Modelling crop yield in Iberia under drought conditions

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

2017-04-01

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

Developing drought impact functions for drought risk management

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S. Bachmair

2017-11-01

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

Extreme Water Deficit in Brazil Detected from Space

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Vieira Getirana

2016-01-01

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.

Socioeconomic Drought in a Changing Climate: Modeling and Management

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AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid

2016-04-01

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

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

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

2018-04-01

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

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

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

2017-03-01

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.

A hybrid spatiotemporal drought forecasting model for operational use

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Vasiliades, L.; Loukas, A.

2010-09-01

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.

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

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Vânia Rosa Pereira

2017-12-01

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.

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

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

2015-03-01

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

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

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H. Shen

2015-05-01

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.

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

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W. Liu

2018-03-01

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

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

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

2015-12-01

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

The Gaussian copula model for the joint deficit index for droughts

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

2018-06-01

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.

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

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

2018-04-01

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.

Spatiotemporal Drought Analysis and Drought Indices Comparison in India

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Janardhanan, A.

2017-12-01

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.

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

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

2014-12-01

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.

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

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H. J. De Boeck

2011-05-01

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.

Phenotyping common beans for adaptation to drought

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

2013-01-01

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

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

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

2014-05-01

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 (www.geo.uio.no/edc/droughtdb/). 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

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

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

2010-01-01

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,

Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

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A. C. S. Silva

2015-06-01

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.

Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

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Silva, A. C. S.; Galvão, C. O.; Silva, G. N. S.

2015-06-01

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.

Comparative metabolomics of drought acclimation in model and forage legumes.

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

2012-01-01

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.

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

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

2015-07-01

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

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

NARCIS (Netherlands)

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

2012-01-01

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

CreativeDrought: An interdisciplinary approach to building resilience to drought

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

2017-04-01

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

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

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Aryal, Y.; Zhu, J.

2015-12-01

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

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

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

2017-12-01

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.

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

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

2015-12-01

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.

Nonparametric Integrated Agrometeorological Drought Monitoring: Model Development and Application

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

2018-01-01

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.

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

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Miao Tian

2016-08-01

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.

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

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

2016-07-01

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

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

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

2017-10-01

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.

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

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B. Orlowsky

2013-05-01

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

Future Drought Projections over the Iberian Peninsula using Drought Indices

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

2017-12-01

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

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

Science.gov (United States)

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

2015-12-01

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.

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

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

2009-04-01

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

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

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

2013-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Guentner, A

2002-09-01

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.)

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

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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

2018-01-01

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.

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

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

2017-12-01

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.

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

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

2016-12-01

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.

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

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

2017-12-01

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

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

Directory of Open Access Journals (Sweden)

Shoaib Ahmed

2013-12-01

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.

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

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

2008-12-01

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.

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

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

2016-04-01

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.

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

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

2017-12-01

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

Projected Changes in Evapotranspiration Rates over Northeast Brazil

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Costa, Alexandre; Guimarães, Sullyandro; Vasconcelos, Francisco, Jr.; Sales, Domingo; da Silva, Emerson

2015-04-01

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.

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

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

2018-03-01

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.

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

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

2012-06-01

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.

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

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

2015-12-01

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

The Prediction of Drought-Related Tree Mortality in Vegetation Models

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

2013-12-01

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.

Measuring the invisible: Analysis of the Sustainable Development Goals in relation to populations exposed to drought.

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Sena, Aderita; de Freitas, Carlos Machado; Barcellos, Christovam; Ramalho, Walter; Corvalan, Carlos

2016-03-01

Brazil, together with all the member countries of the United Nations, is in a process of adoption of a group of Sustainable Development Goals, including targets and indicators. This article considers the implications of these goals and their proposed targets, for the Semi-Arid region of Brazil. This region has recurring droughts which may worsen with climate change, further weakening the situation of access of water for human consumption in sufficient quantity and quality, and as a result, the health conditions of the exposed populations. This study identifies the relationship between drought and health, in an effort to measure progress in this region (1,135 municipalities), comparing relevant indicators with the other 4,430 municipalities in Brazil, based on census data from 1991, 2000 and 2010. Important inequalities between the municipalities of this region and the municipalities of the rest of Brazil are identified, and discussed in the context of what is necessary for achieving the Sustainable Development Goals in the Semi-arid Region, principally in relation to the measures for adaptation to achieve universal and equitable access to drinking water.

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

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

2017-04-01

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?

How 21st century droughts affect food and environmental security

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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.

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

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Mingzhi Yang

2017-09-01

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.

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

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

2017-04-01

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

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

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

2018-01-01

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

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

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

2017-04-01

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.

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

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

2012-12-01

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.

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

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Z. Y. Wu

2011-09-01

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

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

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

2017-12-01

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.

The bioeconomic implications of various drought management ...

African Journals Online (AJOL)

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 ...

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

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Benoit ePallas

2013-11-01

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.

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

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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.

2016-09-01

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.

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

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Hyunwoo Kang

2017-08-01

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.

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

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Jiansheng Wu

2017-05-01

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.

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

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J. Paredes-Arquiola

2016-10-01

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.

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

Science.gov (United States)

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

2012-04-01

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.

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

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

2017-12-01

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

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

Science.gov (United States)

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

2015-12-01

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.

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

Science.gov (United States)

Kurniasih, E.; Impron; Perdinan

2017-03-01

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.

Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

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F. Fundel

2013-01-01

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

Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

Science.gov (United States)

Fundel, F.; Jörg-Hess, S.; Zappa, M.

2013-01-01

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.

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

Science.gov (United States)

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

2018-05-01

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: goo.gl/HDRMYN (El-Nino 2015 episode) and goo.gl/g1sXPl (La-Nina 2016 episode). The model is available at: goo.gl/RiuMQz.

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

Science.gov (United States)

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

2015-12-01

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

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

Directory of Open Access Journals (Sweden)

Hossein Hosseinpour Niknam

2012-07-01

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.

Application of Dynamic naïve Bayesian classifier to comprehensive drought assessment

Science.gov (United States)

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

2017-12-01

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.

Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results

Science.gov (United States)

Tadesse, Tsegaye; Champagne, Catherine; Wardlow, Brian D.; Hadwen, Trevor A.; Brown, Jesslyn; Demisse, Getachew B.; Bayissa, Yared A.; Davidson, Andrew M.

2017-01-01

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

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

Science.gov (United States)

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

2015-12-01

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.

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

Science.gov (United States)

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

2010-12-01

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 (http://hydrology.princeton.edu/monitor). 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

Drought impact on vegetation growth and mortality

Science.gov (United States)

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

2017-12-01

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

Description of future drought indices in Virginia

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Hyunwoo Kang

2017-10-01

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.

The Temporospatial Variations and Propagation of Drought in China

Science.gov (United States)

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

2017-12-01

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.

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

Directory of Open Access Journals (Sweden)

Lei Zou

2018-03-01

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.

Drought variability in six catchments in the UK

Science.gov (United States)

Kwok-Pan, Chun; Onof, Christian; Wheater, Howard

2010-05-01

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.

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

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

2016-09-01

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

Civil conflict sensitivity to growing-season drought

OpenAIRE

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

2016-01-01

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...

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

NARCIS (Netherlands)

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

2008-01-01

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

Importance of soil-water to the Caatinga biome, Brazil

NARCIS (Netherlands)

Alves Rodrigues Pinheiro, Everton; Metselaar, Klaas; Jong van Lier, de Quirijn; Araújo, de José Carlos

2016-01-01

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

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

Science.gov (United States)

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

2013-12-01

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

Drought as a natural disaster

Energy Technology Data Exchange (ETDEWEB)

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)

1995-12-31

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.

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

Science.gov (United States)

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

2015-12-01

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

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

Science.gov (United States)

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

2018-02-20

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.

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

Science.gov (United States)

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

2015-08-01

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.

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

Science.gov (United States)

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

2017-08-30

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.

A hot future for European droughts

Science.gov (United States)

Teuling, Adriaan J.

2018-05-01

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.

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

Science.gov (United States)

Lee, Chieh-Han; Yu, Hwa-Lung

2015-04-01

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.

How climate seasonality modifies drought duration and deficit

NARCIS (Netherlands)

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

2014-01-01

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

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

African Journals Online (AJOL)

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:.

ASSESSING URBAN DROUGHTS IN A SMART CITY FRAMEWORK

Directory of Open Access Journals (Sweden)

R. Obringer

2016-06-01

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.

Drought, Agriculture, and Labor: Understanding Drought Impacts and Vulnerability in California

Science.gov (United States)

Greene, C.

2015-12-01

Hazardous drought impacts are a product of not only the physical intensity of drought, but also the economic, social, and environmental characteristics of the region exposed to drought. Drought risk management requires understanding the complex links between the physical and human dimensions of drought. Yet, there is a research gap in identifying and explaining the socio-economic complexities of drought in the context of the first world, especially for economic and socially marginal groups who rely on seasonal and temporary jobs. This research uses the current drought in California as a case study to identify the socioeconomic impacts of drought on farmworker communities in California's San Joaquin Valley, with a specific focus on the relationship between drought and agricultural labor. Through both a narrative analysis of drought coverage in newspaper media, drought policy documents, and interviews with farmworkers, farmers, community based organizations, and government officials in the San Joaquin Valley, this research aims to highlight the different understandings and experiences of the human impacts of drought and drought vulnerability in order to better inform drought risk planning and policy.

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

Science.gov (United States)

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

2017-09-01

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.

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

Directory of Open Access Journals (Sweden)

Ellen E. Pflug

2018-02-01

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

Seasonal UK Drought Forecasting using Statistical Methods

Science.gov (United States)

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

2016-04-01

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.

Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI)

Science.gov (United States)

Asadi Zarch, Mohammad Amin; Sivakumar, Bellie; Sharma, Ashish

2015-07-01

Both drought and aridity indicate imbalance in water availability. While drought is a natural temporal hazard, aridity is a constant climatic feature. This paper investigates the changes in drought characteristics across different aridity zones with and without consideration of potential evapotranspiration (PET), as a means to better assess drought in a warming climate. Two drought indexes are employed: (1) Standardized precipitation index (SPI), which is solely based on precipitation; and (2) Reconnaissance drought index (RDI), which, in addition to precipitation, takes PET into account. The two indexes are first employed to observed precipitation and PET data for the period 1960-2009 from the CRU (Climate Research Unit, University of East Anglia) TS 3.1 database. The results indicate that although all the aridity zones experience both downward and upward drought trends, no significant trend is found over large parts of the zones. However, the agreement between SPI and RDI reduces from the hyper-arid zone on one extreme toward the humid zone on the other. In the three more humid zones (i.e. semi-arid, sub-humid, and humid), the indexes exhibit different trends, with RDI showing more decreasing trends (i.e. becoming drier). While SPI generally shows more drought prone areas than RDI for the pre-1998 period, the opposite is observed for the post-1998 period. Given the known changes to PET in observed records, and also expected increases as global warming intensifies, these results suggest that RDI will be consistently different to the SPI as global warming intensifies. This hypothesis is further tested for historic and future climate projections from the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia) Mk3.6 global climate model (GCM), with use of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and RCP8.5 (Representative Concentration Pathways). In this case, PET is calculated using FAO56-PM model for assessment of

Cross-sectional Integration of the Water-energy Nexus in Brazil

Directory of Open Access Journals (Sweden)

Theodoros Semertzidis

2018-03-01

Full Text Available This paper analyses the cross-sectoral integration of the water-energy nexus in Brazil. Recent droughts resulted in unprecedented water scarcity. This caused water shortages for population and agriculture, as well as for electricity production (hydropower being the main source of electricity production. As a result, the system became more vulnerable to blackouts. To alleviate the problem, fossil fuels were used as a back up. Droughts, floods and other water-related problems will not dissipate as time goes by in Brazil. The dependency on one single predominant source (hydropower makes Brazil’s electricity supply vulnerable. This study shows through data analysis, flow diagrams and metrics the interrelation between water and energy. Based on historical data, the analysis shows the importance of the water demand for hydropower, cooling for thermal plants, and the extraction and production of biofuels, as well as of the energy demand of water services (water supply, wastewater treatment.

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

Science.gov (United States)

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

2013-05-01

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.

A component-based system for agricultural drought monitoring by remote sensing.

Science.gov (United States)

Dong, Heng; Li, Jun; Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

Drought occurence

Science.gov (United States)

John W. Coulston

2007-01-01

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...

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

Science.gov (United States)

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

2016-12-01

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.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

Science.gov (United States)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

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 drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Anthropogenic warming exacerbates European soil moisture droughts

Science.gov (United States)

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

2018-05-01

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.

Proteomic responses of drought-tolerant and drought-sensitive cotton varieties to drought stress.

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Zhang, Haiyan; Ni, Zhiyong; Chen, Quanjia; Guo, Zhongjun; Gao, Wenwei; Su, Xiujuan; Qu, Yanying

2016-06-01

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

Agricultural Productivity Forecasts for Improved Drought Monitoring

Science.gov (United States)

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

2010-01-01

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

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

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mehdi Komasi

2013-08-01

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.

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

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

2017-12-01

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.

A geospatial suitability model for drought-tolerant switchgrass

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Lewis, S. M.; Kelly, M.

2011-12-01

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.

Spatiotemporal variation of long-term drought propensity through reliability-resilience-vulnerability based Drought Management Index

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Chanda, Kironmala; Maity, Rajib; Sharma, Ashish; Mehrotra, Rajeshwar

2014-10-01

This paper characterizes the long-term, spatiotemporal variation of drought propensity through a newly proposed, namely Drought Management Index (DMI), and explores its predictability in order to assess the future drought propensity and adapt drought management policies for a location. The DMI was developed using the reliability-resilience-vulnerability (RRV) rationale commonly used in water resources systems analysis, under the assumption that depletion of soil moisture across a vertical soil column is equivalent to the operation of a water supply reservoir, and that drought should be managed not simply using a measure of system reliability, but should also take into account the readiness of the system to bounce back from drought to a normal state. Considering India as a test bed, 5 year long monthly gridded (0.5° Lat × 0.5° Lon) soil moisture data are used to compute the RRV at each grid location falling within the study domain. The Permanent Wilting Point (PWP) is used as the threshold, indicative of transition into water stress. The association between resilience and vulnerability is then characterized through their joint probability distribution ascertained using Plackett copula models for four broad soil types across India. The joint cumulative distribution functions (CDF) of resilience and vulnerability form the basis for estimating the DMI as a five-yearly time series at each grid location assessed. The status of DMI over the past 50 years indicate that drought propensity is consistently low toward northern and north eastern parts of India but higher in the western part of peninsular India. Based on the observed past behavior of DMI series on a climatological time scale, a DMI prediction model comprising deterministic and stochastic components is developed. The predictability of DMI for a lead time of 5 years is found to vary across India, with a Pearson correlation coefficient between observed and predicted DMI above 0.6 over most of the study area

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

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

2013-02-01

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.

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

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

2015-12-01

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, calforests.org 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.

