Some models assume drought stress affects the marginal water use efficiency of plants (marginal WUE; i.e. the change in photosynthesis per unit of change in transpiration) whereas others assume drought stress acts directly on photosynthetic capacity. It is not clear whether either of these approaches is sufficient to capture the drought response, or whether the effect of drought varies among species and functional types. A collection of Eucalyptus and Quercus species derived from different hydro-climate habitats, in together with two European riparian species, were conducted with drought treatments respectively in Australia and Spain for three months. Measurements included net CO2 assimilation rate versus substomatal CO2 concentration (A-Ci) curves, fluorescence, and predawn leaf water potential at increasing levels of water stress. The correlations with quantitative plant traits of leaf, stomata, vessel, and wood density, leaf nitrogen content and 13C discrimination were also explored. We analysed the effect of drought effect on leaf gas exchange with a recently developed stomatal model that reconciles the empirical and optimal approaches on predicting optimal stomatal conductance. The model's single parameter g1 is a decreasing function of marginal WUE. The two genera showed consistence on the contrasting response patterns between species derived from mesic and arid habitats, which differed greatly in their estimated g1 values under moist conditions, and in the rate at which g1 declined with water stress. They also differed greatly in the predawn water potential at which apparent carboxylation capacity (apparent Vcmax) and mesophyll conductance (gm) declined most steeply, and in the steepness of this decline. Principal components analysis revealed a gradient in water relation strategies from sclerophyll species to malacophyll species. Malacophylls had higher g1, apparent Vcmax

  5. Irrigated Agriculture in Morocco: An Agent-Based Model of Adaptation and Decision Making Amid Increasingly Frequent Drought Events

    Norton, M.


    In the past 100 years, Morocco has undertaken a heavy investment in developing water infrastructure that has led to a dramatic expansion of irrigated agriculture. Irrigated agriculture is the primary user of water in many arid countries, often accounting for 80-90% of total water usage. Irrigation is adopted by farmers not only because it leads to increased production, but also because it improves resilience to an uncertain climate. However, the Mediterranean region as a whole has also seen an increase in the frequency and severity of drought events. These droughts have had a dramatic impact on farmer livelihoods and have led to a number of coping strategies, including the adoption or disadoption of irrigation. In this study, we use a record of the annual extent of irrigated agriculture in Morocco to model the effect of drought on the extent of irrigated agriculture. Using an agent-based socioeconomic model, we seek to answer the following questions: 1) Do farmers expand irrigated agriculture in response to droughts? 2) Do drought events entail the removal of perennial crops like orchards? 3) Can we detect the retreat of irrigated agriculture in the more fragile watersheds of Morocco? Understanding the determinants of irrigated crop expansion and contractions will help us understand how agro-ecological systems transition from 20th century paradigms of expansion of water supply to a 21st century paradigm of water use efficiency. The answers will become important as countries learn how to manage water in new climate regimes characterized by less reliable and available precipitation.

  6. Developing drought impact functions for drought risk management

    S. Bachmair


    Full Text Available Drought management frameworks are dependent on methods for monitoring and prediction, but quantifying the hazard alone is arguably not sufficient; the negative consequences that may arise from a lack of precipitation must also be predicted if droughts are to be better managed. However, the link between drought intensity, expressed by some hydrometeorological indicator, and the occurrence of drought impacts has only recently begun to be addressed. One challenge is the paucity of information on ecological and socioeconomic consequences of drought. This study tests the potential for developing empirical drought impact functions based on drought indicators (Standardized Precipitation and Standardized Precipitation Evaporation Index as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. While there have been studies exploiting textual evidence of drought impacts, a systematic assessment of the effect of impact quantification method and different functional relationships for modeling drought impacts is missing. Using Southeast England as a case study we tested the potential of three different data-driven models for predicting drought impacts quantified from text-based reports: logistic regression, zero-altered negative binomial regression (hurdle model, and an ensemble regression tree approach (random forest. The logistic regression model can only be applied to a binary impact/no impact time series, whereas the other two models can additionally predict the full counts of impact occurrence at each time point. While modeling binary data results in the lowest prediction uncertainty, modeling the full counts has the advantage of also providing a measure of impact severity, and the counts were found to be reasonably predictable. However, there were noticeable differences in skill between modeling methodologies. For binary data the logistic regression and the random forest model performed similarly well based on

  7. A study of 2014 record drought in India with CFSv2 model: role of water vapor transport

    Ramakrishna, S. S. V. S.; Brahmananda Rao, V.; Srinivasa Rao, B. R.; Hari Prasad, D.; Nanaji Rao, N.; Panda, Roshmitha


    The Indian summer monsoon season of 2014 was erratic and ended up with a seasonal rainfall deficit of 12 % and a record drought in June. In this study we analyze the moisture transport characteristics for the monsoon season of 2014 using both NCEP FNL reanalysis (FNL) and CFSv2 (CFS) model data. In FNL, in June 2014 there was a large area of divergence of moisture flux. In other months also there was lesser flux. This probably is the cause of 2014 drought. The CFS model overestimated the drought and it reproduces poorly the observed rainfall over central India (65E–95E; 5N–35N). The correlation coefficient (CC) between the IMD observed rainfall and CFS model rainfall is only 0.1 while the CC between rainfall and moisture flux convergence in CFS model is only 0.20 and with FNL data −0.78. This clearly shows that the CFS model has serious difficulty in reproducing the moisture flux convergence and rainfall. We found that the rainfall variations are strongly related to the moisture convergence or divergence. The hypothesis of Krishnamurti et al. (J Atmos Sci 67:3423–3441, 2010) namely the intrusion of west African desert air and the associated low convective available potential energy inhibiting convection and rainfall shows some promise to explain dry spells in Indian summer monsoon. However, the rainfall or lack of it is mainly explained by convergence or divergence of moisture flux. © 2016 Springer-Verlag Berlin Heidelberg

  8. A study of 2014 record drought in India with CFSv2 model: role of water vapor transport

    Ramakrishna, S. S. V. S.


    The Indian summer monsoon season of 2014 was erratic and ended up with a seasonal rainfall deficit of 12 % and a record drought in June. In this study we analyze the moisture transport characteristics for the monsoon season of 2014 using both NCEP FNL reanalysis (FNL) and CFSv2 (CFS) model data. In FNL, in June 2014 there was a large area of divergence of moisture flux. In other months also there was lesser flux. This probably is the cause of 2014 drought. The CFS model overestimated the drought and it reproduces poorly the observed rainfall over central India (65E–95E; 5N–35N). The correlation coefficient (CC) between the IMD observed rainfall and CFS model rainfall is only 0.1 while the CC between rainfall and moisture flux convergence in CFS model is only 0.20 and with FNL data −0.78. This clearly shows that the CFS model has serious difficulty in reproducing the moisture flux convergence and rainfall. We found that the rainfall variations are strongly related to the moisture convergence or divergence. The hypothesis of Krishnamurti et al. (J Atmos Sci 67:3423–3441, 2010) namely the intrusion of west African desert air and the associated low convective available potential energy inhibiting convection and rainfall shows some promise to explain dry spells in Indian summer monsoon. However, the rainfall or lack of it is mainly explained by convergence or divergence of moisture flux. © 2016 Springer-Verlag Berlin Heidelberg

  9. Assessings impact of drought on water resources management in the Middle East using the GRACE data and hydrological modeling

    Rateb, A., II; Kuo, C. Y.; Imani, M.; Kao, H. C.; Shum, C. K.; Ching, K. E.; Tseng, K. H.; Lan, W. H.; Tseng, T. P.


    The Middle East (ME) region experiences severe freshwater shortages in 90% of the region due primarily to its semi-arid landscape and climate setting, the growth of its population which outpaces world's average population rate by 3.7%, and rapid economic development. The prolonged and intense drought which started in 2007 resulted in the significant decline of surface water availability in the Tigris-Euphrates basin, and exacerbated the anthropogenic groundwater extraction rate, which declined the productivity of agriculture, and displaced hundreds of thousands of people. Therefore, evaluating the impact of the drought on the total water storage (TWS) and groundwater storage (GWS) decline is critical to quantify water availability, towards more effective water resources management in the region. In this study, we use the monthly Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission gravity solutions, covering April 2002 through December 2015, and hydrological models (GLDAS, CLM4.5, and WGHM2.2b) to monitor the TWS and GWS before and after the onset of the pronged drought which started in 2007. We built an effective Slepian basis concentrated over the Arabian Peninsula (AP) and six regions, including Iran, Iraq, North AP, South AP, Syria-Jordan, and Eastern Turkey, to characterize the impact of the drought at the country scale. The results show that the drought has resulted in further reducing the TWS and GWS depletion rate by more than 50%. The ME region experienced a small negative trend between 2002 and 2007, and then the trend dropped dramatically after 2007. The worst affected regions are northern Iraq, northwestern Iran, and North AP. We compared the estimates with agriculture irrigation maps and characterized the depletion rates have been primarily caused by agriculture irrigation, which is directly linked to the pronged drought. Droughts are arguably longer in duration, more frequency and more intense in an increasingly warmer climate. The

  10. Global drought and severe drought-affected populations in 1.5 and 2 °C warmer worlds

    Liu, Wenbin; Sun, Fubao; Lim, Wee Ho; Zhang, Jie; Wang, Hong; Shiogama, Hideo; Zhang, Yuqing


    The 2015 Paris Agreement proposed a more ambitious climate change mitigation target on limiting global warming to 1.5 °C instead of 2 °C above preindustrial levels. Scientific investigations on environmental risks associated with these warming targets are necessary to inform climate policymaking. Based on the Coupled Model Intercomparison Project phase 5 (CMIP5) climate models, we present the first risk-based assessment of changes in global drought and the impact of severe drought on populations from additional 1.5 and 2 °C warming conditions. Our results highlight the risk of drought on a global scale and in several hotspot regions such as the Amazon, northeastern Brazil, southern Africa and Central Europe at both 1.5 and 2 °C global warming relative to the historical period, showing increases in drought durations from 2.9 to 3.2 months. Correspondingly, more total and urban populations would be exposed to severe droughts globally (+132.5 ± 216.2 million and +194.5 ± 276.5 million total population and +350.2 ± 158.8 million and +410.7 ± 213.5 million urban populations in 1.5 and 2 °C warmer worlds) and regionally (e.g., East Africa, West Africa and South Asia). Less rural populations (-217.7 ± 79.2 million and -216.2 ± 82.4 million rural populations in 1.5 and 2 °C warmer worlds) would be exposed to severe drought globally under climate warming, population growth and especially the urbanization-induced population migration. By keeping global warming at 1.5 °C above the preindustrial levels instead of 2 °C, there is a decrease in drought risks (i.e., less drought duration, less drought intensity and severity but relatively more frequent drought) and the affected total, urban and rural populations would decrease globally and in most regions. While challenging for both East Africa and South Asia, the benefits of limiting warming to below 1.5 °C in terms of global drought risk and impact reduction are significant.

  11. Influence of landscape heterogeneity on water available to tropical forests in an Amazonian catchment and implications for modeling drought response

    Fang, Yilin; Leung, L. Ruby; Duan, Zhuoran; Wigmosta, Mark S.; Maxwell, Reed M.; Chambers, Jeffrey Q.; Tomasella, Javier


    The Amazon basin has experienced periodic droughts in the past, and intense and frequent droughts are predicted in the future. Landscape heterogeneity could play an important role in how tropical forests respond to drought by influencing water available to plants. Using the one-dimensional ACME Land Model and the three-dimensional ParFlow variably saturated flow model, numerical experiments were performed for a catchment in central Amazon to elucidate processes that influence water available for plant use and provide insights for improving Earth system models. Results from ParFlow show that topography has a dominant influence on groundwater table and runoff through lateral flow. Without any representations of lateral processes, ALM simulates very different seasonal variations in groundwater table and runoff compared to ParFlow even if it is able to reproduce the long-term spatial average groundwater table of ParFlow through simple parameter calibration. In the ParFlow simulations, even in the plateau with much deeper water table depth during the dry season in the drought year of 2005, plant transpiration is not water stressed as the soil saturation is still sufficient for the stomata to be fully open based on the empirical wilting formulation in the models. This finding is insensitive to uncertainty in atmospheric forcing and soil parameters, but the empirical wilting formulation is an important factor that should be addressed using observations and modeling of coupled plant hydraulics-soil hydrology processes in future studies. The results could be applicable to other catchments in the Amazon basin with similar seasonal variability and hydrologic regimes.

  12. Drought Early Warning and Agro-Meteorological Risk Assessment using Earth Observation Rainfall Datasets and Crop Water Budget Modelling

    Tarnavsky, E.


    The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.

  13. Comparison of childbirth care models in public hospitals, Brazil.

    Vogt, Sibylle Emilie; Silva, Kátia Silveira da; Dias, Marcos Augusto Bastos


    To compare collaborative and traditional childbirth care models. Cross-sectional study with 655 primiparous women in four public health system hospitals in Belo Horizonte, MG, Southeastern Brazil, in 2011 (333 women for the collaborative model and 322 for the traditional model, including those with induced or premature labor). Data were collected using interviews and medical records. The Chi-square test was used to compare the outcomes and multivariate logistic regression to determine the association between the model and the interventions used. Paid work and schooling showed significant differences in distribution between the models. Oxytocin (50.2% collaborative model and 65.5% traditional model; p relief (85.0% collaborative model and 78.9% traditional model; p = 0.042). The association between the collaborative model and the reduction in the use of oxytocin, artificial rupture of membranes and episiotomy remained after adjustment for confounding. The care model was not associated with complications in newborns or mothers neither with the use of spinal or epidural analgesia. The results suggest that collaborative model may reduce interventions performed in labor care with similar perinatal outcomes.

  14. Toward Understanding Dynamics in Shifting Biomes: An Individual Based Modeling Approach to Characterizing Drought and Mortality in Central Western Canada

    Armstrong, A. H.; Foster, A.; Rogers, B. M.; Hogg, T.; Michaelian, M.; Shuman, J. K.; Shugart, H. H., Jr.; Goetz, S. J.


    The Arctic-Boreal zone is known be warming at an accelerated rate relative to other biomes. Persistent warming has already affected the high northern latitudes, altering vegetation productivity, carbon sequestration, and many other ecosystem processes and services. The central-western Canadian boreal forests and aspen parkland are experiencing a decade long drought, and rainfall has been identified as a key factor controlling the location of the boundary between forest and prairie in this region. Shifting biome with related greening and browning trends are readily measureable with remote sensing, but the dynamics that create and result from them are not well understood. In this study, we use the University of Virginia Forest Model Enhanced (UVAFME), an individual-based forest model, to simulate the changes that are occurring across the southern boreal and parkland forests of west-central Canada. We present a parameterization of UVAFME for western central Canadian forests, validated with CIPHA data (Climate Change Impacts on the Productivity and Health of Aspen), and improved mortality. In order to gain a fine-scale understanding of how climate change and specifically drought will continue to affect the forests of this region, we simulated forest conditions following CMIP5 climate scenarios. UVAFME predictions were compared with statistical models and satellite observations of productivity across the landscape. Changes in forest cover, forest type, aboveground biomass, and mortality and recruitment dynamics are presented, highlighting the high vulnerability of this region to vegetation transitions associated with future droughts.

  15. Bayesian geostatistical modeling of leishmaniasis incidence in Brazil.

    Dimitrios-Alexios Karagiannis-Voules

    Full Text Available BACKGROUND: Leishmaniasis is endemic in 98 countries with an estimated 350 million people at risk and approximately 2 million cases annually. Brazil is one of the most severely affected countries. METHODOLOGY: We applied Bayesian geostatistical negative binomial models to analyze reported incidence data of cutaneous and visceral leishmaniasis in Brazil covering a 10-year period (2001-2010. Particular emphasis was placed on spatial and temporal patterns. The models were fitted using integrated nested Laplace approximations to perform fast approximate Bayesian inference. Bayesian variable selection was employed to determine the most important climatic, environmental, and socioeconomic predictors of cutaneous and visceral leishmaniasis. PRINCIPAL FINDINGS: For both types of leishmaniasis, precipitation and socioeconomic proxies were identified as important risk factors. The predicted number of cases in 2010 were 30,189 (standard deviation [SD]: 7,676 for cutaneous leishmaniasis and 4,889 (SD: 288 for visceral leishmaniasis. Our risk maps predicted the highest numbers of infected people in the states of Minas Gerais and Pará for visceral and cutaneous leishmaniasis, respectively. CONCLUSIONS/SIGNIFICANCE: Our spatially explicit, high-resolution incidence maps identified priority areas where leishmaniasis control efforts should be targeted with the ultimate goal to reduce disease incidence.

  16. How climate seasonality modifies drought duration and deficit

    Loon, van A.F.; Tijdeman, E.; Wanders, N.; Lanen, van H.A.J.; Teuling, A.J.; Uijlenhoet, R.


    Drought propagation through the terrestrial hydrological cycle is associated with a change in drought characteristics (duration and deficit), moving from precipitation via soil moisture to discharge. Here we investigate climate controls on drought propagation with a modeling experiment in 1271

  17. Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding.

    Ndour, Adama; Vadez, Vincent; Pradal, Christophe; Lucas, Mikaël


    Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA) phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding.

  18. Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding

    Adama Ndour


    Full Text Available Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding.

  19. Analysis of Current and Future SPEI Droughts in the La Plata Basin Based on Results from the Regional Eta Climate Model

    Alvaro Sordo-Ward


    Full Text Available We identified and analysed droughts in the La Plata Basin (divided into seven sub-basins for the current period (1961–2005 and estimated their expected evolution under future climate projections for the periods 2011–2040, 2041–2070, and 2071–2099. Future climate projections were analysed from results of the Eta Regional Climate Model (grid resolution of approximately 10 km forced by the global climate model HadGEM2-ES over the La Plata basin, and considering a RCP4.5 emission scenario. Within each sub-basin, we particularly focused our drought analyses on croplands and grasslands, due to their economic relevance. The three-month Standardized Precipitation Evapotranspiration Index (SPEI3 was used for drought identification and characterization. Droughts were evaluated in terms of time (percentage of time from the total length of each climate scenario, space (percentage of total area, and severity (SPEI3 values of cells characterized by cropland and grassland for each sub-basin and climate scenario. Drought-severity–area–frequency curves were developed to quantitatively relate the frequency distribution of drought occurrence to drought severity and area. For the period 2011–2040, droughts dominate the northern sub-basins, whereas alternating wet and short dry periods dominate the southern sub-basins. Wet climate spread from south to north within the La Plata Basin as more distant future scenarios were analysed, due to both a greater number of wet periods and fewer droughts. The area of each sub-basin affected by drought in all climate scenarios was highly varied temporally and spatially. The likelihood of the occurrence of droughts differed significantly between the studied cover types in the Lower Paraguay sub-basin, being higher for cropland than for grassland. Mainly in the Upper Paraguay and in the Upper Paraná basins the climate projections for all scenarios showed an increase of moderate and severe droughts over large regions

  20. Modeling the hepatitis A epidemiological transition in Brazil and Mexico.

    Van Effelterre, Thierry; Guignard, Adrienne; Marano, Cinzia; Rojas, Rosalba; Jacobsen, Kathryn H


    Many low- to middle-income countries have completed or are in the process of transitioning from high or intermediate to low endemicity for hepatitis A virus (HAV). Because the risk of severe hepatitis A disease increases with age at infection, decreased incidence that leaves older children and adults susceptible to HAV infection may actually increase the population-level burden of disease from HAV. Mathematical models can be helpful for projecting future epidemiological profiles for HAV. An age-specific deterministic, dynamic compartmental transmission model with stratification by setting (rural versus urban) was calibrated with country-specific data on demography, urbanization, and seroprevalence of anti-HAV antibodies. HAV transmission was modeled as a function of setting-specific access to safe water. The model was then used to project various HAV-related epidemiological outcomes in Brazil and in Mexico from 1950 to 2050. The projected epidemiological outcomes were qualitatively similar in the 2 countries. The age at the midpoint of population immunity (AMPI) increased considerably and the mean age of symptomatic HAV cases shifted from childhood to early adulthood. The projected overall incidence rate of HAV infections decreased by about two thirds as safe water access improved. However, the incidence rate of symptomatic HAV infections remained roughly the same over the projection period. The incidence rates of HAV infections (all and symptomatic alone) were projected to become similar in rural and urban settings in the next decades. This model featuring population age structure, urbanization and access to safe water as key contributors to the epidemiological transition for HAV was previously validated with data from Thailand and fits equally well with data from Latin American countries. Assuming no introduction of a vaccination program over the projection period, both Brazil and Mexico were projected to experience a continued decrease in HAV incidence rates

  1. Spatiotemporal Drought Analysis and Drought Indices Comparison in India

    Janardhanan, A.


    Droughts and floods are an ever-occurring phenomenon that has been wreaking havoc on humans since the start of time. As droughts are on a very large scale, studying them within a regional context can minimize confounding factors such as climate change. Droughts and floods are extremely erratic and very difficult to predict and therefore necessitate modeling through advanced statistics. The SPI (Standard Precipitation Index) and the SPEI (Standard Precipitation Evapotranspiration Index) are two ways to temporally model drought and flood patterns across each metrological sub basin in India over a variety of different time scales. SPI only accounts for precipitation values, while the SPEI accounts for both precipitation and temperature and is commonly regarded as a more reliable drought index. Using monthly rainfall and temperature data from 1871-2016, these two indices were calculated. The results depict the drought and flood severity index, length of drought, and average SPI or SPEI value for each meteorological sub region in India. A Wilcox Ranksum test was then conducted to determine whether these two indices differed over the long term for drought analysis. The drought return periods were analyzed to determine if the population mean differed between the SPI and SPEI values. Our analysis found no statistical difference between SPI and SPEI with regards to long-term drought analysis. This indicates that temperature is not needed when modeling drought on a long-term time scale and that SPI is just as effective as SPEI, which has the potential to save a lot of time and resources on calculating drought indices.

  2. Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

    Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.


    Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts

  3. Coupling a global climatic model with insurance impact models for flood and drought: an estimation of the financial impact of climate change

    Tinard Pierre


    Full Text Available CCR, a French reinsurance company mostly involved in natural disasters coverage in France, has been developing tools for the estimation of its exposure to climatic risks for many years. Both a flood and a drought models were developed and calibrated on a large policies and claims database supplied every year with insurers’ data. More recently, CCR has been developing a stochastic approach in order to evaluate its financial exposure to extreme events. A large and realistic event set has been generated by applying extreme value statistic tools to simulate hazard and to estimate, using our impact models, the average annual losses and losses related to different return periods. These event sets have been simulated separately for flood and drought, with a hypothesis of independence, consistent with recent annual damage data. The newest development presented here consists in the use of the ARPEGE–Climat model performed by Météo-France to simulate two 200-years sets of hourly atmospheric time series reflecting both the current climate and the RCP 4.5 climate conditions circa year 2050. These climatic data constitute the input data for the flood and drought impact models to detect events and simulate the associated hazard and damages. Our two main goals are (1 to simulate simultaneously flood and drought events for the same simulated years and (2 to evaluate the financial impact of climate change.

  4. A new space-time characterization of Northern Hemisphere drought in model simulations of the past and future as compared to the paleoclimate record

    Coats, S.; Smerdon, J. E.; Stevenson, S.; Fasullo, J.; Otto-Bliesner, B. L.


    The observational record, which provides only limited sampling of past climate variability, has made it difficult to quantitatively analyze the complex spatio-temporal character of drought. To provide a more complete characterization of drought, machine learning based methods that identify drought in three-dimensional space-time are applied to climate model simulations of the last millennium and future, as well as tree-ring based reconstructions of hydroclimate over the Northern Hemisphere extratropics. A focus is given to the most persistent and severe droughts of the past 1000 years. Analyzing reconstructions and simulations in this context allows for a validation of the spatio-temporal character of persistent and severe drought in climate model simulations. Furthermore, the long records provided by the reconstructions and simulations, allows for sufficient sampling to constrain projected changes to the spatio-temporal character of these features using the reconstructions. Along these lines, climate models suggest that there will be large increases in the persistence and severity of droughts over the coming century, but little change in their spatial extent. These models, however, exhibit biases in the spatio-temporal character of persistent and severe drought over parts of the Northern Hemisphere, which may undermine their usefulness for future projections. Despite these limitations, and in contrast to previous claims, there are no systematic changes in the character of persistent and severe droughts in simulations of the historical interval. This suggests that climate models are not systematically overestimating the hydroclimate response to anthropogenic forcing over this period, with critical implications for confidence in hydroclimate projections.

  5. A hot future for European droughts

    Teuling, Adriaan J.


    Low soil moisture conditions can induce drought but also elevate temperatures. Detailed modelling of the drought-temperature link now shows that rising global temperature will bring drier soils and higher heatwave temperatures in Europe.

  6. Elusive drought: uncertainty in observed trends and short- and long-term CMIP5 projections

    B. Orlowsky


    Full Text Available Recent years have seen a number of severe droughts in different regions around the world, causing agricultural and economic losses, famines and migration. Despite their devastating consequences, the Standardised Precipitation Index (SPI of these events lies within the general range of observation-based SPI time series and simulations from the 5th phase of the Coupled Model Intercomparison Project (CMIP5. In terms of magnitude, regional trends of SPI over the last decades remain mostly inconclusive in observation-based datasets and CMIP5 simulations, but Soil Moisture Anomalies (SMAs in CMIP5 simulations hint at increased drought in a few regions (e.g., the Mediterranean, Central America/Mexico, the Amazon, North-East Brazil and South Africa. Also for the future, projections of changes in the magnitude of meteorological (SPI and soil moisture (SMA drought in CMIP5 display large spreads over all time frames, generally impeding trend detection. However, projections of changes in the frequencies of future drought events display more robust signal-to-noise ratios, with detectable trends towards more frequent drought before the end of the 21st century in the Mediterranean, South Africa and Central America/Mexico. Other present-day hot spots are projected to become less drought-prone, or display non-significant changes in drought occurrence. A separation of different sources of uncertainty in projections of meteorological and soil moisture drought reveals that for the near term, internal climate variability is the dominant source, while the formulation of Global Climate Models (GCMs generally becomes the dominant source of spread by the end of the 21st century, especially for soil moisture drought. In comparison, the uncertainty from Green-House Gas (GHG concentrations scenarios is negligible for most regions. These findings stand in contrast to respective analyses for a heat wave index, for which GHG concentrations scenarios constitute the main source

  7. The bioeconomic implications of various drought management ...

    Keywords: Drought management strategies; Herd structures; KwaZulu/Natal; Labour costs; Net present values; Simulation modelling; drought; drought management; management strategy; cattle; semi-arid; savanna; south africa; net present value; simulation model; domestic stock; economics. African Journal of Range ...

  8. Non-linear effects of drought under shade: reconciling physiological and ecological models in plant communities

    Holmgren, M.; Gomez-Aparicio, L.; Quero, J.L.; Valladares, F.


    The combined effects of shade and drought on plant performance and the implications for species interactions are highly debated in plant ecology. Empirical evidence for positive and negative effects of shade on the performance of plants under dry conditions supports two contrasting theoretical

  9. Increased drought impacts on temperate rainforests from southern South America: results of a process-based, dynamic forest model.

    Alvaro G Gutiérrez

    Full Text Available Increased droughts due to regional shifts in temperature and rainfall regimes are likely to affect forests in temperate regions in the coming decades. To assess their consequences for forest dynamics, we need predictive tools that couple hydrologic processes, soil moisture dynamics and plant productivity. Here, we developed and tested a dynamic forest model that predicts the hydrologic balance of North Patagonian rainforests on Chiloé Island, in temperate South America (42°S. The model incorporates the dynamic linkages between changing rainfall regimes, soil moisture and individual tree growth. Declining rainfall, as predicted for the study area, should mean up to 50% less summer rain by year 2100. We analysed forest responses to increased drought using the model proposed focusing on changes in evapotranspiration, soil moisture and forest structure (above-ground biomass and basal area. We compared the responses of a young stand (YS, ca. 60 years-old and an old-growth forest (OG, >500 years-old in the same area. Based on detailed field measurements of water fluxes, the model provides a reliable account of the hydrologic balance of these evergreen, broad-leaved rainforests. We found higher evapotranspiration in OG than YS under current climate. Increasing drought predicted for this century can reduce evapotranspiration by 15% in the OG compared to current values. Drier climate will alter forest structure, leading to decreases in above ground biomass by 27% of the current value in OG. The model presented here can be used to assess the potential impacts of climate change on forest hydrology and other threats of global change on future forests such as fragmentation, introduction of exotic tree species, and changes in fire regimes. Our study expands the applicability of forest dynamics models in remote and hitherto overlooked regions of the world, such as southern temperate rainforests.

  10. Increased drought impacts on temperate rainforests from southern South America: results of a process-based, dynamic forest model.

    Gutiérrez, Alvaro G; Armesto, Juan J; Díaz, M Francisca; Huth, Andreas


    Increased droughts due to regional shifts in temperature and rainfall regimes are likely to affect forests in temperate regions in the coming decades. To assess their consequences for forest dynamics, we need predictive tools that couple hydrologic processes, soil moisture dynamics and plant productivity. Here, we developed and tested a dynamic forest model that predicts the hydrologic balance of North Patagonian rainforests on Chiloé Island, in temperate South America (42°S). The model incorporates the dynamic linkages between changing rainfall regimes, soil moisture and individual tree growth. Declining rainfall, as predicted for the study area, should mean up to 50% less summer rain by year 2100. We analysed forest responses to increased drought using the model proposed focusing on changes in evapotranspiration, soil moisture and forest structure (above-ground biomass and basal area). We compared the responses of a young stand (YS, ca. 60 years-old) and an old-growth forest (OG, >500 years-old) in the same area. Based on detailed field measurements of water fluxes, the model provides a reliable account of the hydrologic balance of these evergreen, broad-leaved rainforests. We found higher evapotranspiration in OG than YS under current climate. Increasing drought predicted for this century can reduce evapotranspiration by 15% in the OG compared to current values. Drier climate will alter forest structure, leading to decreases in above ground biomass by 27% of the current value in OG. The model presented here can be used to assess the potential impacts of climate change on forest hydrology and other threats of global change on future forests such as fragmentation, introduction of exotic tree species, and changes in fire regimes. Our study expands the applicability of forest dynamics models in remote and hitherto overlooked regions of the world, such as southern temperate rainforests.

  11. Experimental prediction of severe droughts on seasonal to intra-annual time scales with GFDL High-Resolution Atmosphere Model

    Yu, Z.; Lin, S.


    Regional heat waves and drought have major economic and societal impacts on regional and even global scales. For example, during and following the 2010-2011 La Nina period, severe droughts have been reported in many places around the world including China, the southern US, and the east Africa, causing severe hardship in China and famine in east Africa. In this study, we investigate the feasibility and predictability of severe spring-summer draught events, 3 to 6 months in advance with the 25-km resolution Geophysical Fluid Dynamics Laboratory High-Resolution Atmosphere Model (HiRAM), which is built as a seamless weather-climate model, capable of long-term climate simulations as well as skillful seasonal predictions (e.g., Chen and Lin 2011, GRL). We adopted a similar methodology and the same (HiRAM) model as in Chen and Lin (2011), which is used successfully for seasonal hurricane predictions. A series of initialized 7-month forecasts starting from Dec 1 are performed each year (5 members each) during the past decade (2000-2010). We will then evaluate the predictability of the severe drought events during this period by comparing model predictions vs. available observations. To evaluate the predictive skill, in this preliminary report, we will focus on the anomalies of precipitation, sea-level-pressure, and 500-mb height. These anomalies will be computed as the individual model prediction minus the mean climatology obtained by an independent AMIP-type "simulation" using observed SSTs (rather than using predictive SSTs in the forecasts) from the same model.

  12. Hydrogeological characterisation of groundwater over Brazil using remotely sensed and model products.

    Hu, Kexiang; Awange, Joseph L; Khandu; Forootan, Ehsan; Goncalves, Rodrigo Mikosz; Fleming, Kevin


    For Brazil, a country frequented by droughts and whose rural inhabitants largely depend on groundwater, reliance on isotope for its monitoring, though accurate, is expensive and limited in spatial coverage. We exploit total water storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) satellites to analyse spatial-temporal groundwater changes in relation to geological characteristics. Large-scale groundwater changes are estimated using GRACE-derived TWS and altimetry observations in addition to GLDAS and WGHM model outputs. Additionally, TRMM precipitation data are used to infer impacts of climate variability on groundwater fluctuations. The results indicate that climate variability mainly controls groundwater change trends while geological properties control change rates, spatial distribution, and storage capacity. Granular rocks in the Amazon and Guarani aquifers are found to influence larger storage capability, higher permeability (>10 -4 m/s) and faster response to rainfall (1 to 3months' lag) compared to fractured rocks (permeability 3months) found only in Bambui aquifer. Groundwater in the Amazon region is found to rely not only on precipitation but also on inflow from other regions. Areas beyond the northern and southern Amazon basin depict a 'dam-like' pattern, with high inflow and slow outflow rates (recharge slope > 0.75, discharge slope 30cm). Amazon's groundwater declined between 2002 and 2008 due to below normal precipitation (wet seasons lasted for about 36 to 47% of the time). The Guarani aquifer and adjacent coastline areas rank second in terms of storage capacity, while the northeast and southeast coastal regions indicate the smallest storage capacity due to lack of rainfall (annual average is rainfall <10cm). Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Drought on the North American High Plains: Modeling Effects of Vegetation, Temperature, and Rainfall Perturbations on Regional Hydrology

    Hein, A. E.; Condon, L. E.; Maxwell, R. M.


    Large scale droughts can disrupt the water supply for agriculture, municipalities and industrial use worldwide. For example, the Dustbowl drought of the 1930s severely damaged agriculture on the North American High Plains. The Dustbowl is generally attributed to three major factors: increased temperature, decreased precipitation, and a change from native grasses that might have tolerated these climate perturbations to dryland wheat farming, which did not. This study explores the individual importance of each of these factors and the feedbacks between them. Previous modeling studies have explored how the High Plains system responds to changes in precipitation or temperature, but these models often depend on simplified or lumped parameter approaches. These approaches may not fully represent all the relevant physical processes, especially those related to energy balance changes due to increased temperature. For this study, we built a high-resolution model of the High Plains using ParFlow-CLM, an integrated hydrologic model that solves both energy and water balances from the subsurface to the top of vegetation. Model inputs including geology and climate forcing, together with representative precipitation and temperature changes for a major drought were assembled from public data. Numerical experiments were run to perturb vegetation, precipitation and temperature separately, as well as a baseline scenario with no changes and a worst-case scenario with all three simultaneously. The impact of each factor on High Plains hydrology and water resources was examined by comparing soil moisture, stream flow and water table levels between the runs. The one-factor experiments were used to show which of these outputs was the most sensitive and responded most quickly to each change. The worst-case scenario revealed interactions between the three factors.

  14. Improving representation of drought stress and fire emissions in climate carbon models: measurements and modeling with a focus on the western USA

    Ehleringer, James [Univ. of Utah, Salt Lake City, UT (United States). Dept. of Biology; Randerson, James [Univ. of California, Irvine, CA (United States); Lai, Chun-Ta [San Diego State Univ., CA (United States)


    The objective of the proposed research was to collect data and develop models to improve our understanding of the role of drought and fire impacts on the terrestrial carbon cycle in the western US, including impacts associated with urban systems as they impacted regional carbon cycles. Using data we collected and a synthesis of other measurements, we developed new ways (a) to evaluate the representation of drought stress and fire emissions in the Community Land Model, (b) to model net ecosystem exchange combining ground level atmospheric observations with boundary layer theory, (c) to model upstream impacts of fire and fossil fuel emissions on atmospheric carbon dioxide observations, and (d) to model carbon dioxide observations within urban systems and at the urban-wildland interfaces of forest ecosystems.

  15. Application of Dynamic naïve Bayesian classifier to comprehensive drought assessment

    Park, D. H.; Lee, J. Y.; Lee, J. H.; KIm, T. W.


    Drought monitoring has already been extensively studied due to the widespread impacts and complex causes of drought. The most important component of drought monitoring is to estimate the characteristics and extent of drought by quantitatively measuring the characteristics of drought. Drought assessment considering different aspects of the complicated drought condition and uncertainty of drought index is great significance in accurate drought monitoring. This study used the dynamic Naïve Bayesian Classifier (DNBC) which is an extension of the Hidden Markov Model (HMM), to model and classify drought by using various drought indices for integrated drought assessment. To provide a stable model for combined use of multiple drought indices, this study employed the DNBC to perform multi-index drought assessment by aggregating the effect of different type of drought and considering the inherent uncertainty. Drought classification was performed by the DNBC using several drought indices: Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Normalized Vegetation Supply Water Index (NVSWI)) that reflect meteorological, hydrological, and agricultural drought characteristics. Overall results showed that in comparison unidirectional (SPI, SDI, and NVSWI) or multivariate (Composite Drought Index, CDI) drought assessment, the proposed DNBC was able to synthetically classify of drought considering uncertainty. Model provided method for comprehensive drought assessment with combined use of different drought indices.

  16. Hydrosedimentological modeling of watershed in southeast Brazil, using SWAT

    Maria Lúcia Calijuri


    Full Text Available The quantitative evaluation of soil loss due to erosion, of water loss and of load sediments that reach water bodies is fundamental to the environmental planning of a watershed, contributing to the process of decision for best options for soil tillage and water quality maintenance. Estimates of these data have been accomplished throughout the world using empiric or conceptual models. Besides being economically viable in scenarios development, environmental models may contribute to the location of critical areas, leading to emergency contention operations caused by erosive processes. Among these models, we highlight the SWAT (Soil and Water Assessment Tool which was applied in São Bartolomeu watershed, located in the Zona da Mata, Minas Gerais state, southeastern Brazil, to identify areas of greater sensitivity to erosion considering the soil type and land use. To validate the model, 10 experimental plots were installed in the dominant crops of the watershed between 2006 and 2008, for monitoring the runoff and soil losses under natural rainfall. Field results and simulations showed the SWAT efficiency for sediment yield and soil losses estimations, as they are influenced by factors such as soil moisture, rainfall intensity, soil type and land use (dominated by Oxisols, Ultisols, Inceptisols and Entisols. These losses can be reduced significantly by improving crops management of. A simulation scenario replacing pastures cover by Eucalyptus was introduced, which significantly reduced soil loss in many parts of the watershed.

  17. South American Monsoon: Recent Droughts in the Context of Changing Global Circulation.

    Seth, A.; Fernandes, K.; Camargo, S. J.


    The 2013-2015 drought in Southeast Brazil led to water shortages in São Paulo, the country's most populous city. The observed drought during austral summers of 2013/2014 and 2014/2015 and related large-scale dynamics are examined. The 2013-2014 precipitation deficits were more concentrated in the state of São Paulo, while in 2014-2015 moderate deficits were seen throughout the region. We find that a persistent warm sea surface temperature (SST) anomaly in the western tropical Pacific Ocean was an important driver of drought via atmospheric teleconnection in the two December-February seasons. The warm SST and associated convective heating initiated a wave train across the South Pacific. The resulting anticyclonic geopotential height anomaly over the southwest Atlantic expanded the westward margin of the South Atlantic high and prevented low-pressure systems from entering southeast Brazil from midlatitudes. This mechanism suggests a hemispheric symmetry to that proposed for the recent California drought. A first look at CMIP5 model projections to examine the role of large scale circulation changes to drought in the Sao Paulo region will be presented.

  18. Receptor models for source apportionment of remote aerosols in Brazil

    Artaxo Netto, P.E.


    The PIXE (particle induced X-ray emission), and PESA (proton elastic scattering analysis) method were used in conjunction with receptor models for source apportionment of remote aerosols in Brazil. The PIXE used in the determination of concentration for elements with Z >- 11, has a detection limit of about 1 ng/m 3 . The concentrations of carbon, nitrogen and oxygen in the fine fraction of Amazon Basin aerosols was measured by PESA. We sampled in Jureia (SP), Fernando de Noronha, Arembepe (BA), Firminopolis (GO), Itaberai (GO) and Amazon Basin. For collecting the airbone particles we used cascade impactors, stacked filter units, and streaker samplers. Three receptor models were used: chemical mass balance, stepwise multiple regression analysis and principal factor analysis. The elemental and gravimetric concentrations were explained by the models within the experimental errors. Three sources of aerosol were quantitatively distinguished: marine aerosol, soil dust and aerosols related to forests. The emission of aerosols by vegetation is very clear for all the sampling sites. In Amazon Basin and Jureia it is the major source, responsible for 60 to 80% of airborne concentrations. (Author) [pt

  19. Drought assessment in the Dongliao River basin: traditional approaches vs. generalized drought assessment index based on water resources systems

    Weng, B. S.; Yan, D. H.; Wang, H.; Liu, J. H.; Yang, Z. Y.; Qin, T. L.; Yin, J.


    Drought is firstly a resource issue, and with its development it evolves into a disaster issue. Drought events usually occur in a determinate but a random manner. Drought has become one of the major factors to affect sustainable socioeconomic development. In this paper, we propose the generalized drought assessment index (GDAI) based on water resources systems for assessing drought events. The GDAI considers water supply and water demand using a distributed hydrological model. We demonstrate the use of the proposed index in the Dongliao River basin in northeastern China. The results simulated by the GDAI are compared to observed drought disaster records in the Dongliao River basin. In addition, the temporal distribution of drought events and the spatial distribution of drought frequency from the GDAI are compared with the traditional approaches in general (i.e., standard precipitation index, Palmer drought severity index and rate of water deficit index). Then, generalized drought times, generalized drought duration, and generalized drought severity were calculated by theory of runs. Application of said runs at various drought levels (i.e., mild drought, moderate drought, severe drought, and extreme drought) during the period 1960-2010 shows that the centers of gravity of them all distribute in the middle reaches of Dongliao River basin, and change with time. The proposed methodology may help water managers in water-stressed regions to quantify the impact of drought, and consequently, to make decisions for coping with drought.

  20. Projection of drought-inducing climate conditions in the Czech Republic according to Euro-CORDEX models

    Štěpánek, Petr; Zahradníček, Pavel; Farda, Aleš; Skalák, Petr; Trnka, Miroslav; Meitner, Jan; Rajdl, Kamil


    Roč. 70, 2-3 (2016), s. 179-193 ISSN 0936-577X R&D Projects: GA MŠk(CZ) LO1415; GA MŠk(CZ) LD14043; GA ČR(CZ) GA14-12262S; GA ČR GA13-19831S; GA ČR(CZ) GA16-16549S Institutional support: RVO:67179843 Keywords : Euro-CORDEX simulations * model bias correction * climate change * drought indices * Czech Republic Subject RIV: DA - Hydrology ; Limnology Impact factor: 1.578, year: 2016

  1. Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

    Paula Mendes Luz


    Full Text Available Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii how vector density spatial heterogeneity influences control efforts; (iii with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4 in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0 that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

  2. Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

    Luz Paula Mendes


    Full Text Available Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii how vector density spatial heterogeneity influences control efforts; (iii with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4 in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0 that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

  3. Spatio-temporal Analysis of Hydrological Drought at Catchment Scale Using a Spatially-distributed Hydrological Model

    Mercado, Vitali Diaz; Perez, Gerald Corzo; Solomatine, Dimitri; Lanen, Van Henny A.J.


    Lately, drought is more intense and much more severe around the globe, causing more deaths than other hazards in the past century. Drought can be characterized quantitatively for its spatial extent, intensity and duration by using drought indicators. Several indicators have been developed in

  4. Drought mitigation in perennial crops by fertilization and adjustments of regional yield models for future climate variability

    Kantola, I. B.; Blanc-Betes, E.; Gomez-Casanovas, N.; Masters, M. D.; Bernacchi, C.; DeLucia, E. H.


    Increased variability and intensity of precipitation in the Midwest agricultural belt due to climate change is a major concern. The success of perennial bioenergy crops in replacing maize for bioethanol production is dependent on sustained yields that exceed maize, and the marketing of perennial crops often emphasizes the resilience of perennial agriculture to climate stressors. Land conversion from maize for bioethanol to Miscanthus x giganteus (miscanthus) increases yields and annual evapotranspiration rates (ET). However, establishment of miscanthus also increases biome water use efficiency (the ratio between net ecosystem productivity after harvest and ET), due to greater belowground biomass in miscanthus than in maize or soybean. In 2012, a widespread drought reduced the yield of 5-year-old miscanthus plots in central Illinois by 36% compared to the previous two years. Eddy covariance data indicated continued soil water deficit during the hydrologically-normal growing season in 2013 and miscanthus yield failed to rebound as expected, lagging behind pre-drought yields by an average of 53% over the next three years. In early 2014, nitrogen fertilizer was applied to half of mature (7-year-old) miscanthus plots in an effort to improve yields. In plots with annual post-emergence application of 60 kg ha-1 of urea, peak biomass was 29% greater than unfertilized miscanthus in 2014, and 113% greater in 2015, achieving statistically similar yields to the pre-drought average. Regional-scale models of perennial crop productivity use 30-year climate averages that are inadequate for predicting long-term effects of short-term extremes on perennial crops. Modeled predictions of perennial crop productivity incorporating repeated extreme weather events, observed crop response, and the use of management practices to mitigate water deficit demonstrate divergent effects on predicted yields.

  5. Drought limitations to leaf-level gas exchange: results from a model linking stomatal optimization and cohesion-tension theory.

    Novick, Kimberly A; Miniat, Chelcy F; Vose, James M


    We merge concepts from stomatal optimization theory and cohesion-tension theory to examine the dynamics of three mechanisms that are potentially limiting to leaf-level gas exchange in trees during drought: (1) a 'demand limitation' driven by an assumption of optimal stomatal functioning; (2) 'hydraulic limitation' of water movement from the roots to the leaves; and (3) 'non-stomatal' limitations imposed by declining leaf water status within the leaf. Model results suggest that species-specific 'economics' of stomatal behaviour may play an important role in differentiating species along the continuum of isohydric to anisohydric behaviour; specifically, we show that non-stomatal and demand limitations may reduce stomatal conductance and increase leaf water potential, promoting wide safety margins characteristic of isohydric species. We used model results to develop a diagnostic framework to identify the most likely limiting mechanism to stomatal functioning during drought and showed that many of those features were commonly observed in field observations of tree water use dynamics. Direct comparisons of modelled and measured stomatal conductance further indicated that non-stomatal and demand limitations reproduced observed patterns of tree water use well for an isohydric species but that a hydraulic limitation likely applies in the case of an anisohydric species. Published 2015. This article is a US Government work and is in the public domain in the USA.

  6. Phenotyping common beans for adaptation to drought

    Beebe, Stephen E.; Rao, Idupulapati M.; Blair, Matthew W.; Acosta-Gallegos, Jorge A.


    Common beans (Phaseolus vulgaris L.) originated in the New World and are the grain legume of greatest production for direct human consumption. Common bean production is subject to frequent droughts in highland Mexico, in the Pacific coast of Central America, in northeast Brazil, and in eastern and southern Africa from Ethiopia to South Africa. This article reviews efforts to improve common bean for drought tolerance, referring to genetic diversity for drought response, the physiology of drought tolerance mechanisms, and breeding strategies. Different races of common bean respond differently to drought, with race Durango of highland Mexico being a major source of genes. Sister species of P. vulgaris likewise have unique traits, especially P. acutifolius which is well adapted to dryland conditions. Diverse sources of tolerance may have different mechanisms of plant response, implying the need for different methods of phenotyping to recognize the relevant traits. Practical considerations of field management are discussed including: trial planning; water management; and field preparation. PMID:23507928

  7. Gully erosion in the Caatinga biome, Brazil: measurement and stochastic modelling

    Lima Alencar, Pedro Henrique; de Araújo, José Carlos; Nonato Távora Costa, Raimundo


    In contrast with inter-rill erosion, which takes a long time to modify the terrain form, gully erosion can fast and severely change the landscape. In the Brazilian semiarid region, a one-million km2 area that coincides with the Caatinga biome, inter-rill erosion prevails due to the silty shallow soils. However, gully erosion does occur in the Caatinga, with temporal increasing severity. This source of sediment impacts the existing dense network of small dams, generating significant deleterious effects, such as water availability reduction in a drought-prone region. This study focuses on the Madalena basin (124 km2, state of Ceará, Brazil), a land-reform settlement with 20 inhabitants per km2, whose main economic activities are agriculture (especially Zea mays), livestock and fishing. In the catchment area, where there are 12 dams (with storage capacity ranging from 6.104 to 2.107 m3), gully erosion has become an issue due to its increasing occurrence. Eight gully-erosion sites have been identified in the basin, but most of them have not yet reached great dimensions (depth and/or width), nor interacted with groundwater, being therefore classified as ephemeral gullies. We selected the three most relevant sites and measured the topography of the eroded channels, as well as the neighboring terrain relief, using accurate total stations and unmanned aerial vehicle. The data was processed with the help of software, such as DataGeosis (Office 7.5) and Surfer (11.0), providing information on gully erosion in terms of (μ ± σ): projection area (317±165 m2), eroded mass (61±36 Mg) and volume (42±25 m3), length (38±6 m), maximum depth (0.58±0.13 m) and maximum width (6.00±2.35 m). The measured data are then compared with those provided by the Foster and Lane model (1986). The model generated results with considerable scatter. This is possibly due to uncertainties in the field parameters, which are neglected in the deterministic approach of most physically-based models

  8. Modelling predicts that tolerance to drought during reproductive development will be required for high yield potential and stability of wheat in Europe

    Semenov, Mikhail A.; Stratonovitch, Pierre; Paul, Matthew J.


    Short periods of extreme weather, such as a spell of high temperature or drought during a sensitive stage of development, could result in substantial yield losses due to reduction in grain number and grain size. In a modelling study (Stratonovitch & Semenov 2015), heat tolerance around flowering in wheat was identified as a key trait for increased yield potential in Europe under climate change. Ji et all (Ji et al. 2010) demonstrated cultivar specific responses of yield to drought stress around flowering in wheat. They hypothesised that carbohydrate supply to anthers may be the key in maintaining pollen fertility and grain number in wheat. It was shown in (Nuccio et al. 2015) that genetically modified varieties of maize that increase the concentration of sucrose in ear spikelets, performed better under non-drought and drought conditions in field experiments. The objective of this modelling study was to assess potential benefits of tolerance to drought during reproductive development for wheat yield potential and yield stability across Europe. We used the Sirius wheat model to optimise wheat ideotypes for 2050 (HadGEM2, RCP8.5) climate scenarios at selected European sites. Eight cultivar parameters were optimised to maximise mean yields, including parameters controlling phenology, canopy growth and water limitation. At those sites where water could be limited, ideotypes sensitive to drought produced substantially lower mean yields and higher yield variability compare with tolerant ideotypes. Therefore, tolerance to drought during reproductive development is likely to be required for wheat cultivars optimised for the future climate in Europe in order to achieve high yield potential and yield stability.

  9. A Distributed Multi-dimensional SOLAP Model of Remote Sensing Data and Its Application in Drought Analysis

    LI Jiyuan


    Full Text Available SOLAP (Spatial On-Line Analytical Processing has been applied to multi-dimensional analysis of remote sensing data recently. However, its computation performance faces a considerable challenge from the large-scale dataset. A geo-raster cube model extended by Map-Reduce is proposed, which refers to the application of Map-Reduce (a data-intensive computing paradigm in the OLAP field. In this model, the existing methods are modified to adapt to distributed environment based on the multi-level raster tiles. Then the multi-dimensional map algebra is introduced to decompose the SOLAP computation into multiple distributed parallel map algebra functions on tiles under the support of Map-Reduce. The drought monitoring by remote sensing data is employed as a case study to illustrate the model construction and application. The prototype is also implemented, and the performance testing shows the efficiency and scalability of this model.

  10. Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches

    Van Loon, Anne F.; Stahl, Kerstin; Di Baldassarre, Giuliano; Clark, Julian; Rangecroft, Sally; Wanders, Niko; Gleeson, Tom; Van Dijk, Albert I. J. M.; Tallaksen, Lena M.; Hannaford, Jamie; Uijlenhoet, Remko; Teuling, Adriaan J.; Hannah, David M.; Sheffield, Justin; Svoboda, Mark; Verbeiren, Boud; Wagener, Thorsten; Van Lanen, Henny A. J.


    are considered normal or reference conditions) over time? Answering these questions requires exploration of qualitative and quantitative data as well as mixed modelling approaches. The challenges related to drought research and management in the Anthropocene are not unique to drought, but do require urgent attention. We give recommendations drawn from the fields of flood research, ecology, water management, and water resources studies. The framework presented here provides a holistic view on drought in the Anthropocene, which will help improve management strategies for mitigating the severity and reducing the impacts of droughts in future.

  11. Drought as a natural disaster

    Maybank, J. [Agvironics Consulting, SK (Canada); Bonsal, B. [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Geography; Jones, K. [Environment Canada, Downsview, ON (Canada). Canadian Climate Centre; Lawford, R. [Canadian Climate Centre, Saskatoon, SK (Canada). National Hydrology Research Centre; O`Brien, E.G. [Agriculture Canada, Ottawa, ON (Canada). Energy Analysis and Policy Div.; Ripley, E.A. [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Soil Science; Wheaton, E. [Saskatchewan Research Council, Saskatoon, SK (Canada)


    A discussion of droughts as a major natural disaster in dry areas such as the Canadian Prairies where precipitation patterns are seasonal, was presented. Environmental damages include soil degradation and erosion, vegetation damage, slough and lake deterioration and wildlife loss. The development and application of specific soil moisture and drought indices based on cumulative precipitation deficits have enhanced drought monitoring programs. The identification of precursor conditions raises the possibility that the likelihood of a drought occurring in a particular year or growing season might be predictable. The ability to forecast seasonal temperature and precipitation anomalies is potentially feasible using a suitable merging of precursor parameters and modelling methodologies. Research activity to identify and evaluate new mitigative measure should be increased to keep pace with the prospects of drought predictability. 90 refs., 1 tab., 7 figs.

  12. Middle Rio Grande Water Sustainability in Extreme Drought: Using Provenance to Trace Modeling Scenarios Selected by Users

    Pennington, D. D.; Garnica Chavira, L.; Villanueva-Rosales, N.


    People living in the vicinity of the middle Rio Grande from Elephant Butte Reservoir in New Mexico through Fort Quitman, Texas, including inhabitants on the Mexican side of the river, are confronted with numerous challenges that include drought, population growth, reduced surface water quality and quantity, declining aquifers, and expected future increases in temperature with more variable precipitation. The transboundary surface water is subject to complex regulation across two U.S. states and two nations (U.S. and Mexico). This presentation will summarize the modeling efforts of a USDA-funded project to characterize potential future solutions for water sustainability while managing agriculture, economic, and human impacts. It will present an online software system designed for rapid, flexible modeling of different climate, policy, and technology scenarios with stakeholders, and the underlying intelligent system that manages model selection, data and parameters, and user choices, and provides a provenance trace based on the W3C PROV standard.

  13. Nanometrology, Standardization and Regulation of Nanomaterials in Brazil: A Proposal for an Analytical-Prospective Model

    Ana Rusmerg Giménez Ledesma


    Full Text Available The main objective of this paper is to propose an analytical-prospective model as a tool to support decision-making processes concerning metrology, standardization and regulation of nanomaterials in Brazil, based on international references and ongoing initiatives in the world. In the context of nanotechnology development in Brazil, the motivation for carrying out this research was to identify potential benefits of metrology, standardization and regulation of nanomaterials production, from the perspective of future adoption of the model by the main stakeholders of development of these areas in Brazil. The main results can be summarized as follows: (i an overview of international studies on metrology, standardization and regulation of nanomaterials, and nanoparticles, in special; (ii the analytical-prospective model; and (iii the survey questionnaire and the roadmapping tool for metrology, standardization and regulation of nanomaterials in Brazil, based on international references and ongoing initiatives in the world.

  14. Global drought and severe drought-affected populations in 1.5 and 2 °C warmer worlds

    W. Liu


    Full Text Available The 2015 Paris Agreement proposed a more ambitious climate change mitigation target on limiting global warming to 1.5 °C instead of 2 °C above preindustrial levels. Scientific investigations on environmental risks associated with these warming targets are necessary to inform climate policymaking. Based on the Coupled Model Intercomparison Project phase 5 (CMIP5 climate models, we present the first risk-based assessment of changes in global drought and the impact of severe drought on populations from additional 1.5 and 2 °C warming conditions. Our results highlight the risk of drought on a global scale and in several hotspot regions such as the Amazon, northeastern Brazil, southern Africa and Central Europe at both 1.5 and 2 °C global warming relative to the historical period, showing increases in drought durations from 2.9 to 3.2 months. Correspondingly, more total and urban populations would be exposed to severe droughts globally (+132.5 ± 216.2 million and +194.5 ± 276.5 million total population and +350.2 ± 158.8 million and +410.7 ± 213.5 million urban populations in 1.5 and 2 °C warmer worlds and regionally (e.g., East Africa, West Africa and South Asia. Less rural populations (−217.7 ± 79.2 million and −216.2 ± 82.4 million rural populations in 1.5 and 2 °C warmer worlds would be exposed to severe drought globally under climate warming, population growth and especially the urbanization-induced population migration. By keeping global warming at 1.5 °C above the preindustrial levels instead of 2 °C, there is a decrease in drought risks (i.e., less drought duration, less drought intensity and severity but relatively more frequent drought and the affected total, urban and rural populations would decrease globally and in most regions. While challenging for both East Africa and South Asia, the benefits of limiting warming to below 1.5 °C in terms of global drought risk

  15. Improving Predictions of Tree Drought Mortality in the Community Land Model Using Hydraulic Physiology Theory and its Effects on Carbon Metabolism

    McNellis, B.; Hudiburg, T. W.


    Tree mortality due to drought is predicted to have increasing impacts on ecosystem structure and function during the 21st century. Models can attempt to predict which forests are most at risk from drought, but novel environments may preclude analysis that relies on past observations. The inclusion of more mechanistic detail may reduce uncertainty in predictions, but can also compound model complexity, especially in global models. The Community Land Model version 5 (CLM5), itself a component of the Community Earth System Model (CESM), has recently integrated cohort-based demography into its dynamic vegetation component and is in the process of coupling this demography to a model of plant hydraulic physiology (FATES-Hydro). Previous treatment of drought stress and plant mortality within CLM has been relatively broad, but a detailed hydraulics module represents a key step towards accurate mortality prognosis. Here, we examine the structure of FATES-Hydro with respect to two key physiological attributes: tissue osmotic potentials and embolism refilling. Specifically, we ask how FATES-Hydro captures mechanistic realism within each attribute and how much support there is within the physiological literature for its further elaboration within the model structure. Additionally, connections to broader aspects of carbon metabolism within FATES are explored to better resolve emergent consequences of drought stress on ecosystem function and tree demographics. An on-going field experiment in managed stands of Pinus ponderosa and mixed conifers is assessed for model parameterization and performance across PNW forests, with important implications for future forest management strategy.

  16. Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

    Zhang, J.; Yang, J.; Pan, S.; Tian, H.


    China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

  17. A physical model for extreme drought over southwest Asia: Chapter 17

    Hoell, Andrew; Funk, Chris; Barlow, Mathew; Cannon, Forrest


    The socioeconomic difficulties of southwest Asia, defined as the area bound by the domain 25°N–40°N and 40°E–70°E, are exacerbated by extreme precipitation deficits during the November–April rainy season. The precipitation deficits during many southwest Asia droughts have been examined in terms of the forcing by climate variability originating over the Pacific Ocean as a result of the El Niño–Southern Oscillation (ENSO), Pacific decadal variability (PDV), and the long-term warming of Pacific (LT) sea surface temperatures (SST). Here we examine how the most extreme November–April southwest Asia droughts relate to global SSTs and the associated large-scale atmospheric circulation anomalies and analyze the specific atmospheric forcing mechanisms responsible for changes in regional southwest Asian precipitation. The driest November–April seasons during 1948–2012 over southwest Asia are forced by subsidence and reductions of moisture fluxes as a result of the interaction of the mean flow with anomalous zonally symmetric high pressure throughout the Northern Hemisphere. The anomalous zonally symmetric high pressure throughout the Northern Hemisphere occurs simultaneously with cool central and eastern Pacific SST anomalies associated with La Niña and the negative phase of PDV and a warm west Pacific Ocean caused in part by the long-term warming of the west Pacific Ocean.

  18. Natural and drought scenarios in an east central Amazon forest: Fidelity of the Community Land Model 3.5 with three biogeochemical models

    Sakaguchi, Koichi; Zeng, Xubin; Christoffersen, Bradley J.; Restrepo-Coupe, Natalia; Saleska, Scott R.; Brando, Paulo M.


    Recent development of general circulation models involves biogeochemical cycles: flows of carbon and other chemical species that circulate through the Earth system. Such models are valuable tools for future projections of climate, but still bear large uncertainties in the model simulations. One of the regions with especially high uncertainty is the Amazon forest where large-scale dieback associated with the changing climate is predicted by several models. In order to better understand the capability and weakness of global-scale land-biogeochemical models in simulating a tropical ecosystem under the present day as well as significantly drier climates, we analyzed the off-line simulations for an east central Amazon forest by the Community Land Model version 3.5 of the National Center for Atmospheric Research and its three independent biogeochemical submodels (CASA', CN, and DGVM). Intense field measurements carried out under Large Scale Biosphere-Atmosphere Experiment in Amazonia, including forest response to drought from a throughfall exclusion experiment, are utilized to evaluate the whole spectrum of biogeophysical and biogeochemical aspects of the models. Our analysis shows reasonable correspondence in momentum and energy turbulent fluxes, but it highlights three processes that are not in agreement with observations: (1) inconsistent seasonality in carbon fluxes, (2) biased biomass size and allocation, and (3) overestimation of vegetation stress to short-term drought but underestimation of biomass loss from long-term drought. Without resolving these issues the modeled feedbacks from the biosphere in future climate projections would be questionable. We suggest possible directions for model improvements and also emphasize the necessity of more studies using a variety of in situ data for both driving and evaluating land-biogeochemical models.

  19. Description of future drought indices in Virginia

    Hyunwoo Kang


    Full Text Available This article presents projected future drought occurrences in five river basins in Virginia. The Soil and Water Assessment Tool (SWAT and the Coupled Model Intercomparison Project Phase 5 (CMIP5 climate models were used to derive input variables of multiple drought indices, such as the Standardized Soil Moisture index (SSI, the Multivariate Standardized Drought Index (MSDI, and the Modified Palmer Drought Severity Index (MPDSI for both historic and future periods. The results of SSI indicate that there was an overall increase in agricultural drought occurrences and that these were caused by increases in evapotranspiration and runoff. However, the results of the MSDI and MPDSI projected a decrease in drought occurrences in future periods due to a greater increase in precipitation in the future. Furthermore, GCM-downscaled products (precipitation and temperature were verified using comparisons with historic observations, and the results of uncertainty analyses suggest that the lower and upper bounds of future drought projections agree with historic conditions.

  20. Financial and Real Sector Leading Indicators of Recessions in Brazil Using Probabilistic Models

    Fernando Nascimento de Oliveira

    Full Text Available We examine the usefulness of various financial and real sector variables to forecast recessions in Brazil between one and eight quarters ahead. We estimate probabilistic models of recession and select models based on their outof-sample forecasts, using the Receiver Operating Characteristic (ROC function. We find that the predictive out-of-sample ability of several models vary depending on the numbers of quarters ahead to forecast and on the number of regressors used in the model specification. The models selected seem to be relevant to give early warnings of recessions in Brazil.

  1. Mathematical Modeling Applied to Prediction of Landslides in Southern Brazil

    Silva, Lúcia; Araújo, João; Braga, Beatriz; Fernandes, Nelson


    Mass movements are natural phenomena that occur on the slopes and are important agents working in landscape development. These movements have caused serious damage to infrastructure and properties. In addition to the mass movements occurring in natural slopes, there is also a large number of accidents induced by human action in the landscape. The change of use and land cover for the introduction of agriculture is a good example that have affected the stability of slopes. Land use and/or land cover changes have direct and indirect effects on slope stability and frequently represent a major factor controlling the occurrence of man-induced mass movements. In Brazil, especially in the southern and southeastern regions, areas of original natural rain forest have been continuously replaced by agriculture during the last decades, leading to important modifications in soil mechanical properties and to major changes in hillslope hydrology. In these regions, such effects are amplified due to the steep hilly topography, intense summer rainfall events and dense urbanization. In November 2008, a major landslide event took place in a rural area with intensive agriculture in the state of Santa Catarina (Morro do Baú) where many catastrophic landslides were triggered after a long rainy period. In this area, the natural forest has been replaced by huge banana and pine plantations. The state of Santa Catarina in recent decades has been the scene of several incidents of mass movements such as this catastrophic event. In this study, based on field mapping and modeling, we characterize the role played by geomorphological and geological factors in controlling the spatial distribution of landslides in the Morro do Baú area. In order to attain such objective, a digital elevation model of the basin was generated with a 10m grid in which the topographic parameters were obtained. The spatial distribution of the scars from this major event was mapped from another image, obtained immediately

  2. Simulating the 2012 High Plains Drought Using Three Single Column Model Versions of the Community Earth System Model (SCM-CESM)

    Medina, I. D.; Denning, S.


    The impact of changes in the frequency and severity of drought on fresh water sustainability is a great concern for many regions of the world. One such location is the High Plains, where the local economy is primarily driven by fresh water withdrawals from the Ogallala Aquifer, which accounts for approximately 30% of total irrigation withdrawals from all U.S. aquifers combined. Modeling studies that focus on the feedback mechanisms that control the climate and eco-hydrology during times of drought are limited in the sense that they use conventional General Circulation Models (GCMs) with grid length scales ranging from one hundred to several hundred kilometers. Additionally, these models utilize crude statistical parameterizations of cloud processes for estimating sub-grid fluxes of heat and moisture and have a poor representation of land surface heterogeneity. For this research, we focus on the 2012 High Plains drought, and will perform numerical simulations using three single column model versions of the Community Earth System Model (SCM-CESM) at multiple sites overlying the Ogallala Aquifer for the 2010-2012 period. In the first version of SCM-CESM, CESM will be used in standard mode (Community Atmospheric Model (CAM) coupled to a single instance of the Community Land Model (CLM)), secondly, CESM will be used in Super-Parameterized mode (SP-CESM), where a cloud resolving model (CRM consists of 32 atmospheric columns) replaces the standard CAM atmospheric parameterization and is coupled to a single instance of CLM, and thirdly, CESM is used in "Multi Instance" SP-CESM mode, where an instance of CLM is coupled to each CRM column of SP-CESM (32 CRM columns coupled to 32 instances of CLM). To assess the physical realism of the land-atmosphere feedbacks simulated at each site by all versions of SCM-CESM, differences in simulated energy and moisture fluxes will be computed between years for the 2010-2012 period, and will be compared to differences calculated using

  3. Experimental droughts: Are precipitation variability and methodological trends hindering our understanding of ecological sensitivities to drought?

    Hoover, D. L.; Wilcox, K.; Young, K. E.


    Droughts are projected to increase in frequency and intensity with climate change, which may have dramatic and prolonged effects on ecosystem structure and function. There are currently hundreds of published, ongoing, and new drought experiments worldwide aimed to assess ecosystem sensitivities to drought and identify the mechanisms governing ecological resistance and resilience. However, to date, the results from these experiments have varied widely, and thus patterns of drought sensitivities have been difficult to discern. This lack of consensus at the field scale, limits the abilities of experiments to help improve land surface models, which often fail to realistically simulate ecological responses to extreme events. This is unfortunate because models offer an alternative, yet complementary approach to increase the spatial and temporal assessment of ecological sensitivities to drought that are not possible in the field due to logistical and financial constraints. Here we examined 89 published drought experiments, along with their associated historical precipitation records to (1) identify where and how drought experiments have been imposed, (2) determine the extremity of drought treatments in the context of historical climate, and (3) assess the influence of precipitation variability on drought experiments. We found an overall bias in drought experiments towards short-term, extreme experiments in water-limited ecosystems. When placed in the context of local historical precipitation, most experimental droughts were extreme, with 61% below the 5th, and 43% below the 1st percentile. Furthermore, we found that interannual precipitation variability had a large and potentially underappreciated effect on drought experiments due to the co-varying nature of control and drought treatments. Thus detecting ecological effects in experimental droughts is strongly influenced by the interaction between drought treatment magnitude, precipitation variability, and key

  4. An Integrated Hydrologic Model and Remote Sensing Synthesis Approach to Study Groundwater Extraction During a Historic Drought in the California Central Valley

    Thatch, L. M.; Maxwell, R. M.; Gilbert, J. M.


    Over the past century, groundwater levels in California's San Joaquin Valley have dropped more than 30 meters in some areas due to excessive groundwater extraction to irrigate agricultural lands and feed a growing population. Between 2012 and 2016 California experienced the worst drought in its recorded history, further exacerbating this groundwater depletion. Due to lack of groundwater regulation, exact quantities of extracted groundwater in California are unknown and hard to quantify. We use a synthesis of integrated hydrologic model simulations and remote sensing products to quantify the impact of drought and groundwater pumping on the Central Valley water tables. The Parflow-CLM model was used to evaluate groundwater depletion in the San Joaquin River basin under multiple groundwater extraction scenarios simulated from pre-drought through recent drought years. Extraction scenarios included pre-development conditions, with no groundwater pumping; historical conditions based on decreasing groundwater level measurements; and estimated groundwater extraction rates calculated from the deficit between the predicted crop water demand, based on county land use surveys, and available surface water supplies. Results were compared to NASA's Gravity Recover and Climate Experiment (GRACE) data products to constrain water table decline from groundwater extraction during severe drought. This approach untangles various factors leading to groundwater depletion within the San Joaquin Valley both during drought and years of normal recharge to help evaluate which areas are most susceptible to groundwater overdraft, as well as further evaluating the spatially and temporally variable sustainable yield. Recent efforts to improve water management and ensure reliable water supplies are highlighted by California's Sustainable Groundwater Management Act (SGMA) which mandates Groundwater Sustainability Agencies to determine the maximum quantity of groundwater that can be withdrawn through

  5. Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall—Southern Malawi case study

    Funk, Christopher C.; Verdin, James; Adams Chavula,; Gregory J. Husak,; Harikishan Jayanthi,; Tamuka Magadzire,


    During 1990s, disaster risk reduction emerged as a novel, proactive approach to managing risks from natural hazards. The World Bank, USAID, and other international donor agencies began making efforts to mainstream disaster risk reduction in countries whose population and economies were heavily dependent on rain-fed agriculture. This approach has more significance in light of the increasing climatic hazard patterns and the climate scenarios projected for different hazard prone countries in the world. The Famine Early Warning System Network (FEWS NET) has been monitoring the food security issues in the sub-Saharan Africa, Asia and in Haiti. FEWS NET monitors the rainfall and moisture availability conditions with the help of NOAA RFE2 data for deriving food security status in Africa. This paper highlights the efforts in using satellite estimated rainfall inputs to develop drought vulnerability models in the drought prone areas in Malawi. The satellite RFE2 based SPI corresponding to the critical tasseling and silking phases (in the months of January, February, and March) were statistically regressed with drought-induced yield losses at the district level. The analysis has shown that the drought conditions in February and early March lead to most damage to maize yields in this region. The district-wise vulnerabilities to drought were upscaled to obtain a regional maize vulnerability model for southern Malawi. The results would help in establishing an early monitoring mechanism for drought impact assessment, give the decision makers additional time to assess seasonal outcomes, and identify potential food-related hazards in Malawi.

  6. Using the CAUSE Model to Understand Public Communication about Water Risks: Perspectives from Texas Groundwater District Officials on Drought and Availability.

    VanDyke, Matthew S; King, Andy J


    Public communication about drought and water availability risks poses challenges to a potentially disinterested public. Water management professionals, though, have a responsibility to work with the public to engage in communication about water and environmental risks. Because limited research in water management examines organizational communication practices and perceptions, insights into research and practice can be gained through investigation of current applications of these risk communication efforts. Guided by the CAUSE model, which explains common goals in communicating risk information to the public (e.g., creating Confidence, generating Awareness, enhancing Understanding, gaining Satisfaction, and motivating Enactment), semistructured interviews of professionals (N = 25) employed by Texas groundwater conservation districts were conducted. The interviews examined how CAUSE model considerations factor in to communication about drought and water availability risks. These data suggest that many work to build constituents' confidence in their districts. Although audiences and constituents living in drought-prone areas were reported as being engaged with water availability risks and solutions, many district officials noted constituents' lack of perceived risk and engagement. Some managers also indicated that public understanding was a secondary concern of their primary responsibilities and that the public often seemed apathetic about technical details related to water conservation risks. Overall, results suggest complicated dynamics between officials and the public regarding information access and motivation. The article also outlines extensions of the CAUSE model and implications for improving public communication about drought and water availability risks. © 2017 Society for Risk Analysis.

  7. Assimilation of GRACE Terrestrial Water Storage into a Land Surface Model: Evaluation 1 and Potential Value for Drought Monitoring in Western and Central Europe

    Li, Bailing; Rodell, Matthew; Zaitchik, Benjamin F.; Reichle, Rolf H.; Koster, Randal D.; van Dam, Tonie M.


    A land surface model s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff correlations with gauge data in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation.

  8. Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

    Wanders, N.; Van Lanen, H. A J


    Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study

  9. The Temporospatial Variations and Propagation of Drought in China

    Ma, F.; Ye, A.; Luo, L.; Duan, Q.


    Drought monitoring and forecasting system is a crucial component of drought preparedness. However, under the changing environment, the hydro-climate presents non-stationarity due to climate change and anthropogenic activities, which brings great challenges for drought forecasts. This study investigates the temporospatial characteristics and propagation of different types of droughts from 1961 to 2016 in China. Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSMI) and Standardized Streamflow Index (SSI) are used to characterize meteorological, agricultural and hydrological droughts, respectively. The soil moisture and streamflow datasets are obtained from simulations by the distributed time-variant gain model (DTVGM) hydrological model, which has been calibrated and validated in China. The spatial patterns of drought frequency and severity, and temporal characteristics of drought coverage, drought duration and drought intensity are investigated. The cross wavelet analysis is used to examine the correlations between meteorological, agricultural and hydrological droughts. The study also explores how different types of droughts are linked and how one drought morphs into another through time. The findings on temporospatial variations and propagation of drought will provide better understanding on drought development to be helpful for improvement of drought monitoring and forecasting.

  10. Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

    Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L


    Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

  11. 3-D Hydraulic Model Testing of the New Roundhead in Suape, Brazil

    Andersen, Thomas Lykke; Burcharth, Hans F.; Sipavicius, A.

    This report deals with a three-dimensional model test study of the extension of the breakwater in Suape, Brazil. The roundhead was tested for stability in various sea conditions. The length scale used for the model tests was 1:35. Unless otherwise specified all values given in this report...

  12. Implementation, availability and regulatory status of an OECD accepted Reconstructed Human Epidermis model in Brazil

    Rodrigo De Vecchi


    Full Text Available Introduction: In 2014, Brazil has joined the growing list of countries to ban cosmetic products from being tested on animal models. The new legislation comes into force in 2019. As a result, the interest for validated alternative testing methods for safety assessment has been increasing in academia, industry and associations. However, the lack of specific legislation on the use of biological material of human origin for toxicological tests makes the access to alternative in vitro models difficult. Furthermore, importation to Brazil is not possible on timely manner. Method: In this article, we report the implementation process of a Reconstructed Human Epidermis (SkinEthic™ RHE, an alternative model internationally accepted by OECD, through a technology transfer from EPISKIN® Lyon to Brazil. Regulatory evolution has been motivating the implementation and wide use of alternative methods to animal testing in several industry segments including cosmetic and pharmaceutical. Results: Protocol has been shown to be robust and highly reproducible. Quality control parameters (histological analysis, barrier function test and tissue viability were performed on 24 batches assembled in Brazil. SkinEthic™ RHE model use allows the full replacement of animal test methods for skin hazards identification. It has regulatory acceptance for several toxicological endpoints, such as the Draize test for skin irritation and corrosion. It allows the reduction and refining of pre-clinical protocols through tiered strategies. Implementation of SkinEthic™ RHE protocol is just a first and important step towards a new approach of toxicological safety testing in Brazil. Conclusion: The implementation was successfully done and reported here. However, in order to follow completely the new legislation up to 2019, the availability of validated models is essential. Quality control tests done on RHE batches produced in Brazil demonstrate that the model met OECD acceptance

  13. Future Drought Projections over the Iberian Peninsula using Drought Indices

    Garcia-Valdecasas Ojeda, M.; Yeste Donaire, P.; Góngora García, T. M.; Gámiz-Fortis, S. R.; Castro-Diez, Y.; Esteban-Parra, M. J.


    Currently, drought events are the cause of numerous annual economic losses. In a context of climate change, it is expected an increase in the severity and the frequency of drought occurrences, especially in areas such as the Mediterranean region. This study makes use of two drought indices in order to analyze the potential changes on future drought events and their effects at different time scales over a vulnerable region, the Iberian Peninsula. The indices selected were the Standardized Precipitation Evapotranspiration Index (SPEI), which takes into account the global warming through the temperature, and the Standardized Precipitation Index (SPI), based solely on precipitation data, at a spatial resolution of 0.088º ( 10 km). For their computation, current (1980-2014) and future (2021-2050 and 2071-2100) high resolution simulations were carried out using the Weather Research and Forecasting (WRF) model over a domain centered in the Iberian Peninsula, and nested in the 0.44 EUROCORDEX region. WRF simulations were driven by two different global bias-corrected climate models: the version 1 of NCAR's Community Earth System Model (CESM1) and the Max Planck Institute's Earth System Model (MPI-ESM-LR), and under two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Future projections were analyzed regarding to changes in mean, median and variance of drought indices with respect to the historical distribution, as well as changes in the frequency and duration of moderate and severe drought events. In general, results suggest an increase in frequency and severity of drought, especially for 2071-2100 period in the RCP 8.5 scenario. Results also shown an increase of drought phenomena more evident using the SPEI. Conclusions from this study could provide a valuable contribution to the understanding of how the increase of the temperature would affect the drought variability in the Mediterranean regions which is necessary for a suitable

  14. Model or Myopia? Exploiting Water Markets to Address Population and Drought Risks in a Changing World

    Reed, P. M.


    Climate change, population demands, and evolving land-use represent strong risks to the sustainable development and stability of world-wide urban water supplies. There is a growing consensus that non-structural supply management instruments such as water markets have significant potential to reduce the risks and vulnerabilities in complex urban water systems. This paper asks a common question, what are the tradeoffs for a city using water market supply instruments?. This question emerges quickly in policy and management, but its answer is deceptively difficult to attain using traditional planning tools and management frameworks. This research demonstrates new frameworks that facilitate rapid evaluation of hypotheses on the reliability, resiliency, adaptability, and cost-effectiveness of urban water supply systems. This study considers a broader exploration of the issues of "nonstationarity" and "uncertainty" in urban water planning. As we invest in new information and prediction frameworks for the coupled human-natural systems that define our water, our problem definitions (i.e., objectives, constraints, preferences, and hypotheses) themselves evolve. From a formal mathematical perspective, this means that our management problems are structurally uncertain and nonstationary (i.e., the definition of optimality changes across regions, times, and stakeholders). This uncertainty and nonstationarity in our problem definitions needs to be more explicitly acknowledged in adaptive management and integrated water resources management. This study demonstrates the potential benefits of exploring these issues in the context of a city in the Lower Rio Grande Valley (LRGV) of Texas, USA determining how to use its regional water market to manage population and drought risks.

  15. Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

    Wang, Guiling


    This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.

  16. Modeling the Effects of Drought, Fire, Beetles, and Management on Future Carbon Cycling in the Western US

    Buotte, P.; Law, B. E.; Hicke, J. A.; Hudiburg, T. W.; Levis, S.; Kent, J.


    Fire and beetle outbreaks can have substantial impacts on forest structure, composition, and function and these types of disturbances are expected to increase in the future. Therefore understanding the ecological impacts of these disturbances into the future is important. We used ecosystem process modeling to estimate the future occurrence of fire and beetle outbreaks and their impacts on forest resilience and carbon sequestration. We modified the Community Land Model (CLM4.5) to better represent forest growth and mortality in the western US through multiple avenues: 1) we increased the ecological resolution to recognize 14 forest types common to the region; 2) we improved CLM4.5's ability to handle drought stress by adding forest type-specific controls on stomatal conductance and increased rates of leaf shed during periods of low soil moisture; 3) we developed and implemented a mechanistic model of beetle population growth and subsequent tree mortality; 4) we modified the current fire module to account for more refined forest types; and 5) we developed multiple scenarios of harvest based on past harvest rates and proposed changes in land management policies. We ran CLM4.5 in offline mode with climate forcing data. We compare future forest growth rates and carbon sequestration with historical metrics to estimate the combined influence of future disturbances on forest composition and carbon sequestration in the western US.

  17. Update and extension of the Brazil SimSmoke model to estimate the health impact of cigarette smoking by pregnant women in Brazil

    Szklo, André Salem; Yuan, Zhe; Levy, David


    Abstract: A previous application of the Brazil SimSmoke tobacco control policy simulation model was used to show the effect of policies implemented between 1989 and 2010 on smoking-attributable deaths (SADs). In this study, we updated and further validated the Brazil SimSmoke model to incorporate policies implemented since 2011 (e.g., a new tax structure with the purpose of increasing revenues/real prices). In addition, we extended the model to estimate smoking-attributable maternal and child...

  18. Influence of landscape heterogeneity on water available to tropical forests in an Amazonian catchment and implications for modeling drought response: Water Available to Tropical Forest

    Fang, Yilin; Leung, Lai-Yung; Duan, Zhuoran; Wigmosta, Mark S.; Maxwell, Reed M.; Chambers, Jeffrey Q.; Tomasella, Javier


    The Amazon basin experienced periodic droughts in the past, and climate models projected more intense and frequent droughts in the future. How tropical forests respond to drought may depend on water availability, which is modulated by landscape heterogeneity. Using the one-dimensional ACME Land Model (ALM) and the three-dimensional ParFlow variably saturated flow model, a series of numerical experiments were performed for the Asu catchment in central Amazon to elucidate processes that influence water available for plant use and provide insights for improving Earth system models. Results from ParFlow show that topography has a dominant influence on groundwater table and runoff through lateral flow. Without any representations of lateral processes, ALM simulates very different seasonal variations in groundwater table and runoff compared to ParFlow even if it is able to reproduce the long-term spatial average groundwater table of ParFlow through simple parameter calibration. In the ParFlow simulations, the groundwater table is evidently deeper and the soil saturation is lower in the plateau compared to the valley. However, even in the plateau during the dry season in the drought year of 2005, plant transpiration is not water stressed in the ParFlow simulations as the soil saturation is still sufficient to maintain a soil matric potential for the stomata to be fully open. This finding is insensitive to uncertainty in atmospheric forcing and soil parameters, but the empirical wilting formulation used in the models is an important factor that should be addressed using observations and modeling of coupled plant hydraulics-soil hydrology processes in future studies.

  19. Socio-hydrological model to inform community adaptation to seasonal drought and climate variability in rural agricultural watersheds in Costa Rica

    Hund, S. V.; Johnson, M. S.; Morillas, L.; McDaniels, T.; Romero Valpreda, J.; Allen, D. M.


    Climate variability and seasonal droughts associated with ENSO (El Niño Southern Oscillation) and increasing water demand due to growing population are leading to serious water conflicts in the wet-dry tropics of Central America. Integrated methods are needed to understand the linkages of these complex socio-hydrological systems and design reliable adaption strategies in a period of global change. With increasing pressure on surface and groundwater resources during long annual dry seasons, rural agricultural communities suffer water shortages, especially in those years preceded by wet seasons with lower rainfall (and reduced groundwater recharge). To support community resilience to rainfall variability and droughts, we conducted a combination of fieldwork (development of hydrologic monitoring system and local stakeholder cooperation), and hydrological modeling for two watersheds with a shared aquifer (Potrero and Caimital) in Northwestern Costa Rica. The agricultural land use of the region and the many rural villages that draw directly on their local water resource and live in close interaction with their watersheds necessitated a socio-hydrological systems approach. In this talk we present results from our hydrologic modeling, for which we used the WEAP (Water Evaluation and Planning) model and locally recorded data. With the integrated water supply and demand features of the WEAP model, we were able to synthesize both the hydrological system and the societal system (specifically, household and agricultural water use), and show feedbacks such as that water use tends to increase during the dry season, likely exacerbating water shortages issues. Further, applying a range of ENSO related rainfall scenarios to the model demonstrated that community adaptation will become in particular important in response to lower water availability in future El Niño years. In collaboration with local stakeholders, we identified a set of feasible adaptation strategies to seasonal

  20. The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

    Yoshida, Y.; Joiner, J.; Tucker, C.; Berry, J.; Lee, J. -E.; Walker, G.; Reichle, R.; Koster, R.; Lyapustin, A.; Wang, Y.


    We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

  1. Plant Survival and Mortality during Drought Can be Mediated by Co-occurring Species' Physiological and Morphological Traits: Results from a Model

    Tai, X.; Mackay, D. S.