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

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

2014-05-01

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

A component-based system for agricultural drought monitoring by remote sensing.

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Heng Dong

Full Text Available In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

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

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Tinard Pierre

2016-01-01

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.

Adverse effects of increasing drought on air quality via natural processes

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Wang, Yuxuan; Xie, Yuanyu; Dong, Wenhao; Ming, Yi; Wang, Jun; Shen, Lu

2017-10-01

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.

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

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

2014-12-01

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.

Model based climate information on drought risk in Africa

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

2012-04-01

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

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

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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.

2017-12-01

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

Indicators to measure risk of disaster associated with drought: Implications for the health sector.

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Aderita Sena

Full Text Available Brazil has a large semiarid region, which covers part of 9 states, over 20% of the 5565 municipalities in the country and at 22.5 million persons, 12% of the country's population. This region experiences recurrent and extended droughts and is characterized by low economic development, scarcity of natural resources including water, and difficult agricultural and livestock production. Local governments and communities need easily obtainable tools to aid their decision making process in managing risks associated with drought.To inform decision-making at the level of municipalities, we investigated factors contributing to the health risks of drought. We used education and poverty indicators to measure vulnerability, number of drought damage evaluations and historical drought occurrences as indicators of hazard, and access to water as an indicator of exposure, to derive a drought disaster risk index.Indicators such as access to piped water, illiteracy and poverty show marked differences in most states and, in nearly all states, the living conditions of communities in the semiarid region are worse than in the rest of each state. There are municipalities at high drought disaster risk in every state and there are a larger number of municipalities at higher risks from the center to the north of the semiarid region.Understanding local hazards, exposures and vulnerabilities provides the means to understand local communities' risks and develop interventions to reduce them. In addition, communities in these regions need to be empowered to add their traditional knowledge to scientific tools, and to identify the actions most relevant to their needs and realities.

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

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Keshavarz, Marzieh; Karami, Ezatollah

2013-09-30

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.

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

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

2014-12-01

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

DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA

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J. Rhee

2016-06-01

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.

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

Energy Technology Data Exchange (ETDEWEB)

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)

2016-02-16

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.

Financial Risk Reduction and Management of Water Reservoirs Using Forecasts: A Case for Pernambuco, Brazil

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Kumar, I.; Josset, L.; e Silva, E. C.; Possas, J. M. C.; Asfora, M. C.; Lall, U.

2017-12-01

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

Using Enhanced Grace Water Storage Data to Improve Drought Detection by the U.S. and North American Drought Monitors

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Houborg, Rasmus; Rodell, Matthew; Lawrimore, Jay; Li, Bailing; Reichle, Rolf; Heim, Richard; Rosencrans, Matthew; Tinker, Rich; Famiglietti, James S.; Svoboda, Mark;

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

Science.gov (United States)

Medina, I. D.; Denning, S.

2014-12-01

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

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

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

2017-09-01

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.

Toward Seasonal Forecasting of Global Droughts: Evaluation over USA and Africa

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Wood, Eric; Yuan, Xing; Roundy, Joshua; Sheffield, Justin; Pan, Ming

2013-04-01

Extreme hydrologic events in the form of droughts are significant sources of social and economic damage. In the United States according to the National Climatic Data Center, the losses from drought exceed US210 billion during 1980-2011, and account for about 24% of all losses from major weather disasters. Internationally, especially for the developing world, drought has had devastating impacts on local populations through food insecurity and famine. Providing reliable drought forecasts with sufficient early warning will help the governments to move from the management of drought crises to the management of drought risk. After working on drought monitoring and forecasting over the USA for over 10 years, the Princeton land surface hydrology group is now developing a global drought monitoring and forecasting system using a dynamical seasonal climate-hydrologic LSM-model (CHM) approach. Currently there is an active debate on the merits of the CHM-based seasonal hydrologic forecasts as compared to Ensemble Streamflow Prediction (ESP). We use NCEP's operational forecast system, the Climate Forecast System version 2 (CFSv2) and its previous version CFSv1, to investigate the value of seasonal climate model forecasts by conducting a set of 27-year seasonal hydrologic hindcasts over the USA. Through Bayesian downscaling, climate models have higher squared correlation (R2) and smaller error than ESP for monthly precipitation averaged over major river basins across the USA, and the forecasts conditional on ENSO show further improvements (out to four months) over river basins in the southern USA. All three approaches have plausible predictions of soil moisture drought frequency over central USA out to six months because of strong soil moisture memory, and seasonal climate models provide better results over central and eastern USA. The R2 of drought extent is higher for arid basins and for the forecasts initiated during dry seasons, but significant improvements from CFSv2 occur

Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast

Directory of Open Access Journals (Sweden)

Junfei Chen

2012-01-01

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.

Exploring the linkage between drought, high temperatures, and hydrologic sensitivities: A case study of the 2012 Great Plains drought.

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Livneh, B.; Hoerling, M. P.

2014-12-01

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

Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

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Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

2012-12-01

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 http://hydrology.princeton.edu/~nchaney/ADM_ML). 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 (http://hydrology.princeton.edu/forecasting) 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

Application of Physically based landslide susceptibility models in Brazil

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Carvalho Vieira, Bianca; Martins, Tiago D.

2017-04-01

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

A global evaluation of streamflow drought characteristics

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A. K. Fleig

2006-01-01

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

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

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

2012-12-01

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

Anthropogenic climate change affects meteorological drought risk in Europe

International Nuclear Information System (INIS)

Gudmundsson, L; Seneviratne, S I

2016-01-01

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)

Spatio-temporal drought characteristics of the tropical Paraiba do Sul River Basin and responses to the Mega Drought in 2014-2016

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Nauditt, Alexandra; Metzke, Daniel; Ribbe, Lars

2017-04-01

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

Spatial patterns of drought persistence in East China

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Meng, L.; Ford, T.

2017-12-01

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.

Projected climatic changes on drought conditions over Spain

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García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

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).

a New Framework for Characterising Simulated Droughts for Future Climates

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Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

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

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

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

2015-03-01

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.

Blended Drought Index: Integrated Drought Hazard Assessment in the Cuvelai-Basin

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Robert Luetkemeier

2017-07-01

Full Text Available Drought is one of the major threats to societies in Sub-Saharan Africa, as the majority of the population highly depends on rain-fed subsistence agriculture and traditional water supply systems. Hot-spot areas of potential drought impact need to be identified to reduce risk and adapt a growing population to a changing environment. This paper presents the Blended Drought Index (BDI, an integrated tool for estimating the impact of drought as a climate-induced hazard in the semi-arid Cuvelai-Basin of Angola and Namibia. It incorporates meteorological and agricultural drought characteristics that impair the population’s ability to ensure food and water security. The BDI uses a copula function to combine common standardized drought indicators that describe precipitation, evapotranspiration, soil moisture and vegetation conditions. Satellite remote sensing products were processed to analyze drought frequency, severity and duration. As the primary result, an integrated drought hazard map was built to spatially depict drought hot-spots. Temporally, the BDI correlates well with millet/sorghum yield (r = 0.51 and local water consumption (r = −0.45 and outperforms conventional indicators. In the light of a drought’s multifaceted impact on society, the BDI is a simple and transferable tool to identify areas highly threatened by drought in an integrated manner.

The effect of severe drought and management after drought on the ...

African Journals Online (AJOL)

The False Thornveld of the Eastern Cape experienced a particularly intense drought during the 1982/1983 growing season. Extensive grass mortality took place during the drought. After the drought, recovery was particularly sensitive to the post-drought management treatment applied. Veld that was grazed immediately ...

Comprehensive Analysis of Drought Persistence, Hazard, and Recovery across the CONUS

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Zarekarizi, M.; Ahmadi, B.; Moradkhani, H.

2017-12-01

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.

Brief communication: Drought likelihood for East Africa

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H. Yang

2018-02-01

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.

Brief communication: Drought likelihood for East Africa

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Yang, Hui; Huntingford, Chris

2018-02-01

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.

Plant hydraulic diversity buffers forest ecosystem responses to drought

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Anderegg, W.; Konings, A. G.; Trugman, A. T.; Pacala, S. W.; Yu, K.; Sulman, B. N.; Sperry, J.; Bowling, D. R.

2017-12-01

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.

Comparative proteome analysis of drought-sensitive and drought-tolerant rapeseed roots and their hybrid F1 line under drought stress.

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Mohammadi, Payam Pour; Moieni, Ahmad; Komatsu, Setsuko

2012-11-01

Rapeseed (Brassica napus L.), which is the third leading source of vegetable oil, is sensitive to drought stress during the early vegetative growth stage. To investigate the initial response of rapeseed to drought stress, changes in the protein expression profiles of drought-sensitive (RGS-003) and drought-tolerant lines (SLM-003), and their F1 hybrid, were analyzed using a proteomics approach. Seven-day-old rapeseed seedlings were treated with drought stress by restricting water for 7 days, and proteins were extracted from roots and separated by two-dimensional polyacrylamide gel electrophoresis. In the sensitive rapeseed line, 35 protein spots were differentially expressed under drought stress, and proteins related to metabolism, energy, disease/defense, and transport were decreased. In the tolerant line, 32 protein spots were differentially expressed under drought stress, and proteins involved in metabolism, disease/defense, and transport were increased, while energy-related proteins were decreased. Six protein spots in F1 hybrid were common among expressed proteins in the drought-sensitive and -tolerant lines. Notably, tubulin beta-2 and heat shock protein 70 were decreased in the drought-sensitive line and hybrid F1 plants, while jasmonate-inducible protein and 20S proteasome subunit PAF1 were increased in the F1 hybrids and drought-tolerant line. These results indicate that (1) V-type H(+) ATPase, plasma-membrane associated cation-binding protein, HSP 90, and elongation factor EF-2 have a role in the drought tolerance of rapeseed; (2) The decreased levels of heat shock protein 70 and tubulin beta-2 in the drought-sensitive and hybrid F1 lines might explain the reduced growth of these lines in drought conditions.

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

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Fei Yuan

2016-01-01

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.

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

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

2017-04-01

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.

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

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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.

2017-12-01

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

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

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

2018-02-01

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.

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

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Alvaro Sordo-Ward

2017-11-01

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

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

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Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

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).

Drought analysis and short-term forecast in the Aison River Basin (Greece

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S. Kavalieratou

2012-05-01

Full Text Available A combined regional drought analysis and forecast is elaborated and applied to the Aison River Basin (Greece. The historical frequency, duration and severity were estimated using the standardized precipitation index (SPI computed on variable time scales, while short-term drought forecast was investigated by means of 3-D loglinear models. A quasi-association model with homogenous diagonal effect was proposed to fit the observed frequencies of class transitions of the SPI values computed on the 12-month time scale. Then, an adapted submodel was selected for each data set through the backward elimination method. The analysis and forecast of the drought class transition probabilities were based on the odds of the expected frequencies, estimated by these submodels, and the respective confidence intervals of these odds. The parsimonious forecast models fitted adequately the observed data. Results gave a comprehensive insight on drought behavior, highlighting a dominant drought period (1988–1991 with extreme drought events and revealing, in most cases, smooth drought class transitions. The proposed approach can be an efficient tool in regional water resources management and short-term drought warning, especially in irrigated districts.

Linking meteorological drivers of spring-summer drought regimes to agricultural drought risk in China

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Dai, L.; Wright, J. S.; Yu, C.; Huang, W. Y.

2017-12-01

As a drought prone country, China has experienced frequent severe droughts in recent decades. Drought frequency and severity are projected to increase in China under climate change. An understanding of the physical processes that contribute to extreme droughts is essential for seasonal forecasting, but the dominant physical mechanisms responsible for droughts in most parts of China are still unclear. Moreover, despite numerous studies on droughts in China, there are few clear connections between the meteorological and climatological drivers of extreme droughts and the associated agricultural consequences. This knowledge gap limits the capacity for decision-making support in drought management. The objectives of this study are (1) to identify robust spring-summer drought regimes over China, (2) to investigate the physical mechanisms associated with each regime, and (3) to better clarify connections between meteorological drought regimes and agricultural drought risk. First, we identify six drought regimes over China by applying an area-weighted k-means clustering technique to spatial patterns of spring-summer Standardized Precipitation Index (SPI) obtained from the ten-member ERA-20CM ensemble for 1900-2010. Second, we project these drought regimes onto agricultural drought risk maps for the three major cereal crops (rice, maize, and wheat) in China. Taking into account historical harvest areas for these crops, we then evaluate the potential impact of each drought regime on agricultural production. Third, the physical mechanisms and meteorological context behind each drought regimes are investigated based on monthly outputs from ERA20CM. We analyze the preceding and concurrent atmospheric circulation anomalies associated with each regime, and propose mechanistic explanations for drought development. This work provides a new perspective on diagnosing the physical mechanisms behind seasonal droughts, and lays a foundation for improving seasonal drought prediction and

GRACE-Assimilated Drought Indicators for the U.S. Drought Monitor

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Rui, Hualan; Vollmer, Bruce; Teng, Bill; Loeser, Carlee; Beaudoing, Hiroko; Rodell, Matt

2018-01-01

The Gravity Recovery and Climate Experiment (GRACE) mission detects changes in Earth's gravity field by precisely monitoring the changes in distance between two satellites orbiting the Earth in tandem. Scientists at NASA's Goddard Space Flight Center generate GRACE-assimilated groundwater and soil moisture drought indicators each week, for drought monitor-related studies and applications. The GRACE-assimilated Drought Indicator Version 2.0 data product (GRACE-DA-DM V2.0) is archived at, and distributed by, the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center). More information about the data and data access is available on the data product landing page at https://disc.gsfc.nasa.gov/datasets /GRACEDADM_CLSM0125US_7D_2.0/summary. The GRACE-DA-DM V2.0 data product contains three drought indicators: Groundwater Percentile, Root Zone Soil Moisture Percentile, and Surface Soil Moisture Percentile. The drought indicators are of wet or dry conditions, expressed as a percentile, indicating the probability of occurrence within the period of record from 1948 to 2012. These GRACE-assimilated drought indicators, with improved spatial and temporal resolutions, should provide a more comprehensive and objective identification of drought conditions. This presentation describes the basic characteristics of the data and data services at NASA GES DISC and collaborative organizations, and uses a few examples to demonstrate the simple ways to explore the GRACE-assimilated drought indicator data.

Information Mining from Heterogeneous Data Sources: A Case Study on Drought Predictions

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Getachew B. Demisse

2017-07-01

Full Text Available The objective of this study was to develop information mining methodology for drought modeling and predictions using historical records of climate, satellite, environmental, and oceanic data. The classification and regression tree (CART approach was used for extracting drought episodes at different time-lag prediction intervals. Using the CART approach, a number of successful model trees were constructed, which can easily be interpreted and used by decision makers in their drought management decisions. The regression rules produced by CART were found to have correlation coefficients from 0.71–0.95 in rules-alone modeling. The accuracies of the models were found to be higher in the instance and rules model (0.77–0.96 compared to the rules-alone model. From the experimental analysis, it was concluded that different combinations of the nearest neighbor and committee models significantly increase the performances of CART drought models. For more robust results from the developed methodology, it is recommended that future research focus on selecting relevant attributes for slow-onset drought episode identification and prediction.

Improved tolerance to post-anthesis drought stress by pre-drought priming at vegetative stages in drought-tolerant and -sensitive wheat cultivars.

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Abid, Muhammad; Tian, Zhongwei; Ata-Ul-Karim, Syed Tahir; Liu, Yang; Cui, Yakun; Zahoor, Rizwan; Jiang, Dong; Dai, Tingbo

2016-09-01

Wheat crop endures a considerable penalty of yield reduction to escape the drought events during post-anthesis period. Drought priming under a pre-drought stress can enhance the crop potential to tolerate the subsequent drought stress by triggering a faster and stronger defense mechanism. Towards these understandings, a set of controlled moderate drought stress at 55-60% field capacity (FC) was developed to prime the plants of two wheat cultivars namely Luhan-7 (drought tolerant) and Yangmai-16 (drought sensitive) during tillering (Feekes 2 stage) and jointing (Feekes 6 stage), respectively. The comparative response of primed and non-primed plants, cultivars and priming stages was evaluated by applying a subsequent severe drought stress at 7 days after anthesis. The results showed that primed plants of both cultivars showed higher potential to tolerate the post-anthesis drought stress through improved leaf water potential, more chlorophyll, and ribulose-1, 5-bisphosphate carboxylase/oxygenase contents, enhanced photosynthesis, better photoprotection and efficient enzymatic antioxidant system leading to less yield reductions. The primed plants of Luhan-7 showed higher capability to adapt the drought stress events than Yangmai-16. The positive effects of drought priming to sustain higher grain yield were pronounced in plants primed at tillering than those primed at jointing. In consequence, upregulated functioning of photosynthetic apparatus and efficient enzymatic antioxidant activities in primed plants indicated their superior potential to alleviate a subsequently occurring drought stress, which contributed to lower yield reductions than non-primed plants. However, genotypic and priming stages differences in response to drought stress also contributed to affect the capability of primed plants to tolerate the post-anthesis drought stress conditions in wheat. Copyright © 2016. Published by Elsevier Masson SAS.

AgMIP Regional Activities in a Global Framework: The Brazil Experience

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Assad, Eduardo D.; Marin, Fabio R.; Valdivia, Roberto O.; Rosenzweig, Cynthia E.

2012-01-01

Climate variability and change are projected to increate the frequency of extreme high-temperature events, floods, and droughts, which can lead to subsequent changes in soil moister in many locations (Alexandrov and Hoogenboom, 2000). In Brazil, observations reveal a tendency for increasing frequency of extreme rainfall events particularly in south Brazil (Alexander et al., 2006; Carvalho et al., 2014; Groissman et al., 2005), as well as projections for increasing extremes in both maximum and minimum temperatures and high spatial variability for rainfall under the IPCC SRES A2 and B2 scenarios (Marengo et al., 2009).

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

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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.

2017-12-01

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

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

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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

2015-01-01

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...

Contribution of Temperature to Chilean Droughts Using Ensemble Climate Projections

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Zambrano-Bigiarini, M.; Alfieri, L.; Naumann, G.; Garreaud, R. D.

2017-12-01

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

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

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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

2017-11-03

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.

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

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A. B. M. Firoz

2018-01-01

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

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

Science.gov (United States)

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

2018-01-01

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.

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

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John D. Shaw

2008-01-01

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...

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

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Aghakouchak, Amir; Tourian, Mohammad J.

2015-04-01

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

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

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

2011-03-01

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.

Impacts of drought on grape yields in Western Cape, South Africa

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Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier

2016-01-01

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

Characterization of future drought conditions in the Lower Mekong River Basin

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Madusanka Thilakarathne

2017-09-01

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.

Spatial differences in drought vulnerability

Science.gov (United States)

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

2012-04-01

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.

The current California drought through EDDI's eyes: early warning and monitoring of agricultural and hydrologic drought with the new Evaporative Demand Drought Index.

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Hobbins, M.; McEvoy, D.; Huntington, J. L.; Wood, A. W.; Morton, C.; Verdin, J. P.

2015-12-01

We have developed a physically based, multi-scalar drought index—the Evaporative Demand Drought Index (EDDI)—to improve treatment of evaporative dynamics in drought monitoring. Existing popular drought indices—such as the Palmer Drought Severity Index that informs much of the US Drought Monitor (USDM)—have primarily relyied on precipitation and temperature (T) to represent hydroclimatic anomalies, leaving evaporative demand (E0) most often derived from poorly performing T-based parameterizations then used to derive actual evapotranspiration (ET) from LSMs. Instead, EDDI leverages the inter-relations of E0 and ET, measuring E0's physical response to surface drying anomalies due to two distinct land surface/atmosphere interactions: (i) in sustained drought, limited moisture availability forces E0 and ET into a complementary relation, whereby ET declines as E0 increases; and (ii) in "flash" droughts, E0 increases due to increasing advection or radiation. E0's rise in response to both drought types suggests EDDI's robustness as a monitor and leading indicator of drought. To drive EDDI, we use for E0 daily reference ET from the ASCE Standardized Reference ET equation forced by North American Land Data Assimilation System drivers. EDDI is derived by aggregating E0 anomalies from its long-term mean across a period of interest and normalizing them to a Z-score. Positive EDDI indicates drier than normal conditions (and so drought). We use the current historic California drought as a test-case in which to examine EDDI's performance in monitoring agricultural and hydrologic drought. We observe drought development and decompose the behavior of drought's evaporative drivers during in-drought intensification periods and wetting events. EDDI's performance as a drought leading indicator with respect to the USDM is tested in important agricultural regions. Comparing streamflow from several USGS gauges in the Sierra Nevada to EDDI, we find that EDDI tracks most major

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

African Journals Online (AJOL)

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 ...

A new multi-sensor integrated index for drought monitoring

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

2017-12-01

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

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

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

2017-12-01

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.

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

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

2017-01-01

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.

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

Directory of Open Access Journals (Sweden)

Adama Ndour

2017-09-01

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.

Temporal Changes in Community Resilience to Drought Hazard

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Mihunov, V.

2017-12-01

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.

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

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Norton, M.

2015-12-01

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.

Potential role of vegetation dynamics on recent extreme droughts over tropical South America

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Wang, G.; Erfanian, A.; Fomenko, L.

2017-12-01

Tropical South America is a drought hot spot. In slightly over a decade (2005-2016), the region encountered three extreme droughts (2005, 2010, and 2016). Recurrent extreme droughts not only impact the region's eco-hydrology and socio-economy, but are also globally important as they can transform the planet's largest rainforest, the Amazon, from a carbon sink to a carbon source. Understanding drought drivers and mechanisms underlying extreme droughts in tropical South America can help better project the fate of the Amazon rainforest in a changing climate. In this study we use a regional climate model (RegCM4.3.4) coupled with a comprehensive land-surface model (CLM4.5) to study the present-day hydroclimate of the region, focusing specifically on what might have caused the frequent recurrence of extreme droughts. In the context of observation natural variability of the global oceanic forcing, we tackle the role of land-atmosphere interactions and ran the model with and without dynamic vegetation to study how vegetation dynamics and carbon-nitrogen cycles may have influenced the drought characteristics. Our results demonstrate skillful simulation of the South American climate in the model, and indicate substantial sensitivity of the region's hydroclimatology to vegetation dynamics. This presentation will compare the role of global oceanic forcing versus regional land surface feedback in the recent recurrent droughts, and will characterize the effects of vegetation dynamics in enhancing the drought severity. Preliminary results on future projections of the regional ecosystem and droughts perspective will be also presented.

Regional to global changes in drought and implications for future changes under global warming

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Sheffield, J.; Wood, E. F.; Kam, J.

2012-12-01

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.

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

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

2013-01-01

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.

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

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Eric J Gustafson; Brian R. Sturtevant

2013-01-01

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...

Civil conflict sensitivity to growing-season drought.

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

2016-11-01

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.

Integrating effective drought index (EDI) and remote sensing derived parameters for agricultural drought assessment and prediction in Bundelkhand region of India

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Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.

2014-11-01

Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product

Assessing changes in drought characteristics with standardized indices

Science.gov (United States)

Vidal, Jean-Philippe; Najac, Julien; Martin, Eric; Franchistéguy, Laurent; Soubeyroux, Jean-Michel

2010-05-01

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

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

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

1996-08-01

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.

Global patterns of drought recovery

Energy Technology Data Exchange (ETDEWEB)

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

2017-08-09

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.

Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast

OpenAIRE

Chen, Junfei; Li, Ming; Wang, Weiguang

2012-01-01

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 ...

Comparative Analysis of Drought Indices for Drought Zone Scheme of Northern Khorasan Province of Iran

Directory of Open Access Journals (Sweden)

Ehsan EYSHI REZAEI

2011-08-01

Full Text Available Drought is one of the natural disasters which deeply influenced agricultural production. Drought monitoring programs could help to forecast and mitigate the impacts of drought. In this study occurrence, severity, and duration of drought were evaluated by monthly rainfall data (1986-2005 that were recorded at all meteorological stations in north Khorasan province of Iran. Drought indices include Standard Rainfall Index (SPI, Decades Index (DI and Percent of Normal (PNI calculated and compared to determine drought severity, duration and drought occurrence for all stations. In addition, drought maps were prepared by Inverse Distance Weighted (IDW method, for each study zone. Based on these indices, the most extensive drought occurred in 1989, 1990, 1995, 1996, 2000, and 2001 years. The longest duration of drought based on SPI happened in 1994 and 1997 years. Furthermore, the extreme drought occurred in 1990 and 2001 in all stations. In conclusion, Central part of this province was more exposed to extreme drought during study period than other parts of this region.

Probabilistic estimates of drought impacts on agricultural production

Science.gov (United States)

Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J.

2017-08-01

Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980-2012, including the Millennium Drought in Australia (2001-2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25-45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

Drought Prediction for Socio-Cultural Stability Project

Science.gov (United States)

Peters-Lidard, Christa; Eylander, John B.; Koster, Randall; Narapusetty, Balachandrudu; Kumar, Sujay; Rodell, Matt; Bolten, John; Mocko, David; Walker, Gregory; Arsenault, Kristi;

An extended multivariate framework for drought monitoring in Mexico

Science.gov (United States)

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

2017-04-01

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.

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

Science.gov (United States)

McNellis, B.; Hudiburg, T. W.

2017-12-01

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.

Drought impacts and resilience on crops via evapotranspiration estimations

Science.gov (United States)

Timmermans, Joris; Asadollahi Dolatabad, Saeid

2015-04-01

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

Water scarcity under scenarios for global climate change and regional development in semiarid Northeastern Brazil

NARCIS (Netherlands)

de Araújo, José Carlos; Döll, Petra; Güntner, Andreas; Krol, Martinus S.; Rodrigues Abreu, Cláudia Beghini; Hauschild, Maike; Mendiondo, Eduardo Mario

2004-01-01

The State of Ceará, located in semiarid Northeastern Brazil, suffers under irregularly recurring droughts that go along with water scarcity. Structural policies to control and reduce water scarcity, as water supply and demand management, should be seen as long-term planning, and thus have to

Hydrological drought across the world: impact of climate and physical catchment structure

Directory of Open Access Journals (Sweden)

H. A. J. Van Lanen

2013-05-01

Full Text Available Large-scale hydrological drought studies have demonstrated spatial and temporal patterns in observed trends, and considerable difference exists among global hydrological models in their ability to reproduce these patterns. In this study a controlled modeling experiment has been set up to systematically explore the role of climate and physical catchment structure (soils and groundwater systems to better understand underlying drought-generating mechanisms. Daily climate data (1958–2001 of 1495 grid cells across the world were selected that represent Köppen–Geiger major climate types. These data were fed into a conceptual hydrological model. Nine realizations of physical catchment structure were defined for each grid cell, i.e., three soils with different soil moisture supply capacity and three groundwater systems (quickly, intermediately and slowly responding. Hydrological drought characteristics (number, duration and standardized deficit volume were identified from time series of daily discharge. Summary statistics showed that the equatorial and temperate climate types (A- and C-climates had about twice as many drought events as the arid and polar types (B- and E-climates, and the durations of more extreme droughts were about half the length. Selected soils under permanent grassland were found to have a minor effect on hydrological drought characteristics, whereas groundwater systems had major impact. Groundwater systems strongly controlled the hydrological drought characteristics of all climate types, but particularly those of the wetter A-, C- and D-climates because of higher recharge. The median number of droughts for quickly responding groundwater systems was about three times higher than for slowly responding systems. Groundwater systems substantially affected the duration, particularly of the more extreme drought events. Bivariate probability distributions of drought duration and standardized deficit for combinations of K�

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

Science.gov (United States)

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

2017-12-01

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.

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

Science.gov (United States)

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

2016-04-01

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

Groundwater drought in different geological conditions

International Nuclear Information System (INIS)

Machlica, A; Stojkovova, M

2008-01-01

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.

The U.S./Canadian GEO Bilateral Drought Indices and Definitions Study: Implications for the Canadian Drought Monitor and a Global Drought Early Warning System

Science.gov (United States)

Hadwen, T.; Heim, R. R.; Howard, A.

2011-12-01

Drought is a difficult phenomenon to define; the way in which it is monitored, measured, assessed and even the very definition of drought vary from location to location based on the regional climate and the potential impacts. Drought is not an absolute condition but an evolving state brought on by relatively dry weather, growing more severe over time. There are many factors that define a drought and many more that define its impacts. Many definitions and indices are based solely on meteorological characteristics. Although this approach has merit, it is often necessary to go further to define those meteorological conditions in a way that is relevant to the land and water use in a region. A Drought Indices and Definitions Study was initiated in 2010 as part of a GEO Bilateral effort to examine drought across the U.S. and Canada. The Study's deliverables will include a survey of the drought indices used to monitor drought, and a bibliography of research addressing the nature of drought, across the diverse climates of the continent. With an increasing pressure to utilize drought monitoring as a primary indicator of need for disaster assistance, the reliability of drought indices must be validated and utilized in appropriate in various regions. In 2009, following over five years of participation in the North American Drought Monitor (NA-DM), the National Agroclimate Information Service of Agriculture and Agri-Food Canada initiated a project to develop a Canadian Drought Monitor (Can-DM), based on primary principles used in the NA-DM and the US Drought Monitor (US-DM). The process of developing an operational monitoring tool and using drought indices in a vast and environmentally diverse country has been challenging. in Canada, many of the commonly used indices are not appropriate in certain regions or data densities do not allow for proper use. This paper will discuss the experiences that the Can-DM team has had dealing with these challenges, how these experiences

Density-dependent vulnerability of forest ecosystems to drought

Science.gov (United States)

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

2017-01-01

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...

Characteristics and drivers of drought in Europe-a summary of the DROUGHT-R&SPI project

NARCIS (Netherlands)

Tallaksen, Lena M.; Stagge, James H.; Stahl, Kerstin; Gudmundsson, Lukas; Orth, Rene; Seneviratne, Sonia I.; Loon, van Anne F.; Lanen, van Henny A.J.