    Interactions among co-occurring species are mediated by plant physiology, morphology and environment. Without proper mechanisms to account for these factors, it remains difficult to predict plant mortality/survival under changing climate. A plant ecophysiological model, TREES, was extended to incorporate co-occurring species' belowground interaction for water. We used it to examine the interaction between two commonly co-occurring species during drought experiment, pine (Pinus edulis) and juniper (Juniperus monosperma), with contrasting physiological traits (vulnerability to cavitation and leaf water potential regulation). TREES was parameterized and validated using field-measured plant physiological traits. The root architecture (depth, profile, and root area to leaf area ratio) of juniper was adjusted to see how root morphology could affect the survival/mortality of its neighboring pine under both ambient and drought conditions. Drought suppressed plant water and carbon uptake, as well increased the average percentage loss of conductivity (PLC). Pine had 59% reduction in water uptake, 48% reduction in carbon uptake, and 38% increase in PLC, while juniper had 56% reduction in water uptake, 50% reduction in carbon and 29% increase in PLC, suggesting different vulnerability to drought as mediated by plant physiological traits. Variations in juniper root architecture further mediated drought stress on pine, from negative to positive. Different juniper root architecture caused variations in response of pine over drought (water uptake reduction ranged 0% ~63%, carbon uptake reduction ranged 0% ~ 70%, and PLC increase ranged 2% ~ 91%). Deeper or more uniformly distributed roots of juniper could effectively mitigate stress experienced by pine. In addition, the total water and carbon uptake tended to increase as the ratio of root area to leaf area increased while PLC showed non-monotonic response, suggesting the potential trade-off between maximizing resource uptake and

  2. Bacterial mediated amelioration of drought stress in drought tolerant ...

    Bacterial mediated amelioration of drought stress in drought tolerant and susceptible cultivars of rice ( Oryza sativa L.) ... and IR-64 (drought sensitive) cultivars of rice (Oryza sativa L.) under different level of drought stress. ... from 32 Countries:.

  3. Drought impact on vegetation growth and mortality

    Xu, C.; Wang, M.; Allen, C. D.; McDowell, N. G.; Middleton, R. S.


    Vegetation is a key regulator of the global carbon cycle via CO2 absorption through photosynthesis and subsequent growth; however, low water availability, heat stress, and disturbances associated with droughts could substantially reduce vegetation growth and increase vegetation mortality. As far as we know, there are few studies have assessed the drought impact on vegetation growth and mortality at regional and global scales. In this study, we analyzed 13 Earth System models (ESMs) to quantify the impact of drought on GPP and linked the remote-sensing based tree mortality to observed drought indices to assess the drought impact on tree mortality in continental US (CONUS). Our analysis of 13 Earth System models (ESMs) shows that the average global gross primary production (GPP) reduction per year associated with extreme droughts over years 2075-2099 is predicted to be 3-5 times larger than that over years 1850-1999. The annual drought-associated reduction in GPP over years 2075-2099 could be 52 and 74 % of annual fossil fuel carbon emission during years 2000-2007. Increasing drought impacts on GPP are driven primarily by the increasing drought frequency. The risks of drought-associated GPP reduction are particularly high for temperate and tropical regions. The consistent prediction of higher drought-associated reduction in NPP across 13 ESMs suggests increasing impacts of drought on the global carbon cycle with atmospheric warming. Our analysis of drought impact on tree mortality showed that drought-associated carbon loss accounts for 12% of forest carbon loss in CONUS for 2000-2014, which is about one-fifth of that resulting from timber harvesting and 1.35 % of average annual fossil fuel emissions in the U.S. for the same period. The carbon stock loss from natural disturbances for 2000-2014 is approximately 75% of the total carbon loss from anthropogenic disturbance (timber harvesting), suggesting that natural disturbances play a very important role on forest

  4. Spatial patterns of drought persistence in East China

    Meng, L.; Ford, T.


    East China has experienced a number of severe droughts in recent decades. Understanding the characteristics of droughts and their persistence will provide operational guidelines for water resource management and agricultural production. This study uses a logistic regression model to measure the probability of drought occurrence in the current season given the previous season's Standardized Precipitation Index (SPI) and Southern Oscillation Index (SOI) as well as drought persistence. Results reveal large spatial and seasonal variations in the relationship between the previous season's SPI and the drought occurrence probability in a given season. The drought persistence averaged over the entire study area for all the four seasons is approximately 34% with large variations from season to season and from region to region. The East and Northeast regions have the largest summer drought persistence ( 40%) and lowest fall drought persistence ( 28%). The spatial pattern in winter and spring drought persistence is dissimilar with stronger winter and weaker spring drought persistence in the Southwest and Northeast relative to other regions. Logistic regression analysis indicates a stronger negative relationship in summer-to-fall (or between fall drought occurrence and summer SPI) than other inter-season relationships. This study demonstrates that the impact of previous season SPI and SOI on current season drought varies substantially from region to region and from season to season. This study also shows stronger drought persistence in summer than in other seasons. In other words, the probability of fall drought occurrence is closely related to summer moisture conditions in the East China.

  5. Processes influencing model-data mismatch in drought-stressed, fire-disturbed eddy flux sites

    Mitchell, Stephen; Beven, Keith; Freer, Jim; Law, Beverly


    Semiarid forests are very sensitive to climatic change and among the most difficult ecosystems to accurately model. We tested the performance of the Biome-BGC model against eddy flux data taken from young (years 2004-2008), mature (years 2002-2008), and old-growth (year 2000) ponderosa pine stands at Metolius, Oregon, and subsequently examined several potential causes for model-data mismatch. We used the Generalized Likelihood Uncertainty Estimation methodology, which involved 500,000 model runs for each stand (1,500,000 total). Each simulation was run with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in modeled estimates of net ecosystem CO2 exchange (NEE) that were compared to measured eddy flux data. Simulations for the young stand exhibited the highest level of performance, though they overestimated ecosystem C accumulation (-NEE) 99% of the time. Among the simulations for the mature and old-growth stands, 100% and 99% of the simulations underestimated ecosystem C accumulation. One obvious area of model-data mismatch is soil moisture, which was overestimated by the model in the young and old-growth stands yet underestimated in the mature stand. However, modeled estimates of soil water content and associated water deficits did not appear to be the primary cause of model-data mismatch; our analysis indicated that gross primary production can be accurately modeled even if soil moisture content is not. Instead, difficulties in adequately modeling ecosystem respiration, mainly autotrophic respiration, appeared to be the fundamental cause of model-data mismatch.

  6. Estimating drought risk across Europe from reported drought impacts, hazard indicators and vulnerability factors

    Blauhut, V.; Stahl, K.; Stagge, J. H.; Tallaksen, L. M.; De Stefano, L.; Vogt, J.


    Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work (1) tests the capability of commonly applied hazard indicators and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and (2) combines information on past drought impacts, drought hazard indicators, and vulnerability factors into estimates of drought risk at the pan-European scale. This "hybrid approach" bridges the gap between traditional vulnerability assessment and probabilistic impact forecast in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro region specific sensitivities of hazard indicators, with the Standardised Precipitation Evapotranspiration Index for a twelve month aggregation period (SPEI-12) as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictor, with information about landuse and water resources as best vulnerability-based predictors. (3) The application of the "hybrid approach" revealed strong regional (NUTS combo level) and sector specific differences in drought risk across Europe. The majority of best predictor combinations rely on a combination of SPEI for shorter and longer aggregation periods, and a combination of information on landuse and water resources. The added value of integrating regional vulnerability information

  7. SVAT modeling of crop physiological response to drought in potatoes under different types of deficit irrigation

    Plauborg, Finn; Mollerup, Mikkel; Abrahamsen, Per

    of abscisic acid in the root system and as well as its influence on stomatal regulation of gas exhange has been implemented in the Daisy model, a comprehensive work partly financed by the SAFIR project ( ). Hence, the improved Daisy model now calculates crop production based on gas...

  8. Spatial differences in drought vulnerability

    Perčec Tadić, M.; Cindić, K.; Gajić-Čapka, M.; Zaninović, K.


    Drought causes the highest economic losses among all hydro-meteorological events in Croatia. It is the most frequent hazard, which produces the highest damages in the agricultural sector. The climate assessment in Croatia according to the aridity index (defined as the ratio of precipitation and potential evapotranspiration) shows that the susceptibility to desertification is present in the warm part of the year and it is mostly pronounced in the Adriatic region and the eastern Croatia lowland. The evidence of more frequent extreme drought events in the last decade is apparent. These facts were motivation to study the drought risk assessment in Croatia. One step in this issue is the construction of the vulnerability map. This map is a complex combination of the geomorphologic and climatological inputs (maps) that are presumed to be natural factors which modify the amount of moisture in the soil. In this study, the first version of the vulnerability map is followed by the updated one that additionally includes the soil types and the land use classes. The first input considered is the geomorphologic slope angle calculated from the digital elevation model (DEM). The SRTM DEM of 100 m resolution is used. The steeper slopes are more likely to lose water and to become dryer. The second climatological parameter, the solar irradiation map, gives for the territory of Croatia the maximum irradiation on the coast. The next meteorological parameter that influences the drought vulnerability is precipitation which is in this assessment included through the precipitation variability expressed by the coefficient of variation. Larger precipitation variability is related with the higher drought vulnerability. The preliminary results for Croatia, according to the recommended procedure in the framework of Drought Management Centre for Southeastern Europe (DMCSEE project), show the most sensitive areas to drought in the southern Adriatic coast and eastern continental lowland.

  9. The Drought Monitor.

    Svoboda, Mark; Lecomte, Doug; Hayes, Mike; Heim, Richard; Gleason, Karin; Angel, Jim; Rippey, Brad; Tinker, Rich; Palecki, Mike; Stooksbury, David; Miskus, David; Stephens, Scott


    information about drought and to receive regional and local input that is in turn incorporated into the product. This paper describes the Drought Monitor and the interactive process through which it is created.

  10. Future oil production in Brazil-Estimates based on a Hubbert model

    Szklo, Alexandre; Machado, Giovani; Schaeffer, Roberto


    This paper forecasts oil production in Brazil, according to the Hubbert model and different probabilities for adding reserves. It analyzes why the Hubbert model might be more appropriate to the Brazilian oil industry than that of Hotelling, as it implicitly emphasizes the impacts of information and depletion on the derivative over time of the accumulated discoveries. Brazil's oil production curves indicate production peaks with a time lag of more than 15 years, depending on the certainty (degree of information) associated with the reserves. Reserves with 75% certainty peak at 3.27 Mbpd in 2020, while reserves with 50% certainty peak at 3.28 Mbpd in 2028, and with 30% certainty peak at 3.88 Mbpd in 2036. These findings show that Brazil oil industry is in a stage where the positive impacts of information on expanding reserves (mainly through discoveries) may outstrip the negative impacts of depletion. The still limited number of wells drilled by accumulated discoveries also explain this assertion. Being a characteristic of frontier areas such as Brazil, this indicates the need for ongoing exploratory efforts

  11. Monetary Channels in Brazil through the Lens of a Semi-Structural Model

    André Minella; Nelson F. Souza-Sobrinho


    We develop and estimate a medium-size, semi-structural model for Brazil's economy during the inflation targeting period. The model captures key features of the economy, and allows us to investigate the transmission mechanisms of monetary policy. We decompose the monetary channels into household interest rate, firm interest rate, and exchange rate channels. We find that the household interest rate channel plays the most important role in explaining output dynamics after a monetary policy shock...

  12. A rate equation model of stomatal responses to vapour pressure deficit and drought

    Shanahan ST


    Full Text Available Abstract Background Stomata respond to vapour pressure deficit (D – when D increases, stomata begin to close. Closure is the result of a decline in guard cell turgor, but the link between D and turgor is poorly understood. We describe a model for stomatal responses to increasing D based upon cellular water relations. The model also incorporates impacts of increasing levels of water stress upon stomatal responses to increasing D. Results The model successfully mimics the three phases of stomatal responses to D and also reproduces the impact of increasing plant water deficit upon stomatal responses to increasing D. As water stress developed, stomata regulated transpiration at ever decreasing values of D. Thus, stomatal sensitivity to D increased with increasing water stress. Predictions from the model concerning the impact of changes in cuticular transpiration upon stomatal responses to increasing D are shown to conform to experimental data. Sensitivity analyses of stomatal responses to various parameters of the model show that leaf thickness, the fraction of leaf volume that is air-space, and the fraction of mesophyll cell wall in contact with air have little impact upon behaviour of the model. In contrast, changes in cuticular conductance and membrane hydraulic conductivity have significant impacts upon model behaviour. Conclusion Cuticular transpiration is an important feature of stomatal responses to D and is the cause of the 3 phase response to D. Feed-forward behaviour of stomata does not explain stomatal responses to D as feedback, involving water loss from guard cells, can explain these responses.

  13. Simulating drought impact and mitigation in cassava using the LINTUL model

    Ezui, K.S.; Leffelaar, P.A.; Franke, A.C.; Mando, A.; Giller, K.E.


    We adapted and used a crop simulation model based on light interception and use efficiency (LINTUL-Cassava) to improve our understanding of water-limited yields of cassava under rain-fed conditions in Southern Togo. Data collected in four different fields in two locations, Sevekpota and

  14. Wildfire potential evaluation during a drought event with a regional climate model and NDVI

    Y. Liu; J. Stanturf; S. Goodrick


    Regional climate modeling is a technique for simulating high-resolution physical processes in the atmosphere, soil and vegetation. It can be used to evaluate wildfire potential by either providing meteorological conditions for computation of fire indices or predicting soil moisture as a direct measure of fire potential. This study examines these roles using a regional...

  15. Parameter optimisation for a better representation of drought by LSMs: inverse modelling vs. sequential data assimilation

    Dewaele, Hélène; Munier, Simon; Albergel, Clément; Planque, Carole; Laanaia, Nabil; Carrer, Dominique; Calvet, Jean-Christophe


    Soil maximum available water content (MaxAWC) is a key parameter in land surface models (LSMs). However, being difficult to measure, this parameter is usually uncertain. This study assesses the feasibility of using a 15-year (1999-2013) time series of satellite-derived low-resolution observations of leaf area index (LAI) to estimate MaxAWC for rainfed croplands over France. LAI interannual variability is simulated using the CO2-responsive version of the Interactions between Soil, Biosphere and Atmosphere (ISBA) LSM for various values of MaxAWC. Optimal value is then selected by using (1) a simple inverse modelling technique, comparing simulated and observed LAI and (2) a more complex method consisting in integrating observed LAI in ISBA through a land data assimilation system (LDAS) and minimising LAI analysis increments. The evaluation of the MaxAWC estimates from both methods is done using simulated annual maximum above-ground biomass (Bag) and straw cereal grain yield (GY) values from the Agreste French agricultural statistics portal, for 45 administrative units presenting a high proportion of straw cereals. Significant correlations (p value Bag and GY are found for up to 36 and 53 % of the administrative units for the inverse modelling and LDAS tuning methods, respectively. It is found that the LDAS tuning experiment gives more realistic values of MaxAWC and maximum Bag than the inverse modelling experiment. Using undisaggregated LAI observations leads to an underestimation of MaxAWC and maximum Bag in both experiments. Median annual maximum values of disaggregated LAI observations are found to correlate very well with MaxAWC.

  16. A model for estimation of potential generation of waste electrical and electronic equipment in Brazil

    Araújo, Marcelo Guimarães; Magrini, Alessandra; Mahler, Cláudio Fernando; Bilitewski, Bernd


    Highlights: ► Literature of WEEE generation in developing countries is reviewed. ► We analyse existing estimates of WEEE generation for Brazil. ► We present a model for WEEE generation estimate. ► WEEE generation of 3.77 kg/capita year for 2008 is estimated. ► Use of constant lifetime should be avoided for non-mature market products. - Abstract: Sales of electrical and electronic equipment are increasing dramatically in developing countries. Usually, there are no reliable data about quantities of the waste generated. A new law for solid waste management was enacted in Brazil in 2010, and the infrastructure to treat this waste must be planned, considering the volumes of the different types of electrical and electronic equipment generated. This paper reviews the literature regarding estimation of waste electrical and electronic equipment (WEEE), focusing on developing countries, particularly in Latin America. It briefly describes the current WEEE system in Brazil and presents an updated estimate of generation of WEEE. Considering the limited available data in Brazil, a model for WEEE generation estimation is proposed in which different methods are used for mature and non-mature market products. The results showed that the most important variable is the equipment lifetime, which requires a thorough understanding of consumer behavior to estimate. Since Brazil is a rapidly expanding market, the “boom” in waste generation is still to come. In the near future, better data will provide more reliable estimation of waste generation and a clearer interpretation of the lifetime variable throughout the years.

  17. Influence of mathematical and physical background of drought indices on their complementarity and drought recognition ability

    Frank, Anna; Armenski, Tanja; Gocic, Milan; Popov, Srdjan; Popovic, Ljiljana; Trajkovic, Slavisa


    The aim of this study is to test how effective and physically correct are the mathematical approaches of operational indices used by relevant National Agencies across the globe. To do so, the following indices were analysed Standardized Precipitation Index (SPI) -1, 3, 6, 12 and 24, Standardized Precipitation - Evapotranspiration Index (SPEI) - 1, 3, 6, 12 and 24, Effective Drought Index (EDI) and Index of Drying Efficiency of Air (IDEA). To make regions more comparable to each other and follow the spatial development of drought SPI index was advised by World Meteorological Organisation to be used widely by official meteorological services. The SPI and SPEI are used for Drought Early Warning in the USA, National Drought Mitigation Center and NASA, and in the EU by the European Drought Centre (EDC) and in the Balkan Region by National Meteorological Agencies. The EDI Index has wide application in Asia. In this paper four different issues were investigated: 1) how the mathematical method used in a drought indicator's computation influence drought indices' (DI) comparative analyses; 2) the sensitivity of the DIs on any change of the length of observational period; 3) similarities between the DIs time series; 4) and how accurate DIs are when compared to historical drought records. Results suggest that it is necessary to apply a few crucial changes in the Drought Monitoring and Early Warning Systems: 1) reconsider use of SPI and SPEI family indices as a measure of quality of other indices; and for Drought Early Recognition Programs 2) switch to DIs with a solid physical background, such as EDI; 3) Adopt solid physics for modelling drought processes and define the physical measure of drought, e.g. EDI and IDEA indices; 4) investigate further the IDEA index, which, supported by our study as well, is valuable for simulation of a drought process.

  18. Understanding and seasonal forecasting of hydrological drought in the Anthropocene

    X. Yuan


    Full Text Available Hydrological drought is not only caused by natural hydroclimate variability but can also be directly altered by human interventions including reservoir operation, irrigation, groundwater exploitation, etc. Understanding and forecasting of hydrological drought in the Anthropocene are grand challenges due to complicated interactions among climate, hydrology and humans. In this paper, five decades (1961–2010 of naturalized and observed streamflow datasets are used to investigate hydrological drought characteristics in a heavily managed river basin, the Yellow River basin in north China. Human interventions decrease the correlation between hydrological and meteorological droughts, and make the hydrological drought respond to longer timescales of meteorological drought. Due to large water consumptions in the middle and lower reaches, there are 118–262 % increases in the hydrological drought frequency, up to 8-fold increases in the drought severity, 21–99 % increases in the drought duration and the drought onset is earlier. The non-stationarity due to anthropogenic climate change and human water use basically decreases the correlation between meteorological and hydrological droughts and reduces the effect of human interventions on hydrological drought frequency while increasing the effect on drought duration and severity. A set of 29-year (1982–2010 hindcasts from an established seasonal hydrological forecasting system are used to assess the forecast skill of hydrological drought. In the naturalized condition, the climate-model-based approach outperforms the climatology method in predicting the 2001 severe hydrological drought event. Based on the 29-year hindcasts, the former method has a Brier skill score of 11–26 % against the latter for the probabilistic hydrological drought forecasting. In the Anthropocene, the skill for both approaches increases due to the dominant influence of human interventions that have been implicitly

  19. Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

    Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.


    The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

  20. State regulation of nuclear sector: comparative study of Argentina and Brazil models

    Monteiro Filho, Joselio Silveira


    This research presents a comparative assessment of the regulation models of the nuclear sector in Argentina - under the responsibility of the Autoridad Regulatoria Nuclear (ARN), and Brazil - under the responsibility of Comissao Nacional de Energia Nuclear (CNEN), trying to identify which model is more adequate aiming the safe use of nuclear energy. Due to the methodology adopted, the theoretical framework resulted in criteria of analysis that corresponds to the characteristics of the Brazilian regulatory agencies created for other economic sector during the State reform staring in the middle of the nineties. Later, these criteria of analysis were used as comparison patterns between the regulation models of the nuclear sectors of Argentina and Brazil. The comparative assessment showed that the regulatory structure of the nuclear sector in Argentina seems to be more adequate, concerning the safe use of nuclear energy, than the model adopted in Brazil by CNEN, because its incorporates the criteria of functional, institutional and financial independence, competence definitions, technical excellence and transparency, indispensable to the development of its functions with autonomy, ethics, exemption and agility. (author)

  1. Econometric modeling of the balance of social security Brazil

    Isaac Figueiredo de Sousa


    This work aims to build models using econometrics techniques to explain the components of the balance of Social Security System, or in other words, the net value of tax revenues and the benefit values of the General Regime of Social Security. These models were subjected to statistic validations indicated in the theoretical reference of econometrics, to apply the method of ordinary least square from the classic model of linear regression. From an increasing longevity and the gradual decr...

  2. Why Different Drought Indexes Show Distinct Future Drought Risk Outcomes in the U.S. Great Plains?

    Feng, S.; Hayes, M. J.; Trnka, M.


    Vigorous discussions and disagreements about the future changes in drought intensity in the US Great Plains have been taking place recently within the literature. These discussions have involved widely varying estimates based on drought indices and model-based projections of the future. To investigate and understand the causes for such a disparity between these previous estimates, we analyzed 10 commonly-used drought indexes using the output from 26 state-of-the-art climate models. These drought indices were computed using potential evapotranspiration estimated by the physically-based Penman-Monteith method (PE_pm) and the empirically-based Thornthwaite method (PE_th). The results showed that the short-term drought indicators are similar to modeled surface soil moisture and show a small but consistent drying trend in the future. The long-term drought indicators and the total column soil moisture, however, are consistent in projecting more intense future drought. When normalized, the drought indices with PE_th all show unprecedented and possibly unrealistic future drying, while the drought indices with PE_pm show comparable dryness with the modeled soil moisture. Additionally, the drought indices with PE_pm are closely related to soil moisture during both the 20th and 21st Centuries. Overall, the drought indices with PE_pm, as well as the modeled total column soil moisture, suggest a widespread and very significant drying of the Great Plains region toward the end of the Century. Our results suggested that the sharp contracts about future drought risk in the Great Plains discussed in previous studies are caused by 1) comparing the projected changes in short-term droughts with that of the long-term droughts, and/or 2) computing the atmospheric evaporative demand using the empirically-based method (e.g., PE_th). Our analysis may be applied for drought projections in other regions across the globe.

  3. Psychological Responses to Drought in Northeastern Brazil

    Angela E. L. Coêlho


    Full Text Available Este estudio de los efectos acumulativos de la sequía en el nordeste Del Brasil, evaluó las respuestas psicológicas (ansiedad, distress emocional y trastorno por estrés pós traumático de 102 individuos que vivían en la ciudad de Queimadas/Paraíba, en un área propensa a la sequía, y comparó con las respuestas de 102 personas que vivían en la ciudad de Areia/Paraíba, libre de la sequía, y de tamaño comparable con la primera. De acuerdo con lo esperado, los resultados revelaron que los residentes en el área de sequía (Queimadas tenían niveles significativamente más altos de ansiedad e distress emocional, en comparación con los residentes Del área sin problemas de sequía (Areia. En el área de sequía, las mujeres tenían niveles significativamente más altos de ansiedad y los hombres tenían niveles significativamente más altos de distress emocional, en comparación con mujeres y hombres, respectivamente, en el área sin problemas de sequía. Probablemente, debido a la vulnerabilidad de su papel social, las mujeres tenían niveles significativamente más altos de ansiedad y distress emocional si comparadas con los hombres. Como también ya se esperaba los casos de trastorno por estrés pós traumático, no se relacionaban con la sequía. Aunque descriptivos, los resultados proporcionan datos para comparaciones en el caso de agravamiento de la sequía, y ofrecen sugerencias para futuras investigaciones sobre las consecuencias psicológicas de la sequía.

  4. Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

    Hao, Zengchao; Singh, Vijay P.; Xia, Youlong


    Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

  5. Towards Improved Understanding of Drought and Drought Impacts from Long Term Earth Observation Records

    Champagne, C.; Wang, S.; Liu, J.; Hadwen, T. A.


    Drought is a complex natural disaster, which often emerges slowly, but can occur at various time scales and have impacts that are not well understood. Long term observations of drought intensity and frequency are often quantified from precipitation and temperature based indices or modelled estimates of soil water storage. The maturity of satellite based observations has created the potential to enhance the understanding of drought and drought impacts, particularly in regions where traditional data sets are limited by remoteness or inaccessibility, and where drought processes are not well-quantified by models. Long term global satellite data records now provide observations of key hydrological variables, including evaporation modelled from thermal sensors, soil moisture from microwave sensors, ground water from gravity sensors and vegetation condition that can be modelled from optical sensors. This study examined trends in drought frequency, intensity and duration over diverse ecoregions in Canada, including agricultural, grassland, forested and wetland areas. Trends in drought were obtained from the Canadian Drought Monitor as well as meteorological based indices from weather stations, and evaluated against satellite derived information on evaporative stress (Anderson et al. 2011), soil moisture (Champagne et al. 2015), terrestrial water storage (Wang and Li 2016) and vegetation condition (Davidson et al. 2009). Data sets were evaluated to determine differences in how different sensors characterize the hydrology and impacts of drought events from 2003 to 2016. Preliminary results show how different hydrological observations can provide unique information that can tie causes of drought (water shortages resulting from precipitation, lack of moisture storage or evaporative stress) to impacts (vegetation condition) that hold the potential to improve the understanding and classification of drought events.

  6. A new multi-sensor integrated index for drought monitoring

    Jiao, W.; Wang, L.; Tian, C.


    Drought is perceived as one of the most expensive and least understood natural disasters. The remote-sensing-based integrated drought indices, which integrate multiple variables, could reflect the drought conditions more comprehensively than single drought indices. However, most of current remote-sensing-based integrated drought indices focus on agricultural drought (i.e., deficit in soil moisture), their application in monitoring meteorological drought (i.e., deficit in precipitation) was limited. More importantly, most of the remote-sensing-based integrated drought indices did not take into consideration of the spatially non-stationary nature of the related variables, so such indices may lose essential local details when integrating multiple variables. In this regard, we proposed a new mathematical framework for generating integrated drought index for meteorological drought monitoring. The geographically weighted regression (GWR) model and principal component analysis were used to composite Moderate-resolution Imaging Spectroradiometer (MODIS) based temperature condition index (TCI), the Vegetation Index based on the Universal Pattern Decomposition method (VIUPD) based vegetation condition index (VCI), tropical rainfall measuring mission (TRMM) based Precipitation Condition Index (PCI) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) based soil moisture condition index (SMCI). We called the new remote-sensing-based integrated drought index geographical-location-based integrated drought index (GLIDI). We examined the utility of the GLIDI for drought monitoring in various climate divisions across the continental United States (CONUS). GLIDI showed high correlations with in-situ drought indices and outperformed most other existing drought indices. The results also indicate that the performance of GLIDI is not affected by environmental factors such as land cover, precipitation, temperature and soil conditions. As such, the GLIDI has considerable potential for

  7. Use of Land Surface Temperature Observations in a Two-Source Energy Balance Model Towards Improved Monitoring of Evapotranspiration and Drought

    Hain, C.; Anderson, M. C.; Otkin, J.; Semmens, K. A.; Zhan, X.; Fang, L.; Li, Z.


    As the world's water resources come under increasing tension due to the dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. However, direct validation of ET models is challenging due to lack of available observations that are sufficiently representative at the model grid scale (10-100 km). Prognostic land-surface models require accurate information about observed precipitation, soil moisture storage, groundwater, and artificial controls on water supply (e.g., irrigation, dams, etc.) to reliably link rainfall to evaporative fluxes. In contrast, diagnostic estimates of ET can be generated, with no prior knowledge of the surface moisture state, by energy balance models using thermal-infrared remote sensing of land-surface temperature (LST) as a boundary condition. One such method, the Atmosphere Land Exchange Inverse (ALEXI) model provides estimates of surface energy fluxes through the use of mid-morning change in LST and radiation inputs. The LST inputs carry valuable proxy information regarding soil moisture and its effect on soil evaporation and canopy transpiration. Additionally, the Evaporative Stress Index (ESI) representing anomalies in the ratio of actual-to-potential ET has shown to be a reliable indicator of drought. ESI maps over the continental US show good correspondence with standard drought metrics and with patterns of precipitation, but can be generated at significantly higher spatial resolution due to a limited reliance on ground observations. Furthermore, ESI is a measure of actual stress rather than potential for stress, and has physical relevance to projected crop development. Because precipitation is not used in construction of the ESI, it provides an independent assessment of drought conditions and has particular utility for real-time monitoring in regions with sparse rainfall data or

  8. Drought limitations to leaf-level gas exchange: results from a model linking stomatal optimization and cohesion-tension theory

    Kimberly A. Novick; Chelcy F. Miniat; James M. Vose


    We merge concepts from stomatal optimization theory and cohesion–tension theory to examine the dynamics of three mechanisms that are potentially limiting to leaf-level gas exchange in trees during drought: (1) a ‘demand limitation’ driven by an assumption of optimal stomatal functioning; (2) ‘hydraulic limitation’ of water movement from the roots to the leaves...

  9. How 21st century droughts affect food and environmental security

    Kogan, Felix

    The first 13th years of the 21st century has begun with a series of widespread, long and intensive droughts around the world. Extreme and severe-to-extreme intensity droughts covered 2-6% and 7-16% of the world land, respectively, affecting environment, economies and humans. These droughts reduced agricultural production, leading to food shortages, human health deterioration, poverty, regional disturbances, population migration and death. This presentation is a travelogue of the 21st century global and regional droughts during the warmest years of the past 100 years. These droughts were identified and monitored with the NOAA operational space technology, called Vegetation Health (VH), which has the longest period of observation and provide good data quality. The VH method was used for assessment of vegetation condition or health, including drought early detection and monitoring. The VH method is based on operational satellites data estimating both land surface greenness (NDVI) and thermal conditions. The 21st century droughts in the USA, Russia, Australia Argentina, Brazil, China, India and other principal grain producing countries were intensive, long, covered large areas and caused huge losses in agricultural production, which affected food and environmental security and led to food riots in some countries. This presentation investigate how droughts affect food and environmental security, if they can be detected earlier, how to monitor their area, intensity, duration and impacts and also their dynamics during the climate warming era with satellite-based vegetation health technology.

  10. Drought and groundwater management

    Amundsen, Eirik S; Jensen, Frank

    This paper considers the problem of a water management authority faced with the threat of a drought that hits at an uncertain date. Three management policies are investigated: i) a laissez-faire (open-access) policy of automatic adjustment through a zero marginal private net benefit condition, ii......-drought steady-state equilibrium stock size of water under policy iii) is smaller than under policy ii) and, hence, a precautionary stock size should not be built up prior to the drought....

  11. Testing a hydraulic trait based model of stomatal control: results from a controlled drought experiment on aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas)

    Love, D. M.; Venturas, M.; Sperry, J.; Wang, Y.; Anderegg, W.


    Modeling approaches for tree stomatal control often rely on empirical fitting to provide accurate estimates of whole tree transpiration (E) and assimilation (A), which are limited in their predictive power by the data envelope used to calibrate model parameters. Optimization based models hold promise as a means to predict stomatal behavior under novel climate conditions. We designed an experiment to test a hydraulic trait based optimization model, which predicts stomatal conductance from a gain/risk approach. Optimal stomatal conductance is expected to maximize the potential carbon gain by photosynthesis, and minimize the risk to hydraulic transport imposed by cavitation. The modeled risk to the hydraulic network is assessed from cavitation vulnerability curves, a commonly measured physiological trait in woody plant species. Over a growing season garden grown plots of aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas) were subjected to three distinct drought treatments (moderate, severe, severe with rehydration) relative to a control plot to test model predictions. Model outputs of predicted E, A, and xylem pressure can be directly compared to both continuous data (whole tree sapflux, soil moisture) and point measurements (leaf level E, A, xylem pressure). The model also predicts levels of whole tree hydraulic impairment expected to increase mortality risk. This threshold is used to estimate survivorship in the drought treatment plots. The model can be run at two scales, either entirely from climate (meteorological inputs, irrigation) or using the physiological measurements as a starting point. These data will be used to study model performance and utility, and aid in developing the model for larger scale applications.

  12. Forecasting of meteorological drought using Wavelet-ANFIS hybrid model for different time steps (case study: Southeastern part of east Azerbaijan province, Iran)

    Shirmohammadi Chelan, Bagher; Moradi, Hamidreza; Moosavi, Vahid; Semiromi, Majid Taie; Zeinali, Ali


    Drought is accounted as one of the most natural hazards. Studying on drought is important for designing and managing of water resources systems. This research is carried out to evaluate the ability of Wavelet-ANN and adaptive neuro-fuzzy inference system (ANFIS) techniques for meteorological drought

  13. Drought in Africa 2

    Dalby, D; Harrison-Church, R J; Berzaz, F [eds.


    The second edition of Drought in Africa is reviewed. The book, which has been greatly expanded, looks at the Sahelian and Ethiopian droughts from a long-term perspective. Among the subjects included are: a description of the meteorological aspects of the drought; changes in animal and human populations; overpopulation of areas of nomadic pastoralism and of crop-producing areas; and mechanisms by which people survived. Cash crops, taxes, the market economy and over-centralized planning receive much of the blame for the effects of the drought.

  14. Kidney transplantation process in Brazil represented in business process modeling notation.

    Peres Penteado, A; Molina Cohrs, F; Diniz Hummel, A; Erbs, J; Maciel, R F; Feijó Ortolani, C L; de Aguiar Roza, B; Torres Pisa, I


    Kidney transplantation is considered to be the best treatment for people with chronic kidney failure, because it improves the patients' quality of life and increases their length of survival compared with patients undergoing dialysis. The kidney transplantation process in Brazil is defined through laws, decrees, ordinances, and resolutions, but there is no visual representation of this process. The aim of this study was to analyze official documents to construct a representation of the kidney transplantation process in Brazil with the use of business process modeling notation (BPMN). The methodology for this study was based on an exploratory observational study, document analysis, and construction of process diagrams with the use of BPMN. Two rounds of validations by specialists were conducted. The result includes the kidney transplantation process in Brazil representation with the use of BPMN. We analyzed 2 digital documents that resulted in 2 processes with 45 total of activities and events, 6 organizations involved, and 6 different stages of the process. The constructed representation makes it easier to understand the rules for the business of kidney transplantation and can be used by the health care professionals involved in the various activities within this process. Construction of a representation with language appropriate for the Brazilian lay public is underway. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Update and extension of the Brazil SimSmoke model to estimate the health impact of cigarette smoking by pregnant women in Brazil

    André Salem Szklo


    Full Text Available Abstract: A previous application of the Brazil SimSmoke tobacco control policy simulation model was used to show the effect of policies implemented between 1989 and 2010 on smoking-attributable deaths (SADs. In this study, we updated and further validated the Brazil SimSmoke model to incorporate policies implemented since 2011 (e.g., a new tax structure with the purpose of increasing revenues/real prices. In addition, we extended the model to estimate smoking-attributable maternal and child health outcomes (MCHOs, such as placenta praevia, placental abruption, preterm birth, low birth weight, and sudden infant death syndrome, to show the role of tobacco control in achieving the Millennium Development Goals. Using data on population, births, smoking, policies, and prevalence of MCHOs, the model is used to assess the effect on both premature deaths and MCHOs of tobacco control policies implemented in Brazil in the last 25 years relative to a counterfactual of policies kept at 1989 levels. Smoking prevalence in Brazil has fallen by an additional 17% for males (16%-19% and 19% for females (14%-24% between 2011 and 2015. As a result of the policies implemented since 1989, 7.5 million (6.4-8.5 deaths among adults aged 18 years or older are projected to be averted by 2050. Current policies are also estimated to reduce a cumulative total of 0.9 million (0.4-2.4 adverse MCHOs by 2050. Our findings show the benefits of tobacco control in reducing both SADs and smoking-attributable MCHOs at population level. These benefits may be used to better inform policy makers in low and middle income countries about allocating resources towards tobacco control policies in this important area.

  16. The Amazon rainforest, climate change, and drought: How will what is below the surface affect the climate of tropical South America?

    Harper, A.; Denning, A. S.; Baker, I.; Randall, D.; Dazlich, D.


    Several climate models have predicted an increase in long-term droughts in tropical South America due to increased greenhouse gases in the atmosphere. Although the Amazon rainforest is resilient to seasonal drought, multi-year droughts pose a definite problem for the ecosystem's health. Furthermore, drought- stressed vegetation participates in feedbacks with the atmosphere that can exacerbate drought. Namely, reduced evapotranspiration further dries out the atmosphere and affects the regional climate. Trees in the rainforest survive seasonal drought by using deep roots to access adequate stores of soil moisture. We investigate the climatic impacts of deep roots and soil moisture by coupling the Simple Biosphere (SiB3) model to Colorado State University's general circulation model (BUGS5). We compare two versions of SiB3 in the GCM during years with anomalously low rainfall. The first has strong vegetative stress due to soil moisture limitations. The second experiences less stress and has more realistic representations of surface biophysics. In the model, basin-wide reductions in soil moisture stress result in increased evapotranspiration, precipitation, and moisture recycling in the Amazon basin. In the savannah region of southeastern Brazil, the unstressed version of SiB3 produces decreased precipitation and weaker moisture flux, which is more in-line with observations. The improved simulation of precipitation and evaporation also produces a more realistic Bolivian high and Nordeste low. These changes highlight the importance of subsurface biophysics for the Amazonian climate. The presence of deep roots and soil moisture will become even more important if climate change brings more frequent droughts to this region in the future.

  17. Hydro-Economic Modeling with Minimum Data Requirements: An Application to the São Francisco River Basin, Brazil

    Torres, M.; Maneta, M.; Vosti, S.; Wallender, W.; Howitt, R.


    Policymakers have been charged with the efficient, equitable, and sustainable use of water resources of the São Francisco River Basin (SFRB), Brazil, and also with the promotion of economic growth and the reduction of poverty within the basin. To date, policymakers lack scientific evidence on the potential consequences for growth, poverty alleviation or environmental sustainability of alternative uses of water resources. To address these key knowledge gaps, we have linked a hydrologic and an economic model of agriculture to investigate how economic decisions affect available water, and vice versa. More specifically, the models are used to predict the effects of the application of Brazilian federal surface water use policies on farmer's net revenues and on the hydrologic system. The Economic Model of Agriculture. A spatially explicit, farm-level model capable of accommodating a broad array of farm sizes and farm/farmer characteristics is developed and used to predict the effects of alternative water policies and neighbors' water use patterns on crop mix choice. A production function comprised of seven categories of non-water-related inputs used in agriculture (land, fertilizers, pesticides, seeds, hired labor, family labor and machinery) and four water-related inputs used in agriculture (applied water, irrigation labor, irrigation capital and energy) is estimated. The parameters emerging from this estimated production function are then introduced into a non-linear, net revenue maximization positive mathematical programming algorithm that is used for simulations. The Hydrological Model. MIKE Basin, a semi-distributed hydrology model, is used to calculate water budgets for the SFRB. MIKE Basin calculates discharge at selected nodes by accumulating runoff down the river network; it simulates reservoirs using stage-area-storage and downstream release rule curves. The data used to run the model are discharge to calculate local runoff, precipitation, reference ET, crop

  18. Knowledge management: Postgraduate Alternative Evaluation Model (MAPA in Brazil

    Deisy Cristina Corrêa Igarashi


    Full Text Available The Brazilian stricto sensu postgraduate programs that include master and / or doctorate courses are evaluated by Coordination for the Improvement of Higher Education Personnel (CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior. The evaluation method used by CAPES is recognized in national and international context. However, several elements of the evaluation method can be improved. For example: to consider programs diversity, heterogeneity and specificities; to reduce subjectivity and to explain how indicators are grouped into different dimensions to generate a final result, which is scoring level reached by a program. This study aims to analyze the evaluation process by CAPES, presenting questions, difficulties and objections raised by researchers. From the analysis, the study proposes an alternative evaluation model for postgraduate (MAPA - Modelo de Avaliação para Pós graduação Alternativo which incorporates fuzzy logic in result analysis to minimize limitations identified. The MAPA was applied in three postgraduate programs, allowing: (1 better understanding of procedures used for the evaluation, (2 identifying elements that need regulation, (3 characterization of indicators that generate local evaluation, (4 support in medium and long term planning.

  19. Agricultural Productivity Forecasts for Improved Drought Monitoring

    Limaye, Ashutosh; McNider, Richard; Moss, Donald; Alhamdan, Mohammad


    Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop

  20. Updated numerical model with uncertainty assessment of 1950-56 drought conditions on brackish-water movement within the Edwards aquifer, San Antonio, Texas

    Brakefield, Linzy K.; White, Jeremy T.; Houston, Natalie A.; Thomas, Jonathan V.


    In 2010, the U.S. Geological Survey, in cooperation with the San Antonio Water System, began a study to assess the brackish-water movement within the Edwards aquifer (more specifically the potential for brackish-water encroachment into wells near the interface between the freshwater and brackish-water transition zones, referred to in this report as the transition-zone interface) and effects on spring discharge at Comal and San Marcos Springs under drought conditions using a numerical model. The quantitative targets of this study are to predict the effects of higher-than-average groundwater withdrawals from wells and drought-of-record rainfall conditions of 1950–56 on (1) dissolved-solids concentration changes at production wells near the transition-zone interface, (2) total spring discharge at Comal and San Marcos Springs, and (3) the groundwater head (head) at Bexar County index well J-17. The predictions of interest, and the parameters implemented into the model, were evaluated to quantify their uncertainty so the results of the predictions could be presented in terms of a 95-percent credible interval.

  1. Drought timing and local climate determine the sensitivity of eastern temperate forests to drought.

    D'Orangeville, Loïc; Maxwell, Justin; Kneeshaw, Daniel; Pederson, Neil; Duchesne, Louis; Logan, Travis; Houle, Daniel; Arseneault, Dominique; Beier, Colin M; Bishop, Daniel A; Druckenbrod, Daniel; Fraver, Shawn; Girard, François; Halman, Joshua; Hansen, Chris; Hart, Justin L; Hartmann, Henrik; Kaye, Margot; Leblanc, David; Manzoni, Stefano; Ouimet, Rock; Rayback, Shelly; Rollinson, Christine R; Phillips, Richard P


    Projected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi-arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America (ENA) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests of ENA, representing 24 species and 346 stands, to determine the broad-scale drivers of drought sensitivity for the dominant trees in ENA. Here we show that two factors-the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration; PET)-are stronger drivers of drought sensitivity than soil and stand characteristics. Drought-induced reductions in tree growth were greatest when the droughts occurred during early-season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highest PET). Further, mean species trait values (rooting depth and ψ 50 ) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early-season PET may exacerbate these effects, and potentially offset gains in C uptake and storage in ENA owing to other global change factors. © 2018 John Wiley & Sons Ltd.