2015-01-01

A prerequisite to mitigate the wide range of drought impacts is to establish a good understanding of the drought generating mechanisms from their initiation as a meteorological drought through to their development as soil moisture and hydrological drought. The DROUGHT-R&SPI project has

A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature

Science.gov (United States)

Ahmadalipour, Ali; Moradkhani, Hamid; Demirel, Mehmet C.

2017-10-01

The changing climate and the associated future increases in temperature are expected to have impacts on drought characteristics and hydrologic cycle. This paper investigates the projected changes in spatiotemporal characteristics of droughts and their future attributes over the Willamette River Basin (WRB) in the Pacific Northwest U.S. The analysis is performed using two subsets of downscaled CMIP5 global climate models (GCMs) each consisting of 10 models from two future scenarios (RCP4.5 and RCP8.5) for 30 years of historical period (1970-1999) and 90 years of future projections (2010-2099). Hydrologic modeling is conducted using the Precipitation Runoff Modeling System (PRMS) as a robust distributed hydrologic model with lower computational cost compared to other models. Meteorological and hydrological droughts are studied using three drought indices (i.e. Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, Standardized Streamflow Index). Results reveal that the intensity and duration of hydrological droughts are expected to increase over the WRB, albeit the annual precipitation is expected to increase. On the other hand, the intensity of meteorological droughts do not indicate an aggravation for most cases. We explore the changes of hydrometeolorogical variables over the basin in order to understand the causes for such differences and to discover the controlling factors of drought. Furthermore, the uncertainty of projections are quantified for model, scenario, and downscaling uncertainty.

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

Science.gov (United States)

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

2017-08-01

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.

Drought episodes over Greece as simulated by dynamical and statistical downscaling approaches

Science.gov (United States)

Anagnostopoulou, Christina

2017-07-01

Drought over the Greek region is characterized by a strong seasonal cycle and large spatial variability. Dry spells longer than 10 consecutive days mainly characterize the duration and the intensity of Greek drought. Moreover, an increasing trend of the frequency of drought episodes has been observed, especially during the last 20 years of the 20th century. Moreover, the most recent regional circulation models (RCMs) present discrepancies compared to observed precipitation, while they are able to reproduce the main patterns of atmospheric circulation. In this study, both a statistical and a dynamical downscaling approach are used to quantify drought episodes over Greece by simulating the Standardized Precipitation Index (SPI) for different time steps (3, 6, and 12 months). A statistical downscaling technique based on artificial neural network is employed for the estimation of SPI over Greece, while this drought index is also estimated using the RCM precipitation for the time period of 1961-1990. Overall, it was found that the drought characteristics (intensity, duration, and spatial extent) were well reproduced by the regional climate models for long term drought indices (SPI12) while ANN simulations are better for the short-term drought indices (SPI3).

Understanding the land-atmospheric interaction in drought forecast from CFSv2 for the 2011 Texas and 2012 Upper Midwest US droughts

Science.gov (United States)

Zhang, Y.; Roundy, J. K.; Ek, M. B.; Wood, E. F.

2015-12-01

Prediction and thus preparedness in advance of hydrological extremes, such as drought and flood events, is crucial for proactively reducing their social and economic impacts. In the summers of 2011 Texas, and 2012 the Upper Midwest, experienced intense droughts that affected crops and the food market in the US. It is expected that seasonal forecasts with sufficient skill would reduce the negative impacts through planning and preparation. However, the forecast skill from models such as Climate Forecast System Version 2 (CFSv2) from National Centers for Environmental Prediction (NCEP) is low over the US, especially during the warm season (Jun - Sep), which restricts their practical use for drought prediction. This study analyzes the processes that lead to premature termination of 2011 and 2012 US summer droughts in CFSv2 forecast resulting in its low forecast skill. Using the North American Land Data Assimilation System version 2 (NLDAS2) and Climate Forecast System Reanalysis (CFSR) as references, this study investigates the forecast skills of CFSv2 initialized at 00, 06, 12, 18z from May 15 - 31 (leads out to September) for each event in terms of land-atmosphere interaction, through a recently developed Coupling Drought Index (CDI), which is based on the Convective Triggering Potential-Humidity Index-soil moisture (CTP-HI-SM) classification of four climate regimes: wet coupling, dry coupling, transitional and atmospherically controlled. A recycling model is used to trace the moisture sources in the CFSv2 forecasts of anomalous precipitation, which lead to the breakdown of drought conditions and a lack of drought forecasting skills. This is then compared with tracing the moisture source in CFSR with the same recycling model, which is used as the verification for the same periods. This helps to identify the parameterization that triggered precipitation in CFSv2 during 2011 and 2012 summer in the US thus has the potential to improve the forecast skill of CSFv2.

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

Directory of Open Access Journals (Sweden)

Csorba Szilveszter

2014-12-01

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.

Assimilation exceeds respiration sensitivity to drought : A FLUXNET synthesis

NARCIS (Netherlands)

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

A comprehensive framework for tourism and recreation drought vulnerability reduction

International Nuclear Information System (INIS)

Thomas, Deborah S K; Wilhelmi, Olga V; Finnessey, Taryn N; Deheza, Veva

2013-01-01

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)

Defining Drought Characteristics for Natural Resource Management

Science.gov (United States)

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

2016-12-01

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

A preliminary study on drought events in Peninsular Malaysia

Science.gov (United States)

Zin, Wan Zawiah Wan; Nahrawi, Siti Aishah; Jemain, Abdul Aziz; Zahari, Marina

2014-06-01

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.

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

International Nuclear Information System (INIS)

Szklo, Alexandre; Machado, Giovani; Schaeffer, Roberto

2007-01-01

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

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

Science.gov (United States)

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

2016-12-01

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.

Drought in the Emerald City

International Nuclear Information System (INIS)

Babcock, S.D.

1993-01-01

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

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

KAUST Repository

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

2016-01-01

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

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

KAUST Repository

Ramakrishna, S. S. V. S.

2016-09-16

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

Floods and droughts: friends or foes?

Science.gov (United States)

Prudhomme, Christel

2017-04-01

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.

Application of NARR-based NLDAS Ensemble Simulations to Continental-Scale Drought Monitoring

Science.gov (United States)

Alonge, C. J.; Cosgrove, B. A.

2008-05-01

Government estimates indicate that droughts cause billions of dollars of damage to agricultural interests each year. More effective identification of droughts would directly benefit decision makers, and would allow for the more efficient allocation of resources that might mitigate the event. Land data assimilation systems, with their high quality representations of soil moisture, present an ideal platform for drought monitoring, and offer many advantages over traditional modeling systems. The recently released North American Regional Reanalysis (NARR) covers the NLDAS domain and provides all fields necessary to force the NLDAS for 27 years. This presents an ideal opportunity to combine NARR and NLDAS resources into an effective real-time drought monitor. Toward this end, our project seeks to validate and explore the NARR's suitability as a base for drought monitoring applications - both in terms of data set length and accuracy. Along the same lines, the project will examine the impact of the use of different (longer) LDAS model climatologies on drought monitoring, and will explore the advantages of ensemble simulations versus single model simulations in drought monitoring activities. We also plan to produce a NARR- and observation-based high quality 27 year, 1/8th degree, 3-hourly, land surface and meteorological forcing data sets. An investigation of the best way to force an LDAS-type system will also be made, with traditional NLDAS and NLDASE forcing options explored. This presentation will focus on an overview of the drought monitoring project, and will include a summary of recent progress. Developments include the generation of forcing data sets, ensemble LSM output, and production of model-based drought indices over the entire NLDAS domain. Project forcing files use 32km NARR model output as a data backbone, and include observed precipitation (blended CPC gauge, PRISM gauge, Stage II, HPD, and CMORPH) and a GOES-based bias correction of downward solar

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

OpenAIRE

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

2017-01-01

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...

Vulnerability analysis for a drought Early Warning System

Science.gov (United States)

Angeluccetti, Irene; Demarchi, Alessandro; Perez, Francesca

2014-05-01

Early Warning Systems (EWS) for drought are often based on risk models that do not, or marginally, take into account the vulnerability factor. The multifaceted nature of drought (hydrological, meteorological, and agricultural) is source of coexistence for different ways to measure this phenomenon and its effects. The latter, together with the complexity of impacts generated by this hazard, causes the current underdevelopment of drought EWS compared to other hazards. In Least Developed Countries, where drought events causes the highest numbers of affected people, the importance of correct monitoring and forecasting is considered essential. Existing early warning and monitoring systems for drought produced at different geographic levels, provide only in a few cases an actual spatial model that tries to describe the cause-effect link between where the hazard is detected and where impacts occur. Integrate vulnerability information in such systems would permit to better estimate affected zones and livelihoods, improving the effectiveness of produced hazard-related datasets and maps. In fact, the need of simplification and, in general, of a direct applicability of scientific outputs is still a matter of concern for field experts and early warning products end-users. Even if the surplus of hazard related information produced right after catastrophic events has, in some cases, led to the creation of specific data-sharing platforms, the conveyed meaning and usefulness of each product has not yet been addressed. The present work is an attempt to fill this gap which is still an open issue for the scientific community as well as for the humanitarian aid world. The study aims at conceiving a simplified vulnerability model to embed into an existing EWS for drought, which is based on the monitoring of vegetation phenological parameters and the Standardized Precipitation Index, both produced using free satellite derived datasets. The proposed vulnerability model includes (i) a

Development of a Strategic Framework for Drought Management

Science.gov (United States)

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

2017-04-01

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

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

NARCIS (Netherlands)

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

2016-01-01

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

Assessing vulnerability to drought: identifying underlying factors across Europe

Science.gov (United States)

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

2015-04-01

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

Accounting for Landscape Heterogeneity Improves Spatial Predictions of Tree Vulnerability to Drought

Science.gov (United States)

Schwantes, A. M.; Parolari, A.; Swenson, J. J.; Johnson, D. M.; Domec, J. C.; Jackson, R. B.; Pelak, N. F., III; Porporato, A. M.

2017-12-01

Globally, as climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability differs regionally and locally depending on landscape position. However, most models used in forecasting forest responses to heatwaves and droughts do not incorporate relevant spatial processes. To improve predictions of spatial tree vulnerability, we employed a non-linear stochastic model of soil moisture dynamics across a landscape, accounting for spatial differences in aspect, topography, and soils. Our unique approach integrated plant hydraulics and landscape processes, incorporating effects from lateral redistribution of water using a topographic index and radiation and temperature differences attributable to aspect. Across a watershed in central Texas we modeled dynamic water stress for a dominant tree species, Juniperus ashei. We compared our results to a detailed spatial dataset of drought-impacted areas (>25% canopy loss) derived from remote sensing during the severe 2011 drought. We then projected future dynamic water stress through the 21st century using climate projections from 10 global climate models under two scenarios, and compared models with and without landscape heterogeneity. Within this watershed, 42% of J. ashei dominated systems were impacted by the 2011 drought. Modeled dynamic water stress tracked these spatial patterns of observed drought-impacted areas. Total accuracy increased from 59%, when accounting only for soil variability, to 73% when including lateral redistribution of water and radiation and temperature effects. Dynamic water stress was projected to increase through the 21st century, with only minimal buffering from the landscape. During the hotter and more severe droughts projected in the 21st century, up to 90% of the watershed crossed a dynamic water stress threshold associated with canopy loss in 2011. Favorable microsites may exist across a landscape where trees can persist; however, if future droughts are

Analysis of Droughts of Northwest of Iran Using the Reconnaissance Drought Index

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behrouz hosseini

2016-02-01

Full Text Available Introduction: Drought is a creeping natural phenomenon, which can occur in any region. Such phenomenon not only affects the region subjected to drought, but its adverse effects can also be extended to other adjacent regions. This phenomenon mainly starts with water deficiency (say less than long- term mean of variable under study such as rainfall, streamflow, groundwater level or soil moisture and progress in time. This period can be ended by increasing the rainfall and reaching the mean level. Even after the ending of a drought period, its adverse effects can be continued for several months. Although, it is not possible (at least at this time to prevent the occurrence of drought in a given region, it is not impossible to alleviate the drought consequences by scientific water management. Such a management should be employed before drought initiation as well as during it and continue on even after the end of the drought period. The frequency of the main drought characteristics is a major concern of this study. The Northwest of Iran recently encountered severe and prolonged droughts, such that a major portion of the Urmia Lake surface disappeared during the last drought in recent years. In order to study drought characteristics, we used the Reconnaissance Drought Index (RDI. This index is based on annual rainfall and potential reference crop evapotranspiration (abbreviated by PET here. This study employed the Monte Carlo simulation technique for synthetic data generation for analysis. Materials and Methods: The information from the 17 synoptic weather stations located in the North-west of Iran was used for drought analysis. Data was gathered from the Islamic Republic of Iran’s Meteorological Organization (IRIMO. In the first stage of research, the ratio of long term mean annual precipitation to evapotranspiration was calculated for each of the stations. For this purpose, the Penman-Montheis (FAO 56 method was selected for PET estimation. In the

Understanding and seasonal forecasting of hydrological drought in the Anthropocene

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X. Yuan

2017-11-01

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

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

Science.gov (United States)

Yu, Z.; Lin, S.

2011-12-01

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.

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

Science.gov (United States)

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

2018-01-01

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.

Economic risk assessment of drought impacts on irrigated agriculture

Science.gov (United States)

Lopez-Nicolas, A.; Pulido-Velazquez, M.; Macian-Sorribes, H.

2017-07-01

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.

USGS integrated drought science

Science.gov (United States)

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

2017-06-05

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.

Simulating US Agriculture in a Modern Dust Bowl Drought

Science.gov (United States)

Glotter, Michael; Elliott, Joshua

2016-01-01

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.

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

Science.gov (United States)

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

2012-04-01

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.

A Look into the National Drought Mitigation Center: Providing 15 Years of Drought Services (Invited)

Science.gov (United States)

Svoboda, M. D.; Hayes, M. J.; Knutson, C. L.; Wardlow, B. D.

2009-12-01

The National Drought Mitigation Center (NDMC) was formed in 1995 at the University of Nebraska-Lincoln. Over the past 15 years, the NDMC has made it a priority to work with various local, state, tribal and federal entities to provide a suite of drought/climate services, with a goal of bringing research to fruition through applications and operations. Through our research and outreach projects, the NDMC has worked to reduce risk to drought by developing several mitigation strategies, monitoring and decision making tools and other services aimed at enhancing our nation’s capacity to cope with drought. Two of the earliest NDMC activities were the creation of a website and assessing drought conditions around the United States. An electronic drought clearinghouse was built in 1995 at drought.unl.edu. The site was designed, and still concentrates, on the concepts of drought monitoring, planning, and mitigation and also serves as a repository of information from around the world. The NDMC’s electronic quarterly newsletter, DroughtScape, disseminates information about all things drought to people across the country. In addition, the NDMC has developed and is home to websites for the U.S. Drought Monitor (USDM), Drought Impact Reporter (DIR), and the Vegetation Drought Response Index (VegDRI). In an effort to inform decision makers, the NDMC continually pursues ways to raise the awareness and visibility of drought as one of the most costly hazards we face. This began in the mid-1990s with the creation of a state-based drought impact assessment map that would help lead to the formation of the USDM in 1999 and the DIR in 2005. The NDMC plays a key role in producing the weekly USDM and the monthly North American Drought Monitor (NADM). The USDM was created out of collaborations between the NDMC, United States Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) and has quickly become one of the most widely used products in assessing

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

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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.

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

NARCIS (Netherlands)

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

2005-01-01

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.

Isoprene emission response to drought and the impact on global atmospheric chemistry

Science.gov (United States)

Jiang, Xiaoyan; Guenther, Alex; Potosnak, Mark; Geron, Chris; Seco, Roger; Karl, Thomas; Kim, Saewung; Gu, Lianhong; Pallardy, Stephen

2018-06-01

Biogenic isoprene emissions play a very important role in atmospheric chemistry. These emissions are strongly dependent on various environmental conditions, such as temperature, solar radiation, plant water stress, ambient ozone and CO2 concentrations, and soil moisture. Current biogenic emission models (i.e., Model of Emissions of Gases and Aerosols from Nature, MEGAN) can simulate emission responses to some of the major driving variables, such as short-term variations in temperature and solar radiation, but the other factors are either missing or poorly represented. In this paper, we propose a new modelling approach that considers the physiological effects of drought stress on plant photosynthesis and isoprene emissions for use in the MEGAN3 biogenic emission model. We test the MEGAN3 approach by integrating the algorithm into the existing MEGAN2.1 biogenic emission model framework embedded into the global Community Land Model of the Community Earth System Model (CLM4.5/CESM1.2). Single-point simulations are compared against available field measurements at the Missouri Ozarks AmeriFlux (MOFLUX) field site. The modelling results show that the MEGAN3 approach of using of a photosynthesis parameter (Vcmax) and soil wetness factor (βt) to determine the drought activity factor leads to better simulated isoprene emissions in non-drought and drought periods. The global simulation with the MEGAN3 approach predicts a 17% reduction in global annual isoprene emissions, in comparison to the value predicted using the default CLM4.5/MEGAN2.1 without any drought effect. This reduction leads to changes in surface ozone and oxidants in the areas where the reduction of isoprene emissions is observed. Based on the results presented in this study, we conclude that it is important to simulate the drought-induced response of biogenic isoprene emission accurately in the coupled Earth System model.

An assessment of global meteorological droughts based on HAPPI experiments

Science.gov (United States)

Liu, Wenbin; Sun, Fubao; Lim, Wee Ho; Zhang, Jie

2017-04-01

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

Early warning system of drought for risk assessment and risk management

International Nuclear Information System (INIS)

Chub, V.E.; Agaltseva, N.A.; Myagkov, S.V.

2004-01-01

In Article 10 point 2 of the UN Convention to Combat Desertification and Drought it is pointed out that the National Action Plans 'envisage the strengthening of the national basis of the climatic, meteorological and hydrological studies and the extending the possibilities for the creation of the system of the early drought forecasting'. The Pilot Project << Early warning system of Drought,, was executed in Uzbekistan at support of Germany project on Convention to combat Desertification (GTZ-CCD). The objective of the project is the creation of the regional automated information system for the early drought warning (AISEWS). In the framework of the project it is proposed to fulfil the main following tasks: - development of concepts of preparing the databases on drought factors and keeping on the databank of drought conditions on territory of Republic Uzbekistan; - the creation of the regional informational basis of the hydro meteorological and agrometeorological information and the system of its keeping on the basis of GIS technique; - analysis of hydro meteorological situations causing the drought in the Aral sea basin; - experimental agrometeorological (in the course of the field studies) and numerical estimation of the parameters of the model of the runoff formation and soil drought; - adaptation of the models complex set of the runoff formation for hydrological objects; - development of out the technique for the long-term drought forecasting basing on the mathematical models of the runoff formation in the river basin; -development of the computer information system for the early drought forecasting with the elements of the operational information transfer to the users. For the Central Asian region the drought means, first of all, the deficit of the water resources that is why the forecasting of the water availability in rivers in the years with the water deficit is of the utmost importance. The following tasks should be fulfilled for the achieving the designed

On the utility of land surface models for agricultural drought monitoring

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W. T. Crow

2012-09-01

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.

Comparative Analysis of Drought Indices for Drought Zone Scheme of Northern Khorasan Province of Iran

OpenAIRE

Ehsan EYSHI REZAEI; Azade MOHAMMADIAN; Mansoreh KOOHI; Mohammad BANNAYAN

2011-01-01

Drought is one of the natural disasters which deeply influenced agricultural production. Drought monitoring programs could help to forecast and mitigate the impacts of drought. In this study occurrence, severity, and duration of drought were evaluated by monthly rainfall data (1986-2005) that were recorded at all meteorological stations in north Khorasan province of Iran. Drought indices include Standard Rainfall Index (SPI), Decades Index (DI) and Percent of Normal (PNI) calculated and compa...

Climate Downscaling over Nordeste, Brazil, Using the NCEP RSM97.

Science.gov (United States)

Sun, Liqiang; Ferran Moncunill, David; Li, Huilan; Divino Moura, Antonio; de Assis de Souza Filho, Francisco

2005-02-01

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.

Ectoparasitic crustaceans on mullet, Mugil curema (Osteichthyes: Mugilidae in the coastal waters of Rio Grande do Norte State, Brazil - doi: 10.4025/actascibiolsci.v33i3.6796 Ectoparasitic crustaceans on mullet, Mugil curema (Osteichthyes: Mugilidae in the coastal waters of Rio Grande do Norte State, Brazil - doi: 10.4025/actascibiolsci.v33i3.6796

Directory of Open Access Journals (Sweden)

Sathyabama Chellappa

2011-07-01

Full Text Available White mullet is a commercial fish species abundant in the coastal waters of Brazil. This study investigated the occurrence of crustacean ectoparasites on white mullet, Mugil curema captured from the littoral waters of Rio Grande do Norte State, Brazil. From 2006 to 2007, 31 individuals of M. curema were captured and encountered ectoparasites were observed, identified and counted. M. curema was parasitized by ectoparasitic crustaceans, caligid copepods, Caligus bonito and Caligus sp.; ergasilid copepods, Ergasilus versicolor and E. lizae; and isopod Cymothoa spinipalpa. Of the caligids detected, 66.66% were C. bonito and 33.33% Caligus sp. C. bonito occurred on males of M. curema during the drought season and Caligus sp. occurred on females during the rainy season. The prevalence of both caligid species was 3.23%. Of the ergasilids detected, E. versicolor (91.67% occurred during the drought and rainy seasons, whereas E. lizae (8.33% occurred during the rainy season. Prevalence of E. versicolor was 35.48% and E. lizae was 3.23%. C. spinipalpa was detected during the drought and rainy seasons with a prevalence of 16.13%. The preferred site of fixation by the parasites was the branchial chambers.White mullet is a commercial fish species abundant in the coastal waters of Brazil. This study investigated the occurrence of crustacean ectoparasites on white mullet, Mugil curema captured from the littoral waters of Rio Grande do Norte State, Brazil. From 2006 to 2007, 31 individuals of M. curema were captured and encountered ectoparasites were observed, identified and counted. M. curema was parasitized by ectoparasitic crustaceans, caligid copepods, Caligus bonito and Caligus sp.; ergasilid copepods, Ergasilus versicolor and E. lizae; and isopod Cymothoa spinipalpa. Of the caligids detected, 66.66% were C. bonito and 33.33% Caligus sp. C. bonito occurred on males of M. curema during the drought season and Caligus sp. occurred on females during the rainy

Drought in Africa 2

Energy Technology Data Exchange (ETDEWEB)

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

1977-01-01

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.

[Physiological responses of mycorrhizal Pinus massoniana seedlings to drought stress and drought resistance evaluation].

Science.gov (United States)

Wang, Yi; Ding, Gui-jie

2013-03-01

A greenhouse pot experiment was conducted to study the effects of inoculating Pisolithus tinctorius, Cenococcum geophilum, Cantharellus cibarius, and Suillus luteus on the physiological characteristics of Pinus massoniana seedlings under the conditions of drought stress and re-watering, with the drought resistance of the mycorrhizal seedlings evaluated. Under drought stress, the MDA content and membrane' s relative permeability of P. massoniana seedlings increased, but these two indices in the inoculated (mycorrhizal) seedlings were significantly lower than these in the un-inoculated (control) seedlings. After re-watering, the MDA content and membrane's relative permeability of mycorrhizal seedlings had a rapid decrease, as compared with the control. In the first 21 days of drought stress, the production rate of superoxide radical of the seedlings increased, and the SOD, POD and NR activities of mycorrhizal seedlings increased significantly. With the extending of drought stress, the seedlings after re-watering had different recovery ability. Under the re-watering after 14 days drought stress, the SOD, POD and NR activities recovered. The drought resistance of the mycorrhizal seedlings was in the order of Suillus luteus 1 > Suillus luteus 7 > Cantharellus cibarius > Cenococcum geophilum > Pisolithus tinctorius. The SOD and MDA activities had a greater correlation with the mycorrhizal seedlings drought resistance, being able to be used as the indicators to evaluate the drought resistance of mycorrhizal seedlings.

Dissecting rice polyamine metabolism under controlled long-term drought stress.

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Phuc Thi Do

Full Text Available A selection of 21 rice cultivars (Oryza sativa L. ssp. indica and japonica was characterized under moderate long-term drought stress by comprehensive physiological analyses and determination of the contents of polyamines and selected metabolites directly related to polyamine metabolism. To investigate the potential regulation of polyamine biosynthesis at the transcriptional level, the expression of 21 genes encoding enzymes involved in these pathways were analyzed by qRT-PCR. Analysis of the genomic loci revealed that 11 of these genes were located in drought-related QTL regions, in agreement with a proposed role of polyamine metabolism in rice drought tolerance. The cultivars differed widely in their drought tolerance and parameters such as biomass and photosynthetic quantum yield were significantly affected by drought treatment. Under optimal irrigation free putrescine was the predominant polyamine followed by free spermidine and spermine. When exposed to drought putrescine levels decreased markedly and spermine became predominant in all cultivars. There were no correlations between polyamine contents and drought tolerance. GC-MS analysis revealed drought-induced changes of the levels of ornithine/arginine (substrate, substrates of polyamine synthesis, proline, product of a competing pathway and GABA, a potential degradation product. Gene expression analysis indicated that ADC-dependent polyamine biosynthesis responded much more strongly to drought than the ODC-dependent pathway. Nevertheless the fold change in transcript abundance of ODC1 under drought stress was linearly correlated with the drought tolerance of the cultivars. Combining metabolite and gene expression data, we propose a model of the coordinate adjustment of polyamine biosynthesis for the accumulation of spermine under drought conditions.

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

Science.gov (United States)

Tarnavsky, E.

2016-12-01

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.

Performing drought indices to identify the relationship between agricultural losses and drought events in Spain.

Science.gov (United States)

Peña Gallardo, Marina; Serrano, Sergio Martín Vicente; Portugués Santiago, Beguería; Burguera Miquel, Tomás

2017-04-01

Drought leads to crop failures reducing the productivity. For this reason, the need of appropriate tool for recognize dry periods and evaluate the impact of drought on crop production is important. In this study, we provide an assessment of the relationship between drought episodes and crop failures in Spain as one of the direct consequences of drought is the diminishing of crop yields. First, different drought indices [the Standardized Precipitation and Evapotranspiration Index (SPEI); the Standardized Precipitation Index (SPI); the self-calibrated Palmer Moisture Anomaly Index (Z-Index), the self-calibrated Crop Moisture Index (CMI) and the Standardized Palmer Drought Index (SPDI)] have been calculated at different time scales in order to identify the dry events occurred in Spain and determine the duration and intensity of each event. Second, the drought episodes have been correlated with crop production estimated and final crop production data provided by the Spanish Crop Insurance System for the available period from 1995 to 2014 at the municipal spatial scale, with the purpose of knowing if the characteristics of the drought episodes are reflected on the agricultural losses. The analysis has been carried out in particular for two types of crop, wheat and barley. The results indicate the existence of an agreement between the most important drought events in Spain and the response of the crop productions and the proportion of hectare insurance. Nevertheless, this agreement vary depending on the drought index applied. Authors found a higher competence of the drought indices calculated at different time scales (SPEI, SPI and SPDI) identifying the begging and end of the drought events and the correspondence with the crop failures.

Prediction of Agriculture Drought Using Support Vector Regression Incorporating with Climatology Indices

Science.gov (United States)

Tian, Y.; Xu, Y. P.

2017-12-01

In this paper, the Support Vector Regression (SVR) model incorporating climate indices and drought indices are developed to predict agriculture drought in Xiangjiang River basin, Central China. The agriculture droughts are presented with the Precipitation-Evapotranspiration Index (SPEI). According to the analysis of the relationship between SPEI with different time scales and soil moisture, it is found that SPEI of six months time scales (SPEI-6) could reflect the soil moisture better than that of three and one month time scale from the drought features including drought duration, severity and peak. Climate forcing like El Niño Southern Oscillation and western Pacific subtropical high (WPSH) are represented by climate indices such as MEI and series indices of WPSH. Ridge Point of WPSH is found to be the key factor that influences the agriculture drought mainly through the control of temperature. Based on the climate indices analysis, the predictions of SPEI-6 are conducted using the SVR model. The results show that the SVR model incorperating climate indices, especially ridge point of WPSH, could improve the prediction accuracy compared to that using drought index only. The improvement was more significant for the prediction of one month lead time than that of three months lead time. However, it needs to be cautious in selection of the input parameters, since adding more useless information could have a counter effect in attaining a better prediction.

Regional applicability of seven meteorological drought indices in China

Institute of Scientific and Technical Information of China (English)

YANG Qing; LI MingXing; ZHENG ZiYan; MA ZhuGuo

2017-01-01

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

Investigation of spatiotemporal relationship between dengue fever and drought

Science.gov (United States)

Lee, Chieh-Han; Yu, Hwa-Lung

2016-04-01

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. Otherwise, another nearby city, Tainan City, had reported the biggest outbreak in 2015. 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.

Flood model for Brazil

Science.gov (United States)

Palán, Ladislav; Punčochář, Petr

2017-04-01

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

The Drought Monitor.

Science.gov (United States)

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

2002-08-01

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.