  2. Location model of specialized terminals for soybe an exports in Brazil

    Alessandra Fraga Dubke


    Full Text Available The purpose of this work is the development of a location model for specialized terminals used as transshipment points in the supply chain of soybeans. The theoretical basis of the study relies on the association of a transshipment model with a multi-commodity, multi-facility capacitated location model. The shipping ports might be seen as specialized terminals that add value to the exported products by transforming raw soy grains into soy oil and soy meal. The proposed model also considers service activities in each terminal and the capacity of the maritime ports. Using representative data from the year 2004, the model is illustrated by a small case study, which considers six points of production in inland Brazil, all served by railways, one maritime port on the north and five on the east coast, and three destination ports in Europe and Asia. The study includes a rough sensitivity analysis regarding volumes, capacities, prices, and transportation costs

  3. Brief communication: Drought likelihood for East Africa

    Yang, Hui; Huntingford, Chris


    The East Africa drought in autumn of year 2016 caused malnutrition, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya needed food, water and medical assistance. Many factors influence drought stress and response. However, inevitably the following question is asked: are elevated greenhouse gas concentrations altering extreme rainfall deficit frequency? We investigate this with general circulation models (GCMs). After GCM bias correction to match the climatological mean of the CHIRPS data-based rainfall product, climate models project small decreases in probability of drought with the same (or worse) severity as 2016 ASO (August to October) East African event. This is by the end of the 21st century compared to the probabilities for present day. However, when further adjusting the climatological variability of GCMs to also match CHIRPS data, by additionally bias-correcting for variance, then the probability of drought occurrence will increase slightly over the same period.

  4. Brief communication: Drought likelihood for East Africa

    H. Yang


    Full Text Available The East Africa drought in autumn of year 2016 caused malnutrition, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya needed food, water and medical assistance. Many factors influence drought stress and response. However, inevitably the following question is asked: are elevated greenhouse gas concentrations altering extreme rainfall deficit frequency? We investigate this with general circulation models (GCMs. After GCM bias correction to match the climatological mean of the CHIRPS data-based rainfall product, climate models project small decreases in probability of drought with the same (or worse severity as 2016 ASO (August to October East African event. This is by the end of the 21st century compared to the probabilities for present day. However, when further adjusting the climatological variability of GCMs to also match CHIRPS data, by additionally bias-correcting for variance, then the probability of drought occurrence will increase slightly over the same period.

  5. Tree responses to drought

    Michael G. Ryan


    With global climate change, drought may become more common in the future (IPCC 2007). Several factors will promote more frequent droughts: earlier snowmelt, higher temperatures and higher variability in precipitation. For ecosystems where the water cycle is dominated by snowmelt, warmer temperatures bring earlier melt (Stewart et al. 2005) and longer, drier snow-free...

  6. USGS integrated drought science

    Ostroff, Andrea C.; Muhlfeld, Clint C.; Lambert, Patrick M.; Booth, Nathaniel L.; Carter, Shawn L.; Stoker, Jason M.; Focazio, Michael J.


    Project Need and OverviewDrought poses a serious threat to the resilience of human communities and ecosystems in the United States (Easterling and others, 2000). Over the past several years, many regions have experienced extreme drought conditions, fueled by prolonged periods of reduced precipitation and exceptionally warm temperatures. Extreme drought has far-reaching impacts on water supplies, ecosystems, agricultural production, critical infrastructure, energy costs, human health, and local economies (Milly and others, 2005; Wihlite, 2005; Vörösmarty and others, 2010; Choat and others, 2012; Ledger and others, 2013). As global temperatures continue to increase, the frequency, severity, extent, and duration of droughts are expected to increase across North America, affecting both humans and natural ecosystems (Parry and others, 2007).The U.S. Geological Survey (USGS) has a long, proven history of delivering science and tools to help decision-makers manage and mitigate effects of drought. That said, there is substantial capacity for improved integration and coordination in the ways that the USGS provides drought science. A USGS Drought Team was formed in August 2016 to work across USGS Mission Areas to identify current USGS drought-related research and core capabilities. This information has been used to initiate the development of an integrated science effort that will bring the full USGS capacity to bear on this national crisis.

  7. Resilient Leaf Physiological Response of European Beech (Fagus sylvatica L. to Summer Drought and Drought Release

    Ellen E. Pflug


    Full Text Available Drought is a major environmental constraint to trees, causing severe stress and thus adversely affecting their functional integrity. European beech (Fagus sylvatica L. is a key species in mesic forests that is commonly expected to suffer in a future climate with more intense and frequent droughts. Here, we assessed the seasonal response of leaf physiological characteristics of beech saplings to drought and drought release to investigate their potential to recover from the imposed stress and overcome previous limitations. Saplings were transplanted to model ecosystems and exposed to a simulated summer drought. Pre-dawn water potentials (ψpd, stomatal conductance (gS, intercellular CO2 concentration (ci, net-photosynthesis (AN, PSII chlorophyll fluorescence (PItot, non-structural carbohydrate concentrations (NSC; soluble sugars, starch and carbon isotope signatures were measured in leaves throughout the growing season. Pre-dawn water potentials (ψpd, gS, ci, AN, and PItot decreased as drought progressed, and the concentration of soluble sugars increased at the expense of starch. Carbon isotopes in soluble sugars (δ13CS showed a distinct increase under drought, suggesting, together with decreased ci, stomatal limitation of AN. Drought effects on ψpd, ci, and NSC disappeared shortly after re-watering, while full recovery of gS, AN, and PItot was delayed by 1 week. The fast recovery of NSC was reflected by a rapid decay of the drought signal in δ13C values, indicating a rapid turnover of assimilates and a reactivation of carbon metabolism. After recovery, the previously drought-exposed saplings showed a stimulation of AN and a trend toward elevated starch concentrations, which counteracted the previous drought limitations. Overall, our results suggest that the internal water relations of beech saplings and the physiological activity of leaves are restored rapidly after drought release. In the case of AN, stimulation after drought may partially

  8. Caracterização climatológica da severidade de secas do Estado do Ceará - Brasil Climatological characterization of the drought severity in the State of Ceará - Brazil

    Tarcisio da S. Barra


    Full Text Available O objetivo deste trabalho foi caracterizar as secas do Estado do Ceará, com base no índice de severidade de seca de Palmer. Foram utilizadas séries históricas de dados pluviométricos e de temperatura do ar de 21 localidades desse Estado, fornecidas, respectivamente, pela Superintendência de Desenvolvimento do Nordeste - SUDENE, e pela Fundação Cearense de Meteorologia e Recursos Hídricos - FUNCEME. Foi constatado a ocorrência de secas com diferentes graus de severidade, no Estado do Ceará, sendo as secas moderadas e severas as mais freqüentes.The objective of this work was to characterize the droughts in the State of Ceará based on the Palmer drought severity index. Historical data series of rainfall and air temperature of 21 localities of this State, were provided by the "Superintendência de Desenvolvimento do Nordeste - SUDENE", and by the "Fundação Cearense de Meteorologia e Recursos Hídricos - FUNCEME", respectively. The occurrences of droughts of different degrees of severity were verified in the State of Ceará, with frequent moderate and severe droughts.

  9. CreativeDrought: An interdisciplinary approach to building resilience to drought

    Rangecroft, Sally; Van Loon, Anne; Rohse, Melanie; Day, Rosie; Birkinshaw, Stephen; Makaya, Eugine


    Drought events cause severe water and food insecurities in many developing countries where resilience to natural hazards and change is low due to a number of reasons (including poverty, social and political inequality, and limited access to information). Furthermore, with climate change and increasing pressures from population and societal change, populations are expected to experience future droughts outside of their historic range. Integrated water resources management is an established tool combining natural science, engineering and management to help address drought and associated impacts. However, it often lacks a strong social and cultural aspect, leading to poor implementation on the ground. For a more holistic approach to building resilience to future drought, a stronger interdisciplinary approach is required which can incorporate the local cultural context and perspectives into drought and water management, and communicate information effectively to communities. In this pilot project 'CreativeDrought', we use a novel interdisciplinary approach aimed at building resilience to future drought in rural Africa by combining hydrological modelling with rich local information and engaging communicative approaches from social sciences. The work is conducted through a series of steps in which we i) engage with local rural communities to collect narratives on drought experiences; ii) generate hydrological modelling scenarios based on IPCC projections, existing data and the collected narratives; iii) feed these back to the local community to gather their responses to these scenarios; iv) iteratively adapt them to obtain hypothetical future drought scenarios; v) engage the community with the scenarios to formulate new future drought narratives; and vi) use this new data to enhance local water resource management. Here we present some of the indigenous knowledge gathered through narratives and the hydrological modelling scenarios for a rural community in Southern Africa

  10. Climate Change Implications to Irrigated Rice Production in Southern Brazil: A Modelling Approach

    Dos Santos, Thiago

    Rice is one of the staple foods for more than three billion people worldwide. When cultivated under irrigated conditions (i.e. lowland rice), rice is one of the most intensive water consumer crops globally. Therefore, representation of rice growth should be integrated into the latest land surface models to allow studies on food security and to ensure that accurate simulations of the bidirectional feedbacks between the land surface and atmosphere take place. In this study, I present a new process-based model for rice fields that includes rice growth and rice irrigation as modules within the Agro-IBIS dynamic agro-ecosystem model. The model includes a series of equations, agricultural management parameters and an irrigation scheme that are specifically tailored for rice crops. The model was evaluated against leaf area index and biomass observations, obtained for one growing season in Rio Grande do Sul state (southern Brazil), and in Los Banos, Philippines. The model accurately captured the temporal dynamics of leaf area index in both the Brazilian and the Philippine sites, and predicted end-of-season biomass with an error of between -9.5% and 11.3% depending on the location and the plant organ. Rice phenology is predicted by the model based on experimentally-derived growth rates, and was evaluated by comparing simulated and observed durations of the four growth phases considered by the model. Agro-IBIS showed a tendency to overestimate the duration of the growth stages between 3% and 16%, but underestimated by 8% the duration of the panicle formation phase in one growing season. The new irrigation model is based on the water balance at the surface and applies irrigation in order to keep the water layer at the paddy field always in the optimum level. A set of climate projections from global climate models under two emission scenarios, and excluding and considering CO2 fertilizations effects, was used to drive the updated Agro-IBIS to estimate the effects of climate

  11. Civil conflict sensitivity to growing-season drought

    von Uexkull, Nina; Croicu, Mihai; Fjelde, Hanne; Buhaug, Halvard


    Understanding the conflict potential of drought is critical for dealing effectively with the societal implications of climate change. Using new georeferenced ethnicity and conflict data for Asia and Africa since 1989, we present an actor-oriented analysis of growing-season drought and conflict involvement among ethnic groups. Results from naive models common in previous research suggest that drought generally has little impact. However, context-sensitive models accounting for the groups’ leve...

  12. Drought tolerance in potato (S. tuberosum L.): Can we learn from drought tolerance research in cereals?

    Monneveux, Philippe; Ramírez, David A; Pino, María-Teresa


    Drought tolerance is a complex trait of increasing importance in potato. Our knowledge is summarized concerning drought tolerance and water use efficiency in this crop. We describe the effects of water restriction on physiological characteristics, examine the main traits involved, report the attempts to improve drought tolerance through in vitro screening and marker assisted selection, list the main genes involved and analyze the potential interest of native and wild potatoes to improve drought tolerance. Drought tolerance has received more attention in cereals than in potato. The review compares these crops for indirect selection methods available for assessment of drought tolerance related traits, use of genetic resources, progress in genomics, application of water saving techniques and availability of models to anticipate the effects of climate change on yield. It is concluded that drought tolerance improvement in potato could greatly benefit from the transfer of research achievements in cereals. Several promising research directions are presented, such as the use of fluorescence, reflectance, color and thermal imaging and stable isotope techniques to assess drought tolerance related traits, the application of the partial root-zone drying technique to improve efficiency of water supply and the exploitation of stressful memory to enhance hardiness. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Drought management plans and water availability in agriculture: A risk assessment model for a Southern European basin

    Carlos Dionisio Pérez-Blanco


    Full Text Available The Drought Management Plans (DMPs are regulatory instruments that establish priorities among the different water uses and define more stringent constraints to access to publicly provided water during droughts, especially for non-priority uses such as agriculture. These plans have recently become widespread across EU southern basins. However, in some of these basins the plans were approved without an assessment of the potential impacts that they may have on the economic activities exposed to water restrictions. This paper develops a stochastic methodology to estimate the expected water availability in agriculture that results from the decision rules of the recently approved DMPs. The methodology is applied to the particular case of the Guadalquivir River Basin in southern Spain. Results show that if DMPs are successfully enforced, available water will satisfy in average 62.2% of current demand, and this figure may drop to 50.2% by the end of the century as a result of climate change. This is much below the minimum threshold of 90% that has been guaranteed to irrigators so far.


    Luís Fernando Ascenção Guedes


    Full Text Available The element that characterizes the information era is the key role of communication and connectivity, broadly speaking, in social life. Among the ways in which users can enter voice or data networks, one of the most prominent is mobile telephony.Therefore, determining the number of mobile phones in operation in Brazil over the next few years is a relevant issue for the strategic planning of firms in this sector. Thus, this article aims to define a mathematical model suitable for calculating the number of mobile phones in operation in Brazil in forthcoming years, as a function of the behavior of the following variables during the course of time: GDP per capita, population and percentage GDP growth.To this end, a quantitative study was conducted, based on secondary data taken from preceding survey; then a linear and polynomial regression was employed to correlate GDP per capita with mobile phone density. The results showed high correlation (97.5% between phone density and Brazil’s GDP growth from 2004 to 2007. This correlation is also high in Russia, India and China.Moreover, we found that the limiting value of good correlation between GDP per capita and mobile phone density is roughly US$20,000.00 and that the limit of mobile telephony penetration is approximately 120%. Thus, taking into account several economic growth rates, we estimate that the penetration of mobile telephony will take 5 to 11 years to reach its upper limit in Brazil.Key words: Mobile telephony. Prediction model. Telecommunications.

  15. Large-scale hydrological modelling in the semi-arid north-east of Brazil

    Güntner, Andreas


    Semi-arid areas are, due to their climatic setting, characterized by small water resources. An increasing water demand as a consequence of population growth and economic development as well as a decreasing water availability in the course of possible climate change may aggravate water scarcity in future, which often exists already for present-day conditions in these areas. Understanding the mechanisms and feedbacks of complex natural and human systems, together with the quantitative assessment of future changes in volume, timing and quality of water resources are a prerequisite for the development of sustainable measures of water management to enhance the adaptive capacity of these regions. For this task, dynamic integrated models, containing a hydrological model as one component, are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability in view of environmental change over a large geographic domain of semi-arid environments. The study area is the Federal State of Ceará (150 000 km2) in the semi-arid north-east of Brazil. Mean annual precipitation in this area is 850 mm, falling in a rainy season with duration of about five months. Being mainly characterized by crystalline bedrock and shallow soils, surface water provides the largest part of the water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. The hydrological model Wasa (Model of Water Availability in Semi-Arid Environments) developed in this study is a deterministic, spatially distributed model being composed of conceptual, process-based approaches. Water availability (river discharge, storage volumes in reservoirs, soil moisture) is determined with daily resolution. Sub-basins, grid cells or administrative units (municipalities) can be chosen as spatial target units. The administrative units enable the coupling of Wasa in


    R. Obringer


    Full Text Available This study aims to integrate environmental data for drought monitoring to reduce uncertainty in urban drought characterization as part of the smart city framework. Currently, drought monitoring in urban areas is a challenge. This is due, in part, to a lack of knowledge on the subject of urban droughts and urban drought vulnerability. A critical part to assessing urban drought and implementing the necessary policies is determining drought conditions. Often the timing and severity of the drought can leave cities to enforce water restrictions, so accuracy of this determination has socioeconomic implications. To determine drought conditions, we need to know the water balance over the urban landscape, of which evapotranspiration (ET is a key variable. However, ET data and models have high uncertainty when compared to other hydrological variables (i.e., precipitation. This is largely due to ill-defined empirical models for characterizing the urban surface resistance parameter (rs that is used in ET calculations. We propose a method to estimate rs values using a combination of the Surface Temperature Initiated Closure (STIC method that calculates regional evapotranspiration data and an inverted version of the Penman-Monteith equation. We use this approach across the region surrounding Indianapolis, IN (USA from 2010-2014. We discuss the potential for this method to be integrated in to smart city framework to improve urban drought assessment.

  17. Intense rainfalls prediction models for the state of Mato Grosso, Brazil

    Sidney Pereira


    Full Text Available Rain intensity data are necessary to increase security of hydraulic projects. The objective of this study was to determine the relationships among intensity-duration-frequency (IDF and Bell’s model for the State of Mato Grosso, Brazil. The equations were obtained by disaggregation of 24 h rainfall data from 136 rain stations available in the National Water Agency (ANA data base. Employing Gumbel distribution, the rainfalls were estimated for each time duration and for the return periods of 2, 5, 10, 25, 50 and 100 years, and thereafter for each season. The coefficients of IDF relationships and Bell’s models were adjusted by the minimum square method, for all seasons evaluated. The coefficients of determination and Willmott agreement index exceeded 0.98 and 0.85, respectively, for all stations, which classifies the adjustment of the rainfall models as great.

  18. Modelling of redox front and uranium movement in a uranium mine at Pocos de Caldas, Brazil

    Cross, J.E.; Gabriel, D.S.; Haworth, A.; Sharland, S.M.; Tweed, C.J.


    A study of the migration of uranium at the Pocos de Caldas uranium mine in Brazil under the influence of the infiltration of oxidising groundwaters has been performed. The modelling was carried out using the coupled chemical equilibria/transport code CHEQMATE. The work presented in this paper extends a previous study. Results give some encouraging agreements with field data, generally increasing confidence in the use of such modelling techniques in problems associated with the migration of radionuclides away from a nuclear waste repository. For particular aspects of the problem where good agreement with field data was not obtained, a number of reasons have been suggested. This study also highlights the importance of accurate thermodynamic data and choice of solubility-limiting mineral phases for modelling such systems. (author)

  19. Searching for the optimal drought index and timescale combination to detect drought: a case study from the lower Jinsha River basin, China

    Fluixá-Sanmartín, Javier; Pan, Deng; Fischer, Luzia; Orlowsky, Boris; García-Hernández, Javier; Jordan, Frédéric; Haemmig, Christoph; Zhang, Fangwei; Xu, Jijun


    Drought indices based on precipitation are commonly used to identify and characterize droughts. Due to the general complexity of droughts, the comparison of index-identified events with droughts at different levels of the complete system, including soil humidity or river discharges, relies typically on model simulations of the latter, entailing potentially significant uncertainties. The present study explores the potential of using precipitation-based indices to reproduce observed droughts in the lower part of the Jinsha River basin (JRB), proposing an innovative approach for a catchment-wide drought detection and characterization. Two indicators, namely the Overall Drought Extension (ODE) and the Overall Drought Indicator (ODI), have been defined. These indicators aim at identifying and characterizing drought events on the basin scale, using results from four meteorological drought indices (standardized precipitation index, SPI; rainfall anomaly index, RAI; percent of normal precipitation, PN; deciles, DEC) calculated at different locations of the basin and for different timescales. Collected historical information on drought events is used to contrast results obtained with the indicators. This method has been successfully applied to the lower Jinsha River basin in China, a region prone to frequent and severe droughts. Historical drought events that occurred from 1960 to 2014 have been compiled and cataloged from different sources, in a challenging process. The analysis of the indicators shows a good agreement with the recorded historical drought events on the basin scale. It has been found that the timescale that best reproduces observed events across all the indices is the 6-month timescale.

  20. Energy from sugarcane bagasse under electricity rationing in Brazil: a computable general equilibrium model

    Scaramucci, Jose A.; Perin, Clovis; Pulino, Petronio; Bordoni, Orlando F.J.G.; Cunha, Marcelo P. da; Cortez, Luis A.B.


    In the midst of the institutional reforms of the Brazilian electric sectors initiated in the 1990s, a serious electricity shortage crisis developed in 2001. As an alternative to blackout, the government instituted an emergency plan aimed at reducing electricity consumption. From June 2001 to February 2002, Brazilians were compelled to curtail electricity use by 20%. Since the late 1990s, but especially after the electricity crisis, energy policy in Brazil has been directed towards increasing thermoelectricity supply and promoting further gains in energy conservation. Two main issues are addressed here. Firstly, we estimate the economic impacts of constraining the supply of electric energy in Brazil. Secondly, we investigate the possible penetration of electricity generated from sugarcane bagasse. A computable general equilibrium (CGE) model is used. The traditional sector of electricity and the remainder of the economy are characterized by a stylized top-down representation as nested CES (constant elasticity of substitution) production functions. The electricity production from sugarcane bagasse is described through a bottom-up activity analysis, with a detailed representation of the required inputs based on engineering studies. The model constructed is used to study the effects of the electricity shortage in the preexisting sector through prices, production and income changes. It is shown that installing capacity to generate electricity surpluses by the sugarcane agroindustrial system could ease the economic impacts of an electric energy shortage crisis on the gross domestic product (GDP)

  1. Drought Forecasting Using Adaptive Neuro-Fuzzy Inference Systems (ANFIS, Drought Time Series and Climate Indices For Next Coming Year, (Case Study: Zahedan

    Hossein Hosseinpour Niknam


    Full Text Available In this research in order to forecast drought for the next coming year in Zahedan, using previous Standardized Precipitation Index (SPI data and 19 other climate indices were used.  For this purpose Adaptive Neuro-Fuzzy Inference System (ANFIS was applied to build the predicting model and SPI drought index for drought quantity.  At first calculating correlation approach for analysis between droughts and climate indices was used and the most suitable indices were selected. In the next stage drought prediction for period of 12 months was done. Different combinations among input variables in ANFIS models were entered. SPI drought index was the output of the model.  The results showed that just using time series like the previous year drought SPI index in forecasting the 12 month drought was effective. However among all climate indices that were used, Nino4 showed the most suitable results.

  2. MAESPA: a model to study interactions between water limitation, environmental drivers and vegetation function at tree and stand levels, with an example application to [CO2] × drought interactions

    B. E. Medlyn


    Full Text Available Process-based models (PBMs of vegetation function can be used to interpret and integrate experimental results. Water limitation to plant carbon uptake is a highly uncertain process in the context of environmental change, and many experiments have been carried out that study drought limitations to vegetation function at spatial scales from seedlings to entire canopies. What is lacking in the synthesis of these experiments is a quantitative tool incorporating a detailed mechanistic representation of the water balance that can be used to integrate and analyse experimental results at scales of both the whole-plant and the forest canopy. To fill this gap, we developed an individual tree-based model (MAESPA, largely based on combining the well-known MAESTRA and SPA ecosystem models. The model includes a hydraulically-based model of stomatal conductance, root water uptake routines, drainage, infiltration, runoff and canopy interception, as well as detailed radiation interception and leaf physiology routines from the MAESTRA model. The model can be applied both to single plants of arbitrary size and shape, as well as stands of trees. The utility of this model is demonstrated by studying the interaction between elevated [CO2] (eCa and drought. Based on theory, this interaction is generally expected to be positive, so that plants growing in eCa should be less susceptible to drought. Experimental results, however, are varied. We apply the model to a previously published experiment on droughted cherry, and show that changes in plant parameters due to long-term growth at eCa (acclimation may strongly affect the outcome of Ca × drought experiments. We discuss potential applications of MAESPA and some of the key uncertainties in process representation.

  3. Modeling temporal and spatial variability of leaf wetness duration in Brazil

    Alvares, Clayton Alcarde; de Mattos, Eduardo Moré; Sentelhas, Paulo Cesar; Miranda, Aline Cristina; Stape, José Luiz


    Leaf wetness duration (LWD) is recognized as a very important conditioner of crops and forests diseases, but clearly, there is a considerable gap in literature on temporal models for prediction of LWD in broad regions from standard meteorological data. The objective of this study was to develop monthly LWD models based on the relationship between hours of relative humidity (RH) ≥ 90 % and average RH for Brazil and based on these models to characterize the temporal and spatial LWD variability across the country. Two different relative humidity databases, being one in an hourly basis (RHh) and another in a monthly basis (RHm), were used. To elaborate the LWD models, 58 automatic weather stations distributed across the country were selected. Monthly LWD maps for the entire country were prepared, and for that, the RHm from the 358 conventional weather stations were interpolated using geostatistical techniques. RHm and LWD showed sigmoidal relationship with determination coefficient above 0.84 and were highly significant ( p LWD monthly models, a very good performance for all months was obtained, with very high precision with r between 0.92 and 0.96. Regarding the errors, mean error showed a slight tendency of overestimation during February (0.29 h day-1), May (0.31 h day-1), July (0.14 h day-1), and August (0.34 h day-1), whereas for the other months, the tendency was of underestimation like January (-0.27 h day-1) and March (-0.25 h day-1). Even as a first approach, the results presented here represent a great advance in the climatology of LWD for Brazil and will allow the development of studies related to crop and forest diseases control plans.

  4. An extended multivariate framework for drought monitoring in Mexico

    Real-Rangel, Roberto; Pedrozo-Acuña, Adrián; Breña-Naranjo, Agustín; Alcocer-Yamanaka, Víctor


    Around the world, monitoring natural hazards, such as droughts, represents a critical task in risk assessment and management plans. A reliable drought monitoring system allows to identify regions affected by these phenomena so that early response measures can be implemented. In Mexico, this activity is performed using Mexico's Drought Monitor, which is based on a similar methodology as the United States Drought Monitor and the North American Drought Monitor. The main feature of these monitoring systems is the combination of ground-based and remote sensing observations that is ultimately validated by local experts. However, in Mexico in situ records of variables such as precipitation and streamflow are often scarce, or even null, in many regions of the country. Another issue that adds uncertainty in drought monitoring is the arbitrary weight given to each analyzed variable. This study aims at providing an operational framework for drought monitoring in Mexico, based on univariate and multivariate nonparametric standardized indexes proposed in recent studies. Furthermore, the framework has been extended by taking into account the Enhanced Vegetation Index (EVI) for the drought severity assessment. The analyzed variables used for computing the drought indexes are mainly derived from remote sensing (MODIS) and land surface models datasets (NASA MERRA-2). A qualitative evaluation of the results shows that the indexes used are capable of adequately describes the intensity and spatial distribution of past drought documented events.

  5. Climate and drought

    McNab, Alan L.

    Drought is a complex phenomenon that can be defined from several perspectives [Wilhite and Glantz, 1987]. The common characteristic and central idea of these perspectives is the straightforward notion of a water deficit. Complexity arises because of the need to specify the part of the hydrologic cycle experiencing the deficit and the associated time period. For example, a long-term deficit in deep groundwater storage can occur simultaneously with a short-term surplus of root zone soil water.Figure 1 [Changnon, 1987] illustrates how the definitions of drought are related to specific components of the hydrologic cycle. The dashed lines indicate the delayed translation of two hypothetical precipitation deficits with respect to runoff, soil moisture, streamflow and groundwater. From this perspective, precipitation can be considered as the carrier of the drought signal, and hydrological processes are among the final indicators that reveal the presence of drought [Hare, 1987; Klemes, 1987].

  6. Palmer Drought Severity Index

    National Oceanic and Atmospheric Administration, Department of Commerce — PDSI from the Dai dataset. The Palmer Drought Severity Index (PDSI) is devised by Palmer (1965) to represent the severity of dry and wet spells over the U.S. based...

  7. Observations and model calculations of an additional layer in the topside ionosphere above Fortaleza, Brazil

    B. Jenkins


    Full Text Available Calculations using the Sheffield University plasmasphere ionosphere model have shown that under certain conditions an additional layer can form in the low latitude topside ionosphere. This layer (the F3 layer has subsequently been observed in ionograms recorded at Fortaleza in Brazil. It has not been observed in ionograms recorded at the neighbouring station São Luis. Model calculations have shown that the F3 layer is most likely to form in summer at Fortaleza due to a combination of the neutral wind and the E×B drift acting to raise the plasma. At the location of São Luis, almost on the geomagnetic equator, the neutral wind has a smaller vertical component so the F3 layer does not form.

  8. The SIR model of Zika virus disease outbreak in Brazil at year 2015

    Aik, Lim Eng; Kiang, Lam Chee; Hong, Tan Wei; Abu, Mohd Syafarudy


    This research study demonstrates a numerical model intended for comprehension the spread of the year 2015 Zika virus disease utilizing the standard SIR framework. In modeling virulent disease dynamics, it is important to explore whether the illness spread could accomplish a pandemic level or it could be eradicated. Information from the year 2015 Zika virus disease event is utilized and Brazil where the event began is considered in this research study. A three dimensional nonlinear differential equation is formulated and solved numerically utilizing the Euler's method in MS excel. It is appeared from the research study that, with health intercessions of public, the viable regenerative number can be decreased making it feasible for the event to cease to exist. It is additionally indicated numerically that the pandemic can just cease to exist when there are no new infected people in the populace.

  9. Context analysis for a new regulatory model for electric utilities in Brazil

    El Hage, Fabio S.; Rufín, Carlos


    This article examines what would have to change in the Brazilian regulatory framework in order to make utilities profit from energy efficiency and the integration of resources, instead of doing so from traditional consumption growth, as it happens at present. We argue that the Brazilian integrated electric sector resembles a common-pool resources problem, and as such it should incorporate, in addition to the centralized operation for power dispatch already in place, demand side management, behavioral strategies, and smart grids, attained through a new business and regulatory model for utilities. The paper proposes several measures to attain a more sustainable and productive electricity distribution industry: decoupling revenues from volumetric sales through a fixed maximum load fee, which would completely offset current disincentives for energy efficiency; the creation of a market for negawatts (saved megawatts) using the current Brazilian mechanism of public auctions for the acquisition of wholesale energy; and the integration of technologies, especially through the growth of unregulated products and services. Through these measures, we believe that Brazil could improve both energy security and overall sustainability of its power sector in the long run. - Highlights: • Necessary changes in the Brazilian regulatory framework towards energy efficiency. • How to incorporate demand side management, behavioral strategies, and smart grids. • Proposition of a market for negawatts at public auctions. • Measures to attain a more sustainable electricity distribution industry in Brazil.

  10. Piloting a Commercial Model for Fortified Rice: Lessons Learned From Brazil.

    Milani, Peiman; Spohrer, Rebecca; Garrett, Greg; Kreis, Katharine


    Two billion people worldwide have micronutrient deficiencies. Food fortification is a proven intervention to increase essential micronutrient availability in diets without requiring consumer behavioral change. Fortification of rice has high potential reach; however, cost, technology, market, and cultural constraints have prevented its wider adoption. From 2010 to 2014, PATH and Global Alliance for Improved Nutrition implemented a pilot project in Brazil testing a model to scale up rice fortification through commercial channels. The project focused on 5 areas: (1) building fortified rice kernel production capacity; (2) supply chain development; (3) distribution channel and market development; (4) demand generation; and (5) advocacy and knowledge dissemination. Primary data were collected in 2 rounds of quantitative research 6 months apart and conducted in 2 regions in Brazil. Secondary data were sourced from published literature, socioeconomic and demographic data, and sales figures from the project's rice miller partner. Postmortem analysis was conducted by the project team with input from external sources. Although the project successfully launched a fortified rice product and a category brand platform, it was unsuccessful in reaching meaningful scale. Market and industry dynamics affected producers' willingness to launch new fortified products. Consumers' strong attachment to rice combined with a weak understanding of micronutrient malnutrition hampered demand creation efforts. This project showed that a purely commercial approach is insufficient for sustainable scale-up of fortified rice to achieve public health goals in a 3- to 5-year period. © The Author(s) 2016.

  11. Institutional adaptation to drought: the case of Fars Agricultural Organization.

    Keshavarz, Marzieh; Karami, Ezatollah


    Recurrent droughts in arid and semi-arid regions are already rendering agricultural production, mainstay of subsistence livelihoods, uncertain. In order to mitigate the impact of drought, agricultural organizations must increase their capacity to adapt. Institutional adaptation refers to the creation of an effective, long-term government institution or set of institutions in charge of planning and policy, and its capacity to develop, revise, and execute drought policies. Using the Fars Agricultural Organization in Iran, as a case study, this paper explores the institutional capacities and capabilities, necessary to adapt to the drought conditions. The STAIR model was used as a conceptual tool, and the Bayesian network and Partial Least Squares (PLS) path modeling was applied to explain the mechanisms by which organizational capacities influence drought management. A survey of 309 randomly selected managers and specialists indicated serious weaknesses in the ability of the organization to apply adaptation strategies effectively. Analysis of the causal models illustrated that organizational culture and resources and infrastructure significantly influenced drought management performance. Moreover, managers and specialists perceived human resources and strategy, goals, and action plan, respectively, as the main drivers of institutional adaptation to drought conditions. Recommendations and implications for drought management policy are offered to increase organizational adaptation to drought and reduce the subsequent sufferings. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Assessing Agricultural Drought in the Anthropocene: A Modified Palmer Drought Severity Index

    Mingzhi Yang


    Full Text Available In the current human-influenced era, drought is initiated by natural and human drivers, and human activities are as integral to drought as meteorological factors. In large irrigated agricultural regions with high levels of human intervention, where the natural farmland soil moisture has usually been changed significantly by high-frequency irrigation, the actual severity of agricultural drought is distorted in traditional drought indices. In this work, an agricultural drought index that considering irrigation processes based on the Palmer drought severity index (IrrPDSI was developed to interpret the real agricultural drought conditions in irrigated regions, with a case study in the Haihe River Basin in northeast China. The water balance model in the original PDSI was revised by an auto-irrigation threshold method combined with a local irrigation schedule. The auto-irrigation setting of the index was used by taking irrigation quotas during specific growth stages of specific crops (wheat–corn into consideration. A series of weekly comparative analyses are as follows: (1 The soil moisture analyses showed that soil moisture values calculated by the modified water balance model were close to the real values; (2 The statistical analyses indicated that most of the stations in the study area based on IrrPDSI had nearly normal distributed values; (3 The time series and spatial analyses showed that the results of the IrrPDSI-reported dry-wet evaluation were more consistent with documented real conditions. All the results revealed that IrrPDSI performed well when used to assess agricultural drought. This work has direct significance for agricultural drought management in large irrigated areas heavily disturbed by human activity.

  13. Development of Forest Drought Index and Forest Water Use Prediction in Gyeonggi Province, Korea Using High-Resolution Weather Research and Forecast Data and Localized JULES Land Surface Model

    Lee, H.; Park, J.; Cho, S.; Lee, S. J.; Kim, H. S.


    Forest determines the amount of water available to low land ecosystems, which use the rest of water after evapotranspiration by forests. Substantial increase of drought, especially for seasonal drought, has occurred in Korea due to climate change, recently. To cope with this increasing crisis, it is necessary to predict the water use of forest. In our study, forest water use in the Gyeonggi Province in Korea was estimated using high-resolution (spatial and temporal) meteorological forecast data and localized Joint UK Land Environment Simulator (JULES) which is one of the widely used land surface models. The modeled estimation was used for developing forest drought index. The localization of the model was conducted by 1) refining the existing two tree plant functional types (coniferous and deciduous trees) into five (Quercus spp., other deciduous tree spp., Pinus spp., Larix spp., and other coniferous spp.), 2) correcting moderate resolution imaging spectroradiometer (MODIS) leaf area index (LAI) through data assimilation with in situ measured LAI, and 3) optimizing the unmeasured plant physiological parameters (e.g. leaf nitrogen contents, nitrogen distribution within canopy, light use efficiency) based on sensitivity analysis of model output values. The high-resolution (hourly and 810 × 810 m) National Center for AgroMeteorology-Land-Atmosphere Modeling Package (NCAM-LAMP) data were employed as meteorological input data in JULES. The plant functional types and soil texture of each grid cell in the same resolution with that of NCAM-LAMP was also used. The performance of the localized model in estimating forest water use was verified by comparison with the multi-year sapflow measurements and Eddy covariance data of Taehwa Mountain site. Our result can be used as referential information to estimate the forest water use change by the climate change. Moreover, the drought index can be used to foresee the drought condition and prepare to it.

  14. Modelling the photochemical pollution over the metropolitan area of Porto Alegre, Brazil

    Borrego, C.; Monteiro, A.; Ferreira, J.; Moraes, M. R.; Carvalho, A.; Ribeiro, I.; Miranda, A. I.; Moreira, D. M.


    The main purpose of this study is to evaluate the photochemical pollution over the Metropolitan Area of Porto Alegre (MAPA), Brazil, where high concentrations of ozone have been registered during the past years. Due to the restricted spatial coverage of the monitoring air quality network, a numerical modelling technique was selected and applied to this assessment exercise. Two different chemistry-transport models - CAMx and CALGRID - were applied for a summer period, driven by the MM5 meteorological model. The meteorological model performance was evaluated comparing its results to available monitoring data measured at the Porto Alegre airport. Validation results point out a good model performance. It was not possible to evaluate the chemistry models performance due to the lack of adequate monitoring data. Nevertheless, the model intercomparison between CAMx and CALGRID shows a similar behaviour in what concerns the simulation of nitrogen dioxide, but some discrepancies concerning ozone. Regarding the fulfilment of the Brazilian air quality targets, the simulated ozone concentrations surpass the legislated value in specific periods, mainly outside the urban area of Porto Alegre. The ozone formation is influenced by the emission of pollutants that act as precursors (like the nitrogen oxides emitted at Porto Alegre urban area and coming from a large refinery complex) and by the meteorological conditions.

  15. Application of Regional Drought and Crop Yield Information System to enhance drought monitoring and forecasting in Lower Mekong region

    Jayasinghe, S.; Dutta, R.; Basnayake, S. B.; Granger, S. L.; Andreadis, K. M.; Das, N.; Markert, K. N.; Cutter, P. G.; Towashiraporn, P.; Anderson, E.


    The Lower Mekong Region has been experiencing frequent and prolonged droughts resulting in severe damage to agricultural production leading to food insecurity and impacts on livelihoods of the farming communities. Climate variability further complicates the situation by making drought harder to forecast. The Regional Drought and Crop Yield Information System (RDCYIS), developed by SERVIR-Mekong, helps decision makers to take effective measures through monitoring, analyzing and forecasting of drought conditions and providing early warnings to farmers to make adjustments to cropping calendars. The RDCYIS is built on regionally calibrated Regional Hydrologic Extreme Assessment System (RHEAS) framework that integrates the Variable Infiltration Capacity (VIC) and Decision Support System for Agro-technology Transfer (DSSAT) models, allowing both nowcast and forecast of drought. The RHEAS allows ingestion of numerus freely available earth observation and ground observation data to generate and customize drought related indices, variables and crop yield information for better decision making. The Lower Mekong region has experienced severe drought in 2016 encompassing the region's worst drought in 90 years. This paper presents the simulation of the 2016 drought event using RDCYIS based on its hindcast and forecast capabilities. The regionally calibrated RDCYIS can help capture salient features of drought through a variety of drought indices, soil variables, energy balance variables and water balance variables. The RDCYIS is capable of assimilating soil moisture data from different satellite products and perform ensemble runs to further reduce the uncertainty of it outputs. The calibrated results have correlation coefficient around 0.73 and NSE between 0.4-0.5. Based on the acceptable results of the retrospective runs, the system has the potential to generate reliable drought monitoring and forecasting information to improve decision-makings at operational, technological and

  16. Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil

    Pao, Hsiao-Tien; Tsai, Chung-Ming


    This paper examines the dynamic relationships between pollutant emissions, energy consumption, and the output for Brazil during 1980-2007. The Grey prediction model (GM) is applied to predict three variables during 2008-2013. In the long-run equilibrium emissions appear to be both energy consumption and output inelastic, but energy is a more important determinant of emissions than output. This may be because Brazilian unsustainable land use and forestry contribute most to the country's greenhouse gas emissions. The findings of the inverted U-shaped relationships of both emissions-income and energy consumption-income imply that both environmental damage and energy consumption firstly increase with income, then stabilize, and eventually decline. The causality results indicate that there is a bidirectional strong causality running between income, energy consumption and emissions. In order to reduce emissions and to avoid a negative effect on the economic growth, Brazil should adopt the dual strategy of increasing investment in energy infrastructure and stepping up energy conservation policies to increase energy efficiency and reduce wastage of energy. The forecasting ability of GM is compared with the autoregressive integrated moving average (ARIMA) model over the out-of-sample period between 2002 and 2007. All of the optimal GMs and ARIMAs have a strong forecasting performance with MAPEs of less than 3%. -- Highlights: → Emissions are energy consumption and output inelastic, but energy is a more important determinant of emissions than output. → The relationship between emissions and income is an inverted U-shaped curve. → The relationship between consumption and income is an inverted U-shaped curve. → The causality results indicate that there is a bidirectional strong causality running between income, energy consumption and emissions. → The Grey prediction model is applied to predict emissions, energy consumption and output during 2008-2013.

  17. A global evaluation of streamflow drought characteristics

    A. K. Fleig


    Full Text Available How drought is characterised depends on the purpose and region of the study and the available data. In case of regional applications or global comparison a standardisation of the methodology to characterise drought is preferable. In this study the threshold level method in combination with three common pooling procedures is applied to daily streamflow series from a wide range of hydrological regimes. Drought deficit characteristics, such as drought duration and deficit volume, are derived, and the methods are evaluated for their applicability for regional studies. Three different pooling procedures are evaluated: the moving-average procedure (MA-procedure, the inter-event time method (IT-method, and the sequent peak algorithm (SPA. The MA-procedure proved to be a flexible approach for the different series, and its parameter, the averaging interval, can easily be optimised for each stream. However, it modifies the discharge series and might introduce dependency between drought events. For the IT-method it is more difficult to find an optimal value for its parameter, the length of the excess period, in particular for flashy streams. The SPA can only be recommended as pooling procedure for the selection of annual maximum series of deficit characteristics and for very low threshold levels to ensure that events occurring shortly after major events are recognized. Furthermore, a frequency analysis of deficit volume and duration is conducted based on partial duration series of drought events. According to extreme value theory, excesses over a certain limit are Generalized Pareto (GP distributed. It was found that this model indeed performed better than or equally to other distribution models. In general, the GP-model could be used for streams of all regime types. However, for intermittent streams, zero-flow periods should be treated as censored data. For catchments with frost during the winter season, summer and winter droughts have to be analysed

  18. Quantifying the contribution of root systems to community and individual drought resilience in the Amazon rainforest

    Agee, E.; Ivanov, V. Y.; Oliveira, R. S.; Brum, M., Jr.; Saleska, S. R.; Bisht, G.; Prohaska, N.; Taylor, T.; Oliveira Junior, R. C.; Restrepo-Coupe, N.