Co-occurring woody species have diverse hydraulic strategies and mortality rates during an extreme drought: Belowground hydraulic failure during drought

Energy Technology Data Exchange (ETDEWEB)

Johnson, Daniel M. [College of Natural Resources, University of Idaho, Moscow ID 83844 USA; Domec, Jean-Christophe [Bordeaux Sciences Agro, UMR INRA-ISPA 1391, Gradignan 33195 France; Nicholas School of the Environment, Duke University, Durham NC 27708 USA; Carter Berry, Z. [College of Natural Resources, University of Idaho, Moscow ID 83844 USA; Department of Natural Resources and the Environment, University of New Hampshire, Durham NH 03824 USA; Schwantes, Amanda M. [Nicholas School of the Environment, Duke University, Durham NC 27708 USA; McCulloh, Katherine A. [Department of Botany, University of Wisconsin-Madison, Madison WI 53705 USA; Woodruff, David R. [US Forest Service, Pacific Northwest Research Station, Corvallis OR 97331 USA; Wayne Polley, H. [Grassland, Soil & Water Research Laboratory USDA-Agricultural Research Service, Temple TX 76502 USA; Wortemann, Remí [INRA Nancy, UMR INRA-UL 1137 Ecologie et Ecophysiologie Forestières, Champenoux 54280 France; Swenson, Jennifer J. [Nicholas School of the Environment, Duke University, Durham NC 27708 USA; Scott Mackay, D. [Department of Geography, State University of New York, Buffalo NY 14261 USA; McDowell, Nate G. [Pacific Northwest National Laboratory, Richland WA 99352 USA; Jackson, Robert B. [Department of Earth System Science, Woods Institute for the Environment, and Precourt Institute for Energy, Stanford University, Stanford CA 94305 USA

2018-01-29

From 2011 to 2013, Texas experienced its worst drought in recorded history. This event provided a unique natural experiment to assess species-specific responses to extreme drought and mortality of four co-occurring woody species: Quercus fusiformis, Diospyros texana, Prosopis glandulosa and Juniperus ashei. We examined hypothesized mechanisms that could promote these species’ diverse mortality patterns using post-drought measurements on surviving trees coupled to retrospective process modeling. The species exhibited a wide range of gas exchange responses, hydraulic strategies, and mortality rates. Multiple proposed indices of mortality mechanisms were not consistent with the observed mortality patterns across species, including measures of iso/anisohydry, photosynthesis, carbohydrate depletion, and hydraulic safety margins. Large losses of growing season whole-tree conductance (driven by belowground losses of conductance), and shallower rooting depths, were associated with species that exhibited greater mortality. Based on this retrospective analysis, we suggest that species more vulnerable to drought were more likely to have succumbed to hydraulic failure belowground.

Local Perception of Drought Impacts in a Changing Climate: The Mega-Drought in Central Chile

Directory of Open Access Journals (Sweden)

Paulina Aldunce

2017-11-01

Full Text Available Droughts are a recurrent and complex natural hazard whose frequency and magnitude are expected to increase with climate change. Despite the advances in responding and adapting to droughts (with the development of new policies, for example, droughts continue to cause serious impacts and suffering. Developing well-targeted public policies requires further research on adaptation. Specifically, understanding the public perception of drought can help to identify drivers of and barriers to adaptation and options. This research seeks to understand the public perception of drought in central Chile in order to inform adaptation-related policies and decision-making processes. This study focused on the Mega-drought, which was a protracted dry spell afflicting central Chile since 2010.

Spatiotemporal drought variability in northwestern Africa over the last nine centuries

Energy Technology Data Exchange (ETDEWEB)

Touchan, Ramzi; Meko, David M. [The University of Arizona, Laboratory of Tree Ring Research, Tucson, AZ (United States); Anchukaitis, Kevin J. [Columbia University, Lamont Doherty Earth Observatory, Palisades, NY (United States); Sabir, Mohamed [National School of Forest Engineering, Sale (Morocco); Attalah, Said [University of Ourgla, Department of Agronomy, Ouargla (Algeria); Aloui, Ali [Institute of Sylvo-pastoral of Tabarka, Tabarka (Tunisia)

2011-07-15

Changes in precipitation patterns and the frequency and duration of drought are likely to be the feature of anthropogenic climate change that will have the most direct and most immediate consequences for human populations. The latest generation of state-of-the-art climate models project future widespread drying in the subtropics. Here, we reconstruct spatially-complete gridded Palmer drought severity index values back to A.D. 1179 over Morocco, Algeria, and Tunisia. The reconstructions provide long-term context for northwest African hydroclimatology, revealing large-scale regional droughts prior to the sixteenth century, as well as more heterogeneous patterns in sixteenth, eighteenth, and twentieth century. Over the most recent decades a shift toward dry conditions over the region is observed, which is consistent with general circulation model projections of greenhouse gas forced enhanced regional subtropical drought. (orig.)

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

Science.gov (United States)

Pandey, V.; Srivastava, P. K.

2018-04-01

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.

INTEGRATION OF SATELLITE, GLOBAL REANALYSIS DATA AND MACROSCALE HYDROLOGICAL MODEL FOR DROUGHT ASSESSMENT IN SUB-TROPICAL REGION OF INDIA

Directory of Open Access Journals (Sweden)

V. Pandey

2018-04-01

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.

Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought

Science.gov (United States)

Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.

2017-12-01

We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.

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

International Nuclear Information System (INIS)

Monteiro Filho, Joselio Silveira

2004-08-01

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)

Drought preparedness and drought mitigation in the developing world׳s drylands

Directory of Open Access Journals (Sweden)

Mahmoud Solh

2014-06-01

Drought is a climatic event that cannot be prevented, but interventions and preparedness to drought can help to: (i be better prepared to cope with drought; (ii develop more resilient ecosystems (iii improve resilience to recover from drought; and (iv mitigate the impacts of droughts. Preparedness strategies to drought include: (a geographical shifts of agricultural systems; (b climate-proofing rainfall-based systems; (c making irrigated systems more efficient; (d expanding the intermediate rainfed–irrigated systems. The paper presents successful research results and case studies applying some innovative techniques where clear impact is demonstrated to cope with drought and contribute to food security in dry areas. The CGIAR Consortium Research Program (CRP on “Integrated and Sustainable Agricultural Production Systems for Improved Food Security and Livelihoods in Dry Areas” (in short, “Dryland Systems”, led by ICARDA, was launched in May 2013 with many partners and stakeholders from 40 countries. It addresses farming systems in dry areas, at a global level, involving 80 partner institutions. The Dryland Systems Program aims at coping with drought and water scarcity to enhance food security and reduce poverty in dry areas through an integrated agro-ecosystem approach. It will also deliver science-based solutions that can be adopted in regions that are not yet experiencing extreme shocks, but will be affected in the medium to long-term. The approach entails shifting the thinking away from the traditional focus on a small number of research components to take an integrated approach aiming to address agro-ecosystems challenges. Such an approach involves crops, livestock, rangeland, trees, soils, water and policies. It is one of the first global research for development efforts that brings “systems thinking” to farming innovations leading to improved livelihoods in the developing world. The new technique uses modern innovation platforms to involve all

Multiyear drought-induced morbidity preceding tree death in southeastern U.S. forests.

Science.gov (United States)

Berdanier, Aaron B; Clark, James S

2016-01-01

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.

Operationalising resilience to drought: Multi-layered safety for flooding applied to droughts

Science.gov (United States)

Rijke, Jeroen; Smith, Jennifer Vessels; Gersonius, Berry; van Herk, Sebastiaan; Pathirana, Assela; Ashley, Richard; Wong, Tony; Zevenbergen, Chris

2014-11-01

This paper sets out a way of thinking about how to prepare for and respond to droughts in a holistic way using a framework developed for managing floods. It shows how the multi-layered safety (MLS) approach for flood resilience can be utilised in the context of drought in a way that three layers of intervention can be distinguished for operationalising drought resilience: (1) protection against water shortage through augmentation and diversification of water supplies; (2) prevention of damage in case of water shortage through increased efficiency of water use and timely asset maintenance; (3) preparedness for future water shortages through mechanisms to reduce the use of water and adopt innovative water technologies. Application of MLS to the cities of Adelaide, Melbourne and Sydney shows that recent water reforms in these cities were primarily focused on protection measures that aim to reduce the hazard source or exposure to insufficient water supplies. Prevention and preparedness measures could be considered in defining interventions that aim to further increase the drought resilience of these cities. Although further research is needed, the application suggests that MLS can be applied to the context of drought risk management. The MLS framework can be used to classify the suite of plans deployed by a city to manage future drought risks and can be considered a planning tool to identify opportunities for increasing the level of redundancy and hence resilience of the drought risk management system.

Seasonal Drought Forecasting for Latin America Using the ECMWF S4 Forecast System

Directory of Open Access Journals (Sweden)

Hugo Carrão

2018-06-01

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

Designing basin-customized combined drought indices via feature extraction

Science.gov (United States)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

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

Methods for estimating drought streamflow probabilities for Virginia streams

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Austin, Samuel H.

2014-01-01

Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.

On the propagation of drought : how climate and catchment characteristics influence hydrological drought development and recovery

NARCIS (Netherlands)

Loon, van A.F.

2013-01-01

Drought is a severe natural disaster resulting in high economic loss and huge ecological and societal impacts. In this thesis drought is defined as a period of below-normal water availability in precipitation (meteorological drought), soil moisture (soil moisture drought), or groundwater and

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

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VanDyke, Matthew S; King, Andy J

2017-12-05

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.

Quantification of agricultural drought occurrence as an estimate for insurance programs

Science.gov (United States)

Bannayan, M.; Hoogenboom, G.

2015-11-01

Temporal irregularities of rainfall and drought have major impacts on rainfed cropping systems. The main goal of this study was to develop an approach for realizing drought occurrence based on local winter wheat yield loss and rainfall. The domain study included 11 counties in the state of Washington that actively grow rainfed winter wheat and an uncertainty rainfall evaluation model using daily rainfall values from 1985 to 2007. An application was developed that calculates a rainfall index for insurance that was then used to determine the drought intensity for each study year and for each study site. Evaluation of the drought intensity showed that both the 1999-2000 and 2000-2001 growing seasons were stressful years for most of the study locations, while the 2005-2006 and the 2006-2007 growing seasons experienced the lowest drought intensity for all locations. Our results are consistent with local extension reports of drought occurrences. Quantification of drought intensity based on this application could provide a convenient index for insurance companies for determining the effect of rainfall and drought on crop yield loss under the varying weather conditions of semi-arid regions.

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

Science.gov (United States)

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

2017-12-01

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

Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

Energy Technology Data Exchange (ETDEWEB)

Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.; Cook, David R.; Matamala, Roser; Fischer, Marc L.; Jin, Cui; Dong, Jinwei; Biradar, Chandrashekhar

2014-09-01

Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared with the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.

Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment

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Ahmadalipour, Ali; Moradkhani, Hamid

2017-12-01

Hydrologic modeling is one of the primary tools utilized for drought monitoring and drought early warning systems. Several sources of uncertainty in hydrologic modeling have been addressed in the literature. However, few studies have assessed the uncertainty of gridded observation datasets from a drought monitoring perspective. This study provides a hydrologic modeling oriented analysis of the gridded observation data uncertainties over the Pacific Northwest (PNW) and its implications on drought assessment. We utilized a recently developed 100-member ensemble-based observed forcing data to simulate hydrologic fluxes at 1/8° spatial resolution using Variable Infiltration Capacity (VIC) model, and compared the results with a deterministic observation. Meteorological and hydrological droughts are studied at multiple timescales over the basin, and seasonal long-term trends and variations of drought extent is investigated for each case. Results reveal large uncertainty of observed datasets at monthly timescale, with systematic differences for temperature records, mainly due to different lapse rates. The uncertainty eventuates in large disparities of drought characteristics. In general, an increasing trend is found for winter drought extent across the PNW. Furthermore, a ∼3% decrease per decade is detected for snow water equivalent (SWE) over the PNW, with the region being more susceptible to SWE variations of the northern Rockies than the western Cascades. The agricultural areas of southern Idaho demonstrate decreasing trend of natural soil moisture as a result of precipitation decline, which implies higher appeal for anthropogenic water storage and irrigation systems.

Long-range hydrometeorological ensemble predictions of drought parameters

Science.gov (United States)

Fundel, F.; Jörg-Hess, S.; Zappa, M.

2012-06-01

Low streamflow as consequence of a drought event affects numerous aspects of life. Economic sectors that may be impacted by drought are, e.g. power production, agriculture, tourism and water quality management. Numerical models have increasingly been used to forecast low-flow 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 low-flow indices duration, severity and magnitude, with a forecast lead-time of one month, to assess their potential usefulness for predictions. The ECMWF VarEPS 5 member reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification shows that, compared to peak flow, probabilistic low-flow forecasts are skillful for longer lead-times, low-flow index forecasts could also be beneficially included in a decision-making process. The results suggest monthly runoff forecasts are useful for accessing the risk of hydrological droughts.

The role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchments

Science.gov (United States)

Van Tiel, Marit; Teuling, Adriaan J.; Wanders, Niko; Vis, Marc J. P.; Stahl, Kerstin; Van Loon, Anne F.

2018-01-01

Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light) model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975-2004) and future (2071-2100) period. Two existing threshold approaches to define future droughts are employed: (1) the threshold from the historical period; (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Petr Maca

2016-01-01

Full Text Available The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI and the standardized precipitation evaporation index (SPEI and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

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

Science.gov (United States)

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

2015-12-01

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.

Temperature impacts on the water year 2014 drought in California

Science.gov (United States)

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

2015-01-01

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.

Forages and Pastures Symposium: assessing drought vulnerability of agricultural production systems in context of the 2012 drought.

Science.gov (United States)

Kellner, O; Niyogi, D

2014-07-01

Weather and climate events and agronomic enterprise are coupled via crop phenology and yield, which is temperature and precipitation dependent. Additional coupling between weather and climate and agronomic enterprise occurs through agricultural practices such as tillage, irrigation, erosion, livestock management, and forage. Thus, the relationship between precipitation, temperature, and yield is coupled to the relationship between temperature, precipitation, and drought. Unraveling the different meteorological and climatological patterns by comparing different growing seasons provides insight into how drought conditions develop and what agricultural producers can do to mitigate and adapt to drought conditions. The 2012 drought in the United States greatly impacted the agricultural sector of the economy. With comparable severity and spatial extent of the droughts of the 1930s, 1950s, and 1980s, the 2012 drought impacted much of the U.S. crop and livestock producers via decreased forage and feed. This brief summary of drought impacts to agricultural production systems includes 1) the basics of drought; 2) the meteorology and climatology involved in forecasting, predicting, and monitoring drought with attribution of the 2012 drought explored in detail; and 3) comparative analysis completed between the 2011 and 2012 growing season. This synthesis highlights the complex nature of drought in agriculture production systems as producers prepare for future climate variability.

Applying Data-mining techniques to study drought periods in Spain

Science.gov (United States)

Belda, F.; Penades, M. C.

2010-09-01

Data-mining is a technique that it can be used to interact with large databases and to help in the discovery relations between parameters by extracting information from massive and multiple data archives. Drought affects many economic and social sectors, from agricultural to transportation, going through urban water deficit and the development of modern industries. With these problems and drought geographical and temporal distribution it's difficult to find a single definition of drought. Improving the understanding of the knowledge of climatic index is necessary to reduce the impacts of drought and to facilitate quick decisions regarding this problem. The main objective is to analyze drought periods from 1950 to 2009 in Spain. We use several kinds of information, different formats, sources and transmission mode. We use satellite-based Vegetation Index, dryness index for several temporal periods. We use daily and monthly precipitation and temperature data and soil moisture data from numerical weather model. We calculate mainly Standardized Precipitation Index (SPI) that it has been used amply in the bibliography. We use OLAP-Mining techniques to discovery of association rules between remote-sensing, numerical weather model and climatic index. Time series Data- Mining techniques organize data as a sequence of events, with each event having a time of recurrence, to cluster the data into groups of records or cluster with similar characteristics. Prior climatological classification is necessary if we want to study drought periods over all Spain.

Economic Drought Impact on Agriculture: analysis of all agricultural sectors affected

Science.gov (United States)

Gil, M.; Garrido, A.; Hernández-Mora, N.

2012-04-01

The analysis of drought impacts is essential to define efficient and sustainable management and mitigation. In this paper we present a detailed analysis of the impacts of the 2004-2008 drought in the agricultural sector in the Ebro river basin (Spain). An econometric model is applied in order to determine the magnitude of the economic loss attributable to water scarcity. Both the direct impacts of drought on agricultural productivity and the indirect impacts of drought on agricultural employment and agroindustry in the Ebro basin are evaluated. The econometric model measures losses in the economic value of irrigated and rainfed agricultural production, of agricultural employment and of Gross Value Added both from the agricultural sector and the agro-industrial sector. The explanatory variables include an index of water availability (reservoir storage levels for irrigated agriculture and accumulated rainfall for rainfed agriculture), a price index representative of the mix of crops grown in each region, and a time variable. The model allows for differentiating the impacts due to water scarcity from other sources of economic losses. Results show how the impacts diminish as we approach the macro-economic indicators from those directly dependent on water abstractions and precipitation. Sectors directly dependent on water are the most affected with identifiable economic losses resulting from the lack of water. From the management perspective implications of these findings are key to develop mitigation measures to reduce drought risk exposure. These results suggest that more open agricultural markets, and wider and more flexible procurement strategies of the agro-industry reduces the socio-economic exposure to drought cycles. This paper presents the results of research conducted under PREEMPT project (Policy relevant assessment of the socioeconomic effects of droughts and floods, ECHO - grant agreement # 070401/2010/579119/SUB/C4), which constitutes an effort to provide

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

Science.gov (United States)

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

2017-12-01

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

Flooding During Drought: Learning from Stakeholder Engagement & Partner Coordination in the California-Nevada Drought Early Warning System (DEWS)

Science.gov (United States)

Sheffield, A. M.

2017-12-01

After more than 5 years of drought, extreme precipitation brought drought relief in California and Nevada and presents an opportunity to reflect upon lessons learned while planning for the future. NOAA's National Integrated Drought Information System (NIDIS) California-Nevada Drought Early Warning System (DEWS) in June 2017 convened a regional coordination workshop to provide a forum to discuss and build upon past drought efforts in the region and increase coordination, collaboration and information sharing across the region as a whole. Participants included federal, tribal, state, academic, and local partners who provided a post-mortem on the recent drought and impacts as well as recent innovations in drought monitoring, forecasts, and decision support tools in response to the historic drought. This presentation will highlight lessons learned from stakeholder outreach and engagement around flooding during drought, and pathways for moving forward coordination and collaboration in the region. Additional focus will be on the potential opportunities from examining California decision making calendars from this drought. Identified gaps and challenges will also be shared, such as the need to connect observations with social impacts, capacity building around available tools and resources, and future drought monitoring needs. Drought will continue to impact California and Nevada, and the CA-NV DEWS works to make climate and drought science readily available, easily understandable and usable for decision makers; and to improve the capacity of stakeholders to better monitor, forecast, plan for and cope with the impacts of drought.

Drought assessment in the Duero basin (Central Spain) by means of multivariate extreme value statistics

Science.gov (United States)

Kallache, M.

2012-04-01

Droughts cause important losses. On the Iberian Peninsula, for example, non-irrigated agriculture and the tourism sector are affected in regular intervals. The goal of this study is the description of droughts and their dependence in the Duero basin in Central Spain. To do so, daily or monthly precipitation data is used. Here cumulative precipitation deficits below a threshold define meteorological droughts. This drought indicator is similar to the commonly used standard precipitation index. However, here the focus lies on the modeling of severe droughts, which is done by applying multivariate extreme value theory (MEVT) to model extreme drought events. Data from several stations are assessed jointly, thus the uncertainty of the results is reduced. Droughts are a complex phenomenon, their severity, spatial extension and duration has to be taken into account. Our approach captures severity and spatial extension. In general we find a high correlation between deficit volumes and drought duration, thus the duration is not explicitely modeled. We apply a MEVT model with asymmetric logistic dependence function, which is capable to model asymptotic dependence and independence (cf. Ramos and Ledford, 2009). To summarize the information on the dependence in the joint tail of the extreme drought events, we utilise the fragility index (Geluk et al., 2007). Results show that droughts also occur frequently in winter. Moreover, it is very common for one site to suffer dry conditions, whilst neighboring areas experience normal or even humid conditions. Interpolation is thus difficult. Bivariate extremal dependence is present in the data. However, most stations are at least asymptotically independent. The according fragility indices are important information for risk calculations. The emerging spatial patterns for bivariate dependence are mostly influenced by topography. When looking at the dependence between more than two stations, it shows that joint extremes can occur more

2000 Years of Drought Variability in Inner Asia from Tree Rings

Science.gov (United States)

Hessl, A. E.; Pederson, N.; Anchukaitis, K. J.; Leland, C.; Byambasuren, O.; Nachin, B.; Andreu-Hayles, L.

2015-12-01

Understanding connections between climate, ecosystems, and society during historical and modern climatic transitions requires annual resolution records with high fidelity climate signals. In semi-arid regions, high temperatures are projected to increase the frequency, duration, and severity of droughts in coming decades. Between 1996-2014, Mongolia experienced an extended drought that coincided with a transition away from pastoralism as thousands of families lost their herds and migrated to informal urban settlements. Because Mongolia's climate is highly variable, it is difficult to place recent climatic extremes and associated social and ecological change in context without long records of climatic variability. Here we ask: how extreme was the 21st century drought in the last 2000 years? We present two 2000 year long tree-ring reconstructions of warm-season drought, derived from live and dead Siberian pine (Pinus sibirica) trees from two lava flows in central Mongolia. Trees growing on the lava today are stunted and widely spaced, occurring on microsites with little to no soil development. These trees are water-stressed and their radial growth is correlated with both soil water availability (scPDSI) and grassland productivity (Normalized Difference Vegetation Index (NDVI)). To contextualize the severity of recent droughts and to explore potential forcing factors, we compare recent drought persistence to the distribution of events in the past and perform long control runs of GFDL climate model. Our reconstructions, calibrated and validated on instrumental June-August scPDSI (1959-2009) account for >55% of the variability in the regional scPDSI when >70% of the annual rainfall occurs. Our tree-ring data combined with existing reconstructions of temperature, meteorological data, and model results suggest that the early 21st century drought was the hottest and one of the most persistent droughts in the last 2000 years. These dry conditions were occurred with

Forecasting Vulnerability to Drought-related Mortality in Western US Forests

Science.gov (United States)

Buotte, P.; Law, B. E.; Hudiburg, T. W.

2017-12-01

Climate-driven tree mortality has been documented across the globe, and continued future mortality is expected. Such mortality could pose threats to ecosystem services, including carbon sequestration. Therefore, forecasting future mortality is critical. Ecosystem process models can be a tool for forecasting forest vulnerability to drought. We modified the Community Land Model (CLM4.5) to forecast forest vulnerability to drought-related mortality in the western US. We increased the ecological resolution by parameterizing CLM4.5 to recognize 14 different forest types common to the region. We used published physiological traits and tuned CLM4.5 to match present day above ground carbon stocks. We incorporated the influence of drought stress through species- or genus-specific controls on stomatal conductance given soil moisture and increased rates of leaf shed during prolonged periods of low soil moisture. We ran CLM4.5 at a 1/24 degree spatial resolution in offline mode using climate forcing data. We compare forest growth and carbon sequestration metrics (e.g. chronic reduction of GPP below its potential) between historical and future time periods to determine relevant metrics of vulnerability to drought-related mortality. Using the robust metrics, we will forecast and map future forest vulnerability to drought-related mortality given a range of climate scenarios.

WRF added value to capture the spatio-temporal drought variability

Science.gov (United States)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and

Climate and drought

Science.gov (United States)

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].

Extreme weather impacts on tropical mangrove forests in the Eastern Brazil Marine Ecoregion.

Science.gov (United States)

Servino, Ricardo Nogueira; Gomes, Luiz Eduardo de Oliveira; Bernardino, Angelo Fraga

2018-07-01

Extreme weather events are likely to become more frequent in the 21st century bringing significant impacts to coastal ecosystems. However, the capacity to detect and measure those impacts are still limited, with effects largely unstudied. In June 2016, a hailstorm with wind gusts of over 100 km·h -1 caused an unprecedented mangrove dieback on Eastern Brazil. To quantify the scale of impact and short-term recovery of mangroves (15-mo), we used satellite imagery and field sampling to evaluate changes in forest structure in control and impacted areas after the hailstorm. Satellite imagery revealed mangrove dieback in over 500 ha, corresponding to 29.3% of the total forest area suddenly impacted after the hailstorm. Fifteen months after the hailstorm, some impacted areas show an initial recovery, while others continued to degrade. The El Niño years of 2014-2016 created mild drought conditions in Eastern Brazil. As observed in wetlands of semi-arid regions during the same period, mangrove recovery may have been impaired by continued physiological stress and climate change effects. Economic losses in the study site from typical mangrove ecosystem services including food provision, climate regulation, raw materials and nurseries are estimated to at least US$ 792,624 yr -1 . This is the first evidence of an extreme weather impact on mangroves in Brazil that typically provide unique ecological and economic subsistence to coastal populations. Our results reveal that there is a pressing need for long-term monitoring and climate change adaptation actions for coastal wetlands in Brazil, and to provide broad estimates of ecosystem values associated with these ecosystems given many areas are already experiencing chronic stress from local impacts, drought and high temperatures. Copyright © 2018 Elsevier B.V. All rights reserved.

A hybrid framework for assessing maize drought vulnerability in Sub-Saharan Africa

Science.gov (United States)

Kamali, B.; Abbaspour, K. C.; Wehrli, B.; Yang, H.

2017-12-01

Drought has devastating impacts on crop yields. Quantifying drought vulnerability is the first step to better design of mitigation policies. The vulnerability of crop yield to drought has been assessed with different methods, however they lack a standardized base to measure its components and a procedure that facilitates spatial and temporal comparisons. This study attempts to quantify maize drought vulnerability through linking the Drought Exposure Index (DEI) to the Crop Failure Index (CFI). DEI and CFI were defined by fitting probability distribution functions to precipitation and maize yield respectively. To acquire crop drought vulnerability index (CDVI), DEI and CFI were combined in a hybrid framework which classifies CDVI with the same base as DEI and CFI. The analysis were implemented on Sub-Saharan African countries using maize yield simulated with the Environmental Policy Integrated Climate (EPIC) model at 0.5° resolution. The model was coupled with the Sequential Uncertainty Fitting algorithm for calibration at country level. Our results show that Central Africa and those Western African countries located below the Sahelian strip receive higher amount of precipitation, but experience high crop failure. Therefore, they are identified as more vulnerable regions compared to countries such as South Africa, Tanzania, and Kenya. We concluded that our hybrid approach complements information on crop drought vulnerability quantification and can be applied to different regions and scales.

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

DEFF Research Database (Denmark)

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...

Land-atmosphere interaction and disaster-causing process of drought in northern China: observation and experiment (DroughtPEX_China)

Science.gov (United States)

Li, Yaohui

2017-04-01

Drought is one of the most common and frequent nature disasters in the world, particularly in China under the continental monsoonal climate with great variation. About thirty percent of economic loss caused by natural disasters is contributed by droughts in China, which is by far the most damaging weather disasters because of its long duration and extensive hazard areas. Droughts not only have a serious impact on the agriculture, water resources, ecology, natural environment, but also seriously affect the socio-economic such as human health, energy and transportation. Worsely, under the background of climate change, droughts in show increases in frequency, duration and scope in many places around the world, particularly northern China. Nowadays, droughts have aroused extensive concern of the scientists, governments and international community, and became one of the important scientific issues in geoscience research. However, most of researches on droughts in China so far were focused on the causes or regulars of one type of droughts (the atmosphere, agriculture or hydrological) from the perspective of the atmospheric circulation anomalies. Few of them considered a whole cycle of the drought-forming process from atmosphere-land interaction to agricultural/ecological one in terms of the land-atmosphere interaction; meanwhile, the feedback mechanism with the drought and land-atmosphere interaction is still unclear as well. All of them is because of lack of the relevant comprehensive observation experiment. "Land-atmosphere interaction and disaster-causing process of drought in northern China: observation and experiment" (DroughtPEX_China)is just launched in this requirement and background. DroughtPEX_China is supported by Special Scientific Research Fund of Public Welfare Industry (Meteorological) of China (Grant No.GYHY201506001)—"Drought Meteorology Scientific Research Project—the disaster-causing process and mechanism of drought in northern China". This project

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

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Ana Rusmerg Giménez Ledesma

2013-05-01

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.

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

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

2010-01-01

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...

Global Drought Services: Collaborations Toward an Information System for Early Warning

Science.gov (United States)

Hayes, M. J.; Pulwarty, R. S.; Svoboda, M.

2014-12-01

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

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

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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.

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

Science.gov (United States)

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

2014-01-01

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.

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

Science.gov (United States)

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.

2017-12-01

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

Impact of drought on wildfires in Iberia

Science.gov (United States)

Russo, Ana; Gouveia, Célia M.; DaCamara, Carlos; Sousa, Pedro; Trigo, Ricardo M.

2015-04-01

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).

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

Science.gov (United States)

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

2017-12-01

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

A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

Science.gov (United States)

Yagci, Ali Levent; Santanello, Joseph A.; Rodell, Matthew; Deng, Meixia; Di, Liping

2018-01-01

The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

Impact of Drought on Groundwater and Soil Moisture - A Geospatial Tool for Water Resource Management

Science.gov (United States)

Ziolkowska, J. R.; Reyes, R.

2016-12-01

For many decades, recurring droughts in different regions in the US have been negatively impacting ecosystems and economic sectors. Oklahoma and Texas have been suffering from exceptional and extreme droughts in 2011-2014, with almost 95% of the state areas being affected (Drought Monitor, 2015). Accordingly, in 2011 alone, around 1.6 billion were lost in the agricultural sector alone as a result of drought in Oklahoma (Stotts 2011), and 7.6 billion in Texas agriculture (Fannin 2012). While surface water is among the instant indicators of drought conditions, it does not translate directly to groundwater resources that are the main source of irrigation water. Both surface water and groundwater are susceptible to drought, while groundwater depletion is a long-term process and might not show immediately. However, understanding groundwater availability is crucial for designing water management strategies and sustainable water use in the agricultural sector and other economic sectors. This paper presents an interactive geospatially weighted evaluation model and a tool at the same time to analyze groundwater resources that can be used for decision support in water management. The tool combines both groundwater and soil moisture changes in Oklahoma and Texas in 2003-2014, thus representing the most important indicators of agricultural and hydrological drought. The model allows for analyzing temporal and geospatial long-term drought at the county level. It can be expanded to other regions in the US and the world. The model has been validated with the Palmer Drought Index Severity Index to account for other indicators of meteorological drought. It can serve as a basis for an upcoming socio-economic and environmental analysis of drought events in the short and long-term in different geographic regions.

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

NARCIS (Netherlands)

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

2015-01-01

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

Tree mortality predicted from drought-induced vascular damage

Science.gov (United States)

Anderegg, William R.L.; Flint, Alan L.; Huang, Cho-ying; Flint, Lorraine E.; Berry, Joseph A.; Davis, Frank W.; Sperry, John S.; Field, Christopher B.

2015-01-01

The projected responses of forest ecosystems to warming and drying associated with twenty-first-century climate change vary widely from resiliency to widespread tree mortality1, 2, 3. Current vegetation models lack the ability to account for mortality of overstorey trees during extreme drought owing to uncertainties in mechanisms and thresholds causing mortality4, 5. Here we assess the causes of tree mortality, using field measurements of branch hydraulic conductivity during ongoing mortality in Populus tremuloides in the southwestern United States and a detailed plant hydraulics model. We identify a lethal plant water stress threshold that corresponds with a loss of vascular transport capacity from air entry into the xylem. We then use this hydraulic-based threshold to simulate forest dieback during historical drought, and compare predictions against three independent mortality data sets. The hydraulic threshold predicted with 75% accuracy regional patterns of tree mortality as found in field plots and mortality maps derived from Landsat imagery. In a high-emissions scenario, climate models project that drought stress will exceed the observed mortality threshold in the southwestern United States by the 2050s. Our approach provides a powerful and tractable way of incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing climate.

Drought in the sertão as a natural or social phenomenon: establishing the Inspetoria Federal de Obras Contra as Secas, 1909-1923

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Eve Elizabeth Buckley

2010-01-01

Full Text Available This paper examines interpretations of the drought problem in Brazil's northeast sertão during the First Republic. It compares analysis of drought as primarily a natural or climatic phenomenon – embraced by civil engineers working for the Inspetoria [Federal] de Obras Contra as Secas (IFOCS – with analyses emphasizing social and political conditions that made drought a crisis for the sertanejo poor. The latter are evident in the report of doctors Belisário Penna and Artur Neiva describing their expedition through the sertão sponsored by IFOCS in 1912. This comparison allows for consideration of the intersection between natural (geographic, climatic and social (political, cultural factors that produced the region's periodic crisis. The analysis is informed by the work of social scientists who highlight the multi-dimensional causes underlying natural disasters in politically marginal communities. Technocrats' faith in the context-independent utility of their expertise lay at the heart of IFOCS's ultimate failure to rescue sertanejos from famine, migration and poverty. Because the drought agency's technical personnel never had the political will or muscle to confront the social organization underlying the sertão's recurrent calamity, their ability to alleviate the human suffering that droughts precipitated was severely limited.

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

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Rodrigo De Vecchi

2018-02-01

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

The Value of Information from a GRACE-Enhanced Drought Severity Index

Science.gov (United States)

Kuwayama, Y.; Bernknopf, R.; Macauley, M.; Brookshire, D.; Zaitchik, B. F.; Rodell, M.

2013-12-01

Water storage anomalies derived from the Gravity Recovery and Climate Experiment Data Assimilation System (GRACE-DAS) have been used to enhance the information contained in drought indicators. The potential value of this information is to inform local and regional decisions to improve economic welfare in the face of drought. Based on a characterization of current drought evaluations, a modeling framework has been structured to analyze the contributed value of the Earth observations in the assessment of the onset and duration of droughts and their regional impacts. The analysis focuses on (1) characterizing how GRACE-DAS provides Earth observation information for a drought warning, (2) assessing how a GRACE-DAS-enhanced U.S. Drought Monitor would improve economic outcomes in a region, and (3) applying this enhancement process in a decision framework to illustrate the potential role of GRACE data products in a recent drought and response scenario for a value-of-information (VOI) analysis. The VOI analysis quantifies the relative contribution of enhanced understanding and communication of the societal benefits associated with GRACE Earth observation science. Our emphasis is to illustrate the role of an enhanced National Integrated Drought Information System outlook on three key societal outcomes: effects on particular economic sectors, changes in land management decisions, and reductions in damages to ecosystem services.

The role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchments

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M. Van Tiel

2018-01-01

Full Text Available Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5. Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975–2004 and future (2071–2100 period. Two existing threshold approaches to define future droughts are employed: (1 the threshold from the historical period; (2 a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical

Fostering drought research and science-policy interfacing

NARCIS (Netherlands)

Lanen, van Henny A.J.; Tallaksen, Lena M.; Assimacopoulos, Dionysis; Stahl, Kerstin; Wolters, Wouter; Andreu, Joaquin; Seneviratne, Sonia I.; Stefano, De Lucia; Seidl, Irmi; Rego, Francisco Castro; Massarutto, Antonio; Garnier, Emmanuel

2015-01-01

The DROUGHT-R&SPI project adopted a transdisciplinary approach that combined drought analyses for six selected Case Studies across Europe with drought analyses at the pan-European scale both for past and future climates. Achievements on drought as natural hazard, drought impacts, responses

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

Science.gov (United States)

Meador, E.; Morrill, C.

2017-12-01

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.

Pathways Into and Out of the 2012-2016 California-Nevada Drought—Lessons for Future Drought and Drought Termination

Science.gov (United States)

Dettinger, M. D.

2017-12-01

Droughts in California have historically been a function of prolonged deficits of precipitation from the largest storms (much more so than from medium to weak storms), and drought endings typically reflect the return of those same large storms and more. The recent 2012-2016 drought in California followed this pattern, being bracketed by the extremely wet 2011 and 2017 water years, both brought about by the arrival of multiple major atmospheric river storms, and was marked by one of the episodic multi-year periods when these storms are diverted from the State by anomalous atmospheric circulations over the northeastern Pacific Ocean. The 2012-2016 episode was also marked by conditions that have been much less "normal" for California droughts, with record warm temperatures adding significantly to the drought and its impacts. Except in the highest mountains, these temperatures contributed as much to the drought potential as did precipitation deficits. The temperatures also led to record snow droughts that focused most in the low to middle altitude snowfields. Together the persistent precipitation deficits and high temperatures of this drought are a prescient example of a major drought with precipitation deficits emphasized at higher altitudes and temperature effects at lower altitudes. This drought ended with the remarkably wet 2017 water year, due to the arrival of a record number of large atmospheric river storms and associated precipitation. But this termination of precipitation drought was marked by its own flirtation with record-breaking "warm" snow drought conditions in late 2016 as well as by an eventual springtime snowpack that was very large but nowhere near as large as in other historical years with correspondingly large precipitation totals, especially at low to middle altitudes. These patterns of temperature-accentuated drought emphasized at lower altitudes and precipitation-driven droughts and drought endings emphasized at higher altitudes, both delineated

Examining the extreme 2017 spring drought event in South Korea using a suite of drought indices (SPI, SC-PDSI, SPEI, EDI)

Science.gov (United States)

Nam, W. H.; Hayes, M. J.; Svoboda, M. D.; Fuchs, B.; Tadesse, T.; Wilhite, D. A.; Hong, E. M.; Kim, T.

2017-12-01

South Korea has experienced extreme droughts in 1994-1995, 2000-2001, 2012, 2015, and 2016-2017. The 2017 spring drought (with especially low winter precipitation recorded in winter 2016) affected a large portion of central and western South Korea, and was one of the most severe droughts in the region since the 2000-2001 drought. The spring drought of 2017 was characterized by exceptionally low precipitation with total precipitation from January to June being 50% lower than the mean normal precipitation record (1981-2010) over most of western South Korea. It was the climatologically driest spring over the 1961-2016 record period. Effective drought monitoring and management depends on which drought indices are selected because each drought index has different drought criteria or levels of drought severity, associated with drought responses. In this study, for the quantitative analysis of the spring 2017 drought event in South Korea, four widely-used drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Self-Calibrated Palmer Drought Severity Index (SC-PDSI), and the Effective Drought Index (EDI) are compared with observed drought damaged areas in the context of agricultural drought impacts. The South Korean government (Ministry of Agriculture, Food and Rural Affairs (MAFRA) and Korea Rural Community Corporation (KRC)) has been operating a government-level drought monitoring system since 2016. Results from this study can be used to improve the drought monitoring applications, as well as drought planning and preparedness in South Korea.

Developing Drought Outlook Forums in Support of a Regional Drought Early Warning Information System

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Mcnutt, C. A.; Pulwarty, R. S.; Darby, L. S.; Verdin, J. P.; Webb, R. S.

2011-12-01

The National Integrated Drought Information System (NIDIS) Act of 2006 (P.L. 109-430) charged NIDIS with developing the leadership and partnerships necessary to implement an integrated national drought monitoring and forecasting system that creates a drought "early warning system". The drought early warning information system should be capable of providing accurate, timely and integrated information on drought conditions at the relevant spatial scale to facilitate proactive decisions aimed at minimizing the economic, social and ecosystem losses associated with drought. As part of this effort, NIDIS has held Regional Drought Outlook Forums in several regions of the U.S. The purpose of the Forums is to inform practices that reduce vulnerability to drought through an interactive and collaborative process that includes the users of the information. The Forums have focused on providing detailed assessments of present conditions and impacts, comparisons with past drought events, and seasonal predictions including discussion of the state and expected evolution of the El Niño Southern Oscillation phenomena. Regional Climate Outlook Forums (RCOFs) that include close interaction between information providers and users are not a new concept, however. RCOFs started in Africa in the 1990s in response to the 1997-98 El Niño and have since expanded to South America, Asia, the Pacific islands, and the Caribbean. As a result of feedback from the RCOFs a large body of research has gone into improving seasonal forecasts and the capacity of the users to apply the information in a way that improves their decision-making. Over time, it has become clear that more is involved than just improving the interaction between the climate forecasters and decision-makers. NIDIS is using the RCOF approach as one component in a larger effort to develop Regional Drought Early Warning Information Systems (RDEWS) around the U.S. Using what has been learned over the past decade in the RCOF process

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

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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...

Projected drought risk in 1.5°C and 2°C warmer climates

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Lehner, F.; Coats, S.; Stocker, T. F.; Pendergrass, A. G.; Sanderson, B. M.; Raible, C.; Smerdon, J. E.

2017-12-01

The large socioeconomic costs of droughts make them a crucial target for impact assessments of climate change scenarios. Using multiple drought metrics and a set of simulations with the Community Earth System Model (CESM) targeting 1.5°C and 2°C above preindustrial global mean temperatures, we investigate changes in aridity and the risk of consecutive drought years. The latter metric is motivated by recent droughts in California and the US Southwest in general, where consecutive years of moderate precipitation deficit can quickly lead to significant drought and elevated pressure on water resources. If warming is limited to 2°C, these simulations suggest little change in drought risk for the U.S. Southwest and Central Plains compared to present day, an interesting result that arises from a delicate balance between increases in evaporative demand and precipitation in CESM in that region. In the Mediterranean, central Europe, and a number of other regions across the globe, however, drought risk increases significantly for both 1.5°C and 2°C warming targets, and the additional 0.5°C of the 2°C climate leads to significantly higher drought risk. Our study suggests that limiting anthropogenic warming to 1.5°C rather than 2°C, as aspired to by the Paris Climate Agreement, may have benefits for future drought risk but that such benefits may be regional and in some cases highly uncertain. We will therefore also discuss the robustness of results across different drought metrics as well as the model uncertainties associated with drought projections for low warming targets.

Assessing the utility of meteorological drought indices in monitoring summer drought based on soil moisture in Chongqing, China

Science.gov (United States)

Chen, Hui; Wu, Wei; Liu, Hong-Bin

2018-04-01

Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index ( M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M ( M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years.

DROUGHTS IN THE TIETÊ-PARANÁ WATERWAY: IMPACTS ON THE DIRECT, INDIRECT AND HIDDEN COSTS IN THE TRANSPORTATION OF SOYBEAN.

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Rodrigo Carlo Toloi

2016-05-01

Full Text Available Brazil's agricultural economy is growing and increasing productivity. Therefore, it has required transportation systems with high load capacity and lower transportation costs. However, with the drought in the Southeast region of Brazil, the waterway Tietê-Paraná closed since May 2014 generating a loss of more than 30 million last year. Thus, this study investigates the impacts on direct, indirect and hidden costs resulting from this change of route for soy transport. The methodology consists of an exploratory, descriptive and bibliographic research that seeks to raise the main costs. The results show that failing to ensure the production of soybeans by the Tiete-Parana waterway and using the highway transportation costs for waterway users are increased by US$ 37,760,146.86.

Quantitative Trait Loci Associated with Drought Tolerance in Brachypodium distachyon

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Yiwei Jiang

2017-05-01

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.

Economics and societal considerations of drought

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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

2016-01-01

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...

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

Science.gov (United States)

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

2017-12-01

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.

Global hydrological droughts in the 21st century under a changing hydrological regime

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N. Wanders

2015-01-01

Full Text Available Climate change very likely impacts future hydrological drought characteristics across the world. Here, we quantify the impact of climate change on future low flows and associated hydrological drought characteristics on a global scale using an alternative drought identification approach that considers adaptation to future changes in hydrological regime. The global hydrological model PCR-GLOBWB was used to simulate daily discharge at 0.5° globally for 1971–2099. The model was forced with CMIP5 climate projections taken from five global circulation models (GCMs and four emission scenarios (representative concentration pathways, RCPs, from the Inter-Sectoral Impact Model Intercomparison Project. Drought events occur when discharge is below a threshold. The conventional variable threshold (VTM was calculated by deriving the threshold from the period 1971–2000. The transient variable threshold (VTMt is a non-stationary approach, where the threshold is based on the discharge values of the previous 30 years implying the threshold to vary every year during the 21st century. The VTMt adjusts to gradual changes in the hydrological regime as response to climate change. Results show a significant negative trend in the low flow regime over the 21st century for large parts of South America, southern Africa, Australia and the Mediterranean. In 40–52% of the world reduced low flows are projected, while increased low flows are found in the snow-dominated climates. In 27% of the global area both the drought duration and the deficit volume are expected to increase when applying the VTMt. However, this area will significantly increase to 62% when the VTM is applied. The mean global area in drought, with the VTMt, remains rather constant (11.7 to 13.4%, compared to the substantial increase when the VTM is applied (11.7 to 20%. The study illustrates that an alternative drought identification that considers adaptation to an altered hydrological regime has a