    The increased intensity and severity of droughts within the Amazon Basin region has emphasized the question of vulnerability and resilience of tropical forests to water limitation. During the recent 2015-2016 drought caused by the anomalous El Nino episode, we monitored a large, diverse sample of trees within the Tapajos National Forest, Brazil, in the footprint of the K67 eddy covariance tower. The observed trees exhibited differential responses in terms of stem water potential and sap flow among species: their regulation of ecophysiological strategies varied from very conservative (`isohydric') behavior, to much less restrained, atmosphere-controlled (`anisohydric') type of response. While much attention has been paid to forest canopies, it remains unclear how the regulation of individual tree root system and root spatial interactions contribute to the emergent individual behavior and the ecosystem-scale characterization of drought resilience. Given the inherent difficulty in monitoring below-ground phenomena, physically-based models are valuable for examining different strategies and properties to reduce the uncertainty of characterization. We use a modified version of the highly parallel DOE PFLOTRAN model to simulate the three-dimensional variably saturated flows and root water uptake for over one thousand individuals within a two-hectare area. Root morphology and intrinsic hydraulic properties are assigned based on statistical distributions developed for tropical trees, which account for the broad spectrum of hydraulic strategies in biodiverse environments. The results demonstrate the dynamic nature of active zone of root water uptake based on local soil water potential gradients. The degree of the corresponding shifts in uptake and root collar potential depend not only on assigned hydraulic properties but also on spatial orientation and size relative to community members. This response highlights the importance of not only tree individual hydraulic traits

  19. Is drought helping or killing dengue? Investigation of spatiotemporal relationship between dengue fever and drought

    Lee, Chieh-Han; Yu, Hwa-Lung


    Dengue Fever is a vector-borne disease that is transmitted between human and mosquitos in tropical and sub-tropical regions. Previous studies have found significant relationship between the epidemic of dengue cases and climate variables, especially temperature and precipitation. Besides, the natural phenomena (e.g., drought) are considered that significantly drop the number of dengue cases by killing vector's breeding environment. However, in Kaohsiung City, Taiwan, there are evidences that the temporal pattern of dengue is correlated to drought events. Kaohsiung City experienced two main dengue outbreaks in 2002 and 2014 that both years were confirmed with serious drought. Especially in 2014, Kaohsiung City was suffered from extremely dengue outbreak in 2014 that reported the highest number of dengue cases in the history. This study constructs the spatiotemporal model of dengue incidences and index of drought events (Standardized Precipitation Index, SPI) based on the distributed lag nonlinear model (DLNM). Other meteorological measures are also included in the analysis.

  20. Global patterns of drought recovery

    Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; Fisher, Joshua B.; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D.; Wolf, Adam; Huntzinger, Deborah N.; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin


    Drought is a recurring multi-factor phenomenon with major impacts on natural and human systems1-3. Drought is especially important for land carbon sink variability, influencing climate regulation of the terrestrial biosphere4. While 20th Century trends in drought regime are ambiguous, “more extreme extremes” as well as more frequent and severe droughts3,7 are expected in the 21st Century. Recovery time, the length of time an ecosystem requires to revert to its pre-drought functional state, is a critical metric of drought impact. Yet the spatiotemporal patterning and controls of drought recovery are largely unknown. Here we use three distinct global datasets of gross primary productivity to show that across diverse terrestrial ecosystems drought recovery times are driven by biological productivity and biodiversity, with drought length and severity of secondary importance. Recovery time, especially for extreme droughts, and the areal extent of ecosystems in recovery from drought generally increase over the 20th Century, supporting an increase globally in drought impact8. Our results indicate that if future Anthropocene droughts become more widespread as expected, that droughts will become more frequent relative to recovery time. This increases the risk of entering a new regime where vegetation never recovers to its original state and widespread degradation of the land carbon sink ensues.

  1. Hydrological Drought in the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation in the U.S.: Hydrological Drought in the Anthropocene

    Wan, Wenhua [State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing China; Pacific Northwest National Laboratory, Richland WA USA; Zhao, Jianshi [State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing China; Li, Hong-Yi [Pacific Northwest National Laboratory, Richland WA USA; Now at Department of Land Resources and Environmental Sciences and Institute on Ecosystems, Montana State University, Bozeman MT USA; Mishra, Ashok [Glenn Department of Civil Engineering, Clemson University, Clemson SC USA; Ruby Leung, L. [Pacific Northwest National Laboratory, Richland WA USA; Hejazi, Mohamad [Pacific Northwest National Laboratory, Richland WA USA; Wang, Wei [The Ministry of Education Key Laboratory for Earth System Modeling, and Center for Earth System Science, Tsinghua University, Beijing China; Lu, Hui [The Ministry of Education Key Laboratory for Earth System Modeling, and Center for Earth System Science, Tsinghua University, Beijing China; Deng, Zhiqun [Pacific Northwest National Laboratory, Richland WA USA; Demissisie, Yonas [Department of Civil and Environmental Engineering, Washington State University, Pullman WA USA; Wang, Hao [State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing China; State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Hydropower and Water Resources, Beijing China


    Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the future. Here we utilize a high-resolution integrated modeling framework that represents water management in terms of both local surface water extraction and reservoir regulation, and use the Standardized Streamflow Index (SSI) to quantify hydrological drought. We explore the impacts of water management on hydrological drought over the contiguous US in a warming climate with and without emissions mitigation. Despite the uncertainty of climate change impacts, local surface water extraction consistently intensifies drought that dominates at the regional to national scale. However, reservoir regulation alleviates drought by enhancing summer flow downstream of reservoirs. The relative dominance of drought intensification or relief is largely determined by the water demand, with drought intensification dominating in regions with intense water demand such as the Great Plains and California, while drought relief dominates in regions with low water demand. At the national level, water management increases the spatial extent of extreme drought despite some alleviations of moderate to severe drought. In an emissions mitigation scenario with increased irrigation demand for bioenergy production, water management intensifies drought more than the business-as-usual scenario at the national level, so the impacts of emissions mitigation must be evaluated by considering its benefit in reducing warming and evapotranspiration against its effects on increasing water demand and intensifying drought.

  2. Cost-utility of quadrivalent versus trivalent influenza vaccine in Brazil – comparison of outcomes from different static model types

    Laure-Anne Van Bellinghen


    Conclusion: All three models predicted a cost per quality-adjusted life year gained for quadrivalent versus trivalent influenza vaccine in the range of R$19,257 (FLORENCE to R$22,768 (FLORA with the best available data in Brazil (Appendix A.

  3. Forecasting the new case detection rate of leprosy in four states of Brazil: A comparison of modelling approaches

    D.J. Blok (David); R.E. Crump (Ron E.); Sundaresh, R. (Ram); M. Ndeffo-Mbah (Martial); Galvani, A.P. (Alison P.); T.C. Porco (Travis C.); S.J. de Vlas (Sake); G.F. Medley (Graham F.); J.H. Richardus (Jan Hendrik)


    textabstractBackground Brazil has the second highest annual number of new leprosy cases. The aim of this study is to formally compare predictions of future new case detection rate (NCDR) trends and the annual probability of NCDR falling below 10/100,000 of four different modelling approaches in four

  4. Assessing the performance of two models on calculating maize actual evapotranspiration in a semi-humid and drought-prone region of China

    Wang, J.; Wang, J. L.; Zhao, C. X.; McGiffen, M. E.; Liu, J. B.; Wang, G. D.


    The two-step and one-step models for calculating evapotranspiration of maize were evaluated in a semi-humid and drought-prone region of northern China. Data were collected in the summers of 2013 and 2014 to determine relative model accuracy in calculating maize evaopotranspiration. The two-step model predicted daily evaoptranspiration with crop coefficients proposed by FAO and crop coefficient calibrated by local field data; the one-step model predicted daily evapotranspiration with coefficients derived by other researcher and coefficients calibrated by local field data. The predicted daily evapotranspiration in 2013 and 2014 growing seasons with the above two different models was both compared with the observed evapotranspiration with eddy covariance method. Furthermore, evapotranspiration in different growth stages of 2013 and 2014 maize growing seasons was predicted using the models with the local calibrated coefficients. The results indicated that calibration of models was necessary before using them to predict daily evapotranspiration. The model with the calibrated coefficients performed better with higher coefficient of determination and index of agreement and lower mean absolute error and root mean square error than before. And the two-step model better predicted daily evapotranspiration than the one-step model in our experimental field. Nevertheless, as to prediction ET of different growth stages, there still had some uncertainty when predicting evapotranspiration in different year. So the comparisons suggested that model prediction of crop evapotranspiration was practical, but requires calibration and validation with more data. Thus, considerable improvement is needed for these two models to be practical in predicting evapotranspiration for maize and other crops, more field data need to be measured, and an in-depth study still needs to be continued.

  5. Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil

    Edison Conde Perez dos Santos


    Full Text Available This study involves an assessment of various artificial intelligence-related techniques which aim to produce a more robust system for sediment transport modeling. The intelligent systems developed in this research are directly applicable to academic knowledge and use data from a report on "water circulation assessment in the “Linguado” Channel and Babitonga Bay ,”Santa Catarina”, Brazil, developed by  Military Engineering Institute (IME. The solution employed for sediment transport was built using an intelligent system from the conception of two hybrid models. The first was a Neuro-Fuzzy (ANFIS hybrid model for the study of hydrodynamic behavior, aiming to determine flow rate in the channel. The second was a fuzzy genetic model, able to assess sediment transport in the “Linguado” Channel. The study's conclusion compares the different effects involved in the dredging equilibrium in the “Linguado” Channel according to this hybrid model with the results obtained using a finite element model in the MIKE21® software.

  6. Bivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA

    Jaewon Kwak


    Full Text Available Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return period plot for the Sacramento River basin. Results showed strong correlation among drought characteristics, and the drought with a 20-year return period (17.2 million acre-feet (MAF per year in the Sacramento River basin could be considered a critical level of drought for water shortages.

  7. Assessing the impacts of droughts and heat waves at thermoelectric power plants in the United States using integrated regression, thermodynamic, and climate models

    Margaret A. Cook


    Full Text Available Recent droughts and heat waves have revealed the vulnerability of some power plants to effects from higher temperature intake water for cooling. In this evaluation, we develop a methodology for predicting whether power plants are at risk of violating thermal pollution limits. We begin by developing a regression model of average monthly intake temperatures for open loop and recirculating cooling pond systems. We then integrate that information into a thermodynamic model of energy flows within each power plant to determine the change in cooling water temperature that occurs at each plant and the relationship of that water temperature to other plants in the river system. We use these models together with climate change models to estimate the monthly effluent temperature at twenty-six power plants in the Upper Mississippi River Basin and Texas between 2015 and 2035 to predict which ones are at risk of reaching thermal pollution limits. The intake model shows that two plants could face elevated intake temperatures between 2015 and 2035 compared to the 2010–2013 baseline. In general, a rise in ambient cooling water temperature of 1 °C could cause a drop in power output of 0.15%–0.5%. The energy balance shows that twelve plants might exceed state summer effluent limits.

  8. Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

    Aghakouchak, Amir; Tourian, Mohammad J.


    Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014

  9. A simple model to estimate radiation doses to aircrew during air flights in Brazil and abroad

    Lavalle Heilbron Filho, Paulo Fernando; Pérez Guerrero, Jesus Salvador; Lavalle Heilbron, Rafael Cabidolusso; Amaral, Mario Luth Gonçalves Henriques do


    The objective of this article is to present the results obtained from the development of a simple model used to estimate cosmic radiation doses from crew members taking into consideration the variation of the dose rates with the altitude and the latitude, airplane cruise velocity and other important parameters such as, cruise height, takeoff time, landing time, takeoff angle, landing angle. The model was incorporated into a Brazilian computer program developed using the “mathematica” symbolic software. The data used to calculate the dose rates with altitude and latitude by the authors takes into consideration the mean solar activity from January 1958 to December 2008 (51 years). Twenty two data including international and national American flights were used to test the program and the results between them compared, showing good agreement. The program also gives excellent results for the doses expected for the crew members of three Brazilian national flights (between capitals cities in Brazil) when compared with the doses values measured for these flights using a radiation detector. According to the results the doses expected for the Brazilian crews of domestic flights can, in some cases, depending on the number of annual flights, overcome the limit of 1 mSv/year established by the Brazilian competent authority in Brazil (Brazilian Nuclear Energy Commission- CNEN) for public annual exposure. In the case of the simulated international flights the results shows a good agreement with the results found in literature especially when considered the different database series used by the authors and by the other references for the solar activity. (authors)

  10. Proposing a Compartmental Model for Leprosy and Parameterizing Using Regional Incidence in Brazil.

    Smith, Rebecca Lee


    Hansen's disease (HD), or leprosy, is still considered a public health risk in much of Brazil. Understanding the dynamics of the infection at a regional level can aid in identification of targets to improve control. A compartmental continuous-time model for leprosy dynamics was designed based on understanding of the biology of the infection. The transmission coefficients for the model and the rate of detection were fit for each region using Approximate Bayesian Computation applied to paucibacillary and multibacillary incidence data over the period of 2000 to 2010, and model fit was validated on incidence data from 2011 to 2012. Regional variation was noted in detection rate, with cases in the Midwest estimated to be infectious for 10 years prior to detection compared to 5 years for most other regions. Posterior predictions for the model estimated that elimination of leprosy as a public health risk would require, on average, 44-45 years in the three regions with the highest prevalence. The model is easily adaptable to other settings, and can be studied to determine the efficacy of improved case finding on leprosy control.

  11. Modeling monthly meteorological and agronomic frost days, based on minimum air temperature, in Center-Southern Brazil

    Alvares, Clayton Alcarde; Sentelhas, Paulo César; Stape, José Luiz


    Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F MET) and agronomic (F AGR) frost day models, based on minimum shelter air temperature (T MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T MN, once the frost day models were based on this variable. All T MN regression models were statistically significant (p Brazilian region are the first zoning of these variables for the country.

  12. Biophysical modelling of intra-ring variations in tracheid features and wood density of Pinus pinaster trees exposed to seasonal droughts.

    Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa


    Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email:

  13. Defining Drought Characteristics for Natural Resource Management

    Ojima, D. S.; Senay, G. B.; McNeeley, S.; Morisette, J. T.


    In the north central region of the US, on-going drought studies are investigating factors determining how drought impacts various ecosystem services and challenge natural resource management decisions. The effort reported here stems from research sponsored by the USGS North Central Climate Science Center, to deal with ecosystem response to drought with the goal to see if there are indicators of drought emerging from the ecosystem interactions with various weather patterns, soil moisture dynamics, and the structural aspects of the ecosystem in question. The North Central domain covers a region from the headwaters of the Missouri River Basin to the northern Great Plains. Using spatial and temporal analysis of remote sensing products and mechanistic daily time-step ecosystem model simulations across the northern Great Plains and northern Rockies, analysis of recent drought conditions over the region will be provided. Drought characteristics will be analyzed related to resource management targets, such as water supply, landscape productivity, or habitat needs for key species. Analysis of ecosystem and landscape patterns of drought relative to net primary productivity, surface temperatures, soil moisture content, evaporation, transpiration, and water use efficiency from 2000 through 2014 will be analyzed for different drought and non-drought events. Comparisons between satellite-derived ET and NPP of different Great Plains ecosystems related to simulated ET and NPP will be presented. These comparisons provide indications of the role that soil moisture dynamics, groundwater recharge and rooting depth of different ecosystems have on determining the sensitivity to water stress due to seasonal warming and reduced precipitation across the region. In addition, indications that average annual rainfall levels over certain ecosystems may result in reduced production due to higher rates of water demand under the observed warmer temperatures and the prolonged warming in the spring

  14. Possible Future Climate Change Impacts on the Hydrological Drought Events in the Weihe River Basin, China

    Fei Yuan


    Full Text Available Quantitative evaluation of future climate change impacts on hydrological drought characteristics is one of important measures for implementing sustainable water resources management and effective disaster mitigation in drought-prone regions under the changing environment. In this study, a modeling system for projecting the potential future climate change impacts on hydrological droughts in the Weihe River basin (WRB in North China is presented. This system consists of a large-scale hydrological model driven by climate outputs from three climate models (CMs for future streamflow projections, a probabilistic model for univariate drought assessment, and a copula-based bivariate model for joint drought frequency analysis under historical and future climates. With the observed historical climate data as the inputs, the Variable Infiltration Capacity hydrological model projects an overall runoff reduction in the WRB under the Intergovernmental Panel on Climate Change A1B scenario. The univariate drought assessment found that although fewer hydrological drought events would occur under A1B scenario, drought duration and severity tend to increase remarkably. Moreover, the bivariate drought assessment reveals that future droughts in the same return period as the baseline droughts would become more serious. With these trends in the future, the hydrological drought situation in the WRB would be further deteriorated.

  15. Assimilation exceeds respiration sensitivity to drought : A FLUXNET synthesis

    Schwalm, Christopher R.; Williams, Christopher A.; Schaefer, Kevin; Arneth, Almut; Bonal, Damien; Buchmann, Nina; Chen, Jiquan; Law, Beverlye; Lindroth, Anders; Luyssaert, Sebastiaan; Reichstein, Markus; Richardson, Andrew D.

    The intensification of the hydrological cycle, with an observed and modeled increase in drought incidence and severity, underscores the need to quantify drought effects on carbon cycling and the terrestrial sink. FLUXNET, a global network of eddy covariance towers, provides dense data streams of

  16. Density-dependent vulnerability of forest ecosystems to drought

    Alessandra Bottero; Anthony W. D' Amato; Brian J. Palik; John B. Bradford; Shawn Fraver; Mike A. Battaglia; Lance A. Asherin; Harald Bugmann


    Climate models predict increasing drought intensity and frequency for many regions, which may have negative consequences for tree recruitment, growth and mortality, as well as forest ecosystem services. Furthermore, practical strategies for minimizing vulnerability to drought are limited. Tree population density, a metric of tree abundance in a given area, is a primary...

  17. Seasonal UK Drought Forecasting using Statistical Methods

    Richardson, Doug; Fowler, Hayley; Kilsby, Chris; Serinaldi, Francesco


    In the UK drought is a recurrent feature of climate with potentially large impacts on public water supply. Water companies' ability to mitigate the impacts of drought by managing diminishing availability depends on forward planning and it would be extremely valuable to improve forecasts of drought on monthly to seasonal time scales. By focusing on statistical forecasting methods, this research aims to provide techniques that are simpler, faster and computationally cheaper than physically based models. In general, statistical forecasting is done by relating the variable of interest (some hydro-meteorological variable such as rainfall or streamflow, or a drought index) to one or more predictors via some formal dependence. These predictors are generally antecedent values of the response variable or external factors such as teleconnections. A candidate model is Generalised Additive Models for Location, Scale and Shape parameters (GAMLSS). GAMLSS is a very flexible class allowing for more general distribution functions (e.g. highly skewed and/or kurtotic distributions) and the modelling of not just the location parameter but also the scale and shape parameters. Additionally GAMLSS permits the forecasting of an entire distribution, allowing the output to be assessed in probabilistic terms rather than simply the mean and confidence intervals. Exploratory analysis of the relationship between long-memory processes (e.g. large-scale atmospheric circulation patterns, sea surface temperatures and soil moisture content) and drought should result in the identification of suitable predictors to be included in the forecasting model, and further our understanding of the drivers of UK drought.

  18. Anthropogenic warming exacerbates European soil moisture droughts

    Samaniego, L.; Thober, S.; Kumar, R.; Wanders, N.; Rakovec, O.; Pan, M.; Zink, M.; Sheffield, J.; Wood, E. F.; Marx, A.


    Anthropogenic warming is anticipated to increase soil moisture drought in the future. However, projections are accompanied by large uncertainty due to varying estimates of future warming. Here, using an ensemble of hydrological and land-surface models, forced with bias-corrected downscaled general circulation model output, we estimate the impacts of 1-3 K global mean temperature increases on soil moisture droughts in Europe. Compared to the 1.5 K Paris target, an increase of 3 K—which represents current projected temperature change—is found to increase drought area by 40% (±24%), affecting up to 42% (±22%) more of the population. Furthermore, an event similar to the 2003 drought is shown to become twice as frequent; thus, due to their increased occurrence, events of this magnitude will no longer be classified as extreme. In the absence of effective mitigation, Europe will therefore face unprecedented increases in soil moisture drought, presenting new challenges for adaptation across the continent.

  19. Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

    Moura, Antonio Divino; Hastenrath, Stefan


    Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

  20. Coping With Droughts

    Zaporozec, Alexander

    This book is a collection of selected papers from the NATO Advanced Study Institute on Droughts entitled “Drought Impact Control Technology,” held at the National Laboratory of Civil Engineering in Lisbon, Portugal, in June 1980. The editors of the book have chosen a nontraditional but successful approach to presenting the papers. Instead of including a verbatim proceedings of the institute, they assembled 21 papers presented by 14 of the institute's lecturers, reshaped and synthesized them, and supplemented them by five new papers that cover obvious gaps in topics. The result is enlightening reading and a more or less complete presentation of the subject. The edited material in the book was arranged around three central themes related to efforts needed to cope with or manage the droughts. In the process, the identity of individual contributors has been preserved.

  1. Drought in the Emerald City

    Babcock, S.D.


    This paper discusses a drought preparedness study being conducted for the Cedar River and Green River basins in western Washington state. The study is one of four regional case studies being managed by the U.S. Army Corps of Engineers as part of the National Study of Water Management During Drought. The overriding objective of the drought preparedness study is to leave the region better prepared for drought, through demonstration and test of drought preparedness tools and strategies. The study has served as a vehicle to promote a greater regional focus on drought related water supply problem solving. The 1992 drought in the Seattle/Tacoma metropolitan area provided a unique opportunity for the study team to demonstrate approaches to drought management being researched and tested as part of the study

  2. Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil

    Werneck Guilherme L.


    Full Text Available Most ecologic studies use geographical areas as units of observation. Because data from areas close to one another tend to be more alike than those from distant areas, estimation of effect size and confidence intervals should consider spatial autocorrelation of measurements. In this report we demonstrate a method for modeling spatial autocorrelation within a mixed model framework, using data on environmental and socioeconomic determinants of the incidence of visceral leishmaniasis (VL in the city of Teresina, Piauí, Brazil. A model with a spherical covariance structure indicated significant spatial autocorrelation in the data and yielded a better fit than one assuming independent observations. While both models showed a positive association between VL incidence and residence in a favela (slum or in areas with green vegetation, values for the fixed effects and standard errors differed substantially between the models. Exploration of the data's spatial correlation structure through the semivariogram should precede the use of these models. Our findings support the hypothesis of spatial dependence of VL rates and indicate that it might be useful to model spatial correlation in order to obtain more accurate point and standard error estimates.

  3. A System Dynamics Model for Long-Term Planning of the Undergraduate Education in Brazil

    Strauss, Luísa Mariele; Borenstein, Denis


    Higher education in Brazil has experienced a rapid expansion since the 1990s as a consequence of the government's pliability in launching new programs and educational institutions. This expansion was mainly driven by the private sector. Despite this expansion, Brazil has not yet achieved the enrollment goal expected in the National Education Plan…

  4. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    F. Fundel


    Full Text Available Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month.

    The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive

  5. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    Fundel, F.; Jörg-Hess, S.; Zappa, M.


    Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month. The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive action based on the forecast.

  6. Report: the current situation of sanitary landfills in Brazil and the importance of the application of economic models

    Oliveira Neto, Raúl; Otávio Petter, Carlos; Cortina Pallás, José Luís


    We present the development stage of the sanitary landfills in Brazil in the context of urban solid residue management, demonstrating the necessity and importance of the employment of economic models. In the article, a cost estimate model is proposed as the basis for studies to be applied by sector management, including the city council, companies, consultants and engineers, contributing to the choice of new areas, public bids, municipal consortia and private public partnerships. Peer Re...

  7. Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

    Lowe, Rachel; Bailey, Trevor C.; Stephenson, David B.; Graham, Richard J.; Coelho, Caio A. S.; Sá Carvalho, Marilia; Barcellos, Christovam


    This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.

  8. Evaluation of alternative future energy scenarios for Brazil using an energy mix model

    Coelho, Maysa Joppert

    The purpose of this study is to model and assess the performance and the emissions impacts of electric energy technologies in Brazil, based on selected economic scenarios, for a time frame of 40 years, taking the year of 1995 as a base year. A Base scenario has been developed, for each of three economic development projections, based upon a sectoral analysis. Data regarding the characteristics of over 300 end-use technologies and 400 energy conversion technologies have been collected. The stand-alone MARKAL technology-based energy-mix model, first developed at Brookhaven National Laboratory, was applied to a base case study and five alternative case studies, for each economic scenario. The alternative case studies are: (1) minimum increase in the thermoelectric contribution to the power production system of 20 percent after 2010; (2) extreme values for crude oil price; (3) minimum increase in the renewable technologies contribution to the power production system of 20 percent after 2010; (4) uncertainty on the cost of future renewable conversion technologies; and (5) model is forced to use the natural gas plants committed to be built in the country. Results such as the distribution of fuel used for power generation, electricity demand across economy sectors, total CO2 emissions from burning fossil fuels for power generation, shadow price (marginal cost) of technologies, and others, are evaluated and compared to the Base scenarios previous established. Among some key findings regarding the Brazilian energy system it may be inferred that: (1) diesel technologies are estimated to be the most cost-effective thermal technology in the country; (2) wind technology is estimated to be the most cost-effective technology to be used when a minimum share of renewables is imposed to the system; and (3) hydroelectric technologies present the highest cost/benefit relation among all conversion technologies considered. These results are subject to the limitations of key input

  9. Assessing vulnerability to drought: identifying underlying factors across Europe

    Urquijo, Julia; Gonzalez Tánago, Itziar; Ballesteros, Mario; De Stefano, Lucia


    Drought is considered one of the most severe and damaging natural hazards in terms of people and sectors affected and associated losses. Drought is a normal and recurrent climatic phenomenon that occurs worldwide, although its spatial and temporal characteristics vary significantly among climates. In the case of Europe, in the last thirty years, the region has suffered several drought events that have caused estimated economic damages over a €100 billion and have affected almost 20% of its territory and population. In recent years, there has been a growing awareness among experts and authorities of the need to shift from a reactive crisis approach to a drought risk management approach, as well as of the importance of designing and implementing policies, strategies and plans at country and river basin levels to deal with drought. The identification of whom and what is vulnerable to drought is a central aspect of drought risk mitigation and planning and several authors agree that societal vulnerability often determines drought risk more than the actual precipitation shortfalls. The final aim of a drought vulnerability assessment is to identify the underlying sources of drought impact, in order to develop policy options that help to enhance coping capacity and therefore to prevent drought impact. This study identifies and maps factors underlying vulnerability to drought across Europe. The identification of factors influencing vulnerability starts from the analysis of past drought impacts in four European socioeconomic sectors. This analysis, along with an extensive literature review, led to the selection of vulnerability factors that are both relevant and adequate for the European context. Adopting the IPCC model, vulnerability factors were grouped to describe exposure, sensitivity and adaptive capacity. The aggregation of these components has resulted in the mapping of vulnerability to drought across Europe at NUTS02 level. Final results have been compared with

  10. Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

    Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.


    By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

  11. Modeling distribution of Phoneutria bahiensis (Araneae: Ctenidae: an endemic and threatened spider from Brazil

    Marcelo A Dias


    Full Text Available Phoneutria bahiensis Simó & Brescovit, 2001 is a large ctenid spider inhabiting the states of Bahia and Espírito Santo, Brazil. Considering that it is probably endemic, this species was included in the Brazilian red book of threatened species. Here, we predict the distribution range of P. bahiensis using 19 bioclimatic variables in the model design. The most septentrional record for this spider was indicated for northern Bahia. The model predicts that the distribution range covers the Atlantic Forest from the state of Paraíba to Rio de Janeiro, with the best suitable area in the Atlantic Forest of the state of Bahia. The bioclimatic variable with the best contribution to the model was precipitation in the driest quarter. Based on collected data, the species inhabits Ombrophilous Forests and Restinga vegetation, two ecosystems of the Atlantic Forest biome. In the best-predicted area of distribution, eleven Conservation Units were included. This information could be considered for future conservation plans of this species.

  12. Introduction 'Governance for Drought Resilience'

    Bressers, Nanny; Bressers, Johannes T.A.; Larrue, Corinne; Bressers, Hans; Bressers, Nanny; Larrue, Corinne


    This book is about governance for drought resilience. But that simple sentence alone might rouse several questions. Because what do we mean with drought, and how does that relate to water scarcity? And what do we mean with resilience, and why is resilience needed for tackling drought? And how does

  13. Assessment of Meteorological Drought Hazard Area using GIS in ...

    Michael Horsfall

    The purpose of this study was to make a model of the meteorological drought hazard area using GIS. ... overlaying different hazard indicator maps in the GIS, deploying the new model. The final ..... Northeast Thailand Project Bangkok. Min. of.

  14. Drought impacts and resilience on crops via evapotranspiration estimations

    Timmermans, Joris; Asadollahi Dolatabad, Saeid


    Currently, the global needs for food and water is at a critical level. It has been estimated that 12.5 % of the global population suffers from malnutrition and 768 million people still do not have access to clean drinking water. This need is increasing because of population growth but also by climate change. Changes in precipitation patterns will result either in flooding or droughts. Consequently availability, usability and affordability of water is becoming challenge and efficient use of water and water management is becoming more important, particularly during severe drought events. Drought monitoring for agricultural purposes is very hard. While meteorological drought can accurately be monitored using precipitation only, estimating agricultural drought is more difficult. This is because agricultural drought is dependent on the meteorological drought, the impacts on the vegetation, and the resilience of the crops. As such not only precipitation estimates are required but also evapotranspiration at plant/plot scale. Evapotranspiration (ET) describes the amount of water evaporated from soil and vegetation. As 65% of precipitation is lost by ET, drought severity is highly linked with this variable. In drought research, the precise quantification of ET and its spatio-temporal variability is therefore essential. In this view, remote sensing based models to estimate ET, such as SEBAL and SEBS, are of high value. However the resolution of current evapotranspiration products are not good enough for monitoring the impact of the droughts on the specific crops. This limitation originates because plot scales are in general smaller than the resolution of the available satellite ET products. As such remote sensing estimates of evapotranspiration are always a combination of different land surface types and cannot be used for plant health and drought resilience studies. The goal of this research is therefore to enable adequate resolutions of daily evapotranspiration estimates

  15. Floods and droughts: friends or foes?

    Prudhomme, Christel


    Water hazards are some of the biggest threats to lives and livelihoods globally, causing serious damages to society and infrastructure. But floods and droughts are an essential part of the hydrological regime that ensures fundamental ecosystem functions, providing natural ways to bring in nutrients, flush out pollutants and enabling soils, rivers and lakes natural biodiversity to thrive. Traditionally, floods and droughts are too often considered separately, with scientific advance in process understanding, modelling, statistical characterisation and impact assessment are often done independently, possibly delaying the development of innovative methods that could be applied to both. This talk will review some of the key characteristics of floods and droughts, highlighting differences and commonalties, losses and benefits, with the aim of identifying future key research challenges faced by both current and next generation of hydrologists.

  16. Anthropogenic climate change affects meteorological drought risk in Europe

    Gudmundsson, L; Seneviratne, S I


    Drought constitutes a significant natural hazard in Europe, impacting societies and ecosystems across the continent. Climate model simulations with increasing greenhouse gas concentrations project increased drought risk in southern Europe, and on the other hand decreased drought risk in the north. Observed changes in water balance components and drought indicators resemble the projected pattern. However, assessments of possible causes of the reported regional changes have so far been inconclusive. Here we investigate whether anthropogenic emissions have altered past and present meteorological (precipitation) drought risk. For doing so we first estimate the magnitude of 20 year return period drought years that would occur without anthropogenic effects on the climate. Subsequently we quantify to which degree the occurrence probability, i.e. the risk, of these years has changed if anthropogenic climate change is accounted for. Both an observational and a climate model-based assessment suggest that it is >95% likely that human emissions have increased the probability of drought years in the Mediterranean, whereas it is >95% likely that the probability of dry years has decreased in northern Europe. In central Europe the evidence is inconclusive. The results highlight that anthropogenic climate change has already increased drought risk in southern Europe, stressing the need to develop efficient mitigation measures. (letter)

  17. Future Projections of Fire Occurrence in Brazil Using EC-Earth Climate Model

    Patrícia Silva

    Full Text Available Abstract Fire has a fundamental role in the Earth system as it influences global and local ecosystem patterns and processes, such as vegetation distribution and structure, the carbon cycle and climate. Since, in the global context, Brazil is one of the regions with higher fire activity, an assessment is here performed of the sensitivity of the wildfire regime in Brazilian savanna and shrubland areas to changes in regional climate during the 21st Century, for an intermediate scenario (RCP4.5 of climate change. The assessment is based on a spatial and temporal analysis of a meteorological fire danger index specifically developed for Brazilian biomes, which was evaluated based on regional climate simulations of temperature, relative humidity and precipitation using the Rossby Centre Regional Climate Model (RCA4 forced by the EC-Earth earth system model. Results show a systematic increase in the extreme levels of fire danger throughout the 21st Century that mainly results from the increase in maximum daily temperature, which rises by about 2 °C between 2005 and 2100. This study provides new insights about projected fire activity in Brazilian woody savannas associated to climate change and is expected to benefit the user community, from governmental policies to land management and climate researches.

  18. Description of the East Brazil Large Marine Ecosystem using a trophic model

    Kátia M.F. Freire


    Full Text Available The objective of this study was to describe the marine ecosystem off northeastern Brazil. A trophic model was constructed for the 1970s using Ecopath with Ecosim. The impact of most of the forty-one functional groups was modest, probably due to the highly reticulated diet matrix. However, seagrass and macroalgae exerted a strong positive impact on manatee and herbivorous reef fishes, respectively. A high negative impact of omnivorous reef fishes on spiny lobsters and of sharks on swordfish was observed. Spiny lobsters and swordfish had the largest biomass changes for the simulation period (1978-2000; tunas, other large pelagics and sharks showed intermediate rates of biomass decline; and a slight increase in biomass was observed for toothed cetaceans, large carnivorous reef fishes, and dolphinfish. Recycling was an important feature of this ecosystem with low phytoplankton-originated primary production. The mean transfer efficiency between trophic levels was 11.4%. The gross efficiency of the fisheries was very low (0.00002, probably due to the low exploitation rate of most of the resources in the 1970s. Basic local information was missing for many groups. When information gaps are filled, this model may serve more credibly for the exploration of fishing policies for this area within an ecosystem approach.

  19. 2.5D Modeling of TEM Data Applied to Hidrogeological Studies in PARANÁ Basin, Brazil

    Bortolozo, C. A.; Porsani, J. L.; Santos, F. M.


    The transient electromagnetic method (TEM) is used all over the world and has shown great potential in hydrological, hazardous waste site characterization, mineral exploration, general geological mapping, and geophysical reconnaissance. However, the behavior of TEM fields are very complex and is not yet fully understood. Forward modeling is one of the most common and effective methods to understand the physical behavior and significance of the electromagnetics responses of a TEM sounding. Until now, there are a limited number of solutions for the 2D forward problem for TEM. More rare are the descriptions of a three-component response of a 3D source over 2D earth, which is the so-called 2.5D. The 2.5D approach is more realistic than the conventional 2D source previous used, once normally the source cannot be realistic represented for a 2D approximation (normally source are square loops). At present the 2.5D model represents the only way of interpreting TEM data in terms of a complex earth, due to the prohibitive amount of computer time and storage required for a full 3D model. In this work we developed a TEM modeling program for understanding the different responses and how the magnetic and electric fields, produced by loop sources at air-earth interface, behave in different geoelectrical distributions. The models used in the examples are proposed focusing hydrogeological studies, once the main objective of this work is for detecting different kinds of aquifers in Paraná sedimentary basin, in São Paulo State - Brazil. The program was developed in MATLAB, a widespread language very common in the scientific community.

  20. Path analysis of phenotypic traits in young cacao plants under drought conditions.

    Santos, Emerson Alves Dos; Almeida, Alex-Alan Furtado de; Branco, Marcia Christina da Silva; Santos, Ivanildes Conceição Dos; Ahnert, Dario; Baligar, Virupax C; Valle, Raúl René


    Drought is worldwide considered one of the most limiting factors of Theobroma cacao production, which can be intensified by global climate changes. In this study, we aimed to investigate the phenotypic correlation among morphological characteristics of cacao progenies submitted to irrigation and drought conditions and their partitions into direct and indirect effects. Path analysis with phenotypic plasticity index was used as criteria for estimation of basic and explanatory variables. The experiment was conducted in a greenhouse at the Cacao Research Center (CEPEC), Ilhéus, Bahia, Brazil, in a randomized block 21 x 2 factorial arrangement [21 cacao progenies obtained from complete diallel crosses and two water regimes (control and drought)] and six replications. In general, drought conditions influenced biomass production in most progenies, causing significant reductions in total leaf area, leaf number, leaf biomass, fine-roots length (diameter cacao progenies drought tolerant.

  1. Drought and the risk of hospital admissions and mortality in older adults in western USA from 2000 to 2013: a retrospective study.

    Berman, Jesse D; Ebisu, Keita; Peng, Roger D; Dominici, Francesca; Bell, Michelle L


    Occurrence, severity and geographic extent of droughts are anticipated to increase under climate change, but the health consequences of drought conditions are unknown. We estimate risks of cardiovascular and respiratory-related hospitalization and mortality associated with drought conditions for the western U.S. elderly population. For counties in the western U.S. (N=618) and for the period 2000 to 2013, we use data from the U.S. Drought Monitor to identify: 1) full drought periods; 2) non-drought periods; and 3) worsening drought periods stratified by low- and high-severity. We use Medicare claims to calculate daily rates of cardiovascular admissions, respiratory admissions, and deaths among adults 65 years or older. Using a two-stage hierarchical model, we estimated the percentage change in health risks when comparing drought to non-drought period days controlling for daily weather and seasonal trends. On average there were 2·1 million days and 0·6 million days classified as non-drought periods and drought periods, respectively. Compared to non-drought periods, respiratory admissions significantly decreased by -1·99% (95% posterior interval (PI): -3·56, -0·38) during the full drought period, but not during worsening drought conditions. Mortality risk significantly increased by 1·55% (95% PI: 0·17, 2·95) during the high-severity worsening drought period, but not the full drought period. Cardiovascular admissions did not differ significantly during either drought or worsening drought periods. In counties where drought occurred less frequently, we found risks for cardiovascular disease and mortality to increase during worsening drought conditions. Drought conditions increased risk of mortality during high-severity worsening drought, but decreased the risk of respiratory admissions during full drought periods among older adults. Counties that experience fewer drought events show larger risk for mortality and cardiovascular disease. This research describes an

  2. Development of a Strategic Framework for Drought Management

    Kang, Jaewon; Kim, Sooyoung; Suh, Aesook; Cho, Younghyun


    A drought starts with lack of precipitation; as the deficit of precipitation is prolonged, the loss of water influences on the amount of soil water because of evapotranspiration. In addition, the decreased runoff of surface and underground water also reduces discharge in rivers and storage in reservoirs; these reductions then lead to the decline in the supply capability of water resources supply facilities. Therefore, individuals may experience a given drought differently depending on their circumstances. In an area with a metropolitan water supply network that draws water from a multipurpose dam, residents might not realize that a meteorological drought is present since they are provided with sufficient water. Similar situation might occur in farmlands for which an irrigation system supplies water from an agricultural reservoir. In Korea, several institutions adopt each drought indices in their roles. Since March 2016, the Ministry of Public Safety and Security, via inter-ministerial cooperation, has been classifying and announcing drought situations in each administrative district of Korea into three types, meteorological, agricultural, or hydrological droughts, with three levels such as 'caution,' 'serious,' or 'very serious.' Deriving the drought index considering storage facilities and other factors and expressing them in three categories are valid as methods. However, the current method that represent the drought situation in an administrative district as a whole should be improved to recognize the drought situation more realistically and to make appropriate strategic responses. This study designs and implements a pilot model of a framework that re-establishes zones for drought situation representation, taking water usage and water supply infrastructure into account based on land use maps. In addition, each resulting district is provided with statistical indices that can assist in the application of appropriate drought indices and the understanding of

  3. Identification of Hydrological Drought in Eastern China Using a Time-Dependent Drought Index

    Lei Zou


    Full Text Available Long records (1960–2013 of monthly streamflow observations from 8 hydrological stations in the East Asian monsoon region are modeled using a nonstationarity framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS. Modeling analyses are used to characterize nonstationarity of monthly streamflow series in different geographic regions and to select optimal distribution among five two-parameter distributions (Gamma, Lognormal, Gumbel, Weibull and Logistic. Based on the optimal nonstationarity distribution, a time-dependent Standardized Streamflow Index (denoted SSIvar that takes account of the possible nonstationarity in streamflow series is constructed and then employed to identify drought characteristics at different time scales (at a 3-month scale and a 12-month scale in the eight selected catchments during 1960–2013 for comparison. Results of GAMLSS models indicate that they are able to represent the magnitude and spread in the monthly streamflow series with distribution parameters that are a linear function of time. For 8 hydrological stations in different geographic regions, a noticeable difference is observed between the historical drought assessment of Standardized Streamflow Index (SSI and SSIvar, indicating that the nonstationarity could not be ignored in the hydrological drought analyses, especially for stations with change point and significant change trends. The constructed SSIvar is, to some extent, found to be more reliable and suitable for regional drought monitoring than traditional SSI in a changing environment, thereby providing a feasible alternative for drought forecasting and water resource management at different time scales.

  4. Modeling and Crustal Structure in the Future Reservoir of Jequitaí, Brazil

    Teixeira, C. D.; Von Huelsen, M. G.; Chemale, F., Jr.; Nascimento, A. V. D. S., Sr.; do Sacramento, V., Sr.; Garcia, V. B. P., Sr.


    Integrated geophysical and geological data analysis in the state of Minas Gerais, Brazil, allowed the modeling of the subsurface framework in a region where a reservoir - the Jequitaí reservoir - will be constructed. Studies of this nature during the previous stages of the construction of large hydroelectric projects are highly important, because the regional geology understanding associated with geophysical data interpretation can help to prevent damage in the physical structure of the dam, which will aid in its preservation. The use of gravity and magnetic data in a 2D crustal model provided information on a possible framework of the area and revealed features not mapped until now, which may be useful for further studies and can contribute to the understanding of this portion of the crust. The results show the presence of high gravity anomalies in the southern part of the study area, besides extensive lineaments that cross the whole area, interpreted as possible faults and dykes. Depth estimation techniques, such as Euler deconvolution and radially averaged power spectrum, allowed the identification of continuous structures up to 400 m depth, and showed differences in the basement depth in the northern and southern portions of the study area. Inversion of the gravity data along a profile crossing a gravity anomaly yielded to information about the depth, thickness and shape of a possible intrusive body. The geological-geophysical model was consistent with the interpretations based on surface geology and in the gravity and magnetic signal, because the section could be modeled respecting the geophysical data and the pre-existing structural proposals.

  5. ABACC - Brazil-Argentina Agency for Accounting and Control of Nuclear Materials, a model of integration and transparence

    Oliveira, Antonio A.; Do Canto, Odilon Marcusso


    Argentina and Brazil began its activities in the nuclear area about the same time, in the 50 century past. The existence of an international nuclear nonproliferation treaty-TNP-seen by Brazil and Argentina as discriminatory and prejudicial to the interests of the countries without nuclear weapons, led to the need for a common system of control of nuclear material between the two countries to somehow provide assurances to the international community of the exclusively peaceful purpose of its nuclear programs. The creation of a common system, assured the establishment of uniform procedures to implement safeguards in Argentina and Brazil, so the same requirements and safeguards procedures took effect in both countries, and the operators of nuclear facilities began to follow the same rules of control of nuclear materials and subjected to the same type of verification and control. On July 18, 1991, the Bilateral Agreement for the Exclusively Peaceful Use of Nuclear Energy created a binational body, the Argentina-Brazil Agency for Accounting and Control of Nuclear Materials-ABACC-to implement the so-called Common System of Accounting and Control of Nuclear materials - SCCC. The deal provided, permanently, a clear commitment to use exclusively for peaceful purposes all material and nuclear facilities under the jurisdiction or control of the two countries. The Quadripartite Agreement, signed in December of that year, between the two countries, ABACC and IAEA completed the legal framework for the implementation of comprehensive safeguards system. The 'model ABACC' now represents a paradigmatic framework in the long process of economic, political, technological and cultural integration of the two countries. Argentina and Brazil were able to establish a guarantee system that is unique in the world today and that consolidated and matured over more than twenty years, has earned the respect of the international community

  6. Short-term estimation of GNSS TEC using a neural network model in Brazil

    Ferreira, Arthur Amaral; Borges, Renato Alves; Paparini, Claudia; Ciraolo, Luigi; Radicella, Sandro M.


    This work presents a novel Neural Network (NN) model to estimate Total Electron Content (TEC) from Global Navigation Satellite Systems (GNSS) measurements in three distinct sectors in Brazil. The purpose of this work is to start the investigations on the development of a regional model that can be used to determine the vertical TEC over Brazil, aiming future applications on a near real-time frame estimations and short-term forecasting. The NN is used to estimate the GNSS TEC values at void locations, where no dual-frequency GNSS receiver that may be used as a source of data to GNSS TEC estimation is available. This approach is particularly useful for GNSS single-frequency users that rely on corrections of ionospheric range errors by TEC models. GNSS data from the first GLONASS network for research and development (GLONASS R&D network) installed in Latin America, and from the Brazilian Network for Continuous Monitoring of the GNSS (RMBC) were used on TEC calibration. The input parameters of the NN model are based on features known to influence TEC values, such as geographic location of the GNSS receiver, magnetic activity, seasonal and diurnal variations, and solar activity. Data from two ten-days periods (from DoY 154 to 163 and from 282 to 291) are used to train the network. Three distinct analyses have been carried out in order to assess time-varying and spatial performance of the model. At the spatial performance analysis, for each region, a set of stations is chosen to provide training data to the NN, and after the training procedure, the NN is used to estimate vTEC behavior for the test station which data were not presented to the NN in training process. An analysis is done by comparing, for each testing station, the estimated NN vTEC delivered by the NN and reference calibrated vTEC. Also, as a second analysis, the network ability to forecast one day after the time interval (DoY 292) based on information of the second period of investigation is also assessed

  7. A new framework for evaluating the impacts of drought on net primary productivity of grassland.

    Lei, Tianjie; Wu, Jianjun; Li, Xiaohan; Geng, Guangpo; Shao, Changliang; Zhou, Hongkui; Wang, Qianfeng; Liu, Leizhen


    This paper presented a valuable framework for evaluating the impacts of droughts (single factor) on grassland ecosystems. This framework was defined as the quantitative magnitude of drought impact that unacceptable short-term and long-term effects on ecosystems may experience relative to the reference standard. Long-term effects on ecosystems may occur relative to the reference standard. Net primary productivity (NPP) was selected as the response indicator of drought to assess the quantitative impact of drought on Inner Mongolia grassland based on the Standardized Precipitation Index (SPI) and BIOME-BGC model. The framework consists of six main steps: 1) clearly defining drought scenarios, such as moderate, severe and extreme drought; 2) selecting an appropriate indicator of drought impact; 3) selecting an appropriate ecosystem model and verifying its capabilities, calibrating the bias and assessing the uncertainty; 4) assigning a level of unacceptable impact of drought on the indicator; 5) determining the response of the indicator to drought and normal weather state under global-change; and 6) investigating the unacceptable impact of drought at different spatial scales. We found NPP losses assessed using the new framework were more sensitive to drought and had higher precision than the long-term average method. Moreover, the total and average losses of NPP are different in different grassland types during the drought years from 1961-2009. NPP loss was significantly increased along a gradient of increasing drought levels. Meanwhile, NPP loss variation under the same drought level was different in different grassland types. The operational framework was particularly suited for integrative assessing the effects of different drought events and long-term droughts at multiple spatial scales, which provided essential insights for sciences and societies that must develop coping strategies for ecosystems for such events. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Modeling HIV/AIDS Drug Price Determinants in Brazil: Is Generic Competition a Myth?

    Meiners, Constance; Sagaon-Teyssier, Luis; Hasenclever, Lia; Moatti, Jean-Paul


    BACKGROUND: Brazil became the first developing country to guarantee free and universal access to HIV/AIDS treatment, with antiretroviral drugs (ARVs) being delivered to nearly 190,000 patients. The analysis of ARV price evolution and market dynamics in Brazil can help anticipate issues soon to afflict other developing countries, as the 2010 revision of the World Health Organization guidelines shifts demand towards more expensive treatments, and, at the same time, current evolution of internat...

  9. Temperature impacts on the water year 2014 drought in California

    Shukla, Shraddhanand; Safeeq, Mohammad; AghaKouchak, Amir; Guan, Kaiyu; Funk, Christopher C.


    California is experiencing one of the worst droughts on record. Here we use a hydrological model and risk assessment framework to understand the influence of temperature on the water year (WY) 2014 drought in California and examine the probability that this drought would have been less severe if temperatures resembled the historical climatology. Our results indicate that temperature played an important role in exacerbating the WY 2014 drought severity. We found that if WY 2014 temperatures resembled the 1916–2012 climatology, there would have been at least an 86% chance that winter snow water equivalent and spring-summer soil moisture and runoff deficits would have been less severe than the observed conditions. We also report that the temperature forecast skill in California for the important seasons of winter and spring is negligible, beyond a lead-time of one month, which we postulate might hinder skillful drought prediction in California.

  10. Climate and Hydrological Data Analysis for hydrological and solute transport modelling purposes in the Muriaé River basin, Atlantic Forest Biome, SE Brazil

    Santos, Juliana; Künne, Annika; Kralisch, Sven; Fink, Manfred; Brenning, Alexander


    The Muriaé River basin in SE Brazil has been experiencing an increasing pressure on water resources, due to the population growth of the Rio de Janeiro urban area connected with the growth of the industrial and agricultural sector. This leads to water scarcity, riverine forest degradation, soil erosion and water quality problems among other impacts. Additionally the region has been suffering with seasonal precipitation variations leading to extreme events such as droughts, floods and landslides. Climate projections for the near future indicate a high inter-annual variability of rainfall with an increase in the frequency and intensity of heavy rainfall events combined with a statistically significant increase in the duration of dry periods and a reduced duration of wet periods. This may lead to increased soil erosion during the wet season, while the longer dry periods may reduce the vegetation cover, leaving the soil even more exposed and vulnerable to soil erosion. In consequence, it is crucial to understand how climate affects the interaction between the timing of extreme rainfall events, hydrological processes, vegetation growth, soil cover and soil erosion. In this context, physically-based hydrological modelling can contribute to a better understanding of spatial-temporal process dynamics in the Earth's system and support Integrated Water Resourses Management (IWRM) and adaptation strategies. The study area is the Muriaé river basin which has an area of approx. 8000 km² in Minas Gerais and Rio de Janeiro States. The basin is representative of a region of domain of hillslopes areas with the predominancy of pasture for livestock production. This study will present some of the relevant analyses which have been carried out on data (climate and streamflow) prior to using them for hydrological modelling, including consistency checks, homogeneity, pattern and statistical analyses, or annual and seasonal trends detection. Several inconsistencies on the raw data were

  11. Analysis of Freight Trip Generation Model for Food and Beverage in Belo Horizonte (Brazil

    Leise Kelli de Oliveira


    Full Text Available Today, one of the main challenges faced in urban logistics is the distribution of goods. In Brazil, mid to large cities have experienced consequences of unplanned urban sprawl and lack of adequate transportation infrastructure. The relationship between urban planning and transport stands out the attractiveness of some urban activities with direct impacts on the movement of people and goods and other component elements of urban space. The segment of bars and restaurants falls within this context, therefore is a vital activity responsible for significant percentage of jobs and revenue in a city. Altogether, foods & beverages commercial activities move daily large volumes of goods to meet the need of customers. This paper presents the results of a freight trip generation model developed for pubs and restaurants in Belo Horizonte (Brazil. Once performed the model determined the number of trips generated per day per establishment. In order to expand the discrete result to a continuous one, the results were geographically interpolated to a continuous surface and extrapolated within the city limits. The data for the freight trip generation model were obtained by survey. For this, we designed a structured questionnaire to obtain information about goods, frequency, operational time, place of performance of the loading/unloading of goods, establishment size and the number of employees. Besides these information, we investigated the acceptance of alternative practices in the delivery of goods, such as off-peak delivery. To accomplish the proposed models, we applied a simple linear regression, correlating the following variables: (i Number of trips versus area of the establishment; (ii Number of trips versus number of employees; (iii Number of trips versus operation day of the establishment. With the results of the linear regression for travel generations, conducted the data interpolation based on the standard deviation of the results to define the sample

  12. Simulating US Agriculture in a Modern Dust Bowl Drought

    Glotter, Michael; Elliott, Joshua


    Drought-induced agricultural loss is one of the most costly impacts of extreme weather, and without mitigation, climate change is likely to increase the severity and frequency of future droughts. The Dust Bowl of the 1930s was the driest and hottest for agriculture in modern US history. Improvements in farming practices have increased productivity, but yields today are still tightly linked to climate variation and the impacts of a 1930s-type drought on current and future agricultural systems remain unclear. Simulations of biophysical process and empirical models suggest that Dust-Bowl-type droughts today would have unprecedented consequences, with yield losses approx.50% larger than the severe drought of 2012. Damages at these extremes are highly sensitive to temperature, worsening by approx.25% with each degree centigrade of warming. We find that high temperatures can be more damaging than rainfall deficit, and, without adaptation, warmer mid-century temperatures with even average precipitation could lead to maize losses equivalent to the Dust Bowl drought. Warmer temperatures alongside consecutive droughts could make up to 85% of rain-fed maize at risk of changes that may persist for decades. Understanding the interactions of weather extremes and a changing agricultural system is therefore critical to effectively respond to, and minimize, the impacts of the next extreme drought event.

  13. Temporal Changes in Community Resilience to Drought Hazard

    Mihunov, V.


    The threat of droughts and their associated impacts on the landscape and human communities have long been recognized. While considerable research on the climatological aspect of droughts has been conducted, studies on the resilience of human communities to the effects of drought remain limited. Understanding how different communities respond to and recover from the drought hazard, i.e. their community resilience, should inform the development of better strategies to cope with the hazard. This research assesses community resilience to drought hazard in South-Central U.S. and captures the temporal changes of community resilience in the region facing the climate change. First, the study applies the Resilience Inference Measurement (RIM) framework using the existing drought incidence, crop damage, socio-economic and food-water-energy nexus variables, which allows to assign county-level resilience scores in the study region and derive variables contributing to the resilience. Second, it captures the temporal changes in community resilience by using the model extracted from the RIM study and socio-economic data from several consecutive time periods. The resilience measurement study should help understand the complex process underlying communities' response to the drought impacts. The results identify gaps in resilience planning and help the improvement of the community resilience to the droughts of increasing frequency and intensity.

  14. Geographic Distribution of Chagas Disease Vectors in Brazil Based on Ecological Niche Modeling

    Rodrigo Gurgel-Gonçalves


    Full Text Available Although Brazil was declared free from Chagas disease transmission by the domestic vector Triatoma infestans, human acute cases are still being registered based on transmission by native triatomine species. For a better understanding of transmission risk, the geographic distribution of Brazilian triatomines was analyzed. Sixteen out of 62 Brazilian species that both occur in >20 municipalities and present synanthropic tendencies were modeled based on their ecological niches. Panstrongylus geniculatus and P. megistus showed broad ecological ranges, but most of the species sort out by the biome in which they are distributed: Rhodnius pictipes and R. robustus in the Amazon; R. neglectus, Triatoma sordida, and T. costalimai in the Cerrado; R. nasutus, P. lutzi, T. brasiliensis, T. pseudomaculata, T. melanocephala, and T. petrocchiae in the Caatinga; T. rubrovaria in the southern pampas; T. tibiamaculata and T. vitticeps in the Atlantic Forest. Although most occurrences were recorded in open areas (Cerrado and Caatinga, our results show that all environmental conditions in the country are favorable to one or more of the species analyzed, such that almost nowhere is Chagas transmission risk negligible.

  15. Analysis of longitudinal data of beef cattle raised on pasture from northern Brazil using nonlinear models.

    Lopes, Fernando B; da Silva, Marcelo C; Marques, Ednira G; McManus, Concepta M


    This study was undertaken to aim of estimating the genetic parameters and trends for asymptotic weight (A) and maturity rate (k) of Nellore cattle from northern Brazil. The data set was made available by the Brazilian Association of Zebu Breeders and collected between the years of 1997 and 2007. The Von Bertalanffy, Brody, Gompertz, and logistic nonlinear models were fitted by the Gauss-Newton method to weight-age data of 45,895 animals collected quarterly of the birth to 750 days old. The curve parameters were analyzed using the procedures GLM and CORR. The estimation of (co)variance components and genetic parameters was obtained using the MTDFREML software. The estimated heritability coefficients were 0.21 ± 0.013 and 0.25 ± 0.014 for asymptotic weight and maturity rate, respectively. This indicates that selection for any trait shall results in genetic progress in the herd. The genetic correlation between A and k was negative (-0.57 ± 0.03) and indicated that animals selected for high maturity rate shall result in low asymptotic weight. The Von Bertalanffy function is adequate to establish the mean growth patterns and to predict the adult weight of Nellore cattle. This model is more accurate in predicting the birth weight of these animals and has better overall fit. The prediction of adult weight using nonlinear functions can be accurate when growth curve parameters and their (co)variance components are estimated jointly. The model used in this study can be applied to the prediction of mature weight in herds where a portion of the animals are culled before they reach the adult age.

  16. Drought variability in six catchments in the UK

    Kwok-Pan, Chun; Onof, Christian; Wheater, Howard


    Drought is fundamentally related to consistent low precipitation levels. Changes in global and regional drought patterns are suggested by numerous recent climate change studies. However, most of the climate change adaptation measures are at a catchment scale, and the development of a framework for studying persistence in precipitation is still at an early stage. Two stochastic approaches for modelling drought severity index (DSI) are proposed to investigate possible changes in droughts in six catchments in the UK. They are the autoregressive integrated moving average (ARIMA) and the generalised linear model (GLM) approach. Results of ARIMA modelling show that mean sea level pressure and possibly the North Atlantic Oscillation (NAO) index are important climate variables for short term drought forecasts, whereas relative humidity is not a significant climate variable despite its high correlation with the DSI series. By simulating rainfall series, the generalised linear model (GLM) approach can provide the probability density function of the DSI. GLM simulations indicate that the changes in the 10th and 50th quantiles of drought events are more noticeable than in the 90th extreme droughts. The possibility of extending the GLM approach to support risk-based water management is also discussed.

  17. The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations.

    Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; Xie, Yangyang; Liu, Saiyan; Meng, Erhao; Li, Pei


    Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating the potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. This study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.

  18. Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

    Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.


    Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system ( that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate

  19. Effects of elevated CO2 and drought on wheat : testing crop simulation models for different experimental and climatic conditions

    Ewert, F.; Rodriguez, D.; Jamieson, P.; Semenov, M.A.; Mitchell, R.A.C.; Goudriaan, J.; Porter, J.R.; Kimball, B.A.; Pinter, P.J.; Manderscheid, R.; Weigel, H.J.; Fangmeier, A.; Fereres, E.; Villalobos, F.


    Effects of increasing carbon dioxide concentration [CO2] on wheat vary depending on water supply and climatic conditions, which are difficult to estimate. Crop simulation models are often used to predict the impact of global atmospheric changes on food production. However, models have rarely been

  20. Estimation of Phosphorus Emissions in the Upper Iguazu Basin (brazil) Using GIS and the More Model

    Acosta Porras, E. A.; Kishi, R. T.; Fuchs, S.; Hilgert, S.


    Pollution emissions into the drainage basin have direct impact on surface water quality. These emissions result from human activities that turn into pollution loads when they reach the water bodies, as point or diffuse sources. Their pollution potential depends on the characteristics and quantity of the transported materials. The estimation of pollution loads can assist decision-making in basin management. Knowledge about the potential pollution sources allows for a prioritization of pollution control policies to achieve the desired water quality. Consequently, it helps avoiding problems such as eutrophication of water bodies. The focus of the research described in this study is related to phosphorus emissions into river basins. The study area is the upper Iguazu basin that lies in the northeast region of the State of Paraná, Brazil, covering about 2,965 km2 and around 4 million inhabitants live concentrated on just 16% of its area. The MoRE (Modeling of Regionalized Emissions) model was used to estimate phosphorus emissions. MoRE is a model that uses empirical approaches to model processes in analytical units, capable of using spatially distributed parameters, covering both, emissions from point sources as well as non-point sources. In order to model the processes, the basin was divided into 152 analytical units with an average size of 20 km2. Available data was organized in a GIS environment. Using e.g. layers of precipitation, the Digital Terrain Model from a 1:10000 scale map as well as soils and land cover, which were derived from remote sensing imagery. Further data is used, such as point pollution discharges and statistical socio-economic data. The model shows that one of the main pollution sources in the upper Iguazu basin is the domestic sewage that enters the river as point source (effluents of treatment stations) and/or as diffuse pollution, caused by failures of sanitary sewer systems or clandestine sewer discharges, accounting for about 56% of the


    E. A. Acosta Porras


    Full Text Available Pollution emissions into the drainage basin have direct impact on surface water quality. These emissions result from human activities that turn into pollution loads when they reach the water bodies, as point or diffuse sources. Their pollution potential depends on the characteristics and quantity of the transported materials. The estimation of pollution loads can assist decision-making in basin management. Knowledge about the potential pollution sources allows for a prioritization of pollution control policies to achieve the desired water quality. Consequently, it helps avoiding problems such as eutrophication of water bodies. The focus of the research described in this study is related to phosphorus emissions into river basins. The study area is the upper Iguazu basin that lies in the northeast region of the State of Paraná, Brazil, covering about 2,965 km2 and around 4 million inhabitants live concentrated on just 16% of its area. The MoRE (Modeling of Regionalized Emissions model was used to estimate phosphorus emissions. MoRE is a model that uses empirical approaches to model processes in analytical units, capable of using spatially distributed parameters, covering both, emissions from point sources as well as non-point sources. In order to model the processes, the basin was divided into 152 analytical units with an average size of 20 km2. Available data was organized in a GIS environment. Using e.g. layers of precipitation, the Digital Terrain Model from a 1:10000 scale map as well as soils and land cover, which were derived from remote sensing imagery. Further data is used, such as point pollution discharges and statistical socio-economic data. The model shows that one of the main pollution sources in the upper Iguazu basin is the domestic sewage that enters the river as point source (effluents of treatment stations and/or as diffuse pollution, caused by failures of sanitary sewer systems or clandestine sewer discharges, accounting for

  2. Effects of prolonged drought on the vegetation cover of sand dunes in the NW Negev Desert: Field survey, remote sensing and conceptual modeling

    Siegal, Z.; Tsoar, H.; Karnieli, A.


    Luminescence dating of stable sand dunes in the large deserts of the world has shown several episodes of mobility during the last 30 k years. The logical explanation for the mobility of fixed dunes is severe drought. Though drought length can be estimated, the level of precipitation drop is unknown. The stabilized sand dunes of the northwestern Negev Desert, Israel have been under an unprecedented prolonged drought since 1995. This has resulted in a vast decrease of shrubs cover on the fixed sand dunes, which changes along the rainfall gradient. In the north, an average of 27% of the shrubs had wilted by 2009, and in the drier southern area, 68% of the shrubs had withered. This loss of shrubbery is not expected to induce dune remobilization because the existing bio-crust cover is not negatively affected by the drought. Eleven aerial photographs taken over the drier southern area from 1956 to 2005 show the change in shrub cover due to human impact and the recent severe drought.

  3. The cyclicality of loan loss provisions under three different accounting models: the United Kingdom, Spain, and Brazil

    Antônio Maria Henri Beyle de Araújo


    Full Text Available ABSTRACT A controversy involving loan loss provisions in banks concerns their relationship with the business cycle. While international accounting standards for recognizing provisions (incurred loss model would presumably be pro-cyclical, accentuating the effects of the current economic cycle, an alternative model, the expected loss model, has countercyclical characteristics, acting as a buffer against economic imbalances caused by expansionary or contractionary phases in the economy. In Brazil, a mixed accounting model exists, whose behavior is not known to be pro-cyclical or countercyclical. The aim of this research is to analyze the behavior of these accounting models in relation to the business cycle, using an econometric model consisting of financial and macroeconomic variables. The study allowed us to identify the impact of credit risk behavior, earnings management, capital management, Gross Domestic Product (GDP behavior, and the behavior of the unemployment rate on provisions in countries that use different accounting models. Data from commercial banks in the United Kingdom (incurred loss, in Spain (expected loss, and in Brazil (mixed model were used, covering the period from 2001 to 2012. Despite the accounting models of the three countries being formed by very different rules regarding possible effects on the business cycles, the results revealed a pro-cyclical behavior of provisions in each country, indicating that when GDP grows, provisions tend to fall and vice versa. The results also revealed other factors influencing the behavior of loan loss provisions, such as earning management.

  4. GEOWOW: a drought scenario for multidisciplinary data access and use

    Santoro, Mattia; Sorichetta, Alessandro; Roglia, Elena; Craglia, Massimo; Nativi, Stefano


    Recent enhancements of the GEOSS Common Infrastructure (GCI;, and in particular the introduction of a middleware in the GCI that brokers across heterogeneous information systems, have increased significantly the number of information resources discoverable worldwide. Now the challenge moves to the next level of ensuring access and use of the resources discovered, which have many different and domain-specific data models, communication protocols, encoding formats, etc. The GEOWOW Project - GEOSS interoperability for Weather, Ocean and Water, - developed a set of multidisciplinary use scenarios to advance the present GCI. This work describes the "Easy discovery and use of GEOSS resources for addressing multidisciplinary challenges related to drought scenarios" showcase demonstrated at the last GEO Plenary in Foz de Iguazu (Brazil). The scientific objectives of this showcase include: prevention and mitigation of water scarcity and drought situations, assessment of the population and geographical area potentially affected, evaluation of the possible distribution of mortality and economic loss risk, and support in building greater capacity to cope with drought. The need to address these challenges calls for producing scientifically robust and consistent information about the extent of land affected by drought and degradation. Similarly, in this context it is important: (i) to address uncertainties about the way in which various biological, physical, social, and economic factors interact each other and influence the occurrence of drought events, and (ii) to develop and test adequate indices and/or combination of them for monitoring and forecasting drought in different geographic locations and at various spatial scales (Brown et al., 2002). The scientific objectives above can be met with an increased interoperability across the multidisciplinary domains relevant to this drought scenario. In particular

  5. Urban slum structure: integrating socioeconomic and land cover data to model slum evolution in Salvador, Brazil.

    Hacker, Kathryn P; Seto, Karen C; Costa, Federico; Corburn, Jason; Reis, Mitermayer G; Ko, Albert I; Diuk-Wasser, Maria A


    The expansion of urban slums is a key challenge for public and social policy in the 21st century. The heterogeneous and dynamic nature of slum communities limits the use of rigid slum definitions. A systematic and flexible approach to characterize, delineate and model urban slum structure at an operational resolution is essential to plan, deploy, and monitor interventions at the local and national level. We modeled the multi-dimensional structure of urban slums in the city of Salvador, a city of 3 million inhabitants in Brazil, by integrating census-derived socioeconomic variables and remotely-sensed land cover variables. We assessed the correlation between the two sets of variables using canonical correlation analysis, identified land cover proxies for the socioeconomic variables, and produced an integrated map of deprivation in Salvador at 30 m × 30 m resolution. The canonical analysis identified three significant ordination axes that described the structure of Salvador census tracts according to land cover and socioeconomic features. The first canonical axis captured a gradient from crowded, low-income communities with corrugated roof housing to higher-income communities. The second canonical axis discriminated among socioeconomic variables characterizing the most marginalized census tracts, those without access to sanitation or piped water. The third canonical axis accounted for the least amount of variation, but discriminated between high-income areas with white-painted or tiled roofs from lower-income areas. Our approach captures the socioeconomic and land cover heterogeneity within and between slum settlements and identifies the most marginalized communities in a large, complex urban setting. These findings indicate that changes in the canonical scores for slum areas can be used to track their evolution and to monitor the impact of development programs such as slum upgrading.

  6. Spatial modeling of limnological parameters in a solar saltwork of northeastern Brazil

    Diógenes Félix da Silva Costa


    Full Text Available AimIn this research, we aimed to model limnological parameters in the Salina Unidos (Macau-Brazil using GIS technology. We hypothesized that in solar saltworks, the geochemical characteristics of the brines (i.e. the strong solution of salts vary considerably through the salt ponds circuit, in which drastic changes can damage the entire salt production.MethodsGeochemical parameters were monitored in seven sampling points distributed along the salt ponds circuit, during a complete cycle of salt production, i.e., from January to December 2007. The open source software Spring 5.1.6 was used to build, store, analyze and model the spatial distribution of the parameters.ResultsWe identified a spatial gradient of the salinity and temperature, with values increasing from evaporation ponds to concentration ponds, showing a relationship with the salt production. The parameters, depth, dissolved oxygen concentrations and total dissolved reactive phosphorus showed a decrease from the evaporation ponds towards the concentration ponds. Among the dissolved inorganic nitrogen forms analyzed (NH3-, NO2- and NO3-, nitrate was the predominant, namely in the concentration ponds, where it reached the highest concentrations. The concentration of chlorophyll awas higher in the initial and intermediate evaporation ponds, showing a distinct dynamics of in relation to other environmental variables.ConclusionsThe increased concentration of the analyzed limnological parameters, from the evaporation ponds towards the concentration ponds, evidenced a heterogeneous distribution varying significantly with season. The geochemical spatialization of brine, as illustrated by GIS approach, is very important for the conservation of these environments because this spatial heterogeneity can provide a high diversity of habitat types. This spatial analysis proved to be a practical tool for an adequate management of solar saltworks considering the environmental (ecosystem and the socio

  7. Regional applicability of seven meteorological drought indices in China

    YANG Qing; LI MingXing; ZHENG ZiYan; MA ZhuGuo


    The definition of a drought index is the foundation of drought research.However,because of the complexity of drought,there is no a unified drought index appropriate for different drought types and objects at the same time.Therefore,it is crucial to determine the regional applicability of various drought indices.Using terrestrial water storage obtained from the Gravity Recovery And Climate Experiment,and the observed soil moisture and streamflow in China,we evaluated the regional applicability of seven meteorological drought indices:the Palmer Drought Severity Index(PDSI),modified PDSI(PDSI_CN) based on observations in China,self-calibrating PDSI(scPDSI),Surface Wetness Index(SWI),Standardized Precipitation Index(SPI),Standardized Precipitation Evapotranspiration Index(SPEI),and soil moisture simulations conducted using the community land model driven by observed atmospheric forcing(CLM3.5/ObsFC).The results showed that the scPDSI is most appropriate for China.However,it should be noted that the scPDSI reduces the value range slightly compared with the PDSI and PDSI_CN;thus,the classification of dry and wet conditions should be adjusted accordingly.Some problems might exist when using the PDSI and PDSI_CN in humid and arid areas because of the unsuitability of empiricalparameters.The SPI and SPEI are more appropriate for humid areas than arid and semiarid areas.This is because contributions of temperature variation to drought are neglected in the SPI,but overestimated in the SPEI,when potential evapotranspiration is estimated by the Thornthwaite method in these areas.Consequently,the SPI and SPEI tend to induce wetter and drier results,respectively.The CLM3.5/ObsFC is suitable for China before 2000,but not for arid and semiarid areas after 2000.Consistent with other drought indices,the SWI shows similar interannual and decadal change characteristics in detecting annual dry/wet variations.Although the long-term trends of drought areas in China detected by these seven

  8. Quantitative Trait Loci Associated with Drought Tolerance in Brachypodium distachyon

    Yiwei Jiang


    Full Text Available The temperate wild grass Brachypodium distachyon (Brachypodium serves as model system for studying turf and forage grasses. Brachypodium collections show diverse responses to drought stress, but little is known about the genetic mechanisms of drought tolerance of this species. The objective of this study was to identify quantitative trait loci (QTLs associated with drought tolerance traits in Brachypodium. We assessed leaf fresh weight (LFW, leaf dry weight (LDW, leaf water content (LWC, leaf wilting (WT, and chlorophyll fluorescence (Fv/Fm under well-watered and drought conditions on a recombinant inbred line (RIL population from two parents (Bd3-1 and Bd1-1 known to differ in their drought adaptation. A linkage map of the RIL population was constructed using 467 single nucleotide polymorphism (SNP markers obtained from genotyping-by-sequencing. The Bd3-1/Bd1-1 map spanned 1,618 cM and had an average distance of 3.5 cM between adjacent single nucleotide polymorphisms (SNPs. Twenty-six QTLs were identified in chromosome 1, 2, and 3 in two experiments, with 14 of the QTLs under well-watered conditions and 12 QTLs under drought stress. In Experiment 1, a QTL located on chromosome 2 with a peak at 182 cM appeared to simultaneously control WT, LWC, and Fv/Fm under drought stress, accounting for 11–18.7% of the phenotypic variation. Allelic diversity of candidate genes DREB2B, MYB, and SPK, which reside in one multi-QTL region, may play a role in the natural variation in whole plant drought tolerance in Brachypodium. Co-localization of QTLs for multiple drought-related traits suggest that the gene(s involved are important regulators of drought tolerance in Brachypodium.

  9. Impact of drought on wildfires in Iberia

    Russo, Ana; Gouveia, Célia M.; DaCamara, Carlos; Sousa, Pedro; Trigo, Ricardo M.


    months in August. In the Eastern and Northwestern regions the correlation was most significant for the SPI for 3 and 6 months. Thus, the relation between wildfires and drought is better explained in the Northern and Southwestern regions by the temperature influence and on the Northwestern and Eastern by the precipitation influence. Gouveia C.M., Bastos A., Trigo R.M., DaCamara C.C. (2012) "Drought impacts on vegetation in the pre and post-fire events over Iberian Peninsula". Natural Hazards and Earth System Sciences, 12, 3123-3137, 2012. Vicente-Serrano S.M., Santiago Beguería, Juan I. López-Moreno (2010) "A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index - SPEI". Journal of Climate 23: 1696-1718. Trigo R.M., Sousa P., Pereira M., Rasilla D., Gouveia C.M. (2013) "Modelling wildfire activity in Iberia with different Atmospheric Circulation Weather Types". International Journal of Climatology, DOI: 10.1002/joc.3749 Sousa PM, Trigo RM, Pereira MG, Bedia J, Gutiérrez JM, 2014. Different approaches to model future burnt area in the Iberian Peninsula. Agricultural and Forest Meteorology 202, 11-25. doi:10.1016/j.agrformet.2014.11.018 Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAGGLO/4155/2012).

  10. Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results

    Tadesse, Tsegaye; Champagne, Catherine; Wardlow, Brian D.; Hadwen, Trevor A.; Brown, Jesslyn; Demisse, Getachew B.; Bayissa, Yared A.; Davidson, Andrew M.


    Drought is a natural climatic phenomenon that occurs throughout the world and impacts many sectors of society. To help decision-makers reduce the impacts of drought, it is important to improve monitoring tools that provide relevant and timely information in support of drought mitigation decisions. Given that drought is a complex natural hazard that manifests in different forms, monitoring can be improved by integrating various types of information (e.g., remote sensing and climate) that is timely and region specific to identify where and when droughts are occurring. The Vegetation Drought Response Index for Canada (VegDRI-Canada) is a recently developed drought monitoring tool for Canada. VegDRI-Canada extends the initial VegDRI concept developed for the conterminous United States to a broader transnational coverage across North America. VegDRI-Canada models are similar to those developed for the United States, integrating satellite observations of vegetation status, climate data, and biophysical information on land use and land cover, soil characteristics, and other environmental factors. Collectively, these different types of data are integrated into the hybrid VegDRI-Canada to isolate the effects of drought on vegetation. Twenty-three weekly VegDRI-Canada models were built for the growing season (April–September) through the weekly analysis of these data using a regression tree-based data mining approach. A 15-year time series of VegDRI-Canada results (s to 2014) was produced using these models and the output was validated by randomly selecting 20% of the historical data, as well as holdout year (15% unseen data) across the growing season that the Pearson’s correlation ranged from 0.6 to 0.77. A case study was also conducted to evaluate the VegDRI-Canada results over the prairie region of Canada for two drought years and one non-drought year for three weekly periods of the growing season (i.e., early-, mid-, and late season). The comparison of the Veg

  11. Groundwater drought in different geological conditions

    Machlica, A; Stojkovova, M


    The identification of hydrological extremes (drought) is very actual at present. The knowledge of the mechanism of hydrological extremes evolution could be useful at many levels of human society, such as scientific, agricultural, local governmental, political and others. The research was performed in the Upper part of the Nitra River catchment (central part of Slovakia) and in the Topla and Ondava River catchments (eastern part of Slovakia). Lumped hydrological model BILAN was used to identify relationships among compounds of the water balance. Presented results are focused on drought in groundwater storage, soil moisture, base flow and discharges. BFI model for baseflow estimation was used and results were compared with those gained by BILAN model. Another item of the research was to compare results of hydrological balance model application on catchments with different geological conditions.

  12. Evaluation of drought impact on groundwater recharge rate using SWAT and Hydrus models on an agricultural island in western Japan

    G. Jin


    Full Text Available Clarifying the variations of groundwater recharge response to a changing non-stationary hydrological process is important for efficiently managing groundwater resources, particularly in regions with limited precipitation that face the risk of water shortage. However, the rate of aquifer recharge is difficult to evaluate in terms of large annual-variations and frequency of flood events. In our research, we attempt to simulate related groundwater recharge processes under variable climate conditions using the SWAT Model, and validate the groundwater recharge using the Hydrus Model. The results show that annual average groundwater recharge comprised approximately 33% of total precipitation, however, larger variation was found for groundwater recharge and surface runoff compared to evapotranspiration, which fluctuated with annual precipitation variations. The annual variation of groundwater resources is shown to be related to precipitation. In spatial variations, the upstream is the main surface water discharge area; the middle and downstream areas are the main groundwater recharge areas. Validation by the Hydrus Model shows that the estimated and simulated groundwater levels are consistent in our research area. The groundwater level shows a quick response to the groundwater recharge rate. The rainfall intensity had a great impact on the changes of the groundwater level. Consequently, it was estimated that large spatial and temporal variation of the groundwater recharge rate would be affected by precipitation uncertainty in future.

  13. A unique model system of microbial carbonate precipitation: Stromatolites of Lagoa Vermelha, Brazil

    Warthmann, R. J.; Vasoncelos, C.; van Lith, Y.; Visscher, P. T.; McKenzie, J. A.


    Modern stromatolites are recognized as analogues to fossil laminated structures, which are remains of microbial activity that are widely found in sedimentary rocks beginning in the Neo-Archean, but are quite rare today. The key difference of modern microbial mats and stromatolites compared to ancient examples is the type of lithification. A few marine and hypersaline microbial mats have been observed to precipitate carbonates, and only in Shark Bay (Western, Australia) and Highborne Cay (Bahamas) has the formation of continuous laminae of carbonates been observed. Lagoa Vermelha, a moderate hypersaline lagoon in Rio de Janeiro, Brazil, offers the ideal conditions to promote lithification. Calcified, sometimes dolomitic stromatolites grow on the sediment surface, whereas within the sediments dolomite precipitates. The factors controlling carbonate precipitation in Lagoa Vermelha are the changing water chemistry and the special hydrology, combined with a high primary production by cyanobacteria, a high rate of respiration and the absence of higher organisms. Here, we present a study of the physico-chemical parameters, microbial processes and bio-minerals associated with these stromatolites and microbial mats. This approach provides boundary conditions to better understand dolomite formation. Several discrete lithified calcium carbonate layers are present. The first lithified layer is found beneath a 2-mm-thick biofilm, which contains Gloeocapsa. Below the underlying dense Microcoleus layer, the second micrite deposit is observed at 4-5 mm depth. Successive micritic laminae are preserved in the layer of decaying cyanobacteria that harbors large numbers of purple sulfur bacteria, heterotrophic microbes and sulfate-reducing bacteria. C-isotope studies of the carbonate layers indicate a contribution of organic derived carbon associated with microbial processes, such as sulfate reduction. The O-isotopic values indicate an evaporitic enrichment of the water. Understanding

  14. New geological model of the Lagoa Real uraniferous albitites from Bahia (Brazil)

    de Oliveira Chaves, Alexandre


    New evidence supported by petrography (including mineral chemistry), lithogeochemistry, U-Pb geochronology by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS), and physicochemical study of fluid and melt inclusions by LA-ICP-MS and microthermometry, point to an orogenic setting of Lagoa Real (Bahia-Brazil) involving uraniferous mineralization. Unlike the previous models in which uraniferous albitites represent Na-metasomatised 1.75 Ga anorogenic granitic rocks, it is understood here that they correspond to metamorphosed sodium-rich and quartz-free 1.9 Ga late-orogenic syenitic rocks (Na-metasyenites). These syenitic rocks are rich not only in albite, but also in U-rich titanite (source of uranium). The interpretation of geochemical data points to a petrogenetic connection between alkali-diorite (local amphibolite protolith) and sodic syenite by fractional crystallization through a transalkaline series. This magmatic differentiation occurred either before or during shear processes, which in turn led to albitite and amphibolite formation. The metamorphic reactions, which include intense recrystallization of magmatic minerals, led uraninite to precipitate at 1.87 Ga under Oxidation/Reduction control. A second population of uraninites was also generated by the reactivation of shear zones during the 0.6 Ga Brasiliano Orogeny. The geotectonic implications include the importance of the Orosirian event in the Paramirim Block during paleoproterozoic Săo Francisco Craton edification and the influence of the Brasiliano event in the Paramirim Block during the West-Gondwana assembly processes. The regional microcline-gneiss, whose protolith is a 2.0 Ga syn-collisional potassic granite, represents the albitite host rock. The microcilne-gneiss has no petrogenetic association to the syenite (albitite protolith) in magmatic evolutionary terms.

  15. Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

    A. C. S. Silva


    Full Text Available Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom's framework for analyzing social-ecological systems (SES was applied. Ostrom's framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997–2000, when Brazil's new water policy was very young, and the other one in 2012–2015. The analysis of SES considering Ostrom's principle "Clearly defined boundaries" showed that deficiencies in water management cause the intensification of drought's impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.

  16. Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

    Silva, A. C. S.; Galvão, C. O.; Silva, G. N. S.


    Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom's framework for analyzing social-ecological systems (SES) was applied. Ostrom's framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997-2000, when Brazil's new water policy was very young, and the other one in 2012-2015. The analysis of SES considering Ostrom's principle "Clearly defined boundaries" showed that deficiencies in water management cause the intensification of drought's impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.

  17. Modeling changes in organic carbon stocks for distinct soils in southeastern brazil after four eucalyptus rotations using the century model

    Augusto Miguel Nascimento Lima


    Full Text Available Soil organic matter (SOM plays an important role in carbon (C cycle and soil quality. Considering the complexity of factors that control SOM cycling and the long time it usually takes to observe changes in SOM stocks, modeling constitutes a very important tool to understand SOM cycling in forest soils. The following hypotheses were tested: (i soil organic carbon (SOC stocks would be higher after several rotations of eucalyptus than in low-productivity pastures; (ii SOC values simulated by the Century model would describe the data better than the mean of observations. So, the aims of the current study were: (i to evaluate the SOM dynamics using the Century model to simulate the changes of C stocks for two eucalyptus chronosequences in the Rio Doce Valley, Minas Gerais State, Brazil; and (ii to compare the C stocks simulated by Century with the C stocks measured in soils of different Orders and regions of the Rio Doce Valley growing eucalyptus. In Belo Oriente (BO, short-rotation eucalyptus plantations had been cultivated for 4.0; 13.0, 22.0, 32.0 and 34.0 years, at a lower elevation and in a warmer climate, while in Virginópolis (VG, these time periods were 8.0, 19.0 and 33.0 years, at a higher elevation and in a milder climate. Soil samples were collected from the 0-20 cm layer to estimate C stocks. Results indicate that the C stocks simulated by the Century model decreased after 37 years of poorly managed pastures in areas previously covered by native forest in the regions of BO and VG. The substitution of poorly managed pastures by eucalyptus in the early 1970´s led to an average increase of C of 0.28 and 0.42 t ha-1 year-1 in BO and VG, respectively. The measured C stocks under eucalyptus in distinct soil Orders and independent regions with variable edapho-climate conditions were not far from the values estimated by the Century model (root mean square error - RMSE = 20.9; model efficiency - EF = 0.29 despite the opposite result obtained

  18. Comprehensive Analysis of Drought Persistence, Hazard, and Recovery across the CONUS

    Zarekarizi, M.; Ahmadi, B.; Moradkhani, H.


    Drought is a creeping intertwined natural hazard affecting society more than any other natural disaster and causing enormous damages on economy and ecosystems. Better understanding of potential drought hazard can help water managers and stakeholders devising mitigation plans to minimize the adverse effects of droughts. In this study, soil moisture, simulated by the Variable Infiltration Capacity (VIC) land surface model, is used to analyze the probability of agricultural drought with different severities across the CONUS. Due to the persistence of soil moisture, a drought episode at a particular time is affected by its earlier status; therefore, this study has utilized a Copula function to model the selected hydrologic variable over the time. The probability of drought intensity for each unit is presented spatially. If the unit remains in the drought condition at the same or lower intensity, drought persists and if it improves above a pre-defined threshold, the unit recovers. Results show that the west of US is more vulnerable to drought persistence in summer and spring while the Midwest and Northeast of US are experiencing drought persistence in fall and winter. In addition, the analysis reveals that as the intensity of drought in a given season decreases the following season has higher chance of recovery.

  19. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast

    Chen, Junfei; Li, Ming; Wang, Weiguang


    Drought is part of natural climate variability and ranks the first natural disaster in the world. Drought forecasting plays an important role in mitigating impacts on agriculture and water resources. In this study, a drought forecast model based on the random forest method is proposed to predict the time series of monthly standardized precipitation index (SPI). We demonstrate model application by four stations in the Haihe river basin, China. The random-forest- (RF-) based forecast model has ...

  20. Financial Risk Reduction and Management of Water Reservoirs Using Forecasts: A Case for Pernambuco, Brazil

    Kumar, I.; Josset, L.; e Silva, E. C.; Possas, J. M. C.; Asfora, M. C.; Lall, U.


    The financial health and sustainability, ensuring adequate supply, and adapting to climate are fundamental challenges faced by water managers. These challenges are worsened in semi-arid regions with socio-economic pressures, seasonal supply of water, and projected increase in intensity and frequency of droughts. Over time, probabilistic rainfall forecasts are improving and for water managers, it could be key in addressing the above challenges. Using forecasts can also help make informed decisions about future infrastructure. The study proposes a model to minimize cost of water supply (including cost of deficit) given ensemble forecasts. The model can be applied to seasonal to annual ensemble forecasts, to determine the least cost solution. The objective of the model is to evaluate the resiliency and cost associated to supplying water. A case study is conducted in one of the largest reservoirs (Jucazinho) in Pernambuco state, Brazil, and four other reservoirs, which provide water to nineteen municipalities in the Jucazinho system. The state has been in drought since 2011, and the Jucazinho reservoir, has been empty since January 2017. The importance of climate adaptation along with risk management and financial sustainability are important to the state as it is extremely vulnerable to droughts, and has seasonal streamflow. The objectives of the case study are first, to check if streamflow forecasts help reduce future supply costs by comparing k-nearest neighbor ensemble forecasts with a fixed release policy. Second, to determine the value of future infrastructure, a new source of supply from Rio São Francisco, considered to mitigate drought conditions. The study concludes that using forecasts improve the supply and financial sustainability of water, by reducing cost of failure. It also concludes that additional infrastructure can help reduce the risks of failure significantly, but does not guarantee supply during prolonged droughts like the one experienced


    J. Rhee


    Full Text Available The reduction of drought impacts may be achieved through sustainable drought management and proactive measures against drought disaster. Accurate and timely provision of drought information is essential. In this study, drought forecasting models to provide high-resolution drought information based on drought indicators for ungauged areas were developed. The developed models predict drought indices of the 6-month Standardized Precipitation Index (SPI6 and the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6. An interpolation method based on multiquadric spline interpolation method as well as three machine learning models were tested. Three machine learning models of Decision Tree, Random Forest, and Extremely Randomized Trees were tested to enhance the provision of drought initial conditions based on remote sensing data, since initial conditions is one of the most important factors for drought forecasting. Machine learning-based methods performed better than interpolation methods for both classification and regression, and the methods using climatology data outperformed the methods using long-range forecast. The model based on climatological data and the machine learning method outperformed overall.

  2. Analysis of a general circulation model product. I - Frontal systems in the Brazil/Malvinas and Kuroshio/Oyashio regions

    Garzoli, Silvia L.; Garraffo, Zulema; Podesta, Guillermo; Brown, Otis


    The general circulation model (GCM) of Semtner and Chervin (1992) is tested by comparing the fields produced by this model with available observations in two western boundary current regions, the Brazil/Malvinas and the Kuroshio/Oyashio confluences. The two sets of data used are the sea surface temperature from satellite observations and the temperature field product from the GCM at levels 1 (12.5 m), 2 (37.5 m), and 6 (160 m). It is shown that the model reproduces intense thermal fronts at the sea surface and in the upper layers (where they are induced by the internal dynamics of the model). The location of the fronts are reproduced in the model within 4 to 5 deg, compared with observations. However, the variability of these fronts was found to be less pronounced in the model than in the observations.

  3. Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part I evaluation of a water and carbon balance model

    Shanlei Sun; Ge Sun; Peter Caldwell; Steven G. McNulty; Erika Cohen; Jingfeng Xiao; Yang Zhang


    Understanding and quantitatively evaluating the regional impacts of climate change and variability (e.g., droughts) on forest ecosystem functions (i.e., water yield, evapotranspiration, and productivity) and services (e.g., fresh water supply and carbon sequestration) is of great importance for developing climate change adaptation strategies for National Forests and...

  4. Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite

    J.-P. Vidal


    Full Text Available Physically-based droughts can be defined as a water deficit in at least one component of the land surface hydrological cycle. The reliance of different activity domains (water supply, irrigation, hydropower, etc. on specific components of this cycle requires drought monitoring to be based on indices related to meteorological, agricultural, and hydrological droughts. This paper describes a high-resolution retrospective analysis of such droughts in France over the last fifty years, based on the Safran-Isba-Modcou (SIM hydrometeorological suite. The high-resolution 1958–2008 Safran atmospheric reanalysis was used to force the Isba land surface scheme and the hydrogeological model Modcou. Meteorological droughts are characterized with the Standardized Precipitation Index (SPI at time scales varying from 1 to 24 months. Similar standardizing methods were applied to soil moisture and streamflow for identifying multiscale agricultural droughts – through the Standardized Soil Wetness Index (SSWI – and multiscale hydrological droughts, through the Standardized Flow Index (SFI. Based on a common threshold level for all indices, drought event statistics over the 50-yr period – number of events, duration, severity and magnitude – have been derived locally in order to highlight regional differences at multiple time scales and at multiple levels of the hydrological cycle (precipitation, soil moisture, streamflow. Results show a substantial variety of temporal drought patterns over the country that are highly dependent on both the variable and time scale considered. Independent spatio-temporal drought events have then been identified and described by combining local characteristics with the evolution of area under drought. Summary statistics have finally been used to compare past severe drought events, from multi-year precipitation deficits (1989–1990 to short hot and dry periods (2003. Results show that the ranking of drought events depends highly

  5. Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

    Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi


    The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

  6. Assessing changes in drought characteristics with standardized indices

    Vidal, Jean-Philippe; Najac, Julien; Martin, Eric; Franchistéguy, Laurent; Soubeyroux, Jean-Michel


    Standardized drought indices like the Standardized Precipitation Index (SPI) are more and more frequently adopted for drought reconstruction, monitoring and forecasting, and the SPI has been recently recommended by the World Meteorological Organization to characterize meteorological droughts. Such indices are based on the statistical distribution of a hydrometeorological variable (e.g., precipitation) in a given reference climate, and a drought event is defined as a period with continuously negative index values. Because of the way these indices are constructed, some issues may arise when using them in a non-stationnary climate. This work thus aims at highlighting such issues and demonstrating the different ways these indices may - or may not - be applied and interpreted in the context of an anthropogenic climate change. Three major points are detailed through examples taken from both a high-resolution gridded reanalysis dataset over France and transient projections from the ARPEGE general circulation model downscaled over France. The first point deals with the choice of the reference climate, and more specifically its type (from observations/reanalysis or from present-day modelled climate) and its record period. Second, the interpretation of actual changes are closely linked with the type of the selected drought feature over a future period: mean index value, under-threshold frequency, or drought event characteristics (number, mean duration and magnitude, seasonality, etc.). Finally, applicable approaches as well as related uncertainties depend on the availability of data from a future climate, whether in the form of a fully transient time series from present-day or only a future time slice. The projected evolution of drought characteristics under climate change must inform present decisions on long-term water resources planning. An assessment of changes in drought characteristics should therefore provide water managers with appropriate information that can help

  7. Leaf area index drives soil water availability and extreme drought-related mortality under elevated CO2 in a temperate grassland model system.

    Manea, Anthony; Leishman, Michelle R


    The magnitude and frequency of climatic extremes, such as drought, are predicted to increase under future climate change conditions. However, little is known about how other factors such as CO2 concentration will modify plant community responses to these extreme climatic events, even though such modifications are highly likely. We asked whether the response of grasslands to repeat extreme drought events is modified by elevated CO2, and if so, what are the underlying mechanisms? We grew grassland mesocosms consisting of 10 co-occurring grass species common to the Cumberland Plain Woodland of western Sydney under ambient and elevated CO2 and subjected them to repeated extreme drought treatments. The 10 species included a mix of C3, C4, native and exotic species. We hypothesized that a reduction in the stomatal conductance of the grasses under elevated CO2 would be offset by increases in the leaf area index thus the retention of soil water and the consequent vulnerability of the grasses to extreme drought would not differ between the CO2 treatments. Our results did not support this hypothesis: soil water content was significantly lower in the mesocosms grown under elevated CO2 and extreme drought-related mortality of the grasses was greater. The C4 and native grasses had significantly higher leaf area index under elevated CO2 levels. This offset the reduction in the stomatal conductance of the exotic grasses as well as increased rainfall interception, resulting in reduced soil water content in the elevated CO2 mesocosms. Our results suggest that projected increases in net primary productivity globally of grasslands in a high CO2 world may be limited by reduced soil water availability in the future.

  8. Projected Changes in Evapotranspiration Rates over Northeast Brazil

    Costa, Alexandre; Guimarães, Sullyandro; Vasconcelos, Francisco, Jr.; Sales, Domingo; da Silva, Emerson


    Climate simulations were performed using a regional model (Regional Atmospheric Modeling System, RAMS 6.0) driven by data from one of the CMIP5 models (Hadley Centre Global Environmental Model, version 2 - Earth System, HadGEM2-ES) over two CORDEX domains (South America and Central America) for the heavy-emission scenario (RCP8.5). Potential evapotranspiraion data from the RCM and from the CMIP5 global models were analyzed over Northeast Brazil, a semiarid region with a short rainy season (usually February to May in its northern portion due to the seasonal shift of the Intertropical Convergence Zone) and over which droughts are frequent. Significant changes in the potential evapotranspiration were found, with most models showing a increasing trend along the 21st century, which are expected to alter the surface water budget, increasing the current water deficit (precipitation is currently much smaller than potential evapotranspiration). Based on the projections from the majority of the models, we expect important impacts over local agriculture and water resources over Northeast Brazil.

  9. Cost-utility of quadrivalent versus trivalent influenza vaccine in Brazil - comparison of outcomes from different static model types.

    Van Bellinghen, Laure-Anne; Marijam, Alen; Tannus Branco de Araujo, Gabriela; Gomez, Jorge; Van Vlaenderen, Ilse

    Influenza burden in Brazil is considerable with 4.2-6.4 million cases in 2008 and influenza-like-illness responsible for 16.9% of hospitalizations. Cost-effectiveness of influenza vaccination may be assessed by different types of models, with limitations due to data availability, assumptions, and modelling approach. To understand the impact of model complexity, the cost-utility of quadrivalent versus trivalent influenza vaccines in Brazil was estimated using three distinct models: a 1-year decision tree population model with three age groups (FLOU); a more detailed 1-year population model with five age groups (FLORA); and a more complex lifetime multi-cohort Markov model with nine age groups (FLORENCE). Analysis 1 (impact of model structure) compared each model using the same data inputs (i.e., best available data for FLOU). Analysis 2 (impact of increasing granularity) compared each model populated with the best available data for that model. Using the best data for each model, the discounted cost-utility ratio of quadrivalent versus trivalent influenza vaccine was R$20,428 with FLOU, R$22,768 with FLORA (versus R$20,428 in Analysis 1), and, R$19,257 with FLORENCE (versus R$22,490 in Analysis 1) using a lifetime horizon. Conceptual differences between FLORA and FLORENCE meant the same assumption regarding increased all-cause mortality in at-risk individuals had an opposite effect on the incremental cost-effectiveness ratio in Analysis 2 versus 1, and a proportionally higher number of vaccinated elderly in FLORENCE reduced this ratio in Analysis 2. FLOU provided adequate cost-effectiveness estimates with data in broad age groups. FLORA increased insights (e.g., in healthy versus at-risk, paediatric, respiratory/non-respiratory complications). FLORENCE provided greater insights and precision (e.g., in elderly, costs and complications, lifetime cost-effectiveness). All three models predicted a cost per quality-adjusted life year gained for quadrivalent versus

  10. Household Choices of Child Labor and Schooling: A Simple Model with Application to Brazil

    Soares, Rodrigo R.; Kruger, Diana; Berthelon, Matias


    This paper argues that conflicting results from previous literature--related to the effect of economic conditions on child labor--derive from different income and substitution effects implicit in different types of income variation. We use agricultural shocks to local economic activity in Brazil (coffee production) to distinguish between increases…

  11. Diurnal oscillations of soybean circadian clock and drought responsive genes.

    Juliana Marcolino-Gomes

    Full Text Available Rhythms produced by the endogenous circadian clock play a critical role in allowing plants to respond and adapt to the environment. While there is a well-established regulatory link between the circadian clock and responses to abiotic stress in model plants, little is known of the circadian system in crop species like soybean. This study examines how drought impacts diurnal oscillation of both drought responsive and circadian clock genes in soybean. Drought stress induced marked changes in gene expression of several circadian clock-like components, such as LCL1-, GmELF4- and PRR-like genes, which had reduced expression in stressed plants. The same conditions produced a phase advance of expression for the GmTOC1-like, GmLUX-like and GmPRR7-like genes. Similarly, the rhythmic expression pattern of the soybean drought-responsive genes DREB-, bZIP-, GOLS-, RAB18- and Remorin-like changed significantly after plant exposure to drought. In silico analysis of promoter regions of these genes revealed the presence of cis-elements associated both with stress and circadian clock regulation. Furthermore, some soybean genes with upstream ABRE elements were responsive to abscisic acid treatment. Our results indicate that some connection between the drought response and the circadian clock may exist in soybean since (i drought stress affects gene expression of circadian clock components and (ii several stress responsive genes display diurnal oscillation in soybeans.

  12. A comprehensive framework for tourism and recreation drought vulnerability reduction

    Thomas, Deborah S K; Wilhelmi, Olga V; Finnessey, Taryn N; Deheza, Veva


    The effects of drought are vast, but loss statistics often do not reflect the impacts on the tourism and recreation sector, which for many places is one of the most critical economic drivers. This is concerning because drought events are common across the globe, with varying frequency, duration, and intensity, and are therefore unavoidable. Over the years, drought conditions have been at record levels in many regions, causing deep societal and economic impacts. However, little research has been conducted on connections between tourism/recreation and drought, revealing a distinct disconnect between the tourism/recreation sector and drought management. To bridge this gap in the current understanding of, and approaches to, managing drought in the tourism/recreation sector, we present an interdisciplinary conceptual framework that integrates tourism/recreation into the drought management process to ensure sustainable economic development and community vitality. The model presented here promotes understanding of critical interactions through a bottom-up stakeholder engagement process balanced with formal top-down management approaches. (letter)

  13. Civil conflict sensitivity to growing-season drought.

    von Uexkull, Nina; Croicu, Mihai; Fjelde, Hanne; Buhaug, Halvard


    To date, the research community has failed to reach a consensus on the nature and significance of the relationship between climate variability and armed conflict. We argue that progress has been hampered by insufficient attention paid to the context in which droughts and other climatic extremes may increase the risk of violent mobilization. Addressing this shortcoming, this study presents an actor-oriented analysis of the drought-conflict relationship, focusing specifically on politically relevant ethnic groups and their sensitivity to growing-season drought under various political and socioeconomic contexts. To this end, we draw on new conflict event data that cover Asia and Africa, 1989-2014, updated spatial ethnic settlement data, and remote sensing data on agricultural land use. Our procedure allows quantifying, for each ethnic group, drought conditions during the growing season of the locally dominant crop. A comprehensive set of multilevel mixed effects models that account for the groups' livelihood, economic, and political vulnerabilities reveals that a drought under most conditions has little effect on the short-term risk that a group challenges the state by military means. However, for agriculturally dependent groups as well as politically excluded groups in very poor countries, a local drought is found to increase the likelihood of sustained violence. We interpret this as evidence of the reciprocal relationship between drought and conflict, whereby each phenomenon makes a group more vulnerable to the other.

  14. Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil.

    Nildimar Alves Honório


    Full Text Available Rio de Janeiro, Brazil, experienced a severe dengue fever epidemic in 2008. This was the worst epidemic ever, characterized by a sharp increase in case-fatality rate, mainly among younger individuals. A combination of factors, such as climate, mosquito abundance, buildup of the susceptible population, or viral evolution, could explain the severity of this epidemic. The main objective of this study is to model the spatial patterns of dengue seroprevalence in three neighborhoods with different socioeconomic profiles in Rio de Janeiro. As blood sampling coincided with the peak of dengue transmission, we were also able to identify recent dengue infections and visually relate them to Aedes aegypti spatial distribution abundance. We analyzed individual and spatial factors associated with seroprevalence using Generalized Additive Model (GAM.Three neighborhoods were investigated: a central urban neighborhood, and two isolated areas characterized as a slum and a suburban area. Weekly mosquito collections started in September 2006 and continued until March 2008. In each study area, 40 adult traps and 40 egg traps were installed in a random sample of premises, and two infestation indexes calculated: mean adult density and mean egg density. Sera from individuals living in the three neighborhoods were collected before the 2008 epidemic (July through November 2007 and during the epidemic (February through April 2008. Sera were tested for DENV-reactive IgM, IgG, Nested RT-PCR, and Real Time RT-PCR. From the before-after epidemics paired data, we described seroprevalence, recent dengue infections (asymptomatic or not, and seroconversion. Recent dengue infection varied from 1.3% to 14.1% among study areas. The highest IgM seropositivity occurred in the slum, where mosquito abundance was the lowest, but household conditions were the best for promoting contact between hosts and vectors. By fitting spatial GAM we found dengue seroprevalence hotspots located at the

  15. Modeling the land requirements and potential productivity of sugarcane and jatropha in Brazil and India using the LPJmL dynamic global vegetation model

    Lapola, David M. [Center for Environmental Systems Research, University of Kassel, D-34109 Kassel (Germany); International Max Planck Research School on Earth System Modeling, D-20146 Hamburg (Germany); Priess, Joerg A. [Center for Environmental Systems Research, University of Kassel, D-34109 Kassel (Germany); Bondeau, Alberte [Potsdam Institute for Climate Impact Research, D-14412 Potsdam (Germany)


    The governments of Brazil and India are planning a large expansion of bioethanol and biodiesel production in the next decade. Considering that limitation of suitable land and/or competition with other land uses might occur in both countries, assessments of potential crop productivity can contribute to an improved planning of land requirements for biofuels under high productivity or marginal conditions. In this paper we model the potential productivity of sugarcane and jatropha in both countries. Land requirements for such expansions are calculated according to policy scenarios based on government targets for biofuel production in 2015. Spatial variations in the potential productivity lead to rather different land requirements, depending on where plantations are located. If jatropha is not irrigated, land requirements to fulfill the Indian government plans in 2015 would be of 410 000 to 95 000 km{sup 2} if grown in low or high productivity areas respectively (mean of 212 000 km{sup 2}). In Brazil land requirements, are of 18 000-89 000 km{sup 2} (mean of 29 000 km{sup 2}), suggesting a promising substitute to soybean biodiesel. Although future demand for sugarcane ethanol in Brazil is approximately ten times larger than in India, land requirements are comparable in both countries due to large differences in ethanol production systems. In Brazil this requirement ranges from 25 000 to 211 000 km{sup 2} (mean of 33 000 km{sup 2}) and in India from 7000 to 161 000 km{sup 2} (mean 17 000 km{sup 2}). Irrigation could reduce the land requirements by 63% and 41% (24% and 15%) in India (Brazil) for jatropha and sugarcane respectively. (author)

  16. Exploring the linkage between drought, high temperatures, and hydrologic sensitivities: A case study of the 2012 Great Plains drought.

    Livneh, B.; Hoerling, M. P.


    The occurrence of drought is associated with agricultural loss, water supply shortfalls, and other economic impacts. Here we explore the physical relationships between precipitation deficits, high temperatures, and hydrologic responses as a pathway to better anticipate drought impacts. Current methodologies to predict hydrologic scarcity include local monitoring of river flows, remote sensing of land-surface wetness, drought indices, expert judgment, climate indices (e.g. SST-relationships) and the application of hydrologic models. At longer lead times, predictions of drought have most frequently been made on the basis of GCM ensembles, with subsequent downscaling of those to scales over which hydrologic predictions can be made. This study focuses on two important aspects of drought. First, we explore the causal hydro-climatic timeline of a drought event, namely (a) the lack of precipitation, which serves to reduce soil moisture and produce (b) a skewed Bowen ratio, i.e. comparatively more sensible heating (warming) with less ET, resulting in (c) anomalously warm conditions. We seek to assess the extent to which the lack of precipitation contributes to warming temperatures, and the further effects of that warming on hydrology and the severity of drought impacts. An ensemble of GCM simulations will be used to explore the evolution of the land surface energy budget during a recent Great Plains drought event, which will subsequently be used to drive a hydrologic model. Second, we examine the impacts of the critical assumptions relating climatic variables with water demand, specifically the relationship between potential evapotranspiration (PET) and temperature. The common oversimplification in relating PET to temperature is explored against a more physically consistent energy balance estimate of PET, using the Penman-Monteith approach and the hydrologic impacts are presented. Results from this work are anticipated to have broad relevance for future water management

  17. Drought, nutrition and food security

    First page Back Continue Last page Overview Graphics. Drought associated with climate change may lead to food and water shortage. Drought associated with climate change may lead to food and water shortage. Greater vulnerability to infectious diseases. Population displacements and mass migrations with all ...

  18. Drought and ecosystem carbon cycling

    Molen, M.K. van der; Dolman, A.J.; Ciais, P.; Eglin, T.; Gobron, N.; Law, B.E.; Meir, P.; Peters, P.; Philips, O.L.; Reichstein, M.; Chen, T.; Dekker, S.C.; Doubkova, M.; Friedl, M.A.; Jung, M.; Hurk, B.J.J.M. van den; Jeu, R.A.M. de; Kruijt, B.; Ohta, T.; Rebel, K.T.; Plummer, S.; Seneviratne, S.I.; Sitch, S.; Teuling, A.J.; Werf, G.R. van der; Wang, G.


    Drought as an intermittent disturbance of the water cycle interacts with the carbon cycle differently than the ‘gradual’ climate change. During drought plants respond physiologically and structurally to prevent excessive water loss according to species-specific water use strategies. This has

  19. Multiyear drought-induced morbidity preceding tree death in southeastern U.S. forests.

    Berdanier, Aaron B; Clark, James S


    Recent forest diebacks, combined with threats of future drought, focus attention on the extent to which tree death is caused by catastrophic events as opposed to chronic declines in health that accumulate over years. While recent attention has focused on large-scale diebacks, there is concern that increasing drought stress and chronic morbidity may have pervasive impacts on forest composition in many regions. Here we use long-term, whole-stand inventory data from southeastern U.S. forests to show that trees exposed to drought experience multiyear declines in growth prior to mortality. Following a severe, multiyear drought, 72% of trees that did not recover their pre-drought growth rates died within 10 yr. This pattern was mediated by local moisture availability. As an index of morbidity prior to death, we calculated the difference in cumulative growth after drought relative to surviving conspecifics. The strength of drought-induced morbidity varied among species and was correlated with drought tolerance. These findings support the ability of trees to avoid death during drought events but indicate shifts that could occur over decades. Tree mortality following drought is predictable in these ecosystems based on growth declines, highlighting an opportunity to address multiyear drought-induced morbidity in models, experiments, and management decisions.

  20. A European Drought Reference Database: Design and Online Implementation

    Stagge, J.H.; Tallaksen, L.M.; Kohn, I.; Stahl, K.; Loon, van A.


    This report presents the structure and status of the online European Drought Reference (EDR) database. This website provides detailed historical information regarding major historical European drought events. Each drought event is summarized using climatological drought indices, hydrological drought

  1. Linking dynamic phenotyping with metabolite analysis to study natural variation in drought responses of Brachypodium distachyon

    Lorraine H.C. Fisher


    Full Text Available Drought is an important environmental stress limiting the productivity of major crops worldwide. Understanding drought tolerance and possible mechanisms for improving drought resistance is therefore a prerequisite to develop drought-tolerant crops that produce significant yields with reduced amounts of water. Brachypodium distachyon (Brachypodium is a key model species for cereals, forage grasses and energy grasses. In this study, initial screening of a Brachypodium germplasm collection consisting of 138 different ecotypes exposed to progressive drought, highlighted the natural variation in morphology, biomass accumulation and responses to drought stress. A core set of ten ecotypes, classified as being either tolerant, susceptible or intermediate, in response to drought stress, were exposed to mild or severe (respectively 15% and 0% soil water content drought stress and phenomic parameters linked to growth and colour changes were assessed. When exposed to severe drought stress, phenotypic data and metabolite profiling combined with multivariate analysis revealed a remarkable consistency in separating the selected ecotypes into their different pre-defined drought tolerance groups. Increases in several metabolites, including for the phytohormones jasmonic acid and salicylic acid, and TCA-cycle intermediates, were positively correlated with biomass yield and with reduced yellow pixel counts; suggestive of delayed senescence, both key target traits for crop improvement to drought stress. While metabolite analysis also separated ecotypes into the distinct tolerance groupings after exposure to mild drought stress, similar analysis of the phenotypic data failed to do so, confirming the value of metabolomics to investigate early responses to drought stress. The results highlight the potential of combining the analyses of phenotypic and metabolic responses to identify key mechanisms and markers associated with drought tolerance in both the Brachypodium

  2. Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

    Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope


    Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.

  3. Accessibility evaluation model to support decision-making in urban investments : the case of Santarém-Brazil

    Ramos, Rui A. R.; Rodrigues, Daniel Souto; Tobias, Maisa


    The main goal of the paper is to present an accessibility evaluation model for the urban area of Santarém, in Brazil. Located midway between the larger cities of Belém and Manaus, Santarém plays a crucial role in the region of Lower Amazonia. The paper describes the research instruments, sampling method and data analysis proposed for mapping urban accessibility. Basic activities (education, health, services, leisure and commerce) provided by the city were used to identify the main key-destina...

  4. Adverse effects of increasing drought on air quality via natural processes

    Wang, Yuxuan; Xie, Yuanyu; Dong, Wenhao; Ming, Yi; Wang, Jun; Shen, Lu


    Drought is a recurring extreme of the climate system with well-documented impacts on agriculture and water resources. The strong perturbation of drought to the land biosphere and atmospheric water cycle will affect atmospheric composition, the nature and extent of which are not well understood. Here we present observational evidence that US air quality is significantly correlated with drought severity. Severe droughts during the period of 1990-2014 were found associated with growth-season (March-October) mean enhancements in surface ozone and PM2.5 of 3.5 ppbv (8 %) and 1.6 µg m-3 (17 %), respectively. The pollutant enhancements associated with droughts do not appear to be affected by the decreasing trend of US anthropogenic emissions, indicating natural processes as the primary cause. Elevated ozone and PM2.5 are attributed to the combined effects of drought on deposition, natural emissions (wildfires, biogenic volatile organic compounds (BVOCs), and dust), and chemistry. Most climate-chemistry models are not able to reproduce the observed correlations of ozone and PM2.5 to drought severity. The model deficiencies are partly attributed to the lack of drought-induced changes in land-atmosphere exchanges of reactive gases and particles and misrepresentation of cloud changes under drought conditions. By applying the observed relationships between drought and air pollutants to climate model projected drought occurrences, we estimate an increase of 1-6 % for ground-level O3 and 1-16 % for PM2.5 in the US by 2100 compared to the 2000s due to increasing drought alone. Drought thus poses an important aspect of climate change penalty on air quality, and a better prediction of such effects would require improvements in model processes.

  5. Changes in tree resistance, recovery and resilience across three successive extreme droughts in the northeast Iberian Peninsula.

    Serra-Maluquer, X; Mencuccini, M; Martínez-Vilalta, J


    Understanding which variables affect forest resilience to extreme drought is key to predict future dynamics under ongoing climate change. In this study, we analyzed how tree resistance, recovery and resilience to drought have changed along three consecutive droughts and how they were affected by species, tree size, plot basal area (as a proxy for competition) and climate. We focused on the three most abundant pine species in the northeast Iberian Peninsula: Pinus halepensis, P. nigra and P. sylvestris during the three most extreme droughts recorded in the period 1951-2010 (occurred in 1986, 1994, and 2005-2006). We cored trees from permanent sample plots and used dendrochronological techniques to estimate resistance (ability to maintain growth level during drought), recovery (growth increase after drought) and resilience (capacity to recover pre-drought growth levels) in terms of tree stem basal area increment. Mixed-effects models were used to determine which tree- and plot-level variables were the main determinants of resistance, recovery and resilience, and to test for differences among the studied droughts. Larger trees were significantly less resistant and resilient. Plot basal area effects were only observed for resilience, with a negative impact only during the last drought. Resistance, recovery and resilience differed across the studied drought events, so that the studied populations became less resistant, less resilient and recovered worse during the last two droughts. This pattern suggests an increased vulnerability to drought after successive drought episodes.

  6. Hydrological Drought in the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation in the U.S.

    Wan, Wenhua; Zhao, Jianshi; Li, Hong-Yi; Mishra, Ashok; Ruby Leung, L.; Hejazi, Mohamad; Wang, Wei; Lu, Hui; Deng, Zhiqun; Demissisie, Yonas; Wang, Hao


    Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the future. Here we utilize a high-resolution integrated modeling framework that represents water management in terms of both local surface water extraction and reservoir regulation and use the Standardized Streamflow Index to quantify hydrological drought. We explore the impacts of water management on hydrological drought over the contiguous U.S. in a warming climate with and without emissions mitigation. Despite the uncertainty of climate change impacts, local surface water extraction consistently intensifies drought that dominates at the regional to national scale. However, reservoir regulation alleviates drought by enhancing summer flow downstream of reservoirs. The relative dominance of drought intensification or relief is largely determined by the water demand, with drought intensification dominating in regions with intense water demand such as the Great Plains and California, while drought relief dominates in regions with low water demand. At the national level, water management increases the spatial extent of extreme drought despite some alleviations of moderate to severe drought. In an emissions mitigation scenario with increased irrigation demand for bioenergy production, water management intensifies drought more than the business-as-usual scenario at the national level, so the impacts of emissions mitigation must be evaluated by considering its benefit in reducing warming and evapotranspiration against its effects on increasing water demand and intensifying drought.

  7. Application of Archimedean copulas to the analysis of drought decadal variation in China

    Zuo, Dongdong; Feng, Guolin; Zhang, Zengping; Hou, Wei


    Based on daily precipitation data collected from 1171 stations in China during 1961-2015, the monthly standardized precipitation index was derived and used to extract two major drought characteristics which are drought duration and severity. Next, a bivariate joint model was established based on the marginal distributions of the two variables and Archimedean copula functions. The joint probability and return period were calculated to analyze the drought characteristics and decadal variation. According to the fit analysis, the Gumbel-Hougaard copula provided the best fit to the observed data. Based on four drought duration classifications and four severity classifications, the drought events were divided into 16 drought types according to the different combinations of duration and severity classifications, and the probability and return period were analyzed for different drought types. The results showed that the occurring probability of six common drought types (0 accounted for 76% of the total probability of all types. Moreover, due to their greater variation, two drought types were particularly notable, i.e., the drought types where D ≥ 6 and S ≥ 2. Analyzing the joint probability in different decades indicated that the location of the drought center had a distinctive stage feature, which cycled from north to northeast to southwest during 1961-2015. However, southwest, north, and northeast China had a higher drought risk. In addition, the drought situation in southwest China should be noted because the joint probability values, return period, and the analysis of trends in the drought duration and severity all indicated a considerable risk in recent years.

  8. Drought Risk Assessment based on Natural and Social Factors

    Huang, Jing; Wang, Huimin; Han, Dawei


    In many parts of the world, drought hazard is becoming more frequent and severe due to climate change and human activities. It is crucial to monitor and assess drought conditions, especially for decision making support in agriculture sector. The vegetation index (VI) decreases, and the land surface temperature (LST) increases when the vegetation is under drought stress. Therefore both of these remotely sensed indices are widely used in drought monitoring and assessment. Temperature-Vegetation Dryness Index (TVDI) is obtained by establishing the feature space of the normalized difference vegetation index (NDVI) and LST, which reflects agriculture dry situation by inverting soil moisture. However, these indices only concern the natural hazard-causing factors. Our society is a complex large-scale system with various natural and social elements. The drought risk is the joint consequence of hazard-causing factors and hazard-affected bodies. For example, as the population increases, the exposure of the hazard-affected bodies also tends to increase. The high GDP enhances the response ability of government, and the irrigation and water conservancy reduces the vulnerability. Such characteristics of hazard-affected bodies should be coupled with natural factors. In this study, the 16-day moderate-resolution imaging spectroradiometer (MODIS) NDVI and LST data are combined to establish NDVI-Ts space according to different land use types in Yunnan Province, China. And then, TVDIs are calculated through dry and wet edges modeled as a linear fit to data for each land cover type. Next, the efforts are turned to establish an integrated drought assessment index of social factors and TVDI through ascertaining attribute weight based on rough sets theory. Thus, the new CDI (comprehensive drought index) recorded during spring of 2010 and the spatial variations in drought are analyzed and compared with TVDI dataset. Moreover, actual drought risk situation in the study area is given to

  9. Modeling HIV/AIDS drug price determinants in Brazil: is generic competition a myth?

    Meiners, Constance; Sagaon-Teyssier, Luis; Hasenclever, Lia; Moatti, Jean-Paul


    Brazil became the first developing country to guarantee free and universal access to HIV/AIDS treatment, with antiretroviral drugs (ARVs) being delivered to nearly 190,000 patients. The analysis of ARV price evolution and market dynamics in Brazil can help anticipate issues soon to afflict other developing countries, as the 2010 revision of the World Health Organization guidelines shifts demand towards more expensive treatments, and, at the same time, current evolution of international legislation and trade agreements on intellectual property rights may reduce availability of generic drugs for HIV care. Our analyses are based on effective prices paid for ARV procurement in Brazil between 1996 and 2009. Data panel structure was exploited to gather ex-ante and ex-post information and address various sources of statistical bias. In-difference estimation offered in-depth information on ARV market characteristics which significantly influence prices. Although overall ARV prices follow a declining trend, changing characteristics in the generic segment help explain recent increase in generic ARV prices. Our results show that generic suppliers are more likely to respond to factors influencing demand size and market competition, while originator suppliers tend to set prices strategically to offset compulsory licensing threats and generic competition. In order to guarantee the long term sustainability of access to antiretroviral treatment, our findings highlight the importance of preserving and stimulating generic market dynamics to sustain developing countries' bargaining power in price negotiations undertaken with originator companies.

  10. Modeling HIV/AIDS drug price determinants in Brazil: is generic competition a myth?

    Constance Meiners

    Full Text Available BACKGROUND: Brazil became the first developing country to guarantee free and universal access to HIV/AIDS treatment, with antiretroviral drugs (ARVs being delivered to nearly 190,000 patients. The analysis of ARV price evolution and market dynamics in Brazil can help anticipate issues soon to afflict other developing countries, as the 2010 revision of the World Health Organization guidelines shifts demand towards more expensive treatments, and, at the same time, current evolution of international legislation and trade agreements on intellectual property rights may reduce availability of generic drugs for HIV care. METHODS AND FINDINGS: Our analyses are based on effective prices paid for ARV procurement in Brazil between 1996 and 2009. Data panel structure was exploited to gather ex-ante and ex-post information and address various sources of statistical bias. In-difference estimation offered in-depth information on ARV market characteristics which significantly influence prices. Although overall ARV prices follow a declining trend, changing characteristics in the generic segment help explain recent increase in generic ARV prices. Our results show that generic suppliers are more likely to respond to factors influencing demand size and market competition, while originator suppliers tend to set prices strategically to offset compulsory licensing threats and generic competition. SIGNIFICANCE: In order to guarantee the long term sustainability of access to antiretroviral treatment, our findings highlight the importance of preserving and stimulating generic market dynamics to sustain developing countries' bargaining power in price negotiations undertaken with originator companies.

  11. Spatio-temporal drought characteristics of the tropical Paraiba do Sul River Basin and responses to the Mega Drought in 2014-2016

    Nauditt, Alexandra; Metzke, Daniel; Ribbe, Lars


    The Paraiba do Sul River Basin (56.000 km2) supplies water to the Brazilian states Sao Paulo and Rio de Janeiro. Their large metropolitan areas were strongly affected by a Mega drought during the years 2014 and 2015 with severe implications for domestic water supply, the hydropower sector as well as for rural agricultural downstream regions. Longer drought periods are expected to become more frequent in the future. However, drought characteristics, low flow hydrology and the reasons for the recurrent water scarcity in this water abundant tropical region are still poorly understood. In order to separate the impact of human abstractions from hydro-climatic and catchment storage related hydrological drought propagation, we assessed the spatio-temporal distribution of drought severity and duration establishing relationships between SPI, SRI and discharge threshold drought anomalies for all subcatchments of the PdS based on a comprehensive hydro-meteorological data set of the Brazilian National Water Agency ANA. The water allocation model "Water Evaluation and Planning System (WEAP)" was established on a monthly basis for the entire Paraiba do Sul river basin incorporating human modifications of the hydrological system as major (hydropower) reservoirs and their operational rules, water diversions and major abstractions. It simulates reasonable discharges and reservoir levels comparable to the observed values. To evaluate the role of climate variability and drought responses for hydrological drought events, scenarios were developed to simulate discharge and reservoir level the impact of 1. Varying meteorological drought frequencies and durations and 2. Implementing operational rules as a response to drought. Uncertainties related to the drought assessment, modelling, parameter and input data were assessed. The outcome of this study for the first time provides an overview on the heterogeneous spatio-temporal drought characteristics of the Paraiba do Sul river basin and

  12. Contribution of Temperature to Chilean Droughts Using Ensemble Climate Projections

    Zambrano-Bigiarini, M.; Alfieri, L.; Naumann, G.; Garreaud, R. D.


    Precipitation deficit is traditionally considered as the main driver of drought events, however the evolution of drought conditions is also influenced by other variables such as temperature, wind speed and evapotranspiration. In view of global warming, the effect of rising temperatures may lead to increased socio-economic drought impacts, particularly in vulnerable developing countries. In this work, we used two drought indices to analyze the impacts of precipitation and temperature on the frequency, severity and duration of Chilean droughts (25°S-56°S) during the XXI century, using multi-model climate projections consistent with the high-end RCP 8.5 scenario. An ensemble of seven global CMIP5 simulations were used to drive the Earth System Model EC-EARTH3-HR v3.1 over the 1976-2100 period, in order to increase the spatial resolution from the original grid to 0.35°. The Standardized Precipitation Index (SPI) was used to describe the impact of precipitation on drought conditions, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the effect of temperature -throughout changes in potential evapotranspiration- on drought characteristics at different time scales. Drought indices along with duration, severity and frequency of drought events were computed for a 30-year baseline period (1976-2005) and then compared to three 30-year periods representing short, medium and long-term scenarios (2011-2040, 2041-2070 and 2071-2100). Indices obtained from climate simulations during the baseline period were compared against the corresponding values derived from ground observations. Results obtained with SPI-12 reveal a progressive decrease in precipitation in Chile, which is consistent through all climate models, though each of them shows a different spatial pattern. Simulations based on SPEI-12 show that the expected increase in evaporative demand (driven by the temperature increase) for the region is likely to exacerbate the severity and

  13. Climatic Droughts and the Impacts on Crop Yields in Northern India during the Past Century

    Ge, Y.; Cai, X.; Zhu, T.


    Drought has become an increasingly severe threat to water and food security recently. This study presents a novel method to calculate the return period of drought, considering drought as event characterized by expected drought inter-arrival time, duration, severity and peak intensity. Recently, Copula distribution, a multivariable probability distribution, is used to deal with strongly correlated variables in analyzing complex hydrologic phenomenon. This study assesses drought conditions in Northern India, including 8 sites, in the past century using Palmer Drought Severity Index (PDSI) from two latest datasets, Dai (2011, 2013) and Sheffield et al. (2012), which concluded conflicting results about global average drought trend. Our results include the change of the severity, intensity and duration of drought events during the past century and the impact of the drought condition on crop yields in the region. It is found that drought variables are highly correlated, thus copulas joint distribution enables the estimation of multi-variate return period. Based on Dai's dataset from 1900 to 2012, for a fixed drought return period the severity and duration is lower for the period before1955 in sites close to the Indus basin (site 1) or off the coast of the Indian Ocean (Bay of Bengal) (site 8), while they are higher for the period after 1955 in other inland sites (sites 3-7), (e.g., severity in Fig.1). Projections based on two models (IPCC AR4 and AR5) in Dai (2011, 2013) suggested less severity and shorter duration in longer-year drought (e.g., 100-year drought), but larger in shorter-year drought (e.g., 2-year drought). Drought could bring nonlinear responses and unexpected losses in agriculture system, thus prediction and management are essential. Therefore, in the years with extreme drought conditions, impact assessment of drought on crop yield of corn, barley, wheat and sorghum will be also conducted through correlating crop yields with drought conditions during

  14. Assessing spatiotemporal variation of drought and its impact on maize yield in Northeast China

    Guo, Enliang; Liu, Xingpeng; Zhang, Jiquan; Wang, Yongfang; Wang, Cailin; Wang, Rui; Li, Danjun


    In the context of global climate change, drought has become an important factor that affects the maize yield in China. To analyse the impact of drought on maize yield loss in Northeast China in current and future climate scenarios, the Composite Meteorological Drought Index (CI) is introduced to reconstruct the following drought indicators: drought accumulative days (DAD), drought accumulative intensity (DAI), and consecutive drought days (CDD). These three drought indicators are used to describe the three-dimensional characteristics of drought in this study. Sen's slope method and three-dimensional copula functions are adopted to analyse the variety of drought features, and Ensemble Empirical Mode Decomposition (EEMD) is used to analyse the variations in maize yield. A temporal assessment of the standardized yield residuals series (SYRS) of maize from 1961 to 2014 is conducted. A panel regression model is applied to demonstrate the drought impact on maize yield at various growth stages under the RCP4.5 scenario. The results show that the drought risk level for midwest Jilin Province, western Liaoning, and eastern Heilongjiang increase with global warming in the current scenario. The shorter three-dimensional joint return periods, 44-80 yr, were mainly located in western Jilin Province, Liaodong Peninsula, and northwestern Liaoning. Eastern Heilongjiang has a slightly longer joint return period of 80-100 yr. The SYRS shows a strong statistical correlation with drought indicator variations; drought-prone regions exhibit strong positive correlations. In comparison, excess precipitation regions show strong negative correlations with drought indicators in most growth stages. Drought indicators have a relatively strong association with SYRS at the milky-mature maize growth stage, and the occurrence of drought during this period primarily determines the maize yield changes in the future. Maize yield changes are -2.04%, -2.65% and -1.57% for Liaoning, Jilin, and

  15. Small area estimation of obesity prevalence and dietary patterns: a model applied to Rio de Janeiro city, Brazil.

    Cataife, Guido


    We propose the use of previously developed small area estimation techniques to monitor obesity and dietary habits in developing countries and apply the model to Rio de Janeiro city. We estimate obesity prevalence rates at the Census Tract through a combinatorial optimization spatial microsimulation model that matches body mass index and socio-demographic data in Brazil's 2008-9 family expenditure survey with Census 2010 socio-demographic data. Obesity ranges from 8% to 25% in most areas and affects the poor almost as much as the rich. Male and female obesity rates are uncorrelated at the small area level. The model is an effective tool to understand the complexity of the problem and to aid in policy design. © 2013 Published by Elsevier Ltd.

  16. Soil-plant transfer models for metals to improve soil screening value guidelines valid for São Paulo, Brazil.

    Dos Santos-Araujo, Sabrina N; Swartjes, Frank A; Versluijs, Kees W; Moreno, Fabio Netto; Alleoni, Luís R F


    In Brazil, there is a lack of combined soil-plant data attempting to explain the influence of specific climate, soil conditions, and crop management on heavy metal uptake and accumulation by plants. As a consequence, soil-plant relationships to be used in risk assessments or for derivation of soil screening values are not available. Our objective in this study was to develop empirical soil-plant models for Cd, Cu, Pb, Ni, and Zn, in order to derive appropriate soil screening values representative of humid tropical regions such as the state of São Paulo (SP), Brazil. Soil and plant samples from 25 vegetable species in the production areas of SP were collected. The concentrations of metals found in these soil samples were relatively low. Therefore, data from temperate regions were included in our study. The soil-plant relations derived had a good performance for SP conditions for 8 out of 10 combinations of metal and vegetable species. The bioconcentration factor (BCF) values for Cd, Cu, Ni, Pb, and Zn in lettuce and for Cd, Cu, Pb, and Zn in carrot were determined under three exposure scenarios at pH 5 and 6. The application of soil-plant models and the BCFs proposed in this study can be an important tool to derive national soil quality criteria. However, this methodological approach includes data assessed under different climatic conditions and soil types and need to be carefully considered.

  17. Politics and drought planning: Friends or foes?

    McDowell, B.D.; Blomquist, W.


    Nothing frustrates the average drought planner more than politics. Yet, droughts cannot be prepared for realistically without reliable political partners, smoothly cooperating government agencies, and strong public support. This paper suggests six rules for linking technical drought planning processes to the political processes and institutions that can implement drought plans

  18. Economics and societal considerations of drought

    Jeff Prestemon; Linda Kruger; Karen L. Abt; Michael Bowker; Consuelo Brandeis; Dave Calkin; Geoffrey H. Donovan; Charlotte Ham; Thomas P. Holmes; Jeffrey Kline; Travis Warziniack


    The economic and social effects of drought are diverse and related to physical characteristics of drought, including spatial extent, severity, duration, and frequency that combine to determine drought’s overall effects on society. Most of the attention given to economic and social impacts of drought focuses on adverse consequences, but technology, public...

  19. Genetic dissection of drought tolerance in potato

    Anithakumari, A.M.


    Drought is the most important cause of crop and yield loss around the world. Breeding for

    drought tolerance is not straightforward, as drought is a complex trait. A better understanding

    of the expression of drought traits, the genes underlying the traits and the way these

  20. Plant hydraulic diversity buffers forest ecosystem responses to drought

    Anderegg, W.; Konings, A. G.; Trugman, A. T.; Pacala, S. W.; Yu, K.; Sulman, B. N.; Sperry, J.; Bowling, D. R.


    Drought impacts carbon, water, and energy cycles in forests and may pose a fundamental threat to forests in future climates. Plant hydraulic transport of water is central to tree drought responses, including curtailing of water loss and the risk of mortality during drought. The effect of biodiversity on ecosystem function has typically been examined in grasslands, yet the diversity of plant hydraulic strategies may influence forests' response to drought. In a combined analysis of eddy covariance measurements, remote-sensing data of plant water content variation, model simulations, and plant hydraulic trait data, we test the degree to which plant water stress schemes influence the carbon cycle and how hydraulic diversity within and across ecosystems affects large-scale drought responses. We find that current plant functional types are not well-suited to capture hydraulic variation and that higher hydraulic diversity buffers ecosystem variation during drought. Our results demonstrate that tree functional diversity, particularly hydraulic diversity, may be critical to simulate in plant functional types in current land surface model projections of future vegetation's response to climate extremes.

  1. Economic risk assessment of drought impacts on irrigated agriculture

    Lopez-Nicolas, A.; Pulido-Velazquez, M.; Macian-Sorribes, H.


    In this paper we present an innovative framework for an economic risk analysis of drought impacts on irrigated agriculture. It consists on the integration of three components: stochastic time series modelling for prediction of inflows and future reservoir storages at the beginning of the irrigation season; statistical regression for the evaluation of water deliveries based on projected inflows and storages; and econometric modelling for economic assessment of the production value of agriculture based on irrigation water deliveries and crop prices. Therefore, the effect of the price volatility can be isolated from the losses due to water scarcity in the assessment of the drought impacts. Monte Carlo simulations are applied to generate probability functions of inflows, which are translated into probabilities of storages, deliveries, and finally, production value of agriculture. The framework also allows the assessment of the value of mitigation measures as reduction of economic losses during droughts. The approach was applied to the Jucar river basin, a complex system affected by multiannual severe droughts, with irrigated agriculture as the main consumptive demand. Probability distributions of deliveries and production value were obtained for each irrigation season. In the majority of the irrigation districts, drought causes a significant economic impact. The increase of crop prices can partially offset the losses from the reduction of production due to water scarcity in some districts. Emergency wells contribute to mitigating the droughts' impacts on the Jucar river system.

  2. Drought Tip: Keeping Plants Alive under Drought or Water Restrictions

    Hartin, Janet; Oki, Loren; Fujino, Dave; Faber, Ben


    Plants that don't receive enough water eventually show signs of water stress. During a drought or under water restrictions aimed at water conservation, keeping plants alive can be particularly difficult.

  3. Extreme Water Deficit in Brazil Detected from Space

    Vieira Getirana


    Extreme droughts have caused significant socioeconomic and environmental damage worldwide. In Brazil, ineffective energy development and water management policies have magnified the impacts of recent severe droughts, which include massive agricultural losses, water supply restrictions, and energy rationing. Spaceborne remote sensing data advance our understanding of the spatiotemporal variability of large-scale droughts and enhance the detection and monitoring of extreme water-related events. In this study, data derived from the Gravity Recovery and Climate Experiment (GRACE) mission are used to detect and quantify an extended major drought over eastern Brazil and provide estimates of impacted areas and region-specific water deficits. Two structural breakpoint detection methods were applied to time series of GRACE-based terrestrial water storage anomalies (TWSA), determining when two abrupt changes occurred. One, in particular, defines the beginning of the current drought. Using TWSA, a water loss rate of 26.1 cmyr21 over southeastern Brazil was detected from 2012 to 2015. Based on analysis of Global Land Data Assimilation System(GLDAS) outputs, the extreme drought is mostly related to lower-than-usual precipitation rates, resulting in high soil moisture depletion and lower-than-usual rates of evapotranspiration. A reduction of 2023 of precipitation over an extended period of 3 years is enough to raise serious water scarcity conditions in the country. Correlations between monthly time series of both grid-based TWSA and ground-based water storage measurements at 16 reservoirs located within southeastern Brazil varied from 0.42 to 0.82. Differences are mainly explained by reservoir sizes and proximity to the drought nucleus.

  4. Characterization of future drought conditions in the Lower Mekong River Basin

    Madusanka Thilakarathne


    Full Text Available This study evaluates future changes to drought characteristics in the Lower Mekong River Basin using climate model projections. The Lower Mekong Basin (LMB, covering Thailand, Cambodia, Laos and Vietnam, is vulnerable to increasing droughts. Univariate analysis was employed in this study to compare drought characteristics associated with different return periods for the historical period 1964–2005 and future scenarios (RCP 4.5 2016–2057, RCP 4.5 2058–2099, RCP 8.5 2016–2057 and RCP 8.5 2058–2099. Because a single drought event is defined by several correlated characteristics, drought risk assessment by a multivariate analysis was deemed appropriate, and a multivariate analysis of droughts was conducted using copula functions to investigate the differences in the trivariate joint occurrence probabilities of the historical period and future scenarios. The Standardized Precipitation Index (SPI was selected as the drought index because of its ability to detect and compare metrological droughts across time and space scales. Historical precipitation data from 1964 to 2005 and future precipitation projections from 2016 to 2099 for 15 global circulation models (GCMs obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP dataset were employed. In all future scenarios, the Lower LMB and 3S subbasins were expected to experience more severe and intense droughts. The multivariate drought risk assessment revealed an increase in drought risks in the LMB. However, the Chi-Mun subbasin may experience an alleviation of future drought characteristics. Because the basin was expected to experience an increase in average monthly precipitation in most months, the variability in magnitude suggested that the LMB region requires adaptation strategies to address future drought occurrences.

  5. For the Construction of a Historico-anthropological Model of Musical Relationships between Brazil, Portugal, and Africa

    Rafael José de Menezes Bastos


    Full Text Available The text postulates a model of a historico-anthropological nature for understanding the musical relationships from Brazil, Portugal, and Atlantic lusophone Africa during the XVII and XIX centuries. The model stars from the constitution of the Atlantic lusophone space as one of continual sociocultural relationships in general and musical in particular up to the first decades of the XIX century and even before. Those musical relationships are based on the existence of vast transatlantic system of musical and dance genres connected through historic and structural transformations. Because it belongs to that system, the lundu-modinha-fado transformation system will be studied, with emphasis on Bazilian dance and Portuguese song. The article elaborates the concept of "musical genre" from the notions of Mikhail Bakhtin´s "discursive genre" and Claude Lévi-Strauss and Marshall Sahlins’s "transformation".

  6. Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff-erosion model in the Mamuaba catchment, Brazil.

    Marques da Silva, Richarde; Guimarães Santos, Celso Augusto; Carneiro de Lima Silva, Valeriano; Pereira e Silva, Leonardo


    This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (soil erosion was estimated to exceed > 12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.

  7. Projected climatic changes on drought conditions over Spain

    García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María


    In a context of global warming, the evapotranspiration processes will have a strong influence on drought severity. For this reason, the Standardized Precipitation Evapotranspiration Index (SPEI) was computed at different timescales in order to explore the projected drought changes for the main watersheds in Spain. For that, the Weather Research and Forecasting (WRF) model has been used in order to obtain current (1980-2010) and future (2021-2050 and 2071-2100) climate output fields. WRF model was used over a domain that spans the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser 0.44° EURO-CORDEX domain, and driving by the global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1), using two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Besides, to examine the behavior of this drought index, a comparison with the Standardized Precipitation Index (SPI), which does not consider the evapotranspiration effects, was also performed. Additionally the relationship between the SPEI index and the soil moisture has also been analyzed. The results of this study suggest an increase in the severity and duration of drought, being larger when the SPEI index is used to define drought events. This fact confirms the relevance of taking into account the evapotranspiration processes to detect future drought events. The results also show a noticeable relationship between the SPEI and the simulated soil moisture content, which is more significant at higher timescales. Keywords: Drought, SPEI, SPI, Climatic change, Projections, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

  8. An assessment of global meteorological droughts based on HAPPI experiments

    Liu, Wenbin; Sun, Fubao; Lim, Wee Ho; Zhang, Jie


    Droughts caused water shortages could lead to serious consequences on the socioeconomic and environmental well-being. In the context of changing climate, droughts monitoring, attributions and impact assessments have been performed using observations (e.g., Sun et al., 2012; Zhang et al., 2016) and climate model projections (e.g., Liu et al., 2016, 2017); with expectation that such scientific knowledge would feed into long-term adaptation and mitigation plans to tackle potentially unfavorable future drought impacts in a warming world. Inspired by the 2015 Paris Agreement, the HAPPI (Half a degree Additional warming, Projections, Prognosis and Impacts) experiments were set up to better inform international policymakers about the socioeconomic and environmental impacts under less severe global warming conditions. This study aims to understand the potential shift in meteorological droughts from the past into the future on a global scale. Based on the HAPPI data, we evaluate the change in drought related indices (i.e., PET/P, PDSI) from the past to the future scenarios (1.5 and 2 degrees Celsius warming). Here we present some early results (MIROC5 as demonstration) on identified hotspots and discuss the differences in severity of droughts between these warming worlds and associated consequences. References: Liu W, and Sun F, 2017. Projecting and attributing future changes of evaporative demand over China in CMIP5 climate models, Journal of Hydrometeorology, doi: 10.1175/JHM-D-16-0204.1 Liu W, and Sun F, 2016. Assessing estimates of evaporative demand in climate models using observed pan evaporation over China. Journal of Geophysical Research-Atmosphere 121, 8329-8349 Zhang J, Sun F, Xu J, Chen Y, Sang Y, -F, and Liu C, 2016. Dependence of trends in and sensitivity of drought over China (1961-2013) on potential evaporation model. Geophysical Research Letters 43, 206-213 Sun F, Roderick M, Farquhar G, 2012. Changes in the variability of global land precipitation

  9. Seasonal Drought Forecasting for Latin America Using the ECMWF S4 Forecast System

    Hugo Carrão


    Full Text Available Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there are still not many studies of the feasibility of such a forecasts at continental level in the region. In this study, precipitation predictions from the European Centre for Medium Range Weather (ECMWF seasonal forecast system S4 are combined with observed precipitation data to generate forecasts of the standardized precipitation index (SPI for Latin America, and their skill is evaluated over the hindcast period 1981–2010. The value-added utility in using the ensemble S4 forecast to predict the SPI is identified by comparing the skill of its forecasts with a baseline skill based solely on their climatological characteristics. As expected, skill of the S4-generated SPI forecasts depends on the season, location, and the specific aggregation period considered (the 3- and 6-month SPI were evaluated. Added skill from the S4 for lead times equaling the SPI accumulation periods is primarily present in regions with high intra-annual precipitation variability, and is found mostly for the months at the end of the dry seasons for 3-month SPI, and half-yearly periods for 6-month SPI. The ECMWF forecast system behaves better than the climatology for clustered grid points in the North of South America, the Northeast of Argentina, Uruguay, southern Brazil and Mexico. The skillful regions are similar for the SPI3 and -6, but become reduced in extent for the severest SPI categories. Forecasting different magnitudes of meteorological drought intensity on a seasonal time scale still remains a challenge. However, the ECMWF S4 forecasting system does capture the occurrence of drought events for the aforementioned regions and seasons reasonably well. In the near term, the largest advances in the prediction of meteorological drought for Latin

  10. Drought, climate change and vegetation response in the succulent karoo, South Africa

    M. T. Hoffman


    Full Text Available For the winter-rainfall region of South Africa, the frequency of drought is predicted to increase over the next 100 years, with dire consequences for the vegetation of this biodiversity hotspot. We analysed historical 20th century rainfall records for six rainfall stations within the succulent karoo biome to determine if the signal of increasing drought frequency is already apparent, and whether mean annual rainfall is decreasing. We found no evidence for a decrease either in mean annual rainfall or in the incidence of drought, as measured by the Standardised Precipitation Index (SPI over the 20th century. Evidence points to a drying trend from 1900–1950 while no significant trend in rainfall and drought was found at most stations from 1951–2000. In a second analysis we synthesised the information concerning the response of adult succulent karoo biome plants and seedlings to extended drought conditions. General findings are that responses to drought differ between species, and that longevity is an important life history trait related to drought survival. Growth form is a poor predictor of drought response across the biome. There was a range of responses to drought among adult plants of various growth forms, and among non-succulent seedlings. Leaf-succulent seedlings, however, exhibited phenomenal drought resistance, the majority surviving drought long after all the experimentally comparative non-succulent seedlings had died. Our synthesis showed that previous studies on the impact of drought on succulent karoo biome plants differ greatly in terms of their location, sampling design, measured values and plant responses. A suite of coordinated long-term field observations, experiments and models are therefore needed to assess the response of succulent karoo biome species to key drought events as they occur over time and to integrate this information into conservation planning.

  11. Global Drought Services: Collaborations Toward an Information System for Early Warning

    Hayes, M. J.; Pulwarty, R. S.; Svoboda, M.


    Drought is a hazard that lends itself well to diligent, sustained monitoring and early warning. However, unlike most hazards, the fact that droughts typically evolve slowly, can last for months or years and cover vast areas spanning multiple political boundaries/jurisdictions and economic sectors can make it a daunting task to monitor, develop plans for, and identify appropriate, proactive mitigation strategies. The National Drought Mitigation Center (NDMC) and National Integrated Drought Information System (NIDIS) have been working together to reduce societal vulnerability to drought by helping decision makers at all levels to: 1) implement drought early warning/forecasting and decision support systems; 2) support and advocate for better collection of, and understanding of drought impacts; and 3) increase long-term resilience to drought through proactive planning. The NDMC and NIDIS risk management approach has been the basis from which many partners around the world are developing a collaboration and coordination nexus with an ultimate goal of building comprehensive global drought early warning information systems (GDEWIS). The core emphasis of this model is on developing and applying useful and usable information that can be integrated and transferred freely to other regions around the globe. The High-Level Ministerial Declaration on Drought, the Integrated Drought Management Programme (IDMP) co-led by the WMO and the Global Water Partnership (GWP), and the Global Framework for Climate Services are drawing extensively from the integrated NDMC-NIDIS risk management framework. This presentation will describe, in detail, the various drought resources, tools, services, and collaborations already being provided and undertaken at the national and regional scales by the NDMC, NIDIS, and their partners. The presentation will be forward-looking, identifying improvements in existing and proposed mechanisms to help strengthen national and international drought early

  12. Screening the banana biodiversity for drought tolerance: can an in vitro growth model and proteomics be used as a tool to discover tolerant varieties and understand homeostasis.

    Vanhove, Anne-Catherine; Vermaelen, Wesley; Panis, Bart; Swennen, Rony; Carpentier, Sebastien C


    There is a great need for research aimed at understanding drought tolerance, screening for drought tolerant varieties and breeding crops with an improved water use efficiency. Bananas and plantains are a major staple food and export product with a worldwide production of over 135 million tonnes per year. Water however is the most limiting abiotic factor in banana production. A screening of the Musa biodiversity has not yet been performed. We at KU Leuven host the Musa International Germplasm collection with over 1200 accessions. To screen the Musa biodiversity for drought tolerant varieties, we developed a screening test for in vitro plants. Five varieties representing different genomic constitutions in banana (AAAh, AAA, AAB, AABp, and ABB) were selected and subjected to a mild osmotic stress. The ABB variety showed the smallest stress induced growth reduction. To get an insight into the acclimation and the accomplishment of homeostasis, the leaf proteome of this variety was characterized via 2D DIGE. After extraction of the leaf proteome of six control and six stressed plants, 2600 spots could be distinguished. A PCA analysis indicates that control and stressed plants can blindly be classified based on their proteome. One hundred and twelve proteins were significantly more abundant in the stressed plants and 18 proteins were significantly more abundant in control plants (FDR α 0.05). Twenty four differential proteins could be identified. The proteome analysis clearly shows that there is a new balance in the stressed plants and that the respiration, metabolism of ROS and several dehydrogenases involved in NAD/NADH homeostasis play an important role.

  13. Improving Federal Response to Drought.

    Wilhite, Donald A.; Rosenberg, Norman J.; Glantz, Michael H.


    Severe and widespread drought occurred over a large portion of the United States between 1974 and 1977. Impacts on agriculture and other industries, as well as local water supplies, were substantial. The federal government responded with forty assistance programs administered by sixteen federal agencies. Assistance was provided primarily in the form of loans and grants to people, businesses and governments experiencing hardship caused by drought. The total cost of the program is estimated at $7-8 billion.Federal response to the mid-1970s drought was largely untimely, ineffective and poorly coordinated. Four recommendations are offered that, if implemented, would improve future drought assessment and response efforts: 1) reliable and timely informational products and dissemination plans; 2) improved impact assessment techniques, especially in the agricultural sector, for use by government to identify periods of enhanced risk and to trigger assistance measures; 3) administratively centralized drought declaration procedures that are well publicized and consistently applied; and 4) standby assistance measures that encourage appropriate levels of risk management by producers and that are equitable, consistent and predictable. The development of a national drought plan that incorporates these four items is recommended. Atmospheric scientists have an important role to play in the collection and interpretation of near-real time weather data for use by government decision makers.

  14. 2003 hydrological drought - natural disaster

    Trninic, Dusan; Bosnjak, Tomislava


    An exceptionally dry and warm period from February to early October 2003 resulted in hydrological drought with attributes of a natural disaster in most of the Croatian regions. The paper presents hydrological analysis of the Sava River near Zupanja for the period 1945-2003 (N=59 years). In defining maximum annual volumes of isolated waves below the reference discharges, the following reference discharges were used:Q 30,95% = 202m 3 s -1 - minimum mean 30-day discharge, 95 % probability, Q 30,80% = 254m 3 s -1 - minimum mean 30-day discharge, 80 % probability, Q 95% = 297m 3 s -1 - (H = -17cm minimum navigation level = 95 % of water level duration from average duration curve). The analysis results have shown that the hydrological drought recorded during the current year belongs to the most thoroughly studied droughts in 59 years. For example, hydrological analysis of the reference discharge of 297m 3 s -1 has shown that this year drought comes second, immediately after the driest year 1946. However, this year hydrological drought hit the record duration of 103 days, unlike the one from 1946, which lasted 98 days. It is interesting that the hydrological droughts affect the Sava River usually in autumn and summer, rarely in winter, and it has never been recorded in spring (referring to the analysed 1945-2003 period). In conclusion, some recommendations are given for increase in low streamflows and on possible impacts of climate changes on these flows.(Author)

  15. The Arabidopsis transcription factor ABIG1 relays ABA signaled growth inhibition and drought induced senescence.

    Liu, Tie; Longhurst, Adam D; Talavera-Rauh, Franklin; Hokin, Samuel A; Barton, M Kathryn


    Drought inhibits plant growth and can also induce premature senescence. Here we identify a transcription factor, ABA INSENSITIVE GROWTH 1 (ABIG1) required for abscisic acid (ABA) mediated growth inhibition, but not for stomatal closure. ABIG1 mRNA levels are increased both in response to drought and in response to ABA treatment. When treated with ABA, abig1 mutants remain greener and produce more leaves than comparable wild-type plants. When challenged with drought, abig1 mutants have fewer yellow, senesced leaves than wild-type. Induction of ABIG1 transcription mimics ABA treatment and regulates a set of genes implicated in stress responses. We propose a model in which drought acts through ABA to increase ABIG1 transcription which in turn restricts new shoot growth and promotes leaf senescence. The results have implications for plant breeding: the existence of a mutant that is both ABA resistant and drought resistant points to new strategies for isolating drought resistant genetic varieties.

  16. Impacts of drought on grape yields in Western Cape, South Africa

    Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier


    Droughts remain a threat to grape yields in South Africa. Previous studies on the impacts of climate on grape yield in the country have focussed on the impact of rainfall and temperature separately; meanwhile, grape yields are affected by drought, which is a combination of rainfall and temperature influences. The present study investigates the impacts of drought on grape yields in the Western Cape (South Africa) at district and farm scales. The study used a new drought index that is based on simple water balance (Standardized Precipitation Evapotranspiration Index; hereafter, SPEI) to identify drought events and used a correlation analysis to identify the relationship between drought and grape yields. A crop simulation model (Agricultural Production Systems sIMulator, APSIM) was applied at the farm scale to investigate the role of irrigation in mitigating the impacts of drought on grape yield. The model gives a realistic simulation of grape yields. The Western Cape has experienced a series of severe droughts in the past few decades. The severe droughts occurred when a decrease in rainfall occurred simultaneously with an increase in temperature. El Niño Southern Oscillation (ENSO) appears to be an important driver of drought severity in the Western Cape, because most of the severe droughts occurred in El Niño years. At the district scale, the correlation between drought index and grape yield is weak ( r≈-0.5), but at the farm scale, it is strong ( r≈-0.9). This suggests that many farmers are able to mitigate the impacts of drought on grape yields through irrigation management. At the farm scale, where the impact of drought on grape yields is high, poor yield years coincide with moderate or severe drought periods. The APSIM simulation, which gives a realistic simulation of grape yields at the farm scale, suggests that grape yields become more sensitive to spring and summer droughts in the absence of irrigation. Results of this study may guide decision-making on

  17. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast

    Junfei Chen


    Full Text Available Drought is part of natural climate variability and ranks the first natural disaster in the world. Drought forecasting plays an important role in mitigating impacts on agriculture and water resources. In this study, a drought forecast model based on the random forest method is proposed to predict the time series of monthly standardized precipitation index (SPI. We demonstrate model application by four stations in the Haihe river basin, China. The random-forest- (RF- based forecast model has consistently shown better predictive skills than the ARIMA model for both long and short drought forecasting. The confidence intervals derived from the proposed model generally have good coverage, but still tend to be conservative to predict some extreme drought events.

  18. Post-breakup tectonics in southeast Brazil from thermochronological data and combined inverse-forward thermal history modeling

    Cogné, Nathan; Gallagher, Kerry; Cobbold, Peter R.; Riccomini, Claudio; Gautheron, Cecile


    The continental margin of southeast Brazil is elevated. Onshore Tertiary basins and Late Cretaceous/Paleogene intrusions are good evidence for post breakup tectono-magmatic activity. To constrain the impact of post-rift reactivation on the geological history of the area, we carried out a new thermochronological study. Apatite fission track ages range from 60.7 ± 1.9 Ma to 129.3 ± 4.3 Ma, mean track lengths from 11.41 ± 0.23 μm to 14.31 ± 0.24 μm and a subset of the (U-Th)/He ages range from 45.1 ± 1.5 to 122.4 ± 2.5 Ma. Results of inverse thermal history modeling generally support the conclusions from an earlier study for a Late Cretaceous phase of cooling. Around the onshore Taubaté Basin, for a limited number of samples, the first detectable period of cooling occurred during the Early Tertiary. The inferred thermal histories for many samples also imply subsequent reheating followed by Neogene cooling. Given the uncertainty of the inversion results, we did deterministic forward modeling to assess the range of possibilities of this Tertiary part of the thermal history. The evidence for reheating seems to be robust around the Taubaté Basin, but elsewhere the data cannot discriminate between this and a less complex thermal history. However, forward modeling results and geological information support the conclusion that the whole area underwent cooling during the Neogene. The synchronicity of the cooling phases with Andean tectonics and those in NE Brazil leads us to assume a plate-wide compressional stress that reactivated inherited structures. The present-day topographic relief of the margin reflects a contribution from post-breakup reactivation and uplift.

  19. Investigating transport capacity equations in sediment yield modelling for the Cariri semi-arid region of Paraiba-PB/Brazil

    E. E. De Figueiredo


    Full Text Available In the semi arid Cariri region of the state of Paraiba, Brazil, runoff is of the Hortonian type generated by excess of rainfall over infiltration capacity, and soil erosion is governed by rainfall intensity and sediment size. However, the governing sediment transport mechanism is not well understood. Sediment transport generally depends on the load of sediment provided by soil erosion and on the transport capacity of the flow. The latter is mainly governed by mechanisms such as water shear stress, or stream power. Accordingly, the load of sediment transported by the flow may vary depending on the mechanism involved in the equation of estimation. Investigation of the sediment transport capacity of the flow via a distributed physically-based model is an important and necessary task, but quite rare in semi-arid climates, and particularly in the Cariri region of the state of Paraíba/Brazil. In this study, the equations of Yalin, Engelund & Hansen, Laursen, DuBoys and Bagnold have been coupled with the MOSEE distributed physically based model aiming at identifying the mechanisms leading to the best model simulations when compared with data observed at various basin scales and land uses in the study region. The results obtained with the investigated methods were quite similar and satisfactory suggesting the feasibility of the mechanisms involved, but the observed values were better represented with Bagnold’s equation, which is physically grounded on the stream power, and we recommend it for simulations of similar climate, runoff generation mechanisms and sediment characteristics as in the study region.

  20. a New Framework for Characterising Simulated Droughts for Future Climates

    Sharma, A.; Rashid, M.; Johnson, F.


    Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross

  1. Integrated drought risk assessment of multi-hazard-affected bodies based on copulas in the Taoerhe Basin, China

    Wang, Rui; Zhang, Jiquan; Guo, Enliang; Alu, Si; Li, Danjun; Ha, Si; Dong, Zhenhua


    Along with global warming, drought disasters are occurring more frequently and are seriously affecting normal life and food security in China. Drought risk assessments are necessary to provide support for local governments. This study aimed to establish an integrated drought risk model based on the relation curve of drought joint probabilities and drought losses of multi-hazard-affected bodies. First, drought characteristics, including duration and severity, were classified using the 1953-2010 precipitation anomaly in the Taoerhe Basin based on run theory, and their marginal distributions were identified by exponential and Gamma distributions, respectively. Then, drought duration and severity were related to construct a joint probability distribution based on the copula function. We used the EPIC (Environmental Policy Integrated Climate) model to simulate maize yield and historical data to calculate the loss rates of agriculture, industry, and animal husbandry in the study area. Next, we constructed vulnerability curves. Finally, the spatial distributions of drought risk for 10-, 20-, and 50-year return periods were expressed using inverse distance weighting. Our results indicate that the spatial distributions of the three return periods are consistent. The highest drought risk is in Ulanhot, and the duration and severity there were both highest. This means that higher drought risk corresponds to longer drought duration and larger drought severity, thus providing useful information for drought and water resource management. For 10-, 20-, and 50-year return periods, the drought risk values ranged from 0.41 to 0.53, 0.45 to 0.59, and 0.50 to 0.67, respectively. Therefore, when the return period increases, the drought risk increases.

  2. Refinement of the daily precipitation simulated by the CMIP5 models over the north of the Northeast of Brazil

    Gyrlene Aparecida Mendes da Silva


    Full Text Available The ability of the Artificial Neural Network (ANN and the Multiple Linear Regression (MLR in reproducing the area-average observed daily precipitation during the rainy season (Feb-Mar-Apr over the north of the Northeast of Brazil (NEB is examined. For the present climate of Dec-Jan-Feb from 1963 to 2003 period these statistical models are developed and validated using the observed daily precipitation and simulated from the historical outputs of 4 models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5. The simulations from all the models during DJF and FMA seasons show an anomalous intensification of the ITCZ and southward displacement in comparison with the climatology. Correlations of 0.54, 0.66 and 0.66 are found between the simulated daily precipitation of the CCSM4, GFDL_ESM2M and MIROC_ESM models during DJF season and the observed values during FMA season. Only the CCSM4 model displays a slightly reasonable agreement with the observations. A comparison between the statistical downscaling using the nonlinear (ANN and linear model (MLR to identify the one most suitable for the analysis of daily precipitation was made. The ANN technique provides more ability to predict the present climate when compared to MLR technique. Based on this result, we examined the accuracy of the ANN model in project the changes for the future climate period from 2055 to 2095 over the same study region. For instance, a comparison between the daily precipitation changes projected indirectly from the ANN during Feb-Mar-Apr with those projected directly from the CMIP5 models forced by RCP 8.5 scenario is made. The results suggest that ANN model weights the CMIP5 projections according to the each model ability in simulating the present climate (and its variability. In others, the ANN model is a potentially promising approach to use as a complementary tool to improvement of the seasonal numerical simulations.

  3. Importance of soil-water to the Caatinga biome, Brazil

    Alves Rodrigues Pinheiro, Everton; Metselaar, Klaas; Jong van Lier, de Quirijn; Araújo, de José Carlos


    Northeastern Brazil is hydrologically characterized by recurrent droughts leading to a highly vulnerable natural water resource system. The region contains the Caatinga biome, covering an area of approximately 800000km2. To increase insight in water balance components for this sparsely

  4. Designing basin-customized combined drought indices via feature extraction

    Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea


    The socio-economic costs of drought are progressively increasing worldwide due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and how to combine them, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). The W-QEISS algorithm relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables (cardinality) and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of a pre-defined model (i.e., an extreme learning machine) of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The proposed methodology is tested in the case study of Lake Como in northern Italy, a regulated lake mainly operated for irrigation supply to four downstream agricultural districts. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as the most common drought indicators at multiple time aggregations. The soil

  5. Climate Downscaling over Nordeste, Brazil, Using the NCEP RSM97.

    Sun, Liqiang; Ferran Moncunill, David; Li, Huilan; Divino Moura, Antonio; de Assis de Souza Filho, Francisco


    The NCEP Regional Spectral Model (RSM), with horizontal resolution of 60 km, was used to downscale the ECHAM4.5 AGCM (T42) simulations forced with observed SSTs over northeast Brazil. An ensemble of 10 runs for the period January-June 1971-2000 was used in this study. The RSM can resolve the spatial patterns of observed seasonal precipitation and capture the interannual variability of observed seasonal precipitation as well. The AGCM bias in displacement of the Atlantic ITCZ is partially corrected in the RSM. The RSM probability distribution function of seasonal precipitation anomalies is in better agreement with observations than that of the driving AGCM. Good potential prediction skills are demonstrated by the RSM in predicting the interannual variability of regional seasonal precipitation. The RSM can also capture the interannual variability of observed precipitation at intraseasonal time scales, such as precipitation intensity distribution and dry spells. A drought index and a flooding index were adopted to indicate the severity of drought and flooding conditions, and their interannual variability was reproduced by the RSM. The overall RSM performance in the downscaled climate of the ECHAM4.5 AGCM is satisfactory over Nordeste. The primary deficiency is a systematic dry bias for precipitation simulation.

  6. Evaluation and prediction of oil biodegradation: a novel approach integrating geochemical and basin modeling techniques in offshore Brazil

    Baudino, Roger [YPF S.A. (Argentina); Santos, Glauce Figueiredo dos; Losilla, Carlos; Cabrera, Ricardo; Loncarich, Ariel; Gavarrino, Alejandro [RepsolYPF do Brasil, Sao Paulo, SP (Brazil)


    Oil fields accounting for a large portion of the world reserves are severely affected by biological degradation. In Brazil, giant fields of the Campos Basin are producing biodegraded oils with widely variable fluid characteristics (10 to 40 deg API) and no apparent logical distribution nor predictability. Modern geochemical techniques allow defining the level of biodegradation. When original (non-degraded) oil samples and other with varying degradation level are available it might be possible to define a distribution trend and to relate it to present day geological factors such as temperature and reservoir geometry. However, other critical factors must be taken into account. But most of all, it is fundamental to have a vision in time of their evolution. This can only be achieved through 3D Basin Models coupled with modern visualization tools. The multi-disciplinary work-flow described here integrates three-dimensional numerical simulations with modern geochemical analyses. (author)

  7. Calibration, uncertainties and use of soybean crop simulation models for evaluating strategies to mitigate the effects of climate change in Southern Brazil

    Rafael Battisti


    The water deficit is a major factor responsible for the soybean yield gap in Southern Brazil and tends to increase under climate change. Crop models are a tool that differ on levels of complexity and performance and can be used to evaluate strategies to manage crops, according the climate conditions. Based on that, the aims of this study were: to assess five soybean crop models and their ensemble; to evaluate the sensitivity of these models to systematic changes in climate; to assess soybean ...

  8. Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil

    Kelvin Balcombe; George Rapsomanikis


    Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest ...

  9. Consumer contribution to food contamination in Brazil: modelling the food safety risk in the home

    Sergio Paulo Olinto da Motta


    Full Text Available Foodborne diseases are among the most widespread public health issues, killing about 2.2 million people annually, and costing hundreds of billions of US dollars for governments, companies, families and consumers (WHO, 2007. In Brazil, foodborne diseases acquired in the home account for 55% of notified outbreaks (BRASIL, 2012. Several studies have investigated aspects of consumer behaviour concerning food poisoning, mapping practices in the home, but it remains a challenge to obtain a full picture of the consumer contribution to food contamination (REDMOND and GRIFFITH, 2003. This study aimed to assess the risks of food contamination in the home. A questionnaire containing 140 questions concerning food safety knowledge, handling practices, personal hygiene and basic health care, covering the stages when the food is under the control of the consumer, was developed and used to gather data for analysis. Appropriate scores were attributed to the questions (consequences to food safety and answers (likelihood of food contamination. A risk estimate algorithm and an appropriate risk ranking scale were used to assess the results. From August 2011 to March 2012, survey questionnaires were collected from 2,775 consumers in Brazil across 19 out of 27 state capitals. The study found risky practices with the potential to lead to food poisoning occurrences in the domestic environment in the following handling steps: food transportation, food preparation, cooking and the handling of leftovers. The personal hygiene, age, formal education, family income and basic health care habits represented the factors most related to the risky practices of consumers, which could orientate food safety educational campaigns for the Brazilian population.

  10. A preliminary study on drought events in Peninsular Malaysia

    Zin, Wan Zawiah Wan; Nahrawi, Siti Aishah; Jemain, Abdul Aziz; Zahari, Marina


    In this research, the Standard Precipitation Index (SPI) is used to represent the dry condition in Peninsular Malaysia. To do this, data of monthly rainfall from 75 stations in Peninsular Malaysia is used to obtain the SPI values at scale one. From the SPI values, two drought characteristics that are commonly used to represent the dry condition in an area that is the duration and severity of a drought period are identified and their respective values calculated for every station. Spatial mappings are then used to identify areas which are more likely to be affected by longer and more severe drought condition from the results. As the two drought characteristics may be correlated with each other, the joint distribution of severity and duration of dry condition is considered. Bivariate copula model is used and five copula models were tested, namely, the Gumbel-Hougard, Clayton, Frank, Joe and Galambos copulas. The copula model, which best represents the relationship between severity and duration, is determined using Akaike information criterion. The results showed that the Joe and Clayton copulas are well-fitted by close to 60% of the stations under study. Based on the results on the most appropriate copula-based joint distribution for each station, some bivariate probabilistic properties of droughts can then be calculated, which will be continued in future research.

  11. Application of the hydrologic model AÇUMOD based on GIS for water resources management of Pirapama River, Pernambuco, Brazil

    Richarde Marques da Silva


    Full Text Available This study presents the application of the distributed hydrological model based on GIS – AÇUMOD to estimate the water discharges and potentialities of Pirapama river sub-basins, to be used by the Pirapama River Basin Committee (COBH-Pirapama. The model application included several steps, such as: precipitation data selection, basin discretization into cells, and model parameter calibration using try-and-error technique. The model was calibrated and validated with monthly precipitation data for the period 1987–2001. It was noted that the following parameters were the most important ones during the calibration process: infiltration function, soil minimum water capacity to generate runoff, and soil mean water storage capacity, which directly affect the computed runoff volume. The difference between observed and computed runoff during the calibration and validation processes were respectively -12.65% and 18.87%. The results of the simulated discharges by AÇUMOD, compared to observed ones, showed that the model satisfactorily represents the water basin behavior and, therefore, it can be considered a promising tool for rain-runoff simulation, permanence curve estimation, and discharge regionalization or prediction for Pirapama river basin as well as to other basins in the northeastern Brazil costal area.

  12. Proteomic responses of drought-tolerant and drought-sensitive cotton varieties to drought stress.

    Zhang, Haiyan; Ni, Zhiyong; Chen, Quanjia; Guo, Zhongjun; Gao, Wenwei; Su, Xiujuan; Qu, Yanying


    Drought, one of the most widespread factors reducing agricultural crop productivity, affects biological processes such as development, architecture, flowering and senescence. Although protein analysis techniques and genome sequencing have made facilitated the proteomic study of cotton, information on genetic differences associated with proteomic changes in response to drought between different cotton genotypes is lacking. To determine the effects of drought stress on cotton seedlings, we used two-dimensional polyacrylamide gel electrophoresis (2-DE) and matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry to comparatively analyze proteome of drought-responsive proteins during the seedling stage in two cotton (Gossypium hirsutum L.) cultivars, drought-tolerant KK1543 and drought-sensitive Xinluzao26. A total of 110 protein spots were detected on 2-DE maps, of which 56 were identified by MALDI-TOF and MALDI-TOF/TOF mass spectrometry. The identified proteins were mainly associated with metabolism (46.4 %), antioxidants (14.2 %), and transport and cellular structure (23.2 %). Some key proteins had significantly different expression patterns between the two genotypes. In particular, 5-methyltetrahydropteroyltriglutamate-homocysteine methyltransferase, UDP-D-glucose pyrophosphorylase and ascorbate peroxidase were up-regulated in KK1543 compared with Xinluzao26. Under drought stress conditions, the vacuolar H(+)-ATPase catalytic subunit, a 14-3-3g protein, translation initiation factor 5A and pathogenesis-related protein 10 were up-regulated in KK1543, whereas ribosomal protein S12, actin, cytosolic copper/zinc superoxide dismutase, protein disulfide isomerase, S-adenosylmethionine synthase and cysteine synthase were down-regulated in Xinluzao26. This work represents the first characterization of proteomic changes that occur in response to drought in roots of cotton plants. These differentially expressed proteins may be related to

  13. Regional to global changes in drought and implications for future changes under global warming

    Sheffield, J.; Wood, E. F.; Kam, J.


    Drought can have large impacts on multiple sectors, including agriculture, water resources, ecosystems, transport, industry and tourism. In extreme cases, regional drought can lead to food insecurity and famine, and in intensive agricultural regions, extend to global economic impacts in a connected world. Recent droughts globally have been severe and costly but whether they are becoming more frequent and severe, and the attribution of this, is a key question. Observational evidence at large scales, such as satellite remote sensing are often subject to short-term records and inhomogeneities, and ground based data are sparse in many regions. Reliance on model output is also subject to error and simplifications in the model physics that can, for example, amplify the impact of global warming on drought. This presentation will show the observational and model evidence for changes in drought, with a focus on the interplay between precipitation and atmospheric evaporative demand and its impact on the terrestrial water cycle and drought. We discuss the fidelity of climate models to reproduce our best estimates of drought variability and its drivers historically, and the implications of this on uncertainties in future projections of drought from CMIP5 models, and how this has changed since CMIP3.

  14. Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

    Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun


    It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite