Observations of cloud and rainfall enhancement over irrigated agriculture in an arid environment

Science.gov (United States)

Garcia-Carreras, Luis; Marsham, John H.; Spracklen, Dominick V.

2017-04-01

The impact of irrigated agriculture on clouds and rainfall remains uncertain, particularly in less studied arid regions. Irrigated crops account for 20% of global cropland area, and non-renewable groundwater accounts for 20% of global irrigation water demand. Quantifying the feedbacks between agriculture and the atmosphere are therefore not only necessary to better understand the climate impacts of land-use change, but are also crucial for predicting long-term water use in water-scarce regions. Here we use high spatial-resolution satellite data to show the impact of irrigated crops in the arid environment of northern Saudi Arabia on cloud cover and rainfall patterns. Land surface temperatures over the crops are 5-10 K lower than their surroundings, linked to evapotranspiration rates of up to 20 mm/ month. Daytime cloud cover is up to 30% higher over the cropland compared to its immediate surroundings, and this enhancement is highly correlated with the seasonal variability in leaf area index. The cloud enhancement is associated with a much more rapid cloud cloud development during the morning. Afternoon rainfall is 85% higher over, and just downwind, of the cropland during the growing season, although rainfall remains very low in absolute terms. The feedback sign we find is the opposite to what has been observed in tropical and semiarid regions, where temperature gradients promote convergence and clouds on the warmer side of land-surface type discontinuities. This suggests that different processes are responsible for the land-atmosphere feedback in very dry environments, where lack of moisture may be a stronger constraint. Increased cloud and rainfall, and associated increases in diffuse radiation and reductions in temperature, can affect vegetation growth thus producing an internal feedback. These effects will therefore need to be taken into account to properly assess the impact of climate change on crop productivity and water use, as well as how global land

Effects of Climate Change on the Yield and Cropping Area of Major Food Crops: A Case of Bangladesh

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Md. Ruhul Amin

2015-01-01

Full Text Available The crops that we grow for food need specific climatic conditions to show better performance in view of economic yield. A changing climate could have both beneficial and harmful effects on crops. Keeping the above view in mind, this study is undertaken to investigate the impacts of climate change (viz. changes in maximum temperature, minimum temperature, rainfall, humidity and sunshine on the yield and cropping area of four major food crops (viz. Aus rice, Aman rice, Boro rice and wheat in Bangladesh. Heteroskedasticity and autocorrelation consistent standard error (HAC and feasible generalized least square (FGLS methods were used to determine the climate-crop interrelations using national level time series data for the period of 1972–2010. Findings revealed that the effects of all the climate variables have had significant contributions to the yield and cropping area of major food crops with distinct variation among them. Maximum temperature statistically significantly affected all the food crops’ yield except Aus rice. Maximum temperature also insignificantly affected cropping area of all the crops. Minimum temperature insignificantly affected Aman rice but benefited other three crops’ yield and cropping area. Rainfall significantly benefitted cropping area of Aus rice, but significantly affected both yield and cropping area of Aman rice. Humidity statistically positively contributed to the yield of Aus and Aman rice but, statistically, negatively influenced the cropping area of Aus rice. Sunshine statistically significantly benefitted only Boro rice yield. Overall, maximum temperature adversely affected yield and cropping area of all the major food crops and rainfall severely affected Aman rice only. Concerning the issue of climate change and ensuring food security, the respective authorities thus should give considerable attention to the generation, development and extension of drought (all major food crops and flood (particularly Aman

Effect of Climate Variability on Crop Income in Central Ethiopia

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Arega Shumetie Ademe

2017-12-01

Full Text Available Ethiopian agriculture is a vulnerable sector from effects of climate variability. This study identified how strong is the effect of climate variability on smallholders’ crop income in Central highlands and Arssi grain plough farming systems of the country. The unbalanced panel data (1994-2014 of the study collected for eight rounds analysed through fixed effect regression. The model result shows that successive increment of crop season rainfall keeping the temperature constant has negative and significant effect on households’ crop income in the study area. The crop income responds similarly for temperature increment if the rainfall remains constant. Given this, simultaneous increment of the two climate related inputs has positive and significant effect on crop income. Other variables like flood, frost, storm, and rainfall inconsistency in the onset and cessation time affected households’ crop income negatively and significantly. Similarly, draught power and human labour, which are critical inputs in the crop production of Ethiopian smallholders, have positive and significant effect on crop income as to the model result. Thus, this study recommended that there should be supplementing the rainfall through irrigation, check dam and other activities to have consistent water supply for the crop production that enable smallholders to collect better income. Additionally, negative effect of temperature increment should be curved through adopting long lasting strategies like afforestation.

Recent trends in rainfall and temperature over North West India during 1871-2016

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Saxena, Rani; Mathur, Prasoon

2018-03-01

Rainfall and temperature are the most important environmental factors influencing crop growth, development, and yield. The northwestern (NW) part of India is one of the main regions of food grain production of the country. It comprises of six meteorological subdivisions (Haryana, Punjab, West Rajasthan, East Rajasthan, Gujarat and Saurashtra, Kutch and Diu). In this study, attempts were made to study variability and trends in rainfall and temperature during 30-year climate normal periods (CN) and 10-year decadal excess or deficit rainfall frequency during the historical period from 1871 to 2016. The Mann-Kendall and Spearman's rank correlation (Spearman's rho) tests were used to determine significance of trends. Least square linear fitting method was adopted to find out the slopes of the trend lines. The long-term mean annual rainfall over North West India is 587.7 mm (standard deviation of 153.0 mm and coefficient of variation 26.0). There was increasing trend in minimum and maximum temperatures during post monsoon season in entire study period and current climate normal period (1991-2016) due to which the sowing of rabi season crops may be delayed and there may be germination problem too. There was a non-significant decreasing trend in rainfall during monsoon season and an increasing trend in rainfall during post monsoon over North West India during entire study period. During current CN5 (1991-2016), all the subdivision (except the Saurashtra region) showed a decreasing trend in rainfall during monsoon season which is a matter of concern for kharif crops and those rabi crops which are grown as rainfed on conserved soil moisture. The decadal annual and seasonal frequencies of excess and deficit years results revealed that the annual total deficit rainfall years (24) exceeded total excess rainfall years (22) in North West India during the entire study period. While during the current decadal period (2011 to 2016), single year was the excess year and 2 years were

A stochastic assessment of the effect of global warming on rainfall ...

African Journals Online (AJOL)

Crop production depends on rainfall, and rainfall is affected by extreme weather conditions. Markov chain and time series model are adapted for the study of the pattern of rainfall in the North Central Region of Nigeria. Results reveal the long run distributions of the dry and wet days to be 0.7841, and 0.2159 respectively.

Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

Science.gov (United States)

Amikuzuno, J.

2012-12-01

Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

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Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2016-04-01

Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

Contribution of landfalling tropical system rainfall to the hydroclimate of the eastern U.S. Corn Belt 1981–2012

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Olivia Kellner

2016-09-01

Landfalling tropical system rainfall accounts for approximately 20% of the observed monthly rainfall during the tropical storm season (June–November across the eastern U.S. Corn Belt (1981–2012. Correlation between the annual number of landfalling tropical systems and annual yield by state results in no relationship, but correlation of August monthly observed rainfall by climate division to crop reporting district annual yields has a weak to moderate, statistically significant correlation in Ohio districts 30–60 and Indiana CRD 90. ANOVA analysis suggests that landfalling tropical rainfall may actually reduce yields in some state's climate divisions/crop reporting districts while increasing yield in others. Results suggest that there is a balance between landfalling tropical storms providing sufficient rainfall or too much rainfall to be of benefit to crops. Findings aim to provide information to producers, crop advisers, risk managers and commodity groups so that seasonal hurricane forecasts can potentially be utilized in planning for above or below normal precipitation during phenologically important portions of the growing season.

Rainfall Variability and its Implications for the Transferability of ...

African Journals Online (AJOL)

Mosrof agrj~ultural qctivities in semi-arid areqs of Tanzania ,d~pend on direct rainfall: Conse-, quently, any significant variation in /he temporal and spatial distribution of rainfall usually results in serious shortage of sQil~water available to plants and thus poor crop and livestock production. In this paper the variafJility and ...

10 Characterisation of Seasonal Rainfall.cdr

African Journals Online (AJOL)

Administrator

El Nino-South Oscillation (ENSO) phenomenon occurs in the Equatorial Eastern Pacific Ocean and has been noted to ... of crops. There is need for more research attention on the onset of rainfall and ... impacts of adverse weather conditions or.

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

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Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the

Analysis of historical rainfall data and associated risks on rain-fed tef ...

African Journals Online (AJOL)

The central theme for this paper is studying the rainfall behavior over the past six decades in relation to the major rainfall induced risks for the rain-fed “tef” production system using 59 years of rainfall data. Risk of dry spell during germination and flowering is computed whereas crop water requirement satisfaction index is ...

How can we improve Mediterranean cropping systems?

DEFF Research Database (Denmark)

Benlhabib, O.; Yazar, A.; Qadir, M.

2014-01-01

In the Mediterranean region, crop productivity and food security are closely linked to the adaptation of cropping systems to multiple abiotic stresses. Limited and unpredictable rainfall and low soil fertility have reduced agricultural productivity and environmental sustainability. For this reason...... the tested interventions, incorporation of crop residues coupled with supplementary irrigation showed a significantly positive effect on crop productivity, yield stability and environmental sustainability....

Crop and varietal diversification of rainfed rice based cropping systems for higher productivity and profitability in Eastern India.

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Lal, B; Gautam, Priyanka; Panda, B B; Raja, R; Singh, Teekam; Tripathi, R; Shahid, M; Nayak, A K

2017-01-01

Rice-rice system and rice fallows are no longer productive in Southeast Asia. Crop and varietal diversification of the rice based cropping systems may improve the productivity and profitability of the systems. Diversification is also a viable option to mitigate the risk of climate change. In Eastern India, farmers cultivate rice during rainy season (June-September) and land leftovers fallow after rice harvest in the post-rainy season (November-May) due to lack of sufficient rainfall or irrigation amenities. However, in lowland areas, sufficient residual soil moistures are available in rice fallow in the post-rainy season (November-March), which can be utilized for raising second crops in the region. Implementation of suitable crop/varietal diversification is thus very much vital to achieve this objective. To assess the yield performance of rice varieties under timely and late sown conditions and to evaluate the performance of dry season crops following them, three different duration rice cultivars were transplanted in July and August. In dry season several non-rice crops were sown in rice fallow to constitute a cropping system. The results revealed that tiller occurrence, biomass accumulation, dry matter remobilization, crop growth rate, and ultimately yield were significantly decreased under late transplanting. On an average, around 30% yield reduction obtained under late sowing may be due to low temperature stress and high rainfall at reproductive stages of the crop. Dry season crops following short duration rice cultivars performed better in terms of grain yield. In the dry season, toria was profitable when sown earlier and if sowing was delayed greengram was suitable. Highest system productivity and profitability under timely sown rice may be due to higher dry matter remobilization from source to sink. A significant correlation was observed between biomass production and grain yield. We infer that late transplanting decrease the tiller occurrence and assimilate

Biofuel crops with CAM photosynthesis: Economic potential on moisture-limited lands

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Bartlett, Mark; Hartzell, Samantha; Porporato, Amilcare

2017-04-01

As the demand for food and renewable energy increases, the intelligent utilization of marginal lands is becoming increasingly critical. In marginal lands classified by limited rainfall or soil salinity, the cultivation of traditional C3 and C4 photosynthesis crops often is economically infeasible. However, in such lands, nontraditional crops with crassulacean acid metabolism (CAM) photosynthesis show great economic potential for cultivation. CAM crops including Opuntia (prickly pear) and Ananas (pineapple) achieve a water use efficiency which is three fold higher than C4 crops such as corn and 6-fold higher than C3 crops such as wheat, leading to a comparable annual productivity with only 20% of the water demand. This feature, combined with a shallow rooting depth and a high water storage capacity, allows CAM plants to take advantage of small, infrequent rainfall amounts in shallow, quickly draining soils. Furthermore, CAM plants typically have properties (e.g., high content of non-structural carbohydrates) that are favorable for biofuel production. Here, for marginal lands characterized by low soil moisture availability and/or high salinity, we assess the potential productivity and economic benefits of CAM plants. CAM productivity is estimated using a recently developed model which simulates CAM photosynthesis under a range of soil and climate conditions. From these results, we compare the energy and water resource inputs required by CAM plants to those required by more traditional C3 and C4 crops (corn, wheat, sorghum), and we evaluate the economic potential of CAM crops as sources of food, fodder, or biofuel in marginal soils. As precipitation events become more intense and infrequent, we show that even though marginal land area may increase, CAM crop cultivation shows great promise for maintaining high productivity with minimal water inputs. Our analysis indicates that on marginal lands, widespread cultivation of CAM crops as biofuel feedstock may help

Adaptability and performance of short-season maize hybrids in the southern high plains

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Drought incidences change with year and location, and are prevalent in the Southern High Plains where annual rainfall is low and highly variable and most maize and other crops are irrigated. The low rainfall and groundwater overuse are leading to shortages of water for crop irrigation in this regio...

The impact of Indian Ocean high pressure system on rainfall and stream flow

International Nuclear Information System (INIS)

Rehman, S.; Nasir, H.; Zia, S.S.; Ansari, W.A.; Salam, K.; Tayyab, N.

2012-01-01

Centre of Action approach is very useful in getting insight of rainfall and stream flow variability of specific region. Hameed et al. showed that Inter-annual variability of Gulf Stream north wall is influenced by low Icelandic pressure system and has more statistically significant correlation than North Atlantic Oscillation (NAO) with longitude of Icelandic low. This study also aims to explore possible relationships between rainfall and stream flow in Collie river catchment in Southwest Western Australia (SWWA) with Indian Ocean high pressure dynamics. The relationship between rainfall and stream flow with Indian Ocean high pressure system have been investigated using correlation analysis for early winter season (MJJA), lag correlation for MJJA versus SOND rainfall and stream flow are also calculated and found significant at 95% confidence level. By investigating the relationship between COA indices with rainfall and stream flow over the period 1976-2008, significant correlations suggests that rainfall and stream flow in Collie river basin is strongly influenced by COA indices. Multiple correlations between rainfall and stream flow with Indian Ocean high pressure (IOHPS and IOHLN) is 0.7 and 0.6 respectively. Centers of Action (COA) indices explain 51% and 36% of rainfall and stream flow respectively. The correlation between rainfall and stream flow with IOHPS is -0.4 and -0.3 whereas, with IOHLN is -0.47 and -0.52 respectively. (author)

High-Resolution Discharge Forecasting for Snowmelt and Rainfall Mixed Events

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Tomasz Berezowski

2018-01-01

Full Text Available Discharge events induced by mixture of snowmelt and rainfall are strongly nonlinear due to consequences of rain-on-snow phenomena and snowmelt dependence on energy balance. However, they received relatively little attention, especially in high-resolution discharge forecasting. In this study, we use Random Forests models for 24 h discharge forecasting in 1 h resolution in a 105.9 km 2 urbanized catchment in NE Poland: Biala River. The forcing data are delivered by Weather Research and Forecasting (WRF model in 1 h temporal and 4 × 4 km spatial resolutions. The discharge forecasting models are set in two scenarios with snowmelt and rainfall and rainfall only predictors in order to highlight the effect of snowmelt on the results (both scenarios use also pre-forecast discharge based predictors. We show that inclusion of snowmelt decrease the forecast errors for longer forecasts’ lead times. Moreover, importance of discharge based predictors is higher in the rainfall only models then in the snowmelt and rainfall models. We conclude that the role of snowmelt for discharge forecasting in mixed snowmelt and rainfall environments is in accounting for nonlinear physical processes, such as initial wetting and rain on snow, which cannot be properly modelled by rainfall only.

Historical and future seasonal rainfall variability in Nusa Tenggara Barat Province, Indonesia: Implications for the agriculture and water sectors

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Dewi G.C. Kirono

2016-01-01

Full Text Available Climate change impacts are most likely to be felt by resource-dependent communities, and consequently locally-relevant data are necessary to inform livelihood adaptation planning. This paper presents information for historical and future seasonal rainfall variability in Nusa Tenggara Barat (NTB Province, Indonesia, where rural livelihoods are highly vulnerable to current climate variability and future change. Historical rainfall variability is investigated using observational data from two stations located on the islands of Lombok and Sumbawa. Future rainfall is examined using an ensemble of six downscaled climate model simulations at a spatial resolution of 14 km for 1971–2100, applying the IPCC SRES-A2 ‘Business as Usual’ emissions scenario, and the six original global climate models (GCMs. Analyses of the observed seasonal rainfall data highlight cyclical variability and long-term declines. The observed periodicities are of about 2–4, 5, 8, 11, and 40–50 years. Furthermore, dry season rainfall is significantly correlated with the El Niño Southern Oscillation (ENSO, while wet season rainfall is weakly correlated with ENSO. The simulated rainfall data reproduce the observed seasonal cycle very well, but overestimate the magnitude of rainfall and underestimate inter-annual rainfall variability. The models also show that the observed rainfall periodicities will continue throughout the 21st century. The models project that rainfall will decline, although with wide ranges of uncertainty, depending on season and location. Crop water demand estimates show that the projected changes will potentially impact the first growing period for rice during November–March. Rainfall may also be insufficient to meet water demand for many crops in the second growing period of March–June, when high value commodities such as chillies and tobacco are produced. The results reinforce the importance to consider all uncertainties when utilizing climate

Crop responses to climatic variation

DEFF Research Database (Denmark)

Porter, John R.; Semenov, Mikhail A.

2005-01-01

The yield and quality of food crops is central to the well being of humans and is directly affected by climate and weather. Initial studies of climate change on crops focussed on effects of increased carbon dioxide (CO2) level and/or global mean temperature and/or rainfall and nutrition on crop...... production. However, crops can respond nonlinearly to changes in their growing conditions, exhibit threshold responses and are subject to combinations of stress factors that affect their growth, development and yield. Thus, climate variability and changes in the frequency of extreme events are important...... for yield, its stability and quality. In this context, threshold temperatures for crop processes are found not to differ greatly for different crops and are important to define for the major food crops, to assist climate modellers predict the occurrence of crop critical temperatures and their temporal...

Climate Variability and Change in Bihar, India: Challenges and Opportunities for Sustainable Crop Production

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Kindie Tesfaye

2017-11-01

Full Text Available Climate change and associated uncertainties have serious direct and indirect consequences for crop production and food security in agriculture-based developing regions. Long-term climate data analysis can identify climate risks and anticipate new ones for planning appropriate adaptation and mitigation options. The aim of this study was to identify near-term (2030 and mid-term (2050 climate risks and/or opportunities in the state of Bihar, one of India’s most populous and poorest states, using weather data for 30 years (1980–2009 as a baseline. Rainfall, maximum and minimum temperatures, and evapotranspiration will all increase in the near- and mid-term periods relative to the baseline period, with the magnitude of the change varying with time, season and location within the state. Bihar’s major climate risks for crop production will be heat stress due to increasing minimum temperatures in the rabi (winter season and high minimum and maximum temperatures in the spring season; and intense rainfall and longer dry spells in the kharif (monsoon season. The increase in annual and seasonal rainfall amounts, and extended crop growing period in the kharif season generally provide opportunities; but increasing temperature across the state will have considerable negative consequences on (staple crops by affecting crop phenology, physiology and plant-water relations. The study helps develop site-specific adaptation and mitigation options that minimize the negative effects of climate change while maximizing the opportunities.

Estimating Vegetation Rainfall Interception Using Remote Sensing Observations at Very High Resolution

Science.gov (United States)

Cui, Y.; Zhao, P.; Hong, Y.; Fan, W.; Yan, B.; Xie, H.

2017-12-01

Abstract: As an important compont of evapotranspiration, vegetation rainfall interception is the proportion of gross rainfall that is intercepted, stored and subsequently evaporated from all parts of vegetation during or following rainfall. Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss estimation using remote sensing observations at the regional scale, and has been applied and validated in the upper reach of the Heihe River Basin of China for different types of vegetation. To eliminate the scale error and the effect of mixed pixels, the RS-Gash model is applied at a fine scale of 30 m with the high resolution vegetation area index retrieved by using the unified model of bidirectional reflectance distribution function (BRDF-U) for the vegetation canopy. Field validation shows that the RMSE and R2 of the interception ratio are 3.7% and 0.9, respectively, indicating the model's strong stability and reliability at fine scale. The temporal variation of vegetation rainfall interception loss and its relationship with precipitation are further investigated. In summary, the RS-Gash model has demonstrated its effectiveness and reliability in estimating vegetation rainfall interception. When compared to the coarse resolution results, the application of this model at 30-m fine resolution is necessary to resolve the scaling issues as shown in this study. Keywords: rainfall interception; remote sensing; RS-Gash analytical model; high resolution

Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

Science.gov (United States)

Guo, Qinghua; Wu, Fangfang; Pang, Shuxin; Zhao, Xiaoqian; Chen, Linhai; Liu, Jin; Xue, Baolin; Xu, Guangcai; Li, Le; Jing, Haichun; Chu, Chengcai

2018-03-01

With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis. As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging (LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional (3D) data accurately, and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China, we developed a high-throughput crop phenotyping platform, named Crop 3D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs, functions and testing results of the Crop 3D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.

Impact of Erratic Rainfall from Climate Change on Pulse Production Efficiency in Lower Myanmar

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Sein Mar

2018-02-01

Full Text Available Erratic rainfall has a detrimental impact on crop productivity but rainfall during the specific growth stage is rarely used in efficiency analysis. This study focuses on this untapped point and examines the influence of rainfall specifically encountered during the sowing stage and early vegetative growth stage and the flowering stage of pulses on productivity and efficiency in Lower Myanmar using data from 182 sample farmers. The results of a stochastic frontier production function reveal that rainfall incidence during the flowering season of pulses has a negatively significant effect on yield while replanting crops after serious damage by rain increases productivity. Controlled rainfall variables, seed rate, human labor and land preparation cost are important parameters influencing pulses yield. In the efficiency model, levels of yield loss have a negative impact while being a male household head, access to government credit, access to training, locating farms in the Bago Region and possessing a large area of pulses have a positively significant effect on technical efficiency. Policy recommendations include the establishment of a safety network, such as crop insurance to protect farmers from losses due to unpredictable weather conditions, promoting training programs on cultural practices adapted to climate change, wide coverage of extension activities, giving priority to small-scale farmers and female farmer participation in training and extension activities and increasing the rate of credit availability to farmers.

Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

Science.gov (United States)

Gao, S.; Fang, N. Z.

2017-12-01

A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher

Impacts of manure application on soil environment, rainfall use efficiency and crop biomass under dryland farming.

Science.gov (United States)

Wang, Xiaojuan; Jia, Zhikuan; Liang, Lianyou; Yang, Baoping; Ding, Ruixia; Nie, Junfeng; Wang, Junpeng

2016-02-12

Because of inadequate nutrient and water supply, soils are often unproductive in Northwest China. We studied the effects of manure application at low (LM 7.5  t ha(-1)), medium (MM 15 t ha(-1)), and high (HM 22.5 t ha(-1)) rates combined with fixed levels of chemical fertilizers on maize growth and rainfall use efficiency compared with chemical fertilizers (CK) under semi-arid conditions over a three-year period. HM and MM treatments could significantly increase soil water storage (0-120 cm) at tasseling stage of maize compared with LM treatment and CK (P < 0.05). Dry matter accumulation and rainfall use efficiency increased as manure application rate increasing (P < 0.05). HM treatment significantly increased rainfall use efficiency by 6.5-12.7% at big trumpeting - tasseling stage compared with LM and MM treatments. HM and MM treatments increased rainfall use efficiency by 8.6-18.1% at tasseling - grain filling stage compared with CK. There was no significant difference on biomass between HM and MM treatments at grain filling and maturity stages of maize in 2009 and 2010.

Effects of Weather Variability on Crop Abandonment

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Kelvin Mulungu

2015-03-01

Full Text Available In Zambia, every year some parts of the maize fields are abandoned post-planting. Reasons for this are not clearly known. In this paper, we examine the influence of soil and climatic factors on crop abandonment using a six-year (2007–2012 panel data by modeling the planted-to-harvested ratio (a good indicator of crop abandonment using a fractional and linear approach. Therefore, for the first time, our study appropriately (as supported by the model specification tests that favour fractional probit over linear models the fractional nature of crop abandonment. Regression results, which are not very different between the two specifications, indicate that, more than anything, high rainfall immediately after planting and inadequate fertilizer are the leading determinants of crop abandonment. In the agro-ecological region where dry planting takes place, low temperature during planting months negatively affects the harvested area. The results have implications on the sustainability of farming systems in the face of a changing climate.

Water Conservation Education with a Rainfall Simulator.

Science.gov (United States)

Kok, Hans; Kessen, Shelly

1997-01-01

Describes a program in which a rainfall simulator was used to promote water conservation by showing water infiltration, water runoff, and soil erosion. The demonstrations provided a good background for the discussion of issues such as water conservation, crop rotation, and conservation tillage practices. The program raised awareness of…

Plant calendar pattern based on rainfall forecast and the probability of its success in Deli Serdang regency of Indonesia

Science.gov (United States)

Darnius, O.; Sitorus, S.

2018-03-01

The objective of this study was to determine the pattern of plant calendar of three types of crops; namely, palawija, rice, andbanana, based on rainfall in Deli Serdang Regency. In the first stage, we forecasted rainfall by using time series analysis, and obtained appropriate model of ARIMA (1,0,0) (1,1,1)12. Based on the forecast result, we designed a plant calendar pattern for the three types of plant. Furthermore, the probability of success in the plant types following the plant calendar pattern was calculated by using the Markov process by discretizing the continuous rainfall data into three categories; namely, Below Normal (BN), Normal (N), and Above Normal (AN) to form the probability transition matrix. Finally, the combination of rainfall forecasting models and the Markov process were used to determine the pattern of cropping calendars and the probability of success in the three crops. This research used rainfall data of Deli Serdang Regency taken from the office of BMKG (Meteorologist Climatology and Geophysics Agency), Sampali Medan, Indonesia.

Characterization of rainfall in the central South African Highveld for application in water harvesting

NARCIS (Netherlands)

Zerizghy, M.G.; Rensburg, van L.D.; Stigter, C.J.

2012-01-01

In-field rainwater harvesting (IRWH), a runoff farming system, is a beneficial water management technique for crop production in arid and semi-arid areas. In-field rainwater harvesting is influenced by rainfall characteristics, and hence this study aimed to identify and characterize rainfall events,

Yields of Selected Catch Crops in Dry Conditions

Directory of Open Access Journals (Sweden)

Martina Handlířová

2016-01-01

Full Text Available Catch crops mainly reduce soil erosion and leaching of nutrients as well as enrich the soil organic matter. The aim of this research is to evaluate the yields of catch crops of Sinapis alba, Phacelia tanacetifolia, Fagopyrum esculentum, Carthamus tinctorius and Secale cereale v. multicaule, and thus determine the possible applicability of catch crops in areas with high average annual temperature and low precipitation totals. The small-plot field experiment was performed on clay-loam gleyic fluvisol at the Field Experimental Station in Žabčice, Southern Moravia, Czech Republic, within the period of 2006-2014. The catch crops were set up after winter wheat in mid-August. The results have shown a statistically significant difference among different catch crops in yield of dry matter and even among years. The yield of catch crops is mainly dependent on a sufficient supply of water in the soil and the appropriate amount and distribution of rainfall over the growing season. Sinapis alba and Phacelia tanacetifolia regularly reached the highest yields. High yields were also achieved with Fagopyrum esculentum. Due to the method of crop rotation in the Czech Republic, with a predominance of Brassica napus var. napus, it is inappropriate to include Sinapis alba. It is the best to grow Phacelia tanacetifolia and even Fagopyrum esculentum, or a mixture thereof, depending on the use of catch crops.

THE EFFECTS OF CLIMATIC VARIABLES AND CROP AREA ON MAIZE YIELD AND VARIABILITY IN GHANA

Directory of Open Access Journals (Sweden)

Henry De-Graft Acquah

2012-10-01

Full Text Available Climate change tends to have negative effects on crop yield through its influence on crop production. Understanding the relationship between climatic variables and crop area on the mean and variance of crop yield will facilitate development of appropriate policies to cope with climate change. This paper examines the effects of climatic variables and crop area on the mean and variance of maize yield in Ghana. The Just and Pope stochastic production function using the Cobb-Douglas functional form was employed. The results show that average maize yield is positively related to crop area and negatively related to rainfall and temperature. Furthermore, increase in crop area and temperature will enlarge maize yield variability while rainfall increase will decrease the variability in maize yield.

Estimation of runoff mitigation by morphologically different cover crop root systems

Science.gov (United States)

Yu, Yang; Loiskandl, Willibald; Kaul, Hans-Peter; Himmelbauer, Margarita; Wei, Wei; Chen, Liding; Bodner, Gernot

2016-07-01

Hydrology is a major driver of biogeochemical processes underlying the distinct productivity of different biomes, including agricultural plantations. Understanding factors governing water fluxes in soil is therefore a key target for hydrological management. Our aim was to investigate changes in soil hydraulic conductivity driven by morphologically different root systems of cover crops and their impact on surface runoff. Root systems of twelve cover crop species were characterized and the corresponding hydraulic conductivity was measured by tension infiltrometry. Relations of root traits to Gardner's hydraulic conductivity function were determined and the impact on surface runoff was estimated using HYDRUS 2D. The species differed in both rooting density and root axes thickness, with legumes distinguished by coarser axes. Soil hydraulic conductivity was changed particularly in the plant row where roots are concentrated. Specific root length and median root radius were the best predictors for hydraulic conductivity changes. For an intensive rainfall simulation scenario up to 17% less rainfall was lost by surface runoff in case of the coarsely rooted legumes Melilotus officinalis and Lathyrus sativus, and the densely rooted Linum usitatissimum. Cover crops with coarse root axes and high rooting density enhance soil hydraulic conductivity and effectively reduce surface runoff. An appropriate functional root description can contribute to targeted cover crop selection for efficient runoff mitigation.

Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India

Science.gov (United States)

Verma, Ram Ratan; Srivastava, Tapendra Kumar; Singh, Pushpa

2018-01-01

Assessment of variability in climate extremes is crucial for managing their aftermath on crops. Sugarcane (Saccharum officinarum L.), a major C4 crop, dominates the Upper Gangetic Plain (UGP) in India and is vulnerable to both direct and indirect effects of changes in temperature and rainfall. The present study was taken up to assess the weekly, monthly, seasonal, and annual trends of rainfall and temperature variability during the period 1956-2015 (60 years) for envisaging the probabilities of different levels of rainfall suitable for sugarcane in UGP in the present climate scenario. The analysis revealed that 87% of total annual rainfall was received during southwest monsoon months (June-September) while post-monsoon (October to February) and pre-monsoon months (March-May) accounted for only 9.4 and 3.6%, respectively. There was a decline in both monthly and annual normal rainfall during the period 1986-2015 as compared to 1956-1985, and an annual rainfall deficiency of 205.3 mm was recorded. Maximum monthly normal rainfall deficiencies of 52.8, 84.2, and 54.0 mm were recorded during the months of July, August, and September, respectively, while a minimum rainfall deficiency of 2.2 mm was observed in November. There was a decline by 196.3 mm in seasonal normal rainfall during June-September (kharif). The initial probability of a week going dry was higher (> 70%) from the 1st to the 25th week; however, standard meteorological weeks (SMW) 26 to 37 had more than 50% probability of going wet. The normal annual maximum temperature (Tmax) decreased by 0.4 °C while normal annual minimum temperatures (Tmin) increased by 0.21 °C. Analysis showed that there was an increase in frequency of drought from 1986 onwards in the zone and a monsoon rainfall deficit by about 21.25% during June-September which coincided with tillering and grand growth stage of sugarcane. The imposed drought during the growth and elongation phase is emerging as a major constraint in realizing high

Seasonal variation and climate change impact in Rainfall Erosivity across Europe

Science.gov (United States)

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine; Ballabio, Cristiano

2017-04-01

Rainfall erosivity quantifies the climatic effect on water erosion and is of high importance for soil scientists, land use planners, agronomists, hydrologists and environmental scientists in general. The rainfall erosivity combines the influence of rainfall duration, magnitude, frequency and intensity. Rainfall erosivity is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minute rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years). The European Commission's Joint Research Centr(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,675 stations. The interpolation of those point erosivity values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511: 801-815). In 2016, REDES extended with a monthly component, which allowed developing monthly and seasonal erosivity maps and assessing rainfall erosivity both spatially and temporally for European Union and Switzerland. The monthly erosivity maps have been used to develop composite indicators that map both intra-annual variability and concentration of erosive events (Science of the Total Environment, 579: 1298-1315). Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year. Finally, the identification of the most erosive month allows recommending certain agricultural management practices (crop

Application of GIS to assess rainfall variability impacts on crop yield ...

African Journals Online (AJOL)

SERVER

2007-09-19

Sep 19, 2007 ... Geospatial analysis. GIS Interpolation and other geospatial Analysis techniques were carried out to ... means of Spatial Decision Support System (SDSS) to plan crops ... rainwater variability on water availability for crop maize ...

Effects of climate variability and climate change on crop production in southern Mali

NARCIS (Netherlands)

Traore, B.; Corbeels, M.; Wijk, van M.T.; Rufino, M.C.; Giller, K.E.

2013-01-01

In West Africa predictions of future changes in climate and especially rainfall are highly uncertain, and up to now no long-term analyses are available of the effects of climate on crop production. This study analyses long-term trends in climate variability at N'Tarla and Sikasso in southern Mali

Effects of cover crops incorporation and nitrogen fertilization on N2O and CO2 emissions

Science.gov (United States)

Kandel, T. P.; Gowda, P. H.; Northup, B. K.; DuPont, J.; Somenahally, A. C.; Rocateli, A.

2017-12-01

In this study, we measured N2O and CO2 fluxes from plots planted to hairy vetch (winter cover crop) and broadleaf vetch (spring cover crop) as N sources for the following crabgrass (summer forage crop) in El Reno, Oklahoma, USA. Comparisons also included 0 and 60 kg ha-1 mineral N fertilizer supplied as dry urea. No significant N2O fluxes were observed during rapid growing periods of cover crops (March-April, 2017), however, large fluxes were observed after hairy vetch incorporation. Immediately after the hairy vetch biomass incorporation, large rainfall events were recorded. The fluxes subsided gradually with drying soil condition but were enhanced after every consecutive rainfall events. A rainfall induced flux measuring up to 8.2 kg N2O ha-1 day-1 was observed after 26 days of biomass incorporation. In total, 29 kg N2O ha-1 (18 kg N ha-1) was emitted within a month after biomass incorporation from hairy vetch plots. Growth of broadleaf vetch was poor and N2O fluxes were also lower. Similarly, plots fertilized with 60 kg N ha-1 had significant fluxes of N2O but the magnitude was much lower than the hairy vetch plots. Dynamics of N2O and CO fluxes correlated strongly. The results thus indicated that although cover crops may provide many environmental/agronomic benefits such as N fixation, soil carbon built-up, weed suppression and erosion control, high N2O emissions may dwarf these benefits.

Spatial and temporal distribution of rainfall and its management for increased productivity in rawalpindi region

International Nuclear Information System (INIS)

Shafiq, M.; Ghafoor, A.; Naeem, M.A.

2005-01-01

Rainfed areas make a significant contribution to agricultural production. However, there is considerable spatial and temporal variability in rainfall characteristics, which affect crop production and soil-erosion problems. For the adoption of soil and water conservation techniques, the information of rainfall-characteristics is very important. This paper describes rainfall-characteristics of three locations of Rawalpindi region. Same practices of rainwater-management have also been discussed for efficient utilization of available water for sustained productivity. (author)

Statistical Analysis of 30 Years Rainfall Data: A Case Study

Science.gov (United States)

Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

2017-07-01

Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

84 income and crop diversification among farming households in a ...

African Journals Online (AJOL)

OLUWOLE AKINNAGBE

This is often necessary in agriculture based peasant economies because of risks such as variability in soil quality, household and crop diseases, price shock, unpredictable rainfall and other weather related events. Income diversification can be achieved by producing a variety of crops and/or pursuing off-farm employment.

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments.

Science.gov (United States)

Truong, Sandra K; McCormick, Ryan F; Mullet, John E

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development

Crop yield estimation in 2014 for Vojvodina using methods of remote sensing

Directory of Open Access Journals (Sweden)

Jovanović Dušan

2014-01-01

Full Text Available Monitoring phenology of crops and yield estimate based on vegetation indices as well as other parameters such as temperature or amount of rainfall were largely reported in literature. In this research, MODIS Normalized Difference Vegetation Index (NDVI was used as an indicator of specific crop condition; the other parameter was Land Surface Temperature (LST which can indicate the amount of crop moisture. Trial years were 2011, 2012, and 2013. For those years sowing structure was acquired from agricultural organizations Nova Budućnost from Žarkovac and Sava Kovačević from Vrbas, both in Serbia. Also, satellite images with high and medium resolution for these areas and years were available. Multiple linear regression was used for crop yield estimate for Vojvodina Province, Serbia where the NDVI and LST were independent variables and the average yield for specific crop was the dependent variable. The results of crop yield estimate two months before harvest are presented (excluding wheat.

Deposition of caesium and strontium substances on growing crops: Effects and countermeasures

International Nuclear Information System (INIS)

Bengtsson, S.

2010-01-01

Full text: To investigate how the two radionuclides caesium ( 134 Cs) and strontium ( 85 Sr) are taken up and transported to the harvested parts (the seeds) by fallout in a growing crop. Further on how this is related to the size and time of the fallout. From the information collected recommendation of suitable countermeasures at different scenarios to prevent further spreading to food stuff can be suggested. In the project a number of field trials where artificial deposited by the two radionuclides 134 Cs and 85 Sr in a contaminated rainfall, on the two agricultural crops Brassica napus L. (spring rape) and Triticum aestivum L. (spring wheat). The trial contained different treatments where the radionuclides where deposited by a rainfall simulator at different growing stages of the crops. The field trial continues for two more years and the reason for that is due to the variation of the climate for the different years. The radionuclides were applied in the form of a wet deposition and the rainfall was about 1 mm m -1 with a concentration of 20 kBq m -1 for each radionuclide. Samples were taken from the plots at the day(s) after the treatment of contaminated rainfall, both from the latest treated plots and from the earlier treated plots. The hypotheses are: 1. That the size of the deposition and the time in relation to the development stages of the crop will steer how much caesium and strontium that are coughed, detained and transferred to the harvested parts. 2. That the levels of caesium and strontium in the harvested parts of the crops are related to the insensitivity of the rainfall after a deposition and also how long time the first intensive rain will occur. 3. That the size of caesium and strontium in harvested plant parts are related to the size of uptake throw the leaves. 4. If the deposition of caesium and strontium will be the same, the levels of caesium will be much higher than strontium in the harvested parts. (author)

Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

Science.gov (United States)

Lucero, Omar A.; Rozas, Daniel

Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of

Trend analysis and forecast of precipitation, reference evapotranspiration and rainfall deficit in the Blackland Prairie of eastern Mississippi

Science.gov (United States)

Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration (ETo) and rainfall deficit are essential for water resources management and cropping system design. Rainfall, ETo, and water deficit patterns and trends in eastern Mississippi USA for a 120-year period (1...

Climate change induced rainfall patterns affect wheat productivity and agroecosystem functioning dependent on soil types

Science.gov (United States)

Tabi Tataw, James; Baier, Fabian; Krottenthaler, Florian; Pachler, Bernadette; Schwaiger, Elisabeth; Whylidal, Stefan; Formayer, Herbert; Hösch, Johannes; Baumgarten, Andreas; Zaller, Johann G.

2014-05-01

Wheat is a crop of global importance supplying more than half of the world's population with carbohydrates. We examined, whether climate change induced rainfall patterns towards less frequent but heavier events alter wheat agroecosystem productivity and functioning under three different soil types. Therefore, in a full-factorial experiment Triticum aestivum L. was cultivated in 3 m2 lysimeter plots containing the soil types sandy calcaric phaeozem, gleyic phaeozem or calcic chernozem. Prognosticated rainfall patterns based on regionalised climate change model calculations were compared with current long-term rainfall patterns; each treatment combination was replicated three times. Future rainfall patterns significantly reduced wheat growth and yield, reduced the leaf area index, accelerated crop development, reduced arbuscular mycorrhizal fungi colonisation of roots, increased weed density and the stable carbon isotope signature (δ13C) of both old and young wheat leaves. Different soil types affected wheat growth and yield, ecosystem root production as well as weed abundance and biomass. The interaction between climate and soil type was significant only for the harvest index. Our results suggest that even slight changes in rainfall patterns can significantly affect the functioning of wheat agroecosystems. These rainfall effects seemed to be little influenced by soil types suggesting more general impacts of climate change across different soil types. Wheat production under future conditions will likely become more challenging as further concurrent climate change factors become prevalent.

Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

Directory of Open Access Journals (Sweden)

C. Z. van de Beek

2010-02-01

Full Text Available This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m and temporal (16 s resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity – rain rate relation is derived from measurements of raindrop size distributions and compared with radar – rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

Science.gov (United States)

Garrigues, S.; Olioso, A.; Carrer, D.; Decharme, B.; Calvet, J.-C.; Martin, E.; Moulin, S.; Marloie, O.

2015-10-01

Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m-2) compared to the negative biases found for SAFRAN (-10 W m-2) and the MSG satellite (-12 W m-2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by -12 and -16 W m-2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The

60 changes in soil properties under alley cropping system of three ...

African Journals Online (AJOL)

OLUWOLE AKINNAGBE

2009-01-01

Jan 1, 2009 ... A study to evaluate the changes in soil properties, under existing alley cropping system with three leguminous crops (Leucaena leucocephala ... of improved farming system is efficient recycling of organic materials. This exploits ... in form of violent shower of short duration. Rainfall is seasonal and defines ...

Rainfall intensity characteristics at coastal and high altitude stations ...

Indian Academy of Sciences (India)

a given amount of rain occurs is important because heavier rainfall leads to greater runoff, greater soil erosion and less infiltration into the water table. A knowledge of rainfall intensity therefore becomes. Keywords. Rainfall intensity; Kerala; cumulative distribution. J. Earth Syst. Sci. 116, No. 5, October 2007, pp. 451–463.

A space-time rainfall generator for highly convective Mediterranean rainstorms

Directory of Open Access Journals (Sweden)

S. Salsón

2003-01-01

Full Text Available Distributed hydrological models require fine resolution rainfall inputs, enhancing the practical interest of space-time rainfall models, capable of generating through numerical simulation realistic space-time rainfall intensity fields. Among different mathematical approaches, those based on point processes and built upon a convenient analytical description of the raincell as the fundamental unit, have shown to be particularly suitable and well adapted when extreme rainfall events of convective nature are considered. Starting from previous formulations, some analytical refinements have been considered, allowing practical generation of space-time rainfall intensity fields for that type of rainstorm events. Special attention is placed on the analytical description of the spatial and temporal evolution of the rainfall intensities produced by the raincells. After deriving the necessary analytical results, the seven parameters of the model have been estimated by the method of moments, for each of the 30 selected rainfall events in the Jucar River Basin (ValenciaSpain – period 1991 to 2000, using 5-min aggregated rainfall data series from an automatic raingauge network.

Prediction of kharif rice yield at Kharagpur using disaggregated extended range rainfall forecasts

Science.gov (United States)

Dhekale, B. S.; Nageswararao, M. M.; Nair, Archana; Mohanty, U. C.; Swain, D. K.; Singh, K. K.; Arunbabu, T.

2017-08-01

The Extended Range Forecasts System (ERFS) has been generating monthly and seasonal forecasts on real-time basis throughout the year over India since 2009. India is one of the major rice producer and consumer in South Asia; more than 50% of the Indian population depends on rice as staple food. Rice is mainly grown in kharif season, which contributed 84% of the total annual rice production of the country. Rice cultivation in India is rainfed, which depends largely on rains, so reliability of the rainfall forecast plays a crucial role for planning the kharif rice crop. In the present study, an attempt has been made to test the reliability of seasonal and sub-seasonal ERFS summer monsoon rainfall forecasts for kharif rice yield predictions at Kharagpur, West Bengal by using CERES-Rice (DSSATv4.5) model. These ERFS forecasts are produced as monthly and seasonal mean values and are converted into daily sequences with stochastic weather generators for use with crop growth models. The daily sequences are generated from ERFS seasonal (June-September) and sub-seasonal (July-September, August-September, and September) summer monsoon (June to September) rainfall forecasts which are considered as input in CERES-rice crop simulation model for the crop yield prediction for hindcast (1985-2008) and real-time mode (2009-2015). The yield simulated using India Meteorological Department (IMD) observed daily rainfall data is considered as baseline yield for evaluating the performance of predicted yields using the ERFS forecasts. The findings revealed that the stochastic disaggregation can be used to disaggregate the monthly/seasonal ERFS forecasts into daily sequences. The year to year variability in rice yield at Kharagpur is efficiently predicted by using the ERFS forecast products in hindcast as well as real time, and significant enhancement in the prediction skill is noticed with advancement in the season due to incorporation of observed weather data which reduces uncertainty of

Effects of sample size on estimation of rainfall extremes at high temperatures

Science.gov (United States)

Boessenkool, Berry; Bürger, Gerd; Heistermann, Maik

2017-09-01

High precipitation quantiles tend to rise with temperature, following the so-called Clausius-Clapeyron (CC) scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD) fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

Effects of sample size on estimation of rainfall extremes at high temperatures

Directory of Open Access Journals (Sweden)

B. Boessenkool

2017-09-01

Full Text Available High precipitation quantiles tend to rise with temperature, following the so-called Clausius–Clapeyron (CC scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.

Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields

DEFF Research Database (Denmark)

Thorndahl, Søren; Smith, James A.; Baeck, Mary Lynn

2014-01-01

that relate to size, structure and evolution of heavy rainfall. Extreme rainfall is also linked with severe weather (tornados, large hail and damaging wind). The diurnal cycle of rainfall for heavy rain days is characterized by an early peak in the largest rainfall rates, an afternoon-evening peak in rain...

Modelling rainfall amounts using mixed-gamma model for Kuantan district

Science.gov (United States)

Zakaria, Roslinazairimah; Moslim, Nor Hafizah

2017-05-01

An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

Use of swine wastewater in oilseed radish crop: agronomic and environmental aspects

Directory of Open Access Journals (Sweden)

Thaisa Pegoraro

2014-12-01

Full Text Available Swine effluent has been applied to soils to promote nutrient cycling and reduce the uncontrolled disposal of effluents into bodies of water. However, the use of these effluents on various crops has raised environmental and public health concerns. Oilseed radish crop (Raphanus sativus L. is a winter crop planted in no-tillage systems as a green fertilizer that also can be used for biodiesel, and it requires high levels of nutrients for its development. Thus, the present study aimed to evaluate the environmental and agronomic effects of the application of swine wastewater on oilseed radish. The experiment was conducted in a 0.162 ha area with the following treatments: unirrigated (rainfed, irrigated, and fertilized with swine wastewater (370 m3 ha-1 cycle-1. After each rainfall event, analyses were conducted for the main macro and micronutrients in the runoff and percolated material from drainage lysimeters. Changes in the physical and chemical characteristics of the soil were also analyzed, as were the agronomic and nutritional indices of the dry crop phytomass in full blooming stage. Application of swine wastewater at a level of 370 m3 ha-1 produces a crop with better agronomic quality. Over the long term, however, caution should be taken regarding the surface runoff of NO3-, P, K, Mn and total salts and the percolation of NO3-, Na and Cu. Moreover, the rainfall occurred one day after fertigation contributed to the increase of the levels of P, K, Na, Cu, Zn and Mn in the percolated material.

Ecohydrology of managed ecosystems: Linking rainfall unpredictability, agronomic performance, and sustainable water use

Science.gov (United States)

Vico, Giulia; Porporato, Amilcare

2014-05-01

The field of ecohydrology, traditionally focusing on natural ecosystems, can offer the necessary quantitative tools to assess and compare the sustainability of agriculture across climates, soil types, crops, and irrigation strategies, including rainfall unpredictability. In particular, irrigation is one of the main strategies to enhance and stabilize agricultural productivity, but represents a cost in terms of often scarce water resources. Here, the sustainability of irrigated and rainfed agriculture is assessed by means of water productivity (defined as the ratio between yield and total supplied water), yields, water requirements, and their variability. These indicators are quantified using a probabilistic description of the soil water balance and crop development. Employing this framework, we interpret changes in water productivity as total water input is altered, in two staple crops (maize and wheat) grown under different soils, climates, and irrigation strategies. Climate change scenarios are explored by using the same approach and altering the rainfall statistics. For a given irrigation strategy, intermediate rainfall inputs leads to the highest variability in yield and irrigation water requirement - it is under these conditions that water management is most problematic. When considering the contrasting needs of limiting water requirements while ensuring adequate yields, micro-irrigation emerges as the most sustainable strategy at the field level, although consideration should be given to its profitability and long-term environmental implications.

Variability in rainfall over tropical Australia during summer and relationships with the Bilybara High

Science.gov (United States)

Reason, C. J. C.

2018-04-01

Variability in summer rainfall over tropical Australia, defined here as that part of the continent north of 25° S, and its linkages with regional circulation are examined. In particular, relationships with the mid-level anticyclone (termed the Bilybara High) that exists over the northwestern Australia/Timor Sea region between August and April are considered. This High forms to the southwest of the upper-level anticyclone via a balance between the upper-level divergence over the region of tropical precipitation maximum and planetary vorticity advection and moves south and strengthens during the spring and summer. It is shown that variations in the strength and position of the Bilybara High are related to anomalies in precipitation and temperature over large parts of tropical Australia as well as some areas in the south and southeast of the landmass. Some of the interannual variations in the High are related to ENSO, but there are also a number of neutral years with large anomalies in the High and hence in rainfall. On decadal time scales, a strong relationship exists between the leading mode of tropical Australian rainfall and the Bilybara High. On both interannual and decadal scales, the relationships between the High and the regional rainfall involve changes in the monsoonal northwesterlies blowing towards northern Australia, and further south, in the easterly trade winds over the region.

Cover Crops in Hillside Agriculture

International Development Research Centre (IDRC) Digital Library (Canada)

Our study focuses on the wet tropical hillsides of northern Honduras (Figure 1). ..... The eastern extreme of the region (Jutiapa) is a dry spot, with less rainfall (2 000 mm a-1) as a result ...... Paper presented at the International Workshop on Green Manure–Cover Crops for Smallholders in ..... Lamaster, J.P.; Jones, I.R. 1923.

Rethinking crop diversification under changing climate, hydrology and food habit in Bangladesh

Directory of Open Access Journals (Sweden)

Aminul Islam Akanda

2011-11-01

Full Text Available Extreme temperature, frequent and intensive flood, cyclone and other natural disasters due to climate change became acute in Bangladesh and would be severe in future. Besides, water crisis due to shortage of upstream flow and very little rainfall in dry season would affect in a same way. Gradual higher dependency on groundwater irrigation during last few decades created pressure on groundwater even after a huge discharge during rainy season. Using secondary data, this research analyzed the changes in cropping pattern along with a forecast of area to be distributed among various crops in 2029-30 and proposed a re-distribution considering probable crop failure, water crisis and change in food habit. Inherit rice-dominated food habit and government incentive policy encouraged farmers to be concentrated highly on water-intensive rice farming. However, a recent tendency of less rice consumption would encourage crop diversification in future. An incentive policy for farming of diversified crops and their intensification in all crop seasons would be effective to reduce pressure on groundwater and to persuade a balanced food basket in Bangladesh.

Study of Climate Change Impact to Local Rainfall Distribution in Lampung Provinces

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Tumiar Katarina Manik

2016-08-01

Full Text Available Global warming which leads to climate change has potential affect to Indonesia agriculture activities and production. Analyzing rainfall pattern and distribution is important to investigate the impact of global climate change to local climate. This study using rainfall data from 1976-2010 from both lowland and upland area of Lampung Province. The results show that rainfall tends to decrease since the 1990s which related to the years with El Nino event. Monsoonal pattern- having rain and dry season- still excist in Lampung; however, since most rain fell below the average, it could not meet crops water need. Farmers conclude that dry seasons were longer and seasonal pattern has been changed. Global climate change might affect Lampung rainfall distribution through changes on sea surface temperature which could intensify the El Nino effect. Therefore, watching the El Nino phenomena and how global warming affects it, is important in predicting local climate especially the rainfall distribution in order to prevent significant loss in agriculture productivities.

Implications of deep drainage through saline clay for groundwater recharge and sustainable cropping in a semi-arid catchment, Australia

Science.gov (United States)

Timms, W. A.; Young, R. R.; Huth, N.

2012-04-01

The magnitude and timing of deep drainage and salt leaching through clay soils is a critical issue for dryland agriculture in semi-arid regions (2000 mm yr-1) such as parts of Australia's Murray-Darling Basin (MDB). In this rare study, hydrogeological measurements and estimations of the historic water balance of crops grown on overlying Grey Vertosols were combined to estimate the contribution of deep drainage below crop roots to recharge and salinization of shallow groundwater. Soil sampling at two sites on the alluvial flood plain of the Lower Namoi catchment revealed significant peaks in chloride concentrations at 0.8-1.2 m depth under perennial vegetation and at 2.0-2.5 m depth under continuous cropping indicating deep drainage and salt leaching since conversion to cropping. Total salt loads of 91-229 t ha-1 NaCl equivalent were measured for perennial vegetation and cropping, with salinity to ≥ 10 m depth that was not detected by shallow soil surveys. Groundwater salinity varied spatially from 910 to 2430 mS m-1 at 21 to 37 m depth (N = 5), whereas deeper groundwater was less saline (290 mS m-1) with use restricted to livestock and rural domestic supplies in this area. The Agricultural Production Systems Simulator (APSIM) software package predicted deep drainage of 3.3-9.5 mm yr-1 (0.7-2.1% rainfall) based on site records of grain yields, rainfall, salt leaching and soil properties. Predicted deep drainage was highly episodic, dependent on rainfall and antecedent soil water content, and over a 39 yr period was restricted mainly to the record wet winter of 1998. During the study period, groundwater levels were unresponsive to major rainfall events (70 and 190 mm total), and most piezometers at about 18 m depth remained dry. In this area, at this time, recharge appears to be negligible due to low rainfall and large potential evapotranspiration, transient hydrological conditions after changes in land use and a thick clay dominated vadose zone. This is in

Implications of deep drainage through saline clay for groundwater recharge and sustainable cropping in a semi-arid catchment, Australia

Directory of Open Access Journals (Sweden)

W. A. Timms

2012-04-01

Full Text Available The magnitude and timing of deep drainage and salt leaching through clay soils is a critical issue for dryland agriculture in semi-arid regions (<500 mm yr⁻¹ rainfall, potential evapotranspiration >2000 mm yr⁻¹ such as parts of Australia's Murray-Darling Basin (MDB. In this rare study, hydrogeological measurements and estimations of the historic water balance of crops grown on overlying Grey Vertosols were combined to estimate the contribution of deep drainage below crop roots to recharge and salinization of shallow groundwater. Soil sampling at two sites on the alluvial flood plain of the Lower Namoi catchment revealed significant peaks in chloride concentrations at 0.8–1.2 m depth under perennial vegetation and at 2.0–2.5 m depth under continuous cropping indicating deep drainage and salt leaching since conversion to cropping. Total salt loads of 91–229 t ha⁻¹ NaCl equivalent were measured for perennial vegetation and cropping, with salinity to ≥ 10 m depth that was not detected by shallow soil surveys. Groundwater salinity varied spatially from 910 to 2430 mS m⁻¹ at 21 to 37 m depth (N = 5, whereas deeper groundwater was less saline (290 mS m⁻¹ with use restricted to livestock and rural domestic supplies in this area. The Agricultural Production Systems Simulator (APSIM software package predicted deep drainage of 3.3–9.5 mm yr⁻¹ (0.7–2.1% rainfall based on site records of grain yields, rainfall, salt leaching and soil properties. Predicted deep drainage was highly episodic, dependent on rainfall and antecedent soil water content, and over a 39 yr period was restricted mainly to the record wet winter of 1998. During the study period, groundwater levels were unresponsive to major rainfall events (70 and 190 mm total, and most piezometers at about 18 m depth remained dry. In this area, at this time, recharge appears to be negligible due to low

Relationships between High Impact Tropical Rainfall Events and Environmental Conditions

Science.gov (United States)

Painter, C.; Varble, A.; Zipser, E. J.

2017-12-01

While rainfall increases as moisture and vertical motion increase, relationships between regional environmental conditions and rainfall event characteristics remain more uncertain. Of particular importance are long duration, heavy rain rate, and significant accumulation events that contribute sizable fractions of overall precipitation over short time periods. This study seeks to establish relationships between observed rainfall event properties and environmental conditions. Event duration, rain rate, and rainfall accumulation are derived using the Tropical Rainfall Measuring Mission (TRMM) 3B42 3-hourly, 0.25° resolution rainfall retrieval from 2002-2013 between 10°N and 10°S. Events are accumulated into 2.5° grid boxes and matched to monthly mean total column water vapor (TCWV) and 500-hPa vertical motion (omega) in each 2.5° grid box, retrieved from ERA-interim reanalysis. Only months with greater than 3 mm/day rainfall are included to ensure sufficient sampling. 90th and 99th percentile oceanic events last more than 20% longer and have rain rates more than 20% lower than those over land for a given TCWV-omega condition. Event duration and accumulation are more sensitive to omega than TCWV over oceans, but more sensitive to TCWV than omega over land, suggesting system size, propagation speed, and/or forcing mechanism differences for land and ocean regions. Sensitivities of duration, rain rate, and accumulation to TCWV and omega increase with increasing event extremity. For 3B42 and ERA-Interim relationships, the 90th percentile oceanic event accumulation increases by 0.93 mm for every 1 Pa/min change in rising motion, but this increases to 3.7 mm for every 1 Pa/min for the 99th percentile. Over land, the 90th percentile event accumulation increases by 0.55 mm for every 1 mm increase in TCWV, whereas the 99th percentile increases by 0.90 mm for every 1 mm increase in TCWV. These changes in event accumulation are highly correlated with changes in event

Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

Directory of Open Access Journals (Sweden)

Shimelis B. Gebere

2015-09-01

Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

Directory of Open Access Journals (Sweden)

A. Cilek

2016-06-01

Full Text Available The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA, a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

Trend Analysis of Droughts during Crop Growing Seasons of Nigeria

Directory of Open Access Journals (Sweden)

Mohammed Sanusi Shiru

2018-03-01

Full Text Available This study assesses the impacts of recent climate changes on drought-affected areas and the occurrence of droughts during different cropping seasons of Nigeria using the standardized precipitation evapotranspiration index (SPEI. The crop growing seasons are considered because the droughts for those periods are more destructive to national agricultural production. The Mann–Kendall test and binary logistic regression were used to quantify the trends in drought-affected areas and the occurrence of crop droughts with different areal extents, respectively. Gauge-based gridded rainfall and temperature data for the period 1961–2010 with spatial resolutions of 0.5° were used. Results showed an increase in the areal extent of droughts during some of the cropping seasons. The occurrences of droughts, particularly moderate droughts with smaller areal extents, were found to increase for all of the seasons. The SPEI values calculated decreased mostly in the regions where rainfall was decreasing. That is, the recent changes in climate were responsible for the increase in the occurrences of droughts with smaller areal extents. These trends in climate indicate that the occurrence of larger areal extent droughts may happen more frequently in Nigeria in the future.

Rainfall-induced runoff from exposed streambed sediments: an important source of water pollution.

Science.gov (United States)

Frey, S K; Gottschall, N; Wilkes, G; Grégoire, D S; Topp, E; Pintar, K D M; Sunohara, M; Marti, R; Lapen, D R

2015-01-01

When surface water levels decline, exposed streambed sediments can be mobilized and washed into the water course when subjected to erosive rainfall. In this study, rainfall simulations were conducted over exposed sediments along stream banks at four distinct locations in an agriculturally dominated river basin with the objective of quantifying the potential for contaminant loading from these often overlooked runoff source areas. At each location, simulations were performed at three different sites. Nitrogen, phosphorus, sediment, fecal indicator bacteria, pathogenic bacteria, and microbial source tracking (MST) markers were examined in both prerainfall sediments and rainfall-induced runoff water. Runoff generation and sediment mobilization occurred quickly (10-150 s) after rainfall initiation. Temporal trends in runoff concentrations were highly variable within and between locations. Total runoff event loads were considered large for many pollutants considered. For instance, the maximum observed total phosphorus runoff load was on the order of 1.5 kg ha. Results also demonstrate that runoff from exposed sediments can be a source of pathogenic bacteria. spp. and spp. were present in runoff from one and three locations, respectively. Ruminant MST markers were also present in runoff from two locations, one of which hosted pasturing cattle with stream access. Overall, this study demonstrated that rainfall-induced runoff from exposed streambed sediments can be an important source of surface water pollution. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Correlation Between Precipitation and Crop Yield for Corn and Cotton Produced in Alabama

Science.gov (United States)

Hayes, Carol E.; Perkey, Donald J.

1998-01-01

In this study, variations in precipitation during the time of corn silking are compared to Alabama corn yields. Also, this study compares precipitation variations during bloom to Alabama cotton yield. The goal is to obtain mathematical correlations between rainfall during the crop's critical period and the crop amount harvested per acre.

Water management options based on rainfall analysis for rainfed maize (Zea Mays L.) production in Rushinga district Zimbabwe

NARCIS (Netherlands)

Nyakudya, I.W.; Stroosnijder, L.

2011-01-01

Maize (Zea mays L.), the dominant and staple food crop in Southern and Eastern Africa, is preferred to the drought-tolerant sorghum and pearl millet even in semi-arid areas. In semi-arid areas production of maize is constrained by droughts and poor rainfall distribution. The best way to grow crops

Climate variability impacts on rice crop production in pakistan

International Nuclear Information System (INIS)

Shakoor, U.; Saboor, A.; Baig, I.

2015-01-01

The climate variability has affected the agriculture production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate changes are believed to have declining effects towards crop production in Pakistan. This study carries an empirical investigation of the effects of climate change on rice crop of Pakistan by employing Vector Auto Regression (VAR) model. Annual seasonal data of the climatic variables from 1980 to 2013 has been used. Results confirmed that rising mean maximum temperature would lead to reduction in rice production while increase in mean minimum temperature would be advantageous towards rice production. Variation in mean minimum temperature brought about seven percent increase in rice productivity as shown by Variance Decomposition. Mean precipitation and mean temperature would increase rice production but simulations scenarios for 2030 confirmed that much increase in rainfall and mean temperature in long run will negatively affect rice production in future. It is therefore important to follow adequate policy action to safeguard crop productions from disastrous effects. Development of varieties resistant to high temperatures as well as droughts will definitely enhance resilience of rice crop in Pakistan. (author)

Biodiversity, evolution and adaptation of cultivated crops.

Science.gov (United States)

Vigouroux, Yves; Barnaud, Adeline; Scarcelli, Nora; Thuillet, Anne-Céline

2011-05-01

The human diet depends on very few crops. Current diversity in these crops is the result of a long interaction between farmers and cultivated plants, and their environment. Man largely shaped crop biodiversity from the domestication period 12,000 B.P. to the development of improved varieties during the last century. We illustrate this process through a detailed analysis of the domestication and early diffusion of maize. In smallholder agricultural systems, farmers still have a major impact on crop diversity today. We review several examples of the major impact of man on current diversity. Finally, biodiversity is considered to be an asset for adaptation to current environmental changes. We describe the evolution of pearl millet in West Africa, where average rainfall has decreased over the last forty years. Diversity in cultivated varieties has certainly helped this crop to adapt to climate variation. Copyright © 2011 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Continuous cropping with 13 - 15 inches of precipitation

Science.gov (United States)

Producers in the Great Plains have use fallow to adjust for inconsistent and often, inadequate rainfall. The prevalent rotation in this region is winter wheat-fallow. Fallow, however, is damaging to soil health. No-till practices have enabled producers to include more crops in the rotation. This...

Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

Science.gov (United States)

Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

2017-04-01

Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

SPI-Based Analyses of Drought Changes over the Past 60 Years in China’s Major Crop-Growing Areas

Directory of Open Access Journals (Sweden)

Lang Xia

2018-01-01

Full Text Available This study analyzes the changes in drought patterns in China’s major crop-growing areas over the past 60 years. The analysis was done using both weather station data and Tropical Rainfall Measuring Mission (TRMM Microwave Imager (TMI rainfall data to calculate the Standardized Precipitation Index (SPI. The results showed that the occurrences of extreme drought were the most serious in recent years in the Southwest China and Sichuan crop-growing areas. The Yangtze River (MLRY and South China crop-growing areas experienced extreme droughts during 1960–1980, whereas the Northeast China and Huang–Huai–Hai crop-growing areas experienced extreme droughts around 2003. The analysis showed that the SPIs calculated by TRMM data at time scales of one, three, and six months were reliable for monitoring drought in the study regions, but for 12 months, the SPIs calculated by gauge and TRMM data showed less consistency. The analysis of the spatial distribution of droughts over the past 15 years using TMI rainfall data revealed that more than 60% of the area experienced extreme drought in 2011 over the MLRY region and in 1998 over the Huang–Huai–Hai region. The frequency of different intensity droughts presented significant spatial heterogeneity in each crop-growing region.

Water dynamics in a bean crop (Phaseolus vulgaris)

International Nuclear Information System (INIS)

Calvache, Marcelo; Garcia, Carlos.

1987-01-01

The dynamics of water was studied at 'La Tola', Experimental Teaching Center of the Central University of Ecuador, in a Sandy-Ioan, typic Haplustoll soil, in wich beans were growing. All the components of the crop water balance were determined. Real evapotranspiration was in direct relation to the growth of the crop, reaching its maximum value of 4.9 mm day-1, at pod setting, then decreasing slowly until maturation of the kernels. Up to 1 meter depth, water loss by drainage depended on rainfall, reaching up to 24% of the total water loss: the soil layer supplying most of the water for the use of the crop was between 0-40 cm, where the root activity was greatest

Characterising agrometeorological climate risks and uncertainties: Crop production in Uganda

DEFF Research Database (Denmark)

Mubiru, Drake N.; Komutunga, Everline; Agona, Ambrose

2012-01-01

, the number of rainy days during this critical period of crop growth is decreasing, which possibly means that crops grown in this season are prone to climatic risks and therefore in need of appropriate adaptation measures. A time-series analysis of the maximum daily temperature clearly revealed an increase......Uganda is vulnerable to climate change as most of its agriculture is rain-fed; agriculture is also the backbone of the economy, and the livelihoods of many people depend upon it. Variability in rainfall may be reflected in the productivity of agricultural systems and pronounced variability may...... in temperature, with the lower limits of the ranges of daily maximums increasing faster than the upper limits. Finally, this study has generated information on seasonal rainfall characteristics that will be vital in exploiting the possibilities offered by climatic variability and also offers opportunities...

Fermentation substrate and forage from south Florida cropping sequences

Energy Technology Data Exchange (ETDEWEB)

Kalmbacher, R.S.; Martin, F.G.; Mislevy, P.

1985-01-01

Zea mays (maize), Sorghum bicolor (sorghum), Ipomoea batatas (Sweet potato), Helianthus tuberosus (Jerusalem artichoke) and Manihot esculenta (cassava) were grown as alcohol biomass crops in various sequences in 1981 and 1982, on a sandy, siliceous, hyperthermic, typic Haplaquod soil. Herbage yield and yield of non-fermentable by-products were measured as potential cattle feed. Grain produced from Z. mays followed by S. bicolor averaged 11.4 Mg/ha and was greater (P less than 0.05) than other graincrop sequences. Highest (P less than 0.05) root yields were from I. batatas (5.1 Mg/ha) in 1981 and M. esculenta (5.3 Mg/ha) in 1982. Total nonstructural carbohydrate was greatest for Z. mays/S. bicolor (6.0 Mg/ha) and Z. mays/I. batatas (6.8 Mg/ha) sequences. Crops of I. batatas and M. esculenta were hindered by high rainfall and poorly drained soil. Cropping sequences including Z. mays and S. bicolor produced more cattle feed, and they can be expected to produce more alcohol biomass with fewer cultural problems, on south-central Florida flatwoods soils. 20 references.

High Severity Wildfire Effect On Rainfall Infiltration And Runoff: A Cellular Automata Based Simulation

Science.gov (United States)

Vergara-Blanco, J. E.; Leboeuf-Pasquier, J.; Benavides-Solorio, J. D. D.

2017-12-01

A simulation software that reproduces rainfall infiltration and runoff for a storm event in a particular forest area is presented. A cellular automaton is utilized to represent space and time. On the time scale, the simulation is composed by a sequence of discrete time steps. On the space scale, the simulation is composed of forest surface cells. The software takes into consideration rain intensity and length, individual forest cell soil absorption capacity evolution, and surface angle of inclination. The software is developed with the C++ programming language. The simulation is executed on a 100 ha area within La Primavera Forest in Jalisco, Mexico. Real soil texture for unburned terrain and high severity wildfire affected terrain is employed to recreate the specific infiltration profile. Historical rainfall data of a 92 minute event is used. The Horton infiltration equation is utilized for infiltration capacity calculation. A Digital Elevation Model (DEM) is employed to reproduce the surface topography. The DEM is displayed with a 3D mesh graph where individual surface cells can be observed. The plot colouring renders water content development at the cell level throughout the storm event. The simulation shows that the cumulative infiltration and runoff which take place at the surface cell level depend on the specific storm intensity, fluctuation and length, overall terrain topography, cell slope, and soil texture. Rainfall cumulative infiltration for unburned and high severity wildfire terrain are compared: unburned terrain exhibits a significantly higher amount of rainfall infiltration.It is concluded that a cellular automaton can be utilized with a C++ program to reproduce rainfall infiltration and runoff under diverse soil texture, topographic and rainfall conditions in a forest setting. This simulation is geared for an optimization program to pinpoint the locations of a series of forest land remediation efforts to support reforestation or to minimize runoff.

First Red-billed Quelea breeding record in the winter rainfall region ...

African Journals Online (AJOL)

This note documents the first breeding of Red-billed Quelea in the winter rainfall region of South Africa. A colony of 350–600 nests was found, with evidence of recent breeding. Red-billed Quelea numbers were low in this region, but if numbers increase in the future in the Western Cape, winter crops could be under threat.

Linking seasonal climate forecasts with crop models in Iberian Peninsula

Science.gov (United States)

Capa, Mirian; Ines, Amor; Baethgen, Walter; Rodriguez-Fonseca, Belen; Han, Eunjin; Ruiz-Ramos, Margarita

2015-04-01

Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast. This study evaluates two methods for disaggregating seasonal climate forecasts into daily weather data: 1) a stochastic weather generator (CondWG), and 2) a forecast tercile resampler (FResampler). Both methods were used to generate 100 (with FResampler) and 110 (with CondWG) weather series/sequences for three scenarios of seasonal rainfall forecasts. Simulated wheat yield is computed with the crop model CERES-wheat (Ritchie and Otter, 1985), which is included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at two locations in northeastern Spain where the crop model was calibrated and validated with independent field data. Once simulated yields were obtained, an assessment of farmer's gross margin for different seasonal climate forecasts was accomplished to estimate production risks under different climate scenarios. This methodology allows farmers to assess the benefits and risks of a seasonal weather forecast in IP prior to the crop growing season. The results of this study may have important implications on both, public (agricultural planning) and private (decision support to farmers, insurance companies) sectors. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Hoogenboom, G. et al., 2010. The Decision

The Use of Cover Crops as Climate-Smart Management in Midwest Cropping Systems

Science.gov (United States)

Basche, A.; Miguez, F.; Archontoulis, S.; Kaspar, T.

2014-12-01

The observed trends in the Midwestern United States of increasing rainfall variability will likely continue into the future. Events such as individual days of heavy rain as well as seasons of floods and droughts have large impacts on agricultural productivity and the natural resource base that underpins it. Such events lead to increased soil erosion, decreased water quality and reduced corn and soybean yields. Winter cover crops offer the potential to buffer many of these impacts because they essentially double the time for a living plant to protect and improve the soil. However, at present, cover crops are infrequently utilized in the Midwest (representing 1-2% of row cropped land cover) in particular due to producer concerns over higher costs and management, limited time and winter growing conditions as well as the potential harm to corn yields. In order to expand their use, there is a need to quantify how cover crops impact Midwest cropping systems in the long term and namely to understand how to optimize the benefits of cover crops while minimizing their impacts on cash crops. We are working with APSIM, a cropping systems platform, to specifically quantify the long term future impacts of cover crop incorporation in corn-based cropping systems. In general, our regional analysis showed only minor changes to corn and soybean yields (<1% differences) when a cover crop was or was not included in the simulation. Further, a "bad spring" scenario (where every third year had an abnormally wet/cold spring and cover crop termination and planting cash crop were within one day) did not result in any major changes to cash crop yields. Through simulations we estimate an average increase of 4-9% organic matter improvement in the topsoil and an average decrease in soil erosion of 14-32% depending on cover crop planting date and growth. Our work is part of the Climate and Corn-based Cropping Systems Coordinated Agriculture Project (CSCAP), a collaboration of eleven Midwestern

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

Science.gov (United States)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2017-12-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

Science.gov (United States)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Applying Customized Climate Advisory Information to Translate Extreme Rainfall Events into Farming Options in the Sudan-Sahel of West Africa

Science.gov (United States)

Salack, S.; Worou, N. O.; Sanfo, S.; Nikiema, M. P.; Boubacar, I.; Paturel, J. E.; Tondoh, E. J.

2017-12-01

In West Africa, the risk of food insecurity linked to the low productivity of small holder farming increases as a result of rainfall extremes. In its recent evolution, the rainy season in the Sudan-Sahel zone presents mixed patterns of extreme climatic events. In addition to intense rain events, the distribution of events is associated with pockets of intra-seasonal long dry spells. The negative consequences of these mixed patterns are obvious on the farm: soil water logging, erosion of arable land, dwartness and dessication of crops, and loss in production. The capacity of local farming communities to respond accordingly to rainfall extreme events is often constrained by lack of access to climate information and advisory on smart crop management practices that can help translate extreme rainfall events into farming options. The objective of this work is to expose the framework and the pre-liminary results of a scheme that customizes climate-advisory information package delivery to subsistence farmers in Bakel (Senegal), Ouahigouya & Dano (Burkina Faso) and Bolgatanga (Ghana) for sustainable family agriculture. The package is based on the provision of timely climate information (48-hours, dekadal & seasonal) embedded with smart crop management practices to explore and exploite the potential advantage of intense rainfall and extreme dry spells in millet, maize, sorghum and cowpea farming communities. It is sent via mobile phones and used on selected farms (i.e agro-climatic farm schools) on which some small on-farm infrastructure were built to alleviate negative impacts of weather. Results provide prominent insight on how co-production of weather/climate information, customized access and guidiance on its use can induce fast learning (capacity building of actors), motivation for adaptation, sustainability, potential changes in cropping system, yields and family income in the face of a rainfall extremes at local scales of Sudan-Sahel of West Africa. Keywords: Climate

Swine manure injection with low-disturbance applicator and cover crops reduce phosphorus losses.

Science.gov (United States)

Kovar, J L; Moorman, T B; Singer, J W; Cambardella, C A; Tomer, M D

2011-01-01

Injection of liquid swine manure disturbs surface soil so that runoff from treated lands can transport sediment and nutrients to surface waters. We determined the effect of two manure application methods on P fate in a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] production system, with and without a winter rye (Secale cereale L.)-oat (Avena sativa L.) cover crop. Treatments included: (i) no manure; (ii) knife injection; and (iii) low-disturbance injection, each with and without the cover crop. Simulated rainfall runoff was analyzed for dissolved reactive P (DRP) and total P (TP). Rainfall was applied 8 d after manure application (early November) and again in May after emergence of the corn crop. Manure application increased soil bioavailable P in the 20- to 30-cm layer following knife injection and in the 5- to 20-cm layer following low-disturbance injection. The low-disturbance system caused less damage to the cover crop, so that P uptake was more than threefold greater. Losses of DRP were greater in both fall and spring following low-disturbance injection; however, application method had no effect on TP loads in runoff in either season. The cover crop reduced fall TP losses from plots with manure applied by either method. In spring, DRP losses were significantly higher from plots with the recently killed cover crop, but TP losses were not affected. Low-disturbance injection of swine manure into a standing cover crop can minimize plant damage and P losses in surface runoff while providing optimum P availability to a subsequent agronomic crop.

Reducing rural households' annual income fluctuations due to rainfall variation through diversification of wildlife use: portfolio theory in a case study of south eastern Zimbabwe

NARCIS (Netherlands)

Poshiwa, X.; Groeneveld, R.A.; Heitkonig, I.M.A.; Prins, H.H.T.; Ierland, van E.C.

2013-01-01

Annual rural incomes in Southern Africa show large rainfall-induced fluctuations. Variable rainfall has serious implications for agro-pastoral activities (crop cultivation and livestock keeping), whereas wildlife and tourism are less affected. The aim of this paper is to investigate the role of

An Updated Decision Support Interface: A Tool for Remote Monitoring of Crop Growing Conditions

Science.gov (United States)

Husak, G. J.; Budde, M. E.; Rowland, J.; Verdin, J. P.; Funk, C. C.; Landsfeld, M. F.

2014-12-01

Remote sensing of agroclimatological variables to monitor food production conditions is a critical component of the Famine Early Warning Systems Network portfolio of tools for assessing food security in the developing world. The Decision Support Interface (DSI) seeks to integrate a number of remotely sensed and modeled variables to create a single, simplified portal for analysis of crop growing conditions. The DSI has been reformulated to incorporate more variables and give the user more freedom in exploring the available data. This refinement seeks to transition the DSI from a "first glance" agroclimatic indicator to one better suited for the differentiation of drought events. The DSI performs analysis of variables over primary agricultural zones at the first sub-national administrative level. It uses the spatially averaged rainfall, normalized difference vegetation index (NDVI), water requirement satisfaction index (WRSI), and actual evapotranspiration (ETa) to identify potential hazards to food security. Presenting this information in a web-based client gives food security analysts and decision makers a lightweight portal for information on crop growing conditions in the region. The crop zones used for the aggregation contain timing information which is critical to the DSI presentation. Rainfall and ETa are accumulated from different points in the crop phenology to identify season-long deficits in rainfall or transpiration that adversely affect the crop-growing conditions. Furthermore, the NDVI and WRSI serve as their own seasonal accumulated measures of growing conditions by capturing vegetation vigor or actual evapotranspiration deficits. The DSI is currently active for major growing regions of sub-Saharan Africa, with intention of expanding to other areas over the coming years.

Assessing Climate Variability using Extreme Rainfall and ...

African Journals Online (AJOL)

user1

extreme frequency); the average intensity of rainfall from extreme events ... frequency and extreme intensity indices, suggesting that extreme events are more frequent and intense during years with high rainfall. The proportion of total rainfall from ...

Comparison of online and offline based merging methods for high resolution rainfall intensities

Science.gov (United States)

Shehu, Bora; Haberlandt, Uwe

2016-04-01

Accurate rainfall intensities with high spatial and temporal resolution are crucial for urban flow prediction. Commonly, raw or bias corrected radar fields are used for forecasting, while different merging products are employed for simulation. The merging products are proven to be adequate for rainfall intensities estimation, however their application in forecasting is limited as they are developed for offline mode. This study aims at adapting and refining the offline merging techniques for the online implementation, and at comparing the performance of these methods for high resolution rainfall data. Radar bias correction based on mean fields and quantile mapping are analyzed individually and also are implemented in conditional merging. Special attention is given to the impact of different spatial and temporal filters on the predictive skill of all methods. Raw radar data and kriging interpolation of station data are considered as a reference to check the benefit of the merged products. The methods are applied for several extreme events in the time period 2006-2012 caused by different meteorological conditions, and their performance is evaluated by split sampling. The study area is located within the 112 km radius of Hannover radar in Lower Saxony, Germany and the data set constitutes of 80 recording stations in 5 min time steps. The results of this study reveal how the performance of the methods is affected by the adjustment of radar data, choice of merging method and selected event. Merging techniques can be used to improve the performance of online rainfall estimation, which gives way to the application of merging products in forecasting.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil.

Science.gov (United States)

Battisti, R; Sentelhas, P C; Boote, K J

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha -1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .

Spatial Analysis of High-Resolution Radar Rainfall and Citizen-Reported Flash Flood Data in Ultra-Urban New York City

Directory of Open Access Journals (Sweden)

Brianne Smith

2017-09-01

Full Text Available New York City (NYC is an ultra-urban region, with over 50% impervious cover and buried stream channels. Traditional flood studies rely on the presence of stream gages to detect flood stage and discharge, but these methods cannot be used in ultra-urban areas. Here we create a high-resolution radar rainfall dataset for NYC and utilize citizen and expert reports of flooding throughout the city to study flash flooding in NYC. Results indicate that interactions between the urban area and land–sea boundary have an important impact on the spatial variability of both heavy rainfall and flooding, sometimes in contrast to results obtained for other cities. Top days of daily and hourly rainfall exhibit a rainfall maximum over the city center and an extended region of higher rainfall downwind of the city. The mechanism for flooding appears to vary across the city, with high groundwater tables influencing more coastal areas and high rain rates or large rain volumes influencing more inland areas. There is also a strong relationship between sewer type and flood frequency, with fewer floods observed in combined sewer areas. Flooding is driven by maximum one-hour to one-day rainfall, which is often substantially less rain than observed for the city-wide daily maximum.

Methodology for application of field rainfall simulator to revise c-factor database for conditions of the Czech Republic

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Neumann, Martin; Dostál, Tomáš; Krása, Josef; Kavka, Petr; Davidová, Tereza; Brant, Václav; Kroulík, Milan; Mistr, Martin; Novotný, Ivan

2016-04-01

The presentation will introduce a methodology of determination of crop and cover management factor (C-faktor) for the universal soil loss equation (USLE) using field rainfall simulator. The aim of the project is to determine the C-factor value for the different phenophases of the main crops of the central-european region, while also taking into account the different agrotechnical methods. By using the field rainfall simulator, it is possible to perform the measurements in specific phenophases, which is otherwise difficult to execute due to the variability and fortuity of the natural rainfall. Due to the number of measurements needed, two identical simulators will be used, operated by two independent teams, with coordinated methodology. The methodology will mainly specify the length of simulation, the rainfall intensity, and the sampling technique. The presentation includes a more detailed account of the methods selected. Due to the wide range of variable crops and soils, it is not possible to execute the measurements for all possible combinations. We therefore decided to perform the measurements for previously selected combinations of soils,crops and agrotechnologies that are the most common in the Czech Republic. During the experiments, the volume of the surface runoff and amount of sediment will be measured in their temporal distribution, as well as several other important parameters. The key values of the 3D matrix of the combinations of the crop, agrotechnique and soil will be determined experimentally. The remaining values will be determined by interpolation or by a model analogy. There are several methods used for C-factor calculation from measured experimental data. Some of these are not suitable to be used considering the type of data gathered. The presentation will discuss the benefits and drawbacks of these methods, as well as the final design of the method used. The problems concerning the selection of a relevant measurement method as well as the final

Detecting trends in 10-day rainfall amounts at five sites in the state ofSão Paulo, Brazil

Directory of Open Access Journals (Sweden)

Gabriel Constantino Blain

2014-09-01

Full Text Available The temporal distribution of the rainfall events within a crop growing season plays a crucial role on the crop yield. In this way, the main goal of this study was to evaluate the presence of climate trends in the 10-day rainfall totalsobtained from five weather stations in the State of São Paulo, Brazil (1951-2012.The autocorrelation function, the Run test and the Durbin-Watson test indicateda lack of significant serial correlation in theseseries. The wavelet analysis revealed no conclusive evidence of periodicities in the temporal variability of this variable. According to the Mann-Kendall test, most of the 10-day rainfall amounts obtained from the five weather stations shows no significant trends. However, for the locations of States Campinas, Pindorama and Ribeirão Preto, the significant decreasing trends observed during the 2nd and 3rd ten days of October suggests a possible change in the climatic patterns of these locations, which may be linked to a delay in the return of the rainy season.

Evaluation of climate adaptation options for Sudano-Sahelian cropping systems

NARCIS (Netherlands)

Traore, B.; Wijk, van M.T.; Descheemaeker, K.K.E.; Corbeels, M.; Rufino, M.C.; Giller, K.E.

2014-01-01

In the Sudano-Sahelian region, smallholder agricultural production is dominated by rain-fed production of millet, sorghum and maize for food consumption and of cotton for the market. A major constraint for crop production is the amount of rainfall and its intra and inter-annual variability. We

Added-values of high spatiotemporal remote sensing data in crop yield estimation

Science.gov (United States)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate

Topographic relationships for design rainfalls over Australia

Science.gov (United States)

Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

2016-02-01

Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as

Assessing methods for developing crop forecasting in the Iberian Peninsula

Science.gov (United States)

Ines, A. V. M.; Capa Morocho, M. I.; Baethgen, W.; Rodriguez-Fonseca, B.; Han, E.; Ruiz Ramos, M.

2015-12-01

Seasonal climate prediction may allow predicting crop yield to reduce the vulnerability of agricultural production to climate variability and its extremes. It has been already demonstrated that seasonal climate predictions at European (or Iberian) scale from ensembles of global coupled climate models have some skill (Palmer et al., 2004). The limited predictability that exhibits the atmosphere in mid-latitudes, and therefore de Iberian Peninsula (PI), can be managed by a probabilistic approach based in terciles. This study presents an application for the IP of two methods for linking tercile-based seasonal climate forecasts with crop models to improve crop predictability. Two methods were evaluated and applied for disaggregating seasonal rainfall forecasts into daily weather realizations: 1) a stochastic weather generator and 2) a forecast tercile resampler. Both methods were evaluated in a case study where the impacts of two seasonal rainfall forecasts (wet and dry forecast for 1998 and 2015 respectively) on rainfed wheat yield and irrigation requirements of maize in IP were analyzed. Simulated wheat yield and irrigation requirements of maize were computed with the crop models CERES-wheat and CERES-maize which are included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at several locations in Spain where the crop model was calibrated and validated with independent field data. These methodologies would allow quantifying the benefits and risks of a seasonal climate forecast to potential users as farmers, agroindustry and insurance companies in the IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse ones. ReferencesPalmer, T. et al., 2004. Development of a European multimodel ensemble system for seasonal-to-interannual prediction (DEMETER). Bulletin of the

Drought-avoiding plants with low water use can achieve high rainfall retention without jeopardising survival on green roofs.

Science.gov (United States)

Szota, Christopher; Farrell, Claire; Williams, Nicholas S G; Arndt, Stefan K; Fletcher, Tim D

2017-12-15

Green roofs are increasingly being used among the suite of tools designed to reduce the volume of surface water runoff generated by cities. Plants provide the primary mechanism for restoring the rainfall retention capacity of green roofs, but selecting plants with high water use is likely to increase drought stress. Using empirically-derived plant physiological parameters, we used a water balance model to assess the trade-off between rainfall retention and plant drought stress under a 30-year climate scenario. We compared high and low water users with either drought avoidance or drought tolerance strategies. Green roofs with low water-using, drought-avoiding species achieved high rainfall retention (66-81%) without experiencing significant drought stress. Roofs planted with other strategies showed high retention (72-90%), but they also experienced >50days of drought stress per year. However, not all species with the same strategy behaved similarly, therefore selecting plants based on water use and drought strategy alone does not guarantee survival in shallow substrates where drought stress can develop quickly. Despite this, it is more likely that green roofs will achieve high rainfall retention with minimal supplementary irrigation if planted with low water users with drought avoidance strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling the impact of conservation agriculture on crop production and soil properties in Mediterranean climate

Science.gov (United States)

Moussadek, Rachid; Mrabet, Rachid; Dahan, Rachid; Laghrour, Malika; Lembiad, Ibtissam; ElMourid, Mohamed

2015-04-01

In Morocco, rainfed agriculture is practiced in the majority of agricultural land. However, the intensive land use coupled to the irregular rainfall constitutes a serious threat that affect country's food security. Conservation agriculture (CA) represents a promising alternative to produce more and sustainably. In fact, the direct seeding showed high yield in arid regions of Morocco but its extending to other more humid agro-ecological zones (rainfall > 350mm) remains scarce. In order to promote CA in Morocco, differents trials have been installed in central plateau of Morocco, to compare CA to conventional tillage (CT). The yields of the main practiced crops (wheat, lentil and checkpea) under CA and CT were analyzed and compared in the 3 soils types (Vertisol, Cambisol and Calcisol). Also, we studied the effect of CA on soil organic matter (SOM) and soil losses (SL) in the 3 different sites. The APSIM model was used to model the long term impact of CA compared to CT. The results obtained in this research have shown favorable effects of CA on crop production, SOM and soil erosion. Key words: Conservation agriculture, yield, soil properties, modeling, APSIM, Morocco.

Water erosion during a 17-year period under two crop rotations in four soil management systems on a Southbrazilian Inceptisol

Science.gov (United States)

Bertol, Ildegardis; Vidal Vázquez, Eva; Paz Ferreiro, Jorge

2010-05-01

Soil erosion still remains a persistent issue in the world, and this in spite of the efforts to ameliorate soil management systems taken into account the point of view of environmental protection against soil losses. In South Brazil water erosion is mainly associated to rainfall events with a great volume and high intensity, which are more or less evenly distributed all over the year. Nowadays, direct drilling is the most widely soil management system used for the main crops of the region. However, some crops still are grown on conventionally tilled soils, which means mainly ploughing and harrowing and less frequently chisel ploughing. In Lages-Santa Catarina State, Brazil, a plot experiment under natural rain was started in 1992 on an Inceptisol with the aim of quantifying soil and water losses. Treatments included bare and vegetated plots. The crop succession was: oats (Avena strigosa), soybean (Glycine max), vetch (Vicia sativa), maize (Zea mays), fodder radish (Raphanus sativus) and beans (Phaseolus vulgaris). Soil tillage systems investigated in this study were: i) conventional tillage (CT), ii) reduced tillage (MT), iii) no tillage (NT) under crop rotation and iv) conventional tillage on bare soil (BS). Treatments CT and BS involved ploughing plus twice harrowing, whereas MT involved chisel ploughing plus harrowing. Rainfall erosivity from January 1 1992 to December 31 2009 was calculated. Soil losses from the BS treatment along the 17 year study period were higher than 1200 Mg ha-1. Crop cover significantly reduced erosion, so that under some crops soil losses in the CT treatment were 80% lower than in the BS treatment. In turn soil losses in the MT treatment, where tillage was performed by chiselling and harrowing, were on average about 50% lower than in the CT treatment. No tillage was the most efficient soil management system in reducing soil erosion, so that soil losses in the NT treatment were about 98% lower than in the BS treatment. The three

Soil Erodibility Parameters Under Various Cropping Systems of Maize

Science.gov (United States)

van Dijk, P. M.; van der Zijp, M.; Kwaad, F. J. P. M.

1996-08-01

For four years, runoff and soil loss from seven cropping systems of fodder maize have been measured on experimental plots under natural and simulated rainfall. Besides runoff and soil loss, several variables have also been measured, including rainfall kinetic energy, degree of slaking, surface roughness, aggregate stability, soil moisture content, crop cover, shear strength and topsoil porosity. These variables explain a large part of the variance in measured runoff, soil loss and splash erosion under the various cropping systems. The following conclusions were drawn from the erosion measurements on the experimental plots (these conclusions apply to the spatial level at which the measurements were carried out). (1) Soil tillage after maize harvest strongly reduced surface runoff and soil loss during the winter; sowing of winter rye further reduced winter erosion, though the difference with a merely tilled soil is small. (2) During spring and the growing season, soil loss is reduced strongly if the soil surface is partly covered by plant residues; the presence of plant residue on the surface appeared to be essential in achieving erosion reduction in summer. (3) Soil loss reductions were much higher than runoff reductions; significant runoff reduction is only achieved by the straw system having flat-lying, non-fixed plant residue on the soil surface; the other systems, though effective in reducing soil loss, were not effective in reducing runoff.

Urban rainfall estimation employing commercial microwave links

Science.gov (United States)

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

2015-04-01

Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

Dryland maize yields and water use efficiency in response to tillage/crop stubble and nutrient management practices in China

NARCIS (Netherlands)

Wang, X.B.; Dai, K.; Zhang, D.; Zhang, X.; Wang, Y.; Zhao, Q.; Cai, D.X.; Hoogmoed, W.B.; Oenema, O.

2011-01-01

Rainfed crop production in northern China is constrained by low and variable rainfall. This study explored the effects of tillage/crop residue and nutrient management practices on maize (Zea mays L.) yield, water use efficiency (WUE), and N agronomic use efficiency (NAE) at Shouyang Dryland Farming

Global Crop Monitoring: A Satellite-Based Hierarchical Approach

Directory of Open Access Journals (Sweden)

Bingfang Wu

2015-04-01

Full Text Available Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China and “sub-countries” (for the nine largest countries. The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI, Vegetation Condition Index (VCI, Cropped Arable Land Fraction (CALF as well as Cropping Intensity (CI. Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI, cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion. Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly “CropWatch bulletin” which

Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

Science.gov (United States)

Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

2014-05-01

Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to Estimate Seasonal Groundwater Use in South India

Directory of Open Access Journals (Sweden)

Sylvain Ferrant

2017-11-01

Full Text Available Indian agriculture relies on monsoon rainfall and irrigation from surface and groundwater. The interannual variability of monsoon rainfalls is high, which forces South Indian farmers to adapt their irrigated areas to local water availability. In this study, we have developed and tested a methodology for monitoring these spatiotemporal variations using Sentinel-1 and -2 observations over the Kudaliar catchment, Telangana State (~1000 km2. These free radar and optical data have been acquired since 2015 on a weekly basis over continental areas, at a high spatial resolution (10–20 m that is well adapted to the small areas of South Indian field crops. A machine learning algorithm, the Random Forest method, was used over three growing seasons (January to March and July to November 2016 and January to March 2017 to classify small patches of inundated rice paddy, maize, and other irrigated crops, as well as surface water stored in the small reservoirs scattered across the landscape. The crop production comprises only irrigated crops (less than 20% of the areas during the dry season (Rabi, December to March, to which rain-fed cotton is added to reach 60% of the areas during the monsoon season (Kharif, June to November. Sentinel-1 radar backscatter provides useful observations during the cloudy monsoon season. The lowest irrigated area totals were found during Rabi 2016 and Kharif 2016, accounting for 3.5 and 5% with moderate classification confusion. This confusion decreases with increasing areas of irrigated crops during Rabi 2017. During this season, 16% of rice and 6% of irrigated crops were detected after the exceptional rainfalls observed in September. Surface water in small surface reservoirs reached 3% of the total area, which corresponds to a high value. The use of both Sentinel datasets improves the method accuracy and strengthens our confidence in the resulting maps. This methodology shows the potential of automatically monitoring, in near

Understanding the Impact of Extreme Temperature on Crop Production in Karnataka in India

Science.gov (United States)

Mahato, S.; Murari, K. K.; Jayaraman, T.

2017-12-01

The impact of extreme temperature on crop yield is seldom explored in work around climate change impact on agriculture. Further, these studies are restricted mainly to crops such as wheat and maize. Since different agro-climatic zones bear different crops and cropping patterns, it is important to explore the nature of the impact of changes in climate variables in agricultural systems under differential conditions. The study explores the effects of temperature rise on the major crops paddy, jowar, ragi and tur in the state of Karnataka of southern India. The choice of the unit of study to understand impact of climate variability on crop yields is largely restricted to availability of data for the unit. While, previous studies have dealt with this issue by replacing yield with NDVI at finer resolution, the use of an index in place of yield data has its limitations and may not reflect the true estimates. For this study, the unit considered is taluk, i.e. sub-district level. The crop yield for taluk is obtained between the year the 1995 to 2011 by aggregating point yield data from crop cutting experiments for each year across the taluks. The long term temperature data shows significantly increasing trend that ranges between 0.6 to 0.75 C across Karnataka. Further, the analysis suggests a warming trend in seasonal average temperature for Kharif and Rabi seasons across districts. The study also found that many districts exhibit the tendency of occurrence of extreme temperature days, which is of particular concern in terms of crop yield, since exposure of crops to extreme temperature has negative consequences for crop production and productivity. Using growing degree days GDD, extreme degree days EDD and total season rainfall as predictor variables, the fixed effect model shows that EDD is a more influential parameter as compared to GDD and rainfall. Also it has a statistically significant negative effect in most cases. Further, quantile regression was used to evaluate

Application of Artificial Neural Networks in Canola Crop Yield Prediction

Directory of Open Access Journals (Sweden)

S. J. Sajadi

2014-02-01

Full Text Available Crop yield prediction has an important role in agricultural policies such as specification of the crop price. Crop yield prediction researches have been based on regression analysis. In this research canola yield was predicted using Artificial Neural Networks (ANN using 11 crop year climate data (1998-2009 in Gonbad-e-Kavoos region of Golestan province. ANN inputs were mean weekly rainfall, mean weekly temperature, mean weekly relative humidity and mean weekly sun shine hours and ANN output was canola yield (kg/ha. Multi-Layer Perceptron networks (MLP with Levenberg-Marquardt backpropagation learning algorithm was used for crop yield prediction and Root Mean Square Error (RMSE and square of the Correlation Coefficient (R2 criterions were used to evaluate the performance of the ANN. The obtained results show that the 13-20-1 network has the lowest RMSE equal to 101.235 and maximum value of R2 equal to 0.997 and is suitable for predicting canola yield with climate factors.

A Merging Framework for Rainfall Estimation at High Spatiotemporal Resolution for Distributed Hydrological Modeling in a Data-Scarce Area

Directory of Open Access Journals (Sweden)

Yinping Long

2016-07-01

Full Text Available Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolution of satellite data are available. The objective of the study is to present a satellite and rain gauge data-merging framework adapting for coarse resolution and data-sparse designs. In the framework, a statistical spatial downscaling method based on the relationships among precipitation, topographical features, and weather conditions was used to downscale the 0.25° daily rainfall field derived from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA precipitation product version 7. The nonparametric merging technique of double kernel smoothing, adapting for data-sparse design, was combined with the global optimization method of shuffled complex evolution, to merge the downscaled TRMM and gauged rainfall with minimum cross-validation error. An indicator field representing the presence and absence of rainfall was generated using the indicator kriging technique and applied to the previously merged result to consider the spatial intermittency of daily rainfall. The framework was applied to estimate daily precipitation at a 1 km resolution in the Qinghai Lake Basin, a data-scarce area in the northeast of the Qinghai-Tibet Plateau. The final estimates not only captured the spatial pattern of daily and annual precipitation with a relatively small estimation error, but also performed very well in stream flow simulation when applied to force the geomorphology-based hydrological model (GBHM. The proposed framework thus appears feasible for rainfall estimation at high spatiotemporal resolution in data-scarce areas.

Colonisation of winter wheat grain by Fusarium spp. and mycotoxin content as dependent on a wheat variety, crop rotation, a crop management system and weather conditions.

Science.gov (United States)

Czaban, Janusz; Wróblewska, Barbara; Sułek, Alicja; Mikos, Marzena; Boguszewska, Edyta; Podolska, Grażyna; Nieróbca, Anna

2015-01-01

Field experiments were conducted during three consecutive growing seasons (2007/08, 2008/09 and 2009/10) with four winter wheat (Triticum aestivum L.) cultivars - 'Bogatka', 'Kris', 'Satyna' and 'Tonacja' - grown on fields with a three-field crop rotation (winter triticale, spring barley, winter wheat) and in a four-field crop rotation experiment (spring wheat, spring cereals, winter rapeseed, winter wheat). After the harvest, kernels were surface disinfected with 2% NaOCl and then analysed for the internal infection by different species of Fusarium. Fusaria were isolated on Czapek-Dox iprodione dichloran agar medium and identified on the basis of macro- and micro-morphology on potato dextrose agar and synthetic nutrient agar media. The total wheat grain infection by Fusarium depended mainly on relative humidity (RH) and a rainfall during the flowering stage. Intensive rainfall and high RH in 2009 and 2010 in the period meant the proportions of infected kernels by the fungi were much higher than those in 2008 (lack of precipitation during anthesis). Weather conditions during the post-anthesis period changed the species composition of Fusarium communities internally colonising winter wheat grain. The cultivars significantly varied in the proportion of infected kernels by Fusarium spp. The growing season and type of crop rotation had a distinct effect on species composition of Fusarium communities colonising the grain inside. A trend of a higher percentage of the colonised kernels by the fungi in the grain from the systems using more fertilisers and pesticides as well as the buried straw could be perceived. The most frequent species in the grain were F. avenaceum, F. tricinctum and F. poae in 2008, and F. avenaceum, F. graminearum, F. tricinctum and F. poae in 2009 and 2010. The contents of deoxynivalenol and zearalenon in the grain were correlated with the percentage of kernels colonised by F. graminearum and were the highest in 2009 in the grain from the four

Rainfall prediction with backpropagation method

Science.gov (United States)

Wahyuni, E. G.; Fauzan, L. M. F.; Abriyani, F.; Muchlis, N. F.; Ulfa, M.

2018-03-01

Rainfall is an important factor in many fields, such as aviation and agriculture. Although it has been assisted by technology but the accuracy can not reach 100% and there is still the possibility of error. Though current rainfall prediction information is needed in various fields, such as agriculture and aviation fields. In the field of agriculture, to obtain abundant and quality yields, farmers are very dependent on weather conditions, especially rainfall. Rainfall is one of the factors that affect the safety of aircraft. To overcome the problems above, then it’s required a system that can accurately predict rainfall. In predicting rainfall, artificial neural network modeling is applied in this research. The method used in modeling this artificial neural network is backpropagation method. Backpropagation methods can result in better performance in repetitive exercises. This means that the weight of the ANN interconnection can approach the weight it should be. Another advantage of this method is the ability in the learning process adaptively and multilayer owned on this method there is a process of weight changes so as to minimize error (fault tolerance). Therefore, this method can guarantee good system resilience and consistently work well. The network is designed using 4 input variables, namely air temperature, air humidity, wind speed, and sunshine duration and 3 output variables ie low rainfall, medium rainfall, and high rainfall. Based on the research that has been done, the network can be used properly, as evidenced by the results of the prediction of the system precipitation is the same as the results of manual calculations.

Temporal changes in climatic variables and their impact on crop yields in southwestern China.

Science.gov (United States)

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing-a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (Pchanges in climatic variables in this region. Yield of rice increased with rainfall (Pclimatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Effects of Carbon and Cover Crop Residues on N2O and N2 Emissions

Science.gov (United States)

Burger, M.; Cooperman, Y.; Horwath, W. R.

2016-12-01

In Mediterranean climate, nitrous oxide emissions occurring with the first rainfall after the dry summer season can contribute up to 50% of agricultural systems' total annual emissions, but the drivers of these emissions have not been clearly identified, and there are only few measurements of atmospheric nitrogen (N2) production (denitrification) during these events. In lab incubations, we investigated N2O and N2 production, gross ammonification and nitrification, and microbial N immobilization with wet-up in soil from a vineyard that was previously fallow or where cover crop residue had been incorporated the previous spring. Before the first rainfall, we measured 120 mg dissolved organic carbon (DOC-C) kg-1 soil in the 0-5 cm layer of this vineyard, and after the rain 10 mg DOC-C kg-1, while nitrate levels before the rain were cover cropped soil. The N2O/N2 production was 2, 7, 9, and 86% in fallow, legume-grass mixture, rye, and legume cover cropped soil. The N2O/N2 ratio tended to increase with lower DOC (post-rain) levels in the soil. The results suggest that accumulated carbon in dry surface soil is the main driving factor of N2O and N2 emissions through denitrification with the first rainfall after prolonged dry periods.

Crops nutrition management as measures for climate change adaptation

Science.gov (United States)

Hladkikh, Yevheniia

2017-04-01

The main feature of climate change in most countries worldwide is the increasing frequency of extreme weather events such as unpredictable floods, droughts and another abiotic stress for crops. It is not surprising that most countries are interested in technologies for adapting agriculture to climate change, and Ukraine is no exception. But traditional measures which exist in the world practice do not sufficiently take into account the importance of interactions between soil and plants. For example, from 138 projects of the European Climate Adaption Platform only 16 are correlated with the soil, but only one of them investigates the interaction in "soil-plant" system. In this connection, the main aim of our research was to determine the effectiveness of agrochemical techniques in plant nutrition management for crops adaptation to extreme weather fluctuations. The influence of different agrochemical measures in "soil-plant" system on the resilience of crops to different climate conditions of the growing season were investigated in a long-term field experiment that was started in 1969. The experiment was on a Chernozem at the Grakivske Experimental Station in Kharkiv region, Ukraine. Soil samples were taken during the growing season from field under different crops. Soil and plant samples analyses included macro- and micronutrients content, soil moisture. Research in the field experiment has demonstrated a close correlation between the average annual rainfall and content of available forms of macronutrients in the soil (especially for nitrate nitrogen the correlation coefficient was 0.98). Studies have shown that increasing the annual rainfall by 100 mm increases the content of nitrate nitrogen in the soil at 7 mg per kg. Another correlation has shown that the decrease amount of precipitation reduces the range of the N:P and consequently the availability of these elements to crops. Thus, in drought conditions, efficiency of the use of available nutrients by crops

Characteristics of the water footprint of rice production under different rainfall years in Jilin Province, China.

Science.gov (United States)

Li, Hongying; Qin, Lijie; He, Hongshi

2018-06-01

Rice is a special crop, and its production differs from that of other crops because it requires a thin layer of water coverage for a long period. The calculation of the water footprint of rice production should differ from that of other crops owing to the rice growing process. This study improved the calculation of blue and grey water footprints of rice production and analyzed the variations in the water footprints for rice production under different rainfall years in Jilin Province. In the drought year, the green water footprint was the lowest and the blue water footprint was the highest among the three years, while in the humid year, the green water footprint was the highest and the blue water footprint was not the lowest. The areas with higher water footprints were found in the east and west regions of Jilin Province, while the areas with lower water footprints were found in the middle east and middle regions of Jilin Province. Blue water was the primary water resource for rice production, although more precipitation provided the highest green water in the humid year; also, the spatial distributions of water footprints were not the same under different rainfall years. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Bias adjustment and advection interpolation of long-term high resolution radar rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Rasmussen, Michael R.

2014-01-01

It is generally acknowledged that in order to apply radar rainfall data for hydrological proposes adjustment against ground observations are crucial. Traditionally, radar reflectivity is transformed into rainfall rates applying a fixed reflectivity – rainfall rate relationship even though...... this is known to depend on the changing drop size distribution of the specific rain. This creates a transient bias between the radar rainfall and the ground observations due to seasonal changes of the drop size distribution as well as other atmospheric effects and effects related to the radar observational...

Leaf wetness distribution within a potato crop

Science.gov (United States)

Heusinkveld, B. G.

2010-07-01

The Netherlands has a mild maritime climate and therefore the major interest in leaf wetness is associated with foliar plant diseases. During moist micrometeorological conditions (i.e. dew, fog, rain), foliar fungal diseases may develop quickly and thereby destroy a crop quickly. Potato crop monocultures covering several hectares are especially vulnerable to such diseases. Therefore understanding and predicting leaf wetness in potato crops is crucial in crop disease control strategies. A field experiment was carried out in a large homogeneous potato crop in the Netherlands during the growing season of 2008. Two innovative sensor networks were installed as a 3 by 3 grid at 3 heights covering an area of about 2 hectares within two larger potato crops. One crop was located on a sandy soil and one crop on a sandy peat soil. In most cases leaf wetting starts in the top layer and then progresses downward. Leaf drying takes place in the same order after sunrise. A canopy dew simulation model was applied to simulate spatial leaf wetness distribution. The dew model is based on an energy balance model. The model can be run using information on the above-canopy wind speed, air temperature, humidity, net radiation and within canopy air temperature, humidity and soil moisture content and temperature conditions. Rainfall was accounted for by applying an interception model. The results of the dew model agreed well with the leaf wetness sensors if all local conditions were considered. The measurements show that the spatial correlation of leaf wetness decreases downward.

The Spatial Scaling of Global Rainfall Extremes

Science.gov (United States)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

Science.gov (United States)

Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

2015-04-01

Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum

Vegetation Variability And Its Effect On Monsoon Rainfall Over South East Asia: Observational and Modeling Results

Science.gov (United States)

Sarkar, S.; Peters-Lidard, C.; Chiu, L.; Kafatos, M.

2005-12-01

vegetation to crop land affects monsoon rainfall in two ways: 1) The presence of cropland increases the sensible heat release from ground, increasing the chances for development of forced convection; 2) Large scale irrigation associated with spring crop development creates a moister lower boundary layer thus inducing more moist instability and free convection in the succeeding season.

First results from comparison of rainfall estimations by GPM IMERG with rainfall measurements from the WegenerNet high density network

Science.gov (United States)

Oo, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Jürgen

2016-04-01

The research level products of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG "Final" run datasets) were compared with rainfall measurements from the WegenerNet high density network as part of ground validation (GV) projects of GPM missions. The WegenerNet network comprises 151 ground level weather stations in an area of 15 km × 20 km in south-eastern Austria (Feldbach region, ˜46.93° N, ˜15.90° E) designed to serve as a long-term monitoring and validation facility for weather and climate research and applications. While the IMERG provides rainfall estimations every half hour at 0.1° resolution, the WegenerNet network measures rainfall every 5 minutes at around 2 km2 resolution and produces 200 m × 200 m gridded datasets. The study was conducted on the domain of the WegenerNet network; eight IMERG grids are overlapped with the network, two of which are entirely covered by the WegenerNet (40 and 39 stations in each grid). We investigated data from April to September of the years 2014 to 2015; the date of first two years after the launch of the GPM Core Observatory. Since the network has a flexibility to work with various spatial and temporal scales, the comparison could be conducted on average-points to pixel basis at both sub-daily and daily timescales. This presentation will summarize the first results of the comparison and future plans to explore the characteristics of errors in the IMERG datasets.

Relationship between drought intensity and crop production in Serbia and Montenegro

International Nuclear Information System (INIS)

Dragovic, Svetimir; Maksimovic, Livija

2004-01-01

Serbia and Montenegro is divided into three parts - the Mediterranean part, the mountainous part and the lowlands. Each part features distinctive local climatic conditions. The lowlands in the northern, eastern and central parts of the country, in which agricultural production is concentrated, have changeable, unstable and unforeseeable rainfall and dry periods between July and September. The northern part of the country (the Vojvodina Province) has a moderately continental climate with warm summers, cold and dry winters and the unevenly distributed precipitation, with frequent occurrences of drought. The analysis of drought has been made on the basis of precipitation data collected in Novi Sad, which represents the northern part, and Zajecar, which represents the eastern part of the country. Precipitation sums by hydrological years (October - September) vary largely, from 322 to 867 mm. The variations during growing season are also significant, from 172 to 487 mm. The precipitation during growing season is important for water provision to plants. The average precipitation sum for the Vojvodina Province (Novi Sad), for the hydrological years in an 81-year period (1923-2002) is 605 mm, 341 mm in the vegetation period and 264 mm in the winter period. In the eastern part (Zajecar), the annual average is 592 mm (from 416 to 704 mm) and the average for growing season is 326 mm (from 170 to 478 mm). In Serbia and Montenegro, droughts are frequent in the northern, eastern, and central parts of the country and they usually hit large areas of land. Droughts are characterized by fairly long spells with no precipitation, high air temperatures, hot and dry winds, increased plant water requirements, and soil moisture levels below the wilting point. Ail these phenomena affect plant growth and development and considerably reduce yields of most crop species. In some years and some regions of the country, drought reaches catastrophic proportions for agricultural production. The

Monsoon Rainfall and Landslides in Nepal

Science.gov (United States)

Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of

Impact of the spatial resolution of climatic data and soil physical properties on regional corn yield predictions using the STICS crop model

Science.gov (United States)

Jégo, Guillaume; Pattey, Elizabeth; Mesbah, S. Morteza; Liu, Jiangui; Duchesne, Isabelle

2015-09-01

The assimilation of Earth observation (EO) data into crop models has proven to be an efficient way to improve yield prediction at a regional scale by estimating key unknown crop management practices. However, the efficiency of prediction depends on the uncertainty associated with the data provided to crop models, particularly climatic data and soil physical properties. In this study, the performance of the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model for predicting corn yield after assimilation of leaf area index derived from EO data was evaluated under different scenarios. The scenarios were designed to examine the impact of using fine-resolution soil physical properties, as well as the impact of using climatic data from either one or four weather stations across the region of interest. The results indicate that when only one weather station was used, the average annual yield by producer was predicted well (absolute error <5%), but the spatial variability lacked accuracy (root mean square error = 1.3 t ha-1). The model root mean square error for yield prediction was highly correlated with the distance between the weather stations and the fields, for distances smaller than 10 km, and reached 0.5 t ha-1 for a 5-km distance when fine-resolution soil properties were used. When four weather stations were used, no significant improvement in model performance was observed. This was because of a marginal decrease (30%) in the average distance between fields and weather stations (from 10 to 7 km). However, the yield predictions were improved by approximately 15% with fine-resolution soil properties regardless of the number of weather stations used. The impact of the uncertainty associated with the EO-derived soil textures and the impact of alterations in rainfall distribution were also evaluated. A variation of about 10% in any of the soil physical textures resulted in a change in dry yield of 0.4 t ha-1. Changes in rainfall distribution

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

Science.gov (United States)

Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

Effect of Different Mulches under Rainfall Concentration System on Corn Production in the Semi-arid Areas of the Loess Plateau

Science.gov (United States)

Ren, Xiaolong; Zhang, Peng; Chen, Xiaoli; Guo, Jingjing; Jia, Zhikuan

2016-01-01

The ridge and furrow farming system for rainfall concentration (RC) has gradually been popularized to improve the water availability for crops and to increase the water use efficiency (WUE), thereby stabilizing high yields. In the RC system, plastic-covered ridges are rainfall harvesting zones and furrows are planting zones. In this study, we optimized the mulching patterns for RC planting to mitigate the risks of drought during crop production in semi-arid agricultural areas. We conducted a four-year field study to determine the effects on corn production of mulching with 0.08-mm plastic film, maize straw, 8% biodegradable film, liquid film, bare furrow, and conventional flat (CF) farming. We found that RC significantly increased (P > 0.05) the soil moisture storage in the top 0-100 cm layer and the topsoil temperature (0-10 cm) during the corn-growing season. Combining RC with mulching further improved the rain-harvesting, moisture-retaining, and yield-increasing effects in furrows. Compared with CF, the four-year average yield increased by 1497.1 kg ha-1 to 2937.3 kg ha-1 using RC with mulch treatments and the WUE increased by 2.3 kg ha-1 mm-1 to 5.1 kg ha-1 mm-1.

Validation of a global satellite rainfall product for real time monitoring of meteorological extremes

Science.gov (United States)

Cánovas-García, Fulgencio; García-Galiano, Sandra; Karbalaee, Negar

2017-10-01

The real time monitoring of storms is important for the management and prevention of flood risks. However, in the southeast of Spain, it seems that the density of the rain gauge network may not be sufficient to adequately characterize the rainfall spatial distribution or the high rainfall intensities that are reached during storms. Satellite precipitation products such as PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System) could be used to complement the automatic rain gauge networks and so help solve this problem. However, the PERSIANN-CCS product has only recently become available, so its operational validity for areas such as south-eastern Spain is not yet known. In this work, a methodology for the hourly validation of PERSIANN-CCS is presented. We used the rain gauge stations of the SIAM (Sistema de Información Agraria de Murcia) network to study three storms with a very high return period. These storms hit the east and southeast of the Iberian Peninsula and resulted in the loss of human life, major damage to agricultural crops and a strong impact on many different types of infrastructure. The study area is the province of Murcia (Region of Murcia), located in the southeast of the Iberian Peninsula, covering an area of more than 11,000 km2 and with a population of almost 1.5 million. In order to validate the PERSIANN-CCS product for these three storms, contrasts were made with the hyetographs registered by the automatic rain gauges, analyzing statistics such as bias, mean square difference and Pearson's correlation coefficient. Although in some cases the temporal distribution of rainfall was well captured by PERSIANN-CCS, in several rain gauges high intensities were not properly represented. The differences were strongly correlated with the rain gauge precipitation, but not with satellite-obtained rainfall. The main conclusion concerns the need for specific local calibration

Radioactivity in food crops from high background radiation area in southwest area

International Nuclear Information System (INIS)

Shanthi, G.; Maniyan, C.G.; Allan Gnana Raj, G.; Thampi Thanka Kumaran, J.

2009-01-01

The study was carried out to evaluate radioactive concentration in food crops grown in naturally high-background radiation areas in southwest India. Seventeen varieties of food crops were collected from different parts of Kanyakumari district. The gross alpha and beta activities of the collected samples were measured using alpha scintillation counter and low beta counter respectively. The alpha activity was maximum in tapioca (497± 72 Bq kg -1 ) and the beta activity was maximum in paddy grain (10,946±583 Bq kg -1 ). The gamma activity of the food samples was studied by measuring the activity concentration of the radionuclides ( 226 Ra, 228 Th, 238 U, 40 K) in the food crops. The radioactivity content of the food crops from high-background radiation area was higher when compared to similar samples collected from low-background radiation area. The daily radionuclide intake from the food crops grown and consumed by the public was 127.696 Bq and daily internal dose resulting from ingestion of radionuclides in food was 2.34 μSv. (author)

Herbaceous energy crops in humid lower South USA

Energy Technology Data Exchange (ETDEWEB)

Prine, G.M.; Woodard, K.R. [Univ. of Florida, Gainesville, FL (United States)

1993-12-31

The humid lower South has the long warm growing season and high rainfall conditions needed for producing high-yielding perennial herbaceous grasses and shrubs. Many potential biomass plants were evaluated during a ten-year period. Perennial tall grasses such as elephantgrass (Pennisetum purpureum), sugarcane and energycane (Saccharum spp.) and the leguminous shrub Leucaena leucocephala were the highest in biomass production. These perennial crops often have top growth killed by winter freezes and regenerate from underground parts. The tall grasses have high yields because of linear crop growth rates of 18 to 27 g m{sup 2} d{sup {minus}1} for long periods (140 to 196 d) each season. Tall grasses must be planted vegetatively, which is more costly than seed propagation, however, once established, they may persist for many seasons. Oven dry biomass yields have varied from 20 to 45 Mg ha{sup {minus}1} yr{sup {minus}1} in colder subtropical to mild temperate locations to over 60 Mg ha{sup {minus}1} yr{sup {minus}1} in the lower portion of the Florida peninsular. Highest biomass yields have been produced when irrigated with sewage effluent or when grown on phosphatic clay and muck soils in south Florida. The energy content of 1 Mg of oven dry tall grass and leucaena is equivalent to that of about 112 and 123 gallons of number 2 diesel fuel, respectively.

Geo-statistical model of Rainfall erosivity by using high temporal resolution precipitation data in Europe

Science.gov (United States)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

2015-04-01

Rainfall erosivity (R-factor) is among the 6 input factors in estimating soil erosion risk by using the empirical Revised Universal Soil Loss Equation (RUSLE). R-factor is a driving force for soil erosion modelling and potentially can be used in flood risk assessments, landslides susceptibility, post-fire damage assessment, application of agricultural management practices and climate change modelling. The rainfall erosivity is extremely difficult to model at large scale (national, European) due to lack of high temporal resolution precipitation data which cover long-time series. In most cases, R-factor is estimated based on empirical equations which take into account precipitation volume. The Rainfall Erosivity Database on the European Scale (REDES) is the output of an extensive data collection of high resolution precipitation data in the 28 Member States of the European Union plus Switzerland taking place during 2013-2014 in collaboration with national meteorological/environmental services. Due to different temporal resolutions of the data (5, 10, 15, 30, 60 minutes), conversion equations have been applied in order to homogenise the database at 30-minutes interval. The 1,541 stations included in REDES have been interpolated using the Gaussian Process Regression (GPR) model using as covariates the climatic data (monthly precipitation, monthly temperature, wettest/driest month) from WorldClim Database, Digital Elevation Model and latitude/longitude. GPR has been selected among other candidate models (GAM, Regression Kriging) due the best performance both in cross validation (R2=0.63) and in fitting dataset (R2=0.72). The highest uncertainty has been noticed in North-western Scotland, North Sweden and Finland due to limited number of stations in REDES. Also, in highlands such as Alpine arch and Pyrenees the diversity of environmental features forced relatively high uncertainty. The rainfall erosivity map of Europe available at 500m resolution plus the standard error

Rainfall erosivity in Europe.

Science.gov (United States)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

2015-04-01

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods

Prediction of rainfall-induced shallow landslides at national scale in Italy

Science.gov (United States)

Montrasio, Lorella; Valentino, Roberto; Rossi, Lauro; Rudari, Roberto; Terrone, Andrea

2013-04-01

In Italy, landslides are very frequent, widespread and dangerous phenomena. In the last decades, climate changes, which provoked weather conditions characterized by localized rainfall events of high intensity and short duration, together with modifications of land use and an increase of urban areas, have led to a progressive increase of the frequency and extent of rainfall-induced landslides. These phenomena caused, in turn, considerable damage to structures, infrastructure and crops, as well as casualties. These natural and anthropogenic factors determine a series of hydrogeological problems for both land resource and for inhabited areas, industrial areas and for the infrastructural network. The need for a continued monitoring activity that ensures the preservation of life and human activities, and for a real-time assessment of landslide risk, in close correlation with rainfall forecasts, is therefore increasing. The paper deals with the application, on national scale in the Italian territory, of the physically-based stability model SLIP (Shallow Landslides Instability Prediction). The SLIP model has been firstly developed at the Department of Civil Engineering at the University of Parma since 1997, in order to describe the triggering mechanism of rainfall-induced landslides. More recently, the SLIP model has been tested as a prototype early warning system for rainfall-induced landslides in Italy, using rainfall data and geospatial datasets. The model, which is based on the limit equilibrium method, is deliberately simplified, in order to evaluate the safety factor of a slope in function of the geotechnical characteristics of the soil, the geometrical features of the slope and the rainfall depth. A back analysis concerning the occurrence of some recent case-histories of rainfall-induced shallow landslides in the Italian territory is carried out and the main results are shown. The main features of the SLIP model are briefly recalled and particular attention is

Relevance of Indian Summer Monsoon and its Tropical Indo-Pacific Climate Drivers for the Kharif Crop Production

Science.gov (United States)

Amat, Hemadri Bhusan; Karumuri, Ashok

2017-12-01

While the Indian agriculture has earlier been dependent on the Indian summer monsoon rainfall (ISMR), a multifold increase in irrigation and storage facilities raise a question whether the ISMR is still as relevant. We revisit this question using the latest observational climate datasets as well as the crop production data and find that the ISMR is still relevant for the Kharif crop production (KCP). In addition, in the recent changes in the tropical Indo-Pacific driver evolutions and frequency, particularly more frequent occurrence of the ENSO Modokis in place of the canonical ENSOs, we carry out a correlation analysis to estimate the impact of the various Indo-Pacific climate drivers on the rainfall of individual Indian states for the period 1998-2013, for which crop production data for the most productive Indian states, namely West Bengal, Odisha, United Andhra Pradesh (UAP), Haryana, Punjab, Karnataka, Kerala, Madhya Pradesh, Bihar and Uttar Pradesh are available. The results suggest that the KCP of the respective states are significantly correlated with the summer monsoon rainfall at the 95-99% confidence levels. Importantly, we find that the NINO 3.4 and ENSO Modoki indices have a statistically significant correlation with the KCP of most of the Indian states, particularly in states such as UAP and Karnataka, through induction of anomalous local convergence/divergence, well beyond the equatorial Indian Ocean. The KCP of districts in UAP also has a significant response to all the climate drivers, having implication for prediction of local crop yield.

Assessing the impact of climate variability on cropping patterns in Kenya

Science.gov (United States)

Wahome, A.; Ndungu, L. W.; Ndubi, A. O.; Ellenburg, W. L.; Flores Cordova, A. I.

2017-12-01

Climate variability coupled with over-reliance on rain-fed agricultural production on already strained land that is facing degradation and declining soil fertility; highly impacts food security in Africa. In Kenya, dependence on the approximately 20% of land viable for agricultural production under climate stressors such as variations in amount and frequency of rainfall within the main growing season in March-April-May(MAM) and changing temperatures influence production. With time, cropping zones have changed with the changing climatic conditions. In response, the needs of decision makers to effectively assess the current cropped areas and the changes in cropping patterns, SERVIR East and Southern Africa developed updated crop maps and change maps. Specifically, the change maps depict the change in cropping patterns between 2000 and 2015 with a further assessment done on important food crops such as maize. Between 2001 and 2015 a total of 5394km2 of land was converted to cropland with 3370km2 being conversion to maize production. However, 318 sq km were converted from maize to other crops or conversion to other land use types. To assess the changes in climatic conditions, climate parameters such as precipitation trends, variation and averages over time were derived from CHIRPs (Climate Hazards Infra-red Precipitation with stations) which is a quasi-global blended precipitation dataset available at a resolution of approximately 5km. Water Requirements Satisfaction Index (WRSI) water balance model was used to assess long term trends in crop performance as a proxy for maize yields. From the results, areas experiencing declining and varying precipitation with a declining WRSI index during the long rains displayed agricultural expansion with new areas being converted to cropland. In response to climate variability, farmers have converted more land to cropland instead of adopting better farming methods such as adopting drought resistant cultivars and using better farm

Assessment of summer rainfall forecast skill in the Intra-Americas in GFDL high and low-resolution models

Science.gov (United States)

Krishnamurthy, Lakshmi; Muñoz, Ángel G.; Vecchi, Gabriel A.; Msadek, Rym; Wittenberg, Andrew T.; Stern, Bill; Gudgel, Rich; Zeng, Fanrong

2018-05-01

The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July-August-September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications

Mycorrhiza formation and nutrient concentration in leeks (¤Allium porrum¤) in relation to previous crop and cover crop management on high P soils

DEFF Research Database (Denmark)

Sørensen, J.N.; Larsen, J.; Jakobsen, I.

2005-01-01

An improved integration of mycorrhizas may increase the sustainability in plant production. Two strategies for increasing the soil inoculum potential of mycorrhizal fungi were investigated in field experiments with leeks: Pre-cropping with mycorrhizal main crops and pre-establishment of mycorrhizal......, increased the colonization of leek roots by mycorrhizal fungi. During early growth stages, this increase was 45-95% relative to no cover crop. However, cover cropping did not significantly increase nutrient concentration or growth. These variables were not influenced by the time of cover crop incorporation...... or tillage treatments. Differences in colonization, nutrient uptake and plant growth diminished during the growing period and at the final harvest date, the effects on plant production disappeared. High soil P level or high soil inoculum level was most likely responsible for the limited response of increased...

Addressing crop interactions within cropping systems in LCA

DEFF Research Database (Denmark)

Goglio, Pietro; Brankatschk, Gerhard; Knudsen, Marie Trydeman

2018-01-01

objectives of this discussion article are as follows: (i) to discuss the characteristics of cropping systems which might affect the LCA methodology, (ii) to discuss the advantages and the disadvantages of the current available methods for the life-cycle assessment of cropping systems, and (iii) to offer...... management and emissions, and (3) functional unit issues. The LCA approaches presented are as follows: cropping system, allocation approaches, crop-by-crop approach, and combined approaches. The various approaches are described together with their advantages and disadvantages, applicability...... considers cropping system issues if they are related to multiproduct and nutrient cycling, while the crop-by-crop approach is highly affected by assumptions and considers cropping system issues only if they are related to the analyzed crop. Conclusions Each LCA approach presents advantages and disadvantages...

Soil Management Practices to Improve Nutrient-use Efficiencies and Reduce Risk in Millet-based Cropping Systems in the Sahel

Directory of Open Access Journals (Sweden)

Koala, S.

2003-01-01

Full Text Available Low soil fertility and moisture deficit are among the main constraints to sustainable crop yields in the Sahel. A study therefore, was conducted at the ICRISAT Sahelian Center, Sadore in Niger to test the hypothesis that integrated soil husbandry practices consisting of manure, fertilizer and crop residues in rotational cropping systems use organic and mineral fertilizes efficiently, thereby resulting in higher yields and reduced risk. Results from an analysis of variance showed that choice of cropping systems explained more than 50% of overall variability in millet and cowpea grain yields. Among the cropping systems, rotation gave higher yields than sole crop and intercropping systems and increased millet yield by 46% without fertilizer. Rainfall-use efficiency and partial factor productivity of fertilizer were similarly higher in rotations than in millet monoculture system. Returns from cowpea grown in cowpea-millet rotation without fertilizer and the medium rates of fertilizers (4 kg P.ha-1 + 15 kg N.ha-1 were found to be most profitable in terms of high returns and low risk, principally because of a higher price of cowpea than millet. The study recommends crop diversification, either in the form of rotations or relay intercropping systems for the Sahel as an insurance against total crop failure.

Heterogeneity of Dutch rainfall

NARCIS (Netherlands)

Witter, J.V.

1984-01-01

Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

Rainfall and Development of Zika Virus

African Journals Online (AJOL)

2017-11-01

Nov 1, 2017 ... between rainfall and incidence of arbovirus disease such as dengue is well demonstrated (2). For Zika virus an infection, a similar observation can be expected. A recent report from Thailand can also show the expected pattern of the prevalence of Zika virus infection in the areas with high rainfall (3).

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010.

Science.gov (United States)

Mukabutera, Assumpta; Thomson, Dana; Murray, Megan; Basinga, Paulin; Nyirazinyoye, Laetitia; Atwood, Sidney; Savage, Kevin P; Ngirimana, Aimable; Hedt-Gauthier, Bethany L

2016-08-05

Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff) but had no impact among children in household with improved toilets. Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

Sprinkling experiments to simulate high and intense rainfall for process based investigations - a comparison of two methods

Science.gov (United States)

Müller, C.; Seeger, M.; Schneider, R.; Johst, M.; Casper, M.

2009-04-01

Land use and land management changes affect runoff and erosion dynamics. So, measures within this scope are often directed towards the mitigation of natural hazards such as floods and landslides. However, the effects of these changes (e.g. in soil physics after reforestation or a less extensive agriculture) are i) detectable first many years later or ii) hardly observable with conventional methods. Therefore, sprinkling experiments are frequently used for process based investigations of near-surface hydrological response as well as rill and interrill erosion. In this study, two different sprinkling systems have been applied under different land use and at different scales to elucidate and quantify dominant processes of runoff generation, as well as to relate them to the detachment and transport of solids. The studies take place at the micro-scale basin Zemmer and Frankelbach in Germany. At the Zemmer basin the sprinkling experiments were performed on agricultural land while the experiments in Frankelbach were performed at reforested sites. The experiments were carried out i) with a small mobile rainfall simulator of high rainfall intensities (40 mm h-1) and ii) with a larger one covering a slope segment and simulating high rainfall amounts (120 mm in 3 days). Both methods show basically comparable results. On the agricultural sites clear differences could be observed between different soil management types: contrasting to the conventionally tilled soils, deep loosened soils (in combination with conservative tillage) do not produce overland flow, but tend to transfer more water by interflow processes, retaining large amounts in the subsoil. For the forested sites runoff shows a high variability as determined the larger and the smaller rainfall simulations. This variability is rather due to the different forest and soil types than to methodologically different settings of the sprinkling systems. Both rainfall simulation systems characterized the runoff behavior in a

Rainfall Characteristics and Regionalization in Peninsular Malaysia Based on a High Resolution Gridded Data Set

Directory of Open Access Journals (Sweden)

Chee Loong Wong

2016-11-01

Full Text Available Daily gridded rainfall data over Peninsular Malaysia are delineated using an objective clustering algorithm, with the objective of classifying rainfall grids into groups of homogeneous regions based on the similarity of the rainfall annual cycles. It has been demonstrated that Peninsular Malaysia can be statistically delineated into eight distinct rainfall regions. This delineation is closely associated with the topographic and geographic characteristics. The variation of rainfall over the Peninsula is generally characterized by bimodal variations with two peaks, i.e., a primary peak occurring during the autumn transitional period and a secondary peak during the spring transitional period. The east coast zones, however, showed a single peak during the northeast monsoon (NEM. The influence of NEM is stronger compared to the southwest monsoon (SWM. Significantly increasing rainfall trends at 95% confidence level are not observed in all regions during the NEM, with exception of northwest zone (R1 and coastal band of west coast interior region (R3. During SWM, most areas have become drier over the last three decades. The study identifies higher variation of mean monthly rainfall over the east coast regions, but spatially, the rainfall is uniformly distributed. For the southwestern coast and west coast regions, a larger range of coefficients of variation is mostly obtained during the NEM, and to a smaller extent during the SWM. The inland region received least rainfall in February, but showed the largest spatial variation. The relationship between rainfall and the El Niño Southern Oscillation (ENSO was examined based on the Multivariate ENSO Index (MEI. Although the concurrent relationships between rainfall in the different regions and ENSO are generally weak with negative correlations, the rainfall shows stronger positive correlation with preceding ENSO signals with a time lag of four to eight months.

Uganda rainfall variability and prediction

Science.gov (United States)

Jury, Mark R.

2018-05-01

This study analyzes large-scale controls on Uganda's rainfall. Unlike past work, here, a May-October season is used because of the year-round nature of agricultural production, vegetation sensitivity to rainfall, and disease transmission. The Uganda rainfall record exhibits steady oscillations of ˜3 and 6 years over 1950-2013. Correlation maps at two-season lead time resolve the subtropical ridge over global oceans as an important feature. Multi-variate environmental predictors include Dec-May south Indian Ocean sea surface temperature, east African upper zonal wind, and South Atlantic wind streamfunction, providing a 33% fit to May-Oct rainfall time series. Composite analysis indicates that cool-phase El Niño Southern Oscillation supports increased May-Oct Uganda rainfall via a zonal overturning lower westerly/upper easterly atmospheric circulation. Sea temperature anomalies are positive in the east Atlantic and negative in the west Indian Ocean in respect of wet seasons. The northern Hadley Cell plays a role in limiting the northward march of the equatorial trough from May to October. An analysis of early season floods found that moist inflow from the west Indian Ocean converges over Uganda, generating diurnal thunderstorm clusters that drift southwestward producing high runoff.

Characterization of yield reduction in Ethiopia using a GIS-based crop water balance model

Science.gov (United States)

Senay, G.B.; Verdin, J.

2003-01-01

In many parts of sub-Saharan Africa, subsistence agriculture is characterized by significant fluctuations in yield and production due to variations in moisture availability to staple crops. Widespread drought can lead to crop failures, with associated deterioration in food security. Ground data collection networks are sparse, so methods using geospatial rainfall estimates derived from satellite and gauge observations, where available, have been developed to calculate seasonal crop water balances. Using conventional crop production data for 4 years in Ethiopia (1996-1999), it was found that water-limited and water-unlimited growing regions can be distinguished. Furthermore, maize growing conditions are also indicative of conditions for sorghum. However, another major staple, teff, was found to behave sufficiently differently from maize to warrant studies of its own.

The Response of Durum Wheat to the Preceding Crop in a Mediterranean Environment

Directory of Open Access Journals (Sweden)

Laura Ercoli

2014-01-01

Full Text Available Crop sequence is an important management practice that may affect durum wheat (Triticum durum Desf. production. Field research was conducted in 2007-2008 and 2008-2009 seasons in a rain-fed cold Mediterranean environment to examine the impact of the preceding crops alfalfa (Medicago sativa L., maize (Zea mays L., sunflower (Helianthus annuus L., and bread wheat (Triticum aestivum L. on yield and N uptake of four durum wheat varieties. The response of grain yield of durum wheat to the preceding crop was high in 2007-2008 and was absent in the 2008-2009 season, because of the heavy rainfall that negatively impacted establishment, vegetative growth, and grain yield of durum wheat due to waterlogging. In the first season, durum wheat grain yield was highest following alfalfa, and was 33% lower following wheat. The yield increase of durum wheat following alfalfa was mainly due to an increased number of spikes per unit area and number of kernels per spike, while the yield decrease following wheat was mainly due to a reduction of spike number per unit area. Variety growth habit and performance did not affect the response to preceding crop and varieties ranked in the order Levante > Saragolla = Svevo > Normanno.

Rainfall Erosivity in Europe

DEFF Research Database (Denmark)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

2015-01-01

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the Rfactor in the USLE model and its revised version, RUSLE. At national...... and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based...

Multivariate Analysis of Erosivity Indices and Rainfall Physical Characteristics Associated with Rainfall Patterns in Rio de Janeiro

Directory of Open Access Journals (Sweden)

Roriz Luciano Machado

2017-12-01

Full Text Available ABSTRACT The identification of areas with greater erosive potential is important for planning soil and water conservation. The objective of this study was to evaluate the physical characteristics of rainfall events in the state of Rio de Janeiro, Brazil, and their interactions with rainfall patterns through multivariate statistical analysis. Rainfall depth, kinetic energy, 30-min intensity (I30, duration of rainfall events, and the erosivity indices KE >10, KE >25, and EI30 in 36 locations (stations were subjected to principal component analysis (PCA and canonical discriminant analysis (CDA. Based on evaluation of the respective historical series of hyetographs, it was found that the advanced pattern occurs with highest frequency (51.8 %, followed by the delayed pattern (26.1 %, and by the intermediate pattern (22.1 %. All the evaluated rainfall characteristics have high response capacity in describing localities and rainfall patterns through PCA and CDA. In CDA, the Tukey test (p<0.05 applied to the scores of the first canonical discriminant function (CDF1 allowed differentiation of the stations with respect to the rainfall and erosivity characteristics for the advanced and delayed patterns. In the delayed pattern, the localities of Angra dos Reis, Campos, Eletrobrás, Manuel Duarte, Santa Isabel do Rio Preto, Tanguá, Teresópolis, Vila Mambucaba, and Xerém had the highest CDF1 scores, indicating that they have rainfalls with higher depth, I30, and duration because the standardized canonical coefficient (SCC and the correlation coefficient (“r” of these characteristics were positive. The rainfall events in the state of Rio de Janeiro differ from one locality to another in relation to the advanced and delayed rainfall patterns, mainly due to the physical characteristics of rainfall depth, I30, and duration, indicating a higher risk of soil loss and runoff in the localities where rainfall events with the delayed pattern prevail.

Censored rainfall modelling for estimation of fine-scale extremes

Science.gov (United States)

Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

2018-01-01

Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

A Method of High Throughput Monitoring Crop Physiology Using Chlorophyll Fluorescence and Multispectral Imaging.

Science.gov (United States)

Wang, Heng; Qian, Xiangjie; Zhang, Lan; Xu, Sailong; Li, Haifeng; Xia, Xiaojian; Dai, Liankui; Xu, Liang; Yu, Jingquan; Liu, Xu

2018-01-01

We present a high throughput crop physiology condition monitoring system and corresponding monitoring method. The monitoring system can perform large-area chlorophyll fluorescence imaging and multispectral imaging. The monitoring method can determine the crop current condition continuously and non-destructively. We choose chlorophyll fluorescence parameters and relative reflectance of multispectral as the indicators of crop physiological status. Using tomato as experiment subject, the typical crop physiological stress, such as drought, nutrition deficiency and plant disease can be distinguished by the monitoring method. Furthermore, we have studied the correlation between the physiological indicators and the degree of stress. Besides realizing the continuous monitoring of crop physiology, the monitoring system and method provide the possibility of machine automatic diagnosis of the plant physiology. Highlights: A newly designed high throughput crop physiology monitoring system and the corresponding monitoring method are described in this study. Different types of stress can induce distinct fluorescence and spectral characteristics, which can be used to evaluate the physiological status of plants.

Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

Science.gov (United States)

Langousis, Andreas; Mamalakis, Antonis; Deidda, Roberto; Marrocu, Marino

2015-04-01

regional level. This is done for an intermediate-sized catchment in Italy, i.e. the Flumendosa catchment, using climate model rainfall and atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com). In doing so, we split the historical rainfall record of mean areal precipitation (MAP) in 15-year calibration and 45-year validation periods, and compare the historical rainfall statistics to those obtained from: a) Q-Q corrected climate model rainfall products, and b) synthetic rainfall series generated by the suggested downscaling scheme. To our knowledge, this is the first time that climate model rainfall and statistically downscaled precipitation are compared to catchment-averaged MAP at a daily resolution. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the climate model used and the length of the calibration period. This is particularly the case for the yearly rainfall maxima, where direct statistical correction of climate model rainfall outputs shows increased sensitivity to the length of the calibration period and the climate model used. The robustness of the suggested downscaling scheme in modeling rainfall extremes at a daily resolution, is a notable feature that can effectively be used to assess hydrologic risk at a regional level under changing climatic conditions. Acknowledgments The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. CRS4 highly acknowledges the contribution of the Sardinian regional authorities.

Soil water improvements with the long-term use of a winter rye cover crop

Science.gov (United States)

The Midwestern United States, a region that produces one-third of maize and one-quarter of soybeans globally, is projected to experience increasing rainfall variability with future climate change. One approach to mitigate climate impacts is to utilize crop and soil management practices that enhance ...

Detecting Climate Variability in Tropical Rainfall

Science.gov (United States)

Berg, W.

2004-05-01

A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to

Development of High Resolution Data for Irrigated Area and Cropping Patterns in India

Science.gov (United States)

K a, A.; Mishra, V.

2015-12-01

Information of crop phenology and its individual effect on irrigation is essential to improve the simulation of land surface states and fluxes. We use moderate resolution imaging spectroradiometer (MODIS) - Normalized difference vegetation index (NDVI) at 250 m resolution for monitoring temporal changes in irrigation and cropping patterns in India. We used the obtained dataset of cropping pattern for quantifying the effect of irrigation on land surface states and fluxes by using an uncoupled land surface model. The cropping patterns are derived by using the planting, heading, harvesting, and growing dates for each agro-ecological zone separately. Moreover, we developed a high resolution irrigated area maps for the period of 1999-2014 for India. The high resolution irrigated area was compared with relatively coarse resolution (~ 10km) irrigated area from the Food and Agricultural Organization. To identify the seasonal effects we analyzed the spatial and temporal change of irrigation and cropping pattern for different temporal seasons. The new irrigation area information along with cropping pattern was used to study the water budget in India using the Noah Land surface Model (Noah LSM) for the period of 1999-2014.

Feasibility of High-Resolution Soil Erosion Measurements by Means of Rainfall Simulations and SfM Photogrammetry

Directory of Open Access Journals (Sweden)

Phoebe Hänsel

2016-11-01

Full Text Available The silty soils of the intensively used agricultural landscape of the Saxon loess province, eastern Germany, are very prone to soil erosion, mainly caused by water erosion. Rainfall simulations, and also increasingly structure-from-motion (SfM photogrammetry, are used as methods in soil erosion research not only to assess soil erosion by water, but also to quantify soil loss. This study aims to validate SfM photogrammetry determined soil loss estimations with rainfall simulations measurements. Rainfall simulations were performed at three agricultural sites in central Saxony. Besides the measured data runoff and soil loss by sampling (in mm, terrestrial images were taken from the plots with digital cameras before and after the rainfall simulation. Subsequently, SfM photogrammetry was used to reconstruct soil surface changes due to soil erosion in terms of high resolution digital elevation models (DEMs for the pre- and post-event (resolution 1 × 1 mm. By multi-temporal change detection, the digital elevation model of difference (DoD and an averaged soil loss (in mm is received, which was compared to the soil loss by sampling. Soil loss by DoD was higher than soil loss by sampling. The method of SfM photogrammetry-determined soil loss estimations also include a comparison of three different ground control point (GCP approaches, revealing that the most complex one delivers the most reliable soil loss by DoD. Additionally, soil bulk density changes and splash erosion beyond the plot were measured during the rainfall simulation experiments in order to separate these processes and associated surface changes from the soil loss by DoD. Furthermore, splash was negligibly small, whereas higher soil densities after the rainfall simulations indicated soil compaction. By means of calculated soil surface changes due to soil compaction, the soil loss by DoD achieved approximately the same value as the soil loss by rainfall simulation.

A comprehensive continent-wide regionalisation investigation for daily design rainfall

OpenAIRE

F. Johnson; J. Green

2018-01-01

Study region: Australia. Study focus: Design rainfalls, in the form of Intensity Duration Frequency curves, are the standard input for most flood studies. Methods to combine rainfall data across space are required to provide optimal estimates of design rainfalls and constrain their uncertainty. This paper robustly investigates the use of a variety of regionalization methods to provide Australia wide design rainfall estimates using 8619 high quality rainfall stations. The influence of an indiv...

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010

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Assumpta Mukabutera

2016-08-01

Full Text Available Abstract Background Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. Methods We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Results Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff but had no impact among children in household with improved toilets. Conclusion Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

Spatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates

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Tingting Shi

2015-09-01

Full Text Available The accurate assessment of spatiotemporal rainfall variability is a crucial and challenging task in many hydrological applications, mainly due to the lack of a sufficient number of rain gauges. The purpose of the present study is to investigate the spatiotemporal variations of annual and monthly rainfall over Fujian province in China by combining the Bayesian maximum entropy (BME method and satellite rainfall estimates. Specifically, based on annual and monthly rainfall data at 20 meteorological stations from 2000 to 2012, (1 the BME method with Tropical Rainfall Measuring Mission (TRMM estimates considered as soft data, (2 ordinary kriging (OK and (3 cokriging (CK were employed to model the spatiotemporal variations of rainfall in Fujian province. Subsequently, the performance of these methods was evaluated using cross-validation statistics. The results demonstrated that BME with TRMM as soft data (BME-TRMM performed better than the other two methods, generating rainfall maps that represented the local rainfall disparities in a more realistic manner. Of the three interpolation (mapping methods, the mean absolute error (MAE and root mean square error (RMSE values of the BME-TRMM method were the smallest. In conclusion, the BME-TRMM method improved spatiotemporal rainfall modeling and mapping by integrating hard data and soft information. Lastly, the study identified new opportunities concerning the application of TRMM rainfall estimates.

Geo-environmental model for the prediction of potential transmission risk of Dirofilaria in an area with dry climate and extensive irrigated crops. The case of Spain.

Science.gov (United States)

Simón, Luis; Afonin, Alexandr; López-Díez, Lucía Isabel; González-Miguel, Javier; Morchón, Rodrigo; Carretón, Elena; Montoya-Alonso, José Alberto; Kartashev, Vladimir; Simón, Fernando

2014-03-01

Zoonotic filarioses caused by Dirofilaria immitis and Dirofilaria repens are transmitted by culicid mosquitoes. Therefore Dirofilaria transmission depends on climatic factors like temperature and humidity. In spite of the dry climate of most of the Spanish territory, there are extensive irrigated crops areas providing moist habitats favourable for mosquito breeding. A GIS model to predict the risk of Dirofilaria transmission in Spain, based on temperatures and rainfall data as well as in the distribution of irrigated crops areas, is constructed. The model predicts that potential risk of Dirofilaria transmission exists in all the Spanish territory. Highest transmission risk exists in several areas of Andalucía, Extremadura, Castilla-La Mancha, Murcia, Valencia, Aragón and Cataluña, where moderate/high temperatures coincide with extensive irrigated crops. High risk in Balearic Islands and in some points of Canary Islands, is also predicted. The lowest risk is predicted in Northern cold and scarcely or non-irrigated dry Southeastern areas. The existence of irrigations locally increases transmission risk in low rainfall areas of the Spanish territory. The model can contribute to implement rational preventive therapy guidelines in accordance with the transmission characteristics of each local area. Moreover, the use of humidity-related factors could be of interest in future predictions to be performed in countries with similar environmental characteristics. Copyright © 2014 Elsevier B.V. All rights reserved.

Effect of crop rotation on soil nutrient balance and weediness in soddy podzolic organic farming fields

Science.gov (United States)

Zarina, Livija; Zarina, Liga

2017-04-01

The nutrient balance in different crop rotations under organic cropping system has been investigated in Latvia at the Institute of Agricultural Resources and Economics since 2006. Latvia is located in a humid and moderate climatic region where the rainfall exceeds evaporation (soil moisture coefficient > 1) and the soil moisture regime is characteristic with percolation. The average annual precipitation is 670-850 mm. The average temperature varies from -6.7° C in January to 16.5 °C in July. The growing season is 175 - 185 days. The most widespread are podzolic soils and mainly they are present in agricultural fields in all regions of Latvia. In a wider sense the goal of the soil management in organic farming is a creation of the biologically active flora and fauna in the soil by maintaining a high level of soil organic matter which is good for crops nutrient balance. Crop rotation is a central component of organic farming systems and has many benefits, including growth of soil microbial activity, which may increase nutrient availability. The aim of the present study was to calculate nutrient balance for each crop in the rotations and average in each rotation. Taking into account that crop rotations can limit build-up of weeds, additionally within the ERA-net CORE Organic Plus transnational programs supported project PRODIVA the information required for a better utilization of crop diversification for weed management in North European organic arable cropping systems was summarized. It was found that the nutrient balance was influenced by nutrients uptake by biomass of growing crops in crop rotation. The number of weeds in the organic farming fields with crop rotation is dependent on the cultivated crops and the succession of crops in the crop rotation.

Organic carbon fluxes in stemflow, throughfall and rainfall in an olive orchard

Science.gov (United States)

Lombardo, L.; Vanwalleghem, T.; Gomez, J. A.

2012-04-01

The importance of rainfall distribution under the vegetation canopy for nutrient cycling of forest ecosystems has been widely studied (e.g. Kolkai et al., 1999, Bath et al., 2011). It has been demonstrated how throughfall and stemflow reach the soil as chemically-enriched water, by incorporating soluble organic and inorganic particles deriving from plant exudates and from atmospheric depositions (dryfall and wetfall) present on the surfaces of the plant (leaves, bark, fruits). Dissolved (DOC) and particulate (POC) organic carbon inputs from stem- and canopy-derived hydrologic fluxes are small but important components of the natural carbon cycle. DOC has also the capability to form complexes that control the transport and solubility of heavy metals in surface and ground waters, being composed for the most part (75-90%) of fulvic, humic or tanninic compounds, and for the resting part of molecules like carbohydrates, hydrocarbons, waxes, fatty acids, amino and hydroxy acids. However, very little data is available for agricultural tree crops, especially olive trees. In this sense, the objective of this work is to investigate the concentration and fluxes of organic carbon in rainfall, throughfall, and stemflow in a mature olive orchard located in Cordoba, in Southern Spain and to relate them to rainfall characteristics and tree physiology. The measurements started in October 2011. Four high density polyethylene bottles with 18-cm-diameter polyethylene funnels for throughfall collection were placed beneath the canopy of each of the three selected olive trees; four more collectors were placed in open spaces in the same orchard for rainfall sampling. Stemflow was collected through PVC spiral tubes wrapped around the trunks and leading into collection bins. The throughflow sampling points were chosen randomly. Total and dissolved organic carbon concentrations in unfiltered (TOC) and filtered (0.45 µm membrane filter, DOC) collected waters were measured using a TOC analyzer

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

Science.gov (United States)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model

Contrasting rainfall declines in northern and southern Tanzania: Potential differential impacts of west Pacific warming and east Pacific cooling

Science.gov (United States)

Harrison, L.; Funk, C. C.; Verdin, J. P.; Pedreros, D. H.; Shukla, S.; Husak, G. J.

2015-12-01

Here, we present analysis of a new 1900-2014 rainfall record for the Greater Horn of Africa with high station density (CenTrends), and evaluate potential climate change "hot spots" in Tanzania. We identify recent (1981-2014) downward trends in Tanzanian rainfall, use CenTrends to place these in a longer historical context, and relate rainfall in these regions to decadal changes in global sea surface temperatures (SSTs). To identify areas of concern, we consider the potential food security impacts of the recent rainfall declines and also rapid population growth. Looking forward, we consider what the links to SSTs might mean for rainfall in the next several decades based on SST projections. In addition to CenTrends, we use a variety of geographic data sets, including 1981-2014 rainfall from the Climate Hazards group InfraRed Precipitation with Stations (CHIRPSv2.0), simulated crop stress from the USGS Geospatial Water Requirement Satisfaction Index (GeoWRSI) model, NOAA Extended Reconstructed SSTs (ERSST v4), SST projections from the Coupled Model Intercomparison Project (CMIP5), and land cover and population maps from SERVIR, WorldPOP, and CIESIN's Gridded Population of the World. The long-term CenTrends record allows us to suggest an interesting dichotomy in decadal rainfall forcing. During the March to June season, SSTs in the west Pacific appear to be driving post-1980 rainfall reductions in northern Tanzania. In the 2000s, northern Tanzania's densely populated Pangani River, Internal Drainage, and Lake Victoria basins experienced the driest period in more than a century. During summer, negative trends in southern Tanzania appear linked to a negative SST trend in the Nino3.4 region. Since the SST trend in the west (east) Pacific appears strongly influenced by global warming (natural decadal variability), we suggest that water resources in northern Tanzania may face increasing challenges, but that this will be less the case in southern Tanzania.

A blended approach to analyze staple and high-value crops using remote sensing with radiative transfer and crop models.

Science.gov (United States)

Davitt, A. W. D.; Winter, J.; McDonald, K. C.; Escobar, V. M.; Steiner, N.

2017-12-01

The monitoring of staple and high-value crops is important for maintaining food security. The recent launch of numerous remote sensing satellites has created the ability to monitor vast amounts of crop lands, continuously and in a timely manner. This monitoring provides users with a wealth of information on various crop types over different regions of the world. However, a challenge still remains on how to best quantify and interpret the crop and surface characteristics that are measured by visible, near-infrared, and active and passive microwave radar. Currently, two NASA funded projects are examining the ability to monitor different types of crops in California with different remote sensing platforms. The goal of both projects is to develop a cost-effective monitoring tool for use by vineyard and crop managers. The first project is designed to examine the capability to monitor vineyard water management and soil moisture in Sonoma County using Soil Moisture Active Passive (SMAP), Sentinel-1A and -2, and Landsat-8. The combined mission products create thorough and robust measurements of surface and vineyard characteristics that can potentially improve the ability to monitor vineyard health. Incorporating the Michigan Microwave Canopy Scattering (MIMICS), a radiative transfer model, enables us to better understand surface and vineyard features that influence radar measurements from Sentinel-1A. The second project is a blended approach to analyze corn, rice, and wheat growth using Sentinel-1A products with Decision Support System for Agrotechnology Transfer (DSSAT) and MIMICS models. This project aims to characterize the crop structures that influence Sentinel-1A radar measurements. Preliminary results have revealed the corn, rice, and wheat structures that influence radar measurements during a growing season. The potential of this monitoring tool can be used for maintaining food security. This includes supporting sustainable irrigation practices, identifying crop

Sensitivity of point scale surface runoff predictions to rainfall resolution

Directory of Open Access Journals (Sweden)

A. J. Hearman

2007-01-01

Full Text Available This paper investigates the effects of using non-linear, high resolution rainfall, compared to time averaged rainfall on the triggering of hydrologic thresholds and therefore model predictions of infiltration excess and saturation excess runoff at the point scale. The bounded random cascade model, parameterized to three locations in Western Australia, was used to scale rainfall intensities at various time resolutions ranging from 1.875 min to 2 h. A one dimensional, conceptual rainfall partitioning model was used that instantaneously partitioned water into infiltration excess, infiltration, storage, deep drainage, saturation excess and surface runoff, where the fluxes into and out of the soil store were controlled by thresholds. The results of the numerical modelling were scaled by relating soil infiltration properties to soil draining properties, and in turn, relating these to average storm intensities. For all soil types, we related maximum infiltration capacities to average storm intensities (k* and were able to show where model predictions of infiltration excess were most sensitive to rainfall resolution (ln k*=0.4 and where using time averaged rainfall data can lead to an under prediction of infiltration excess and an over prediction of the amount of water entering the soil (ln k*>2 for all three rainfall locations tested. For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating drainage coefficients to average storm intensities (g* and parameter ranges where predicted runoff was dominated by infiltration excess or saturation excess depending on the resolution of rainfall data were determined (ln g*<2. Infiltration excess predicted from high resolution rainfall was short and intense, whereas saturation excess produced from low resolution rainfall was more constant and less intense. This has important implications for the accuracy of current hydrological models that use time

The relationship between extreme weather events and crop losses in central Taiwan

Science.gov (United States)

Lai, Li-Wei

2017-09-01

The frequency of extreme weather events, which cause severe crop losses, is increasing. This study investigates the relationship between crop losses and extreme weather events in central Taiwan from 2003 to 2015 and determines the main factors influencing crop losses. Data regarding the crop loss area and meteorological information were obtained from government agencies. The crops were categorised into the following five groups: `grains', `vegetables', `fruits', `flowers' and `other crops'. The extreme weather events and their synoptic weather patterns were categorised into six and five groups, respectively. The data were analysed using the z score, correlation coefficient and stepwise regression model. The results show that typhoons had the highest frequency of all extreme weather events (58.3%). The largest crop loss area (4.09%) was caused by two typhoons and foehn wind in succession. Extreme wind speed coupled with heavy rainfall is an important factor affecting the losses in the grain and vegetable groups. Extreme wind speed is a common variable that affects the loss of `grains', `vegetables', `fruits' and `flowers'. Consecutive extreme weather events caused greater crop losses than individual events. Crops with long production times suffered greater losses than those with short production times. This suggests that crops with physical structures that can be easily damaged and long production times would benefit from protected cultivation to maintain food security.

Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

Science.gov (United States)

Liong, Shie-Yui; He, Shan

2010-05-01

Rainfall forecasting and nowcasting are of great importance, for instance, in real-time flood early warning systems. Long term rainfall forecasting demands global climate, land, and sea data, thus, large computing power and storage capacity are required. Rainfall nowcasting's computing requirement, on the other hand, is much less. Rainfall nowcasting may use data captured by radar and/or weather stations. This paper presents the application of Artificial Neural Network (ANN) on rainfall nowcasting using data observed at weather and/or rainfall stations. The study focuses on the North-East monsoon period (December, January and February) in Singapore. Rainfall and weather data from ten stations, between 2000 and 2006, were selected and divided into three groups for training, over-fitting test and validation of the ANN. Several neural network architectures were tried in the study. Two architectures, Backpropagation ANN and Group Method of Data Handling ANN, yielded better rainfall nowcasting, up to two hours, than the other architectures. The obtained rainfall nowcasts were then used by a catchment model to forecast catchment runoff. The results of runoff forecast are encouraging and promising.With ANN's high computational speed, the proposed approach may be deliverable for creating the real-time flood early warning system.

Climate change and farmers’ cropping patterns in Cemoro watershed area, Central Java, Indonesia

Science.gov (United States)

Sugihardjo; Sutrisno, J.; Setyono, P.; Suntoro

2018-03-01

Cropping pattern applied by farmers is usually based on the availability of water. Farmers cultivate rice when water is available. If it is unavailable, farmers will choose to plant crops that need less water. Climate change greatly affects to farmers in determining the cropping pattern as it alters the rainfall pattern and distribution in the region. This condition requires farmers to adjust the cropping pattern so that they can do the farming successfully. This study aims to examine the application of cropping patterns applied by the farmers in the Cemoro Watershed, Central Java, Indonesia. Descriptive analysis approach is employed in this research. The results showed that farmers’ cropping pattern is not based on the availability of water. However, it adopts a habit that has been practiced since long time ago or just adopt others farmer's habit. The cropping pattern applied by irrigated paddy farmers in Cemoro watershed area consists of two types: rice-rice-rice and rice-rice-secondary crops. Among those two types, most farmers apply the rice-rice-rice pattern. Meanwhile, there are three cropping patterns applied in the rain-land, namely rice-rice-rice, rice-rice-secondary crop, and rice-rice-fallow. The majority of farmers apply the second pattern (rice-rice-secondary crops). It was also found that farmers’ cropping pattern was not in accordance with the recommendation of the local government.

Rainfall simulation in education

Science.gov (United States)

Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

2016-04-01

Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain

Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops.

Science.gov (United States)

Wasson, A P; Richards, R A; Chatrath, R; Misra, S C; Prasad, S V Sai; Rebetzke, G J; Kirkegaard, J A; Christopher, J; Watt, M

2012-05-01

Wheat yields globally will depend increasingly on good management to conserve rainfall and new varieties that use water efficiently for grain production. Here we propose an approach for developing new varieties to make better use of deep stored water. We focus on water-limited wheat production in the summer-dominant rainfall regions of India and Australia, but the approach is generally applicable to other environments and root-based constraints. Use of stored deep water is valuable because it is more predictable than variable in-season rainfall and can be measured prior to sowing. Further, this moisture is converted into grain with twice the efficiently of in-season rainfall since it is taken up later in crop growth during the grain-filling period when the roots reach deeper layers. We propose that wheat varieties with a deeper root system, a redistribution of branch root density from the surface to depth, and with greater radial hydraulic conductivity at depth would have higher yields in rainfed systems where crops rely on deep water for grain fill. Developing selection systems for mature root system traits is challenging as there are limited high-throughput phenotyping methods for roots in the field, and there is a risk that traits selected in the lab on young plants will not translate into mature root system traits in the field. We give an example of a breeding programme that combines laboratory and field phenotyping with proof of concept evaluation of the trait at the beginning of the selection programme. This would greatly enhance confidence in a high-throughput laboratory or field screen, and avoid investment in screens without yield value. This approach requires careful selection of field sites and years that allow expression of deep roots and increased yield. It also requires careful selection and crossing of germplasm to allow comparison of root expression among genotypes that are similar for other traits, especially flowering time and disease and toxicity

Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa.

Science.gov (United States)

Ayanlade, Ayansina; Radeny, Maren; Morton, John F; Muchaba, Tabitha

2018-07-15

This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days 0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Rainfall: State of the Science

Science.gov (United States)

Testik, Firat Y.; Gebremichael, Mekonnen

Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

Science.gov (United States)

Mayowa, Olaniya Olusegun; Pour, Sahar Hadi; Shahid, Shamsuddin; Mohsenipour, Morteza; Harun, Sobri Bin; Heryansyah, Arien; Ismail, Tarmizi

2015-12-01

The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

Effect of rooting depth, plant density and planting date on maize (Zea Mays L.) yield and water use efficiency in semi-arid Zimbabwe: Modelling with AquaCrop

NARCIS (Netherlands)

Nyakudya, I.W.; Stroosnijder, L.

2014-01-01

Under low and poorly distributed rainfall higher food production can be achieved by increasing crop water use efficiency (WUE) through optimum soil fertility management and selection of deep-rooting cultivars, appropriate plant density and planting dates. We explored AquaCrop's applicability in

Evaluation of different gridded rainfall datasets for rainfed wheat yield prediction in an arid environment

Science.gov (United States)

Lashkari, A.; Salehnia, N.; Asadi, S.; Paymard, P.; Zare, H.; Bannayan, M.

2018-05-01

The accuracy of daily output of satellite and reanalysis data is quite crucial for crop yield prediction. This study has evaluated the performance of APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation), PERSIANN (Rainfall Estimation from Remotely Sensed Information using Artificial Neural Networks), TRMM (Tropical Rainfall Measuring Mission), and AgMERRA (The Modern-Era Retrospective Analysis for Research and Applications) precipitation products to apply as input data for CSM-CERES-Wheat crop growth simulation model to predict rainfed wheat yield. Daily precipitation output from various sources for 7 years (2000-2007) was obtained and compared with corresponding ground-observed precipitation data for 16 ground stations across the northeast of Iran. Comparisons of ground-observed daily precipitation with corresponding data recorded by different sources of datasets showed a root mean square error (RMSE) of less than 3.5 for all data. AgMERRA and APHRODITE showed the highest correlation (0.68 and 0.87) and index of agreement (d) values (0.79 and 0.89) with ground-observed data. When daily precipitation data were aggregated over periods of 10 days, the RMSE values, r, and d values increased (30, 0.8, and 0.7) for AgMERRA, APHRODITE, PERSIANN, and TRMM precipitation data sources. The simulations of rainfed wheat leaf area index (LAI) and dry matter using various precipitation data, coupled with solar radiation and temperature data from observed ones, illustrated typical LAI and dry matter shape across all stations. The average values of LAImax were 0.78, 0.77, 0.74, 0.70, and 0.69 using PERSIANN, AgMERRA, ground-observed precipitation data, APHRODITE, and TRMM. Rainfed wheat grain yield simulated by using AgMERRA and APHRODITE daily precipitation data was highly correlated (r 2 ≥ 70) with those simulated using observed precipitation data. Therefore, gridded data have high potential to be used to supply lack of data and

Climate change impact and potential adaptation strategies under alternate realizations of climate scenarios for three major crops in Europe

International Nuclear Information System (INIS)

Donatelli, Marcello; Srivastava, Amit Kumar; Duveiller, Gregory; Niemeyer, Stefan; Fumagalli, Davide

2015-01-01

This study presents an estimate of the effects of climate variables and CO 2 on three major crops, namely wheat, rapeseed and sunflower, in EU27 Member States. We also investigated some technical adaptation options which could offset climate change impacts. The time-slices 2000, 2020 and 2030 were chosen to represent the baseline and future climate, respectively. Furthermore, two realizations within the A1B emission scenario proposed by the Special Report on Emissions Scenarios (SRES), from the ECHAM5 and HadCM3 GCM, were selected. A time series of 30 years for each GCM and time slice were used as input weather data for simulation. The time series were generated with a stochastic weather generator trained over GCM-RCM time series (downscaled simulations from the ENSEMBLES project which were statistically bias-corrected prior to the use of the weather generator). GCM-RCM simulations differed primarily for rainfall patterns across Europe, whereas the temperature increase was similar in the time horizons considered. Simulations based on the model CropSyst v. 3 were used to estimate crop responses; CropSyst was re-implemented in the modelling framework BioMA. The results presented in this paper refer to abstraction of crop growth with respect to its production system, and consider growth as limited by weather and soil water. How crop growth responds to CO 2 concentrations; pests, diseases, and nutrients limitations were not accounted for in simulations. The results show primarily that different realization of the emission scenario lead to noticeably different crop performance projections in the same time slice. Simple adaptation techniques such as changing sowing dates and the use of different varieties, the latter in terms of duration of the crop cycle, may be effective in alleviating the adverse effects of climate change in most areas, although response to best adaptation (within the techniques tested) differed across crops. Although a negative impact of climate

Climate change impact and potential adaptation strategies under alternate realizations of climate scenarios for three major crops in Europe

Science.gov (United States)

Donatelli, Marcello; Srivastava, Amit Kumar; Duveiller, Gregory; Niemeyer, Stefan; Fumagalli, Davide

2015-07-01

This study presents an estimate of the effects of climate variables and CO2 on three major crops, namely wheat, rapeseed and sunflower, in EU27 Member States. We also investigated some technical adaptation options which could offset climate change impacts. The time-slices 2000, 2020 and 2030 were chosen to represent the baseline and future climate, respectively. Furthermore, two realizations within the A1B emission scenario proposed by the Special Report on Emissions Scenarios (SRES), from the ECHAM5 and HadCM3 GCM, were selected. A time series of 30 years for each GCM and time slice were used as input weather data for simulation. The time series were generated with a stochastic weather generator trained over GCM-RCM time series (downscaled simulations from the ENSEMBLES project which were statistically bias-corrected prior to the use of the weather generator). GCM-RCM simulations differed primarily for rainfall patterns across Europe, whereas the temperature increase was similar in the time horizons considered. Simulations based on the model CropSyst v. 3 were used to estimate crop responses; CropSyst was re-implemented in the modelling framework BioMA. The results presented in this paper refer to abstraction of crop growth with respect to its production system, and consider growth as limited by weather and soil water. How crop growth responds to CO2 concentrations; pests, diseases, and nutrients limitations were not accounted for in simulations. The results show primarily that different realization of the emission scenario lead to noticeably different crop performance projections in the same time slice. Simple adaptation techniques such as changing sowing dates and the use of different varieties, the latter in terms of duration of the crop cycle, may be effective in alleviating the adverse effects of climate change in most areas, although response to best adaptation (within the techniques tested) differed across crops. Although a negative impact of climate

High-resolution, regional-scale crop yield simulations for the Southwestern United States

Science.gov (United States)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and

Characterizing rainfall parameters which influence erosivity in southeastern Nigeria

International Nuclear Information System (INIS)

Obi, M.E.; Salako, F.K.

1993-12-01

An investigation was carried out to characterize some selected parameters which influence rainfall erosivity in southeastern Nigeria. Rainfall amount, distribution, duration, intensity, storm types, energy loads and frequency of rain events in the region were studied using data from stations located in three major agroecological zones. Raindrop size and detaching capacity were evaluated in one of the stations for two months. The mean annual rainfall erosivity values for southeastern Nigeria point to the fact that rainfall tend to be highly erosive. 25 refs, 6 figs, 8 tabs

Biogas production from high-yielding energy crops in boreal conditions

Energy Technology Data Exchange (ETDEWEB)

Seppala, M.

2013-11-01

In this thesis, the methane production potential of traditional and novel energy crops was evaluated in boreal conditions. The highest methane yield per hectare was achieved with maize (4 000-9 200 m{sup 3}CH{sub 4} ha{sup -1} a{sup -1}) and the second highest with brown knapweed (2 700-6 100 m{sup 3}CH{sub 4} ha{sup -1} a{sup -1}). Recently, the most feasible energy crop, grass, produced 1 200-3 600 m{sup 3}CH{sub 4} ha{sup -1} a{sup -1}. The specific methane yields of traditional and novel energy crops varied from 170-500 l kg{sup -1} volatile solid (VS). The highest specific methane yields were obtained with maize, while the novel energy crops were at a lower range. The specific methane yields decreased in the later harvest time with maize and brown knapweed, and the specific methane yield of the grasses decreased from the 1st to 2nd harvests. Maize and brown knapweed produced the highest total solid (TS) yields per hectare 13-23 tTS ha{sup -1}, which were high when compared with the TS yields of grasses (6-13 tTS ha{sup -1}). The feasibility of maize and brown knapweed in co-digestion with liquid cow manure, in continuously stirred tank reactors (CSTR), was evaluated. According to the CSTR runs, maize and brown knapweed are suitable feeds and have stable processes, producing the highest methane yields (organic loading rate 2 kgVS m{sup -3}d{sup -1}), with maize at 259 l kgVS{sup -1} and brown knapweed at 254 l kgVS{sup -1}. The energy balance (input/output) of the cultivation of the grasses, maize and brown knapweed was calculated in boreal conditions, and it was better when the digestate was used as a fertilizer (1.8-4.8 %) than using chemical fertilizers (3.7-16.2 %), whose production is the most energy demanding process in cultivation. In conclusion, the methane production of maize, grasses and novel energy crops can produce high methane yields and are suitable feeds for anaerobic digestion. The cultivation managements of maize and novel energy crops for

Effect of monthly areal rainfall uncertainty on streamflow simulation

Science.gov (United States)

Ndiritu, J. G.; Mkhize, N.

2017-08-01

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

Science.gov (United States)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

[Effects of rainfall intensity on rainfall infiltration and redistribution in soil on Loess slope land].

Science.gov (United States)

Li, Yi; Shao, Ming'an

2006-12-01

With simulation test, this paper studied the patterns of rainfall infiltration and redistribution in soil on typical Loess slope land, and analyzed the quantitative relations between the infiltration and redistribution and the movement of soil water and mass, with rainfall intensity as the main affecting factor. The results showed that rainfall intensity had significant effects on the rainfall infiltration and water redistribution in soil, and the microcosmic movement of soil water. The larger the rainfall intensity, the deeper the wetting front of rainfall infiltration and redistribution was, and the wetting front of soil water redistribution had a slower increase velocity than that of rainfall infiltration. The power function of the wetting front with time, and also with rainfall intensity, was fitted well. There was also a quantitative relation between the wetting front of rainfall redistribution and the duration of rainfall. The larger the rainfall intensity, the higher the initial and steady infiltration rates were, and the cumulative infiltration increased faster with time. Moreover, the larger the rainfall intensity, the smaller the wetting front difference was at the top and the end of the slope. With the larger rainfall intensity, both the difference of soil water content and its descending trend between soil layers became more obvious during the redistribution process on slope land.

Spatial and temporal variability of rainfall in the Tocantins-Araguaia hydrographic region

Directory of Open Access Journals (Sweden)

Glauber Epifanio Loureiro

2015-01-01

Full Text Available Current paper examines the space-time dynamics of yearly rainfall of the Tocantins-Araguaia Hydrographic Region (TAHR, foregrounded on rainfall volume from isohyet maps and interpolated by Kriging geo-statistical method.  Rainfall space dynamics was undertaken by the analysis of descriptive statistics, Index of Meteorological Irregularity (IMI and Variation Coefficient. Temporal dynamics was analyzed through the distribution of total annual volume precipitation for each TAHR sub-basin by the Standardized Anomaly Index, trend and magnitude test provided by Mann-Kendall and Sen Tests. Results correlated with meteorological anomalies of the Atlantic (Dipole and Pacific (ENOS Oceans show a highly heterogeneous rainfall behavior with temporal variability. Or rather, a decrease of rainfall extensiveness during years of intense meteorological anomaly with a rainfall increase south of the High Tocantins and Araguaia sub-basins and a decrease of rainfall in the Lower Tocantins sub-basin, with El Niño features. Although the Mann-Kendall test does not show statistically a significant trend for rainfall in the TAHR region, Sen’s estimator reveals a decrease in rainfall in the High Tocantins (-1.24 km³ year-1 and Araguaia (-1.13 km³ year-1 sub-basins and a rainfall increase in the Lower Tocantins sub-basin (0.53 km³ year-1 and in the TAHR region (-1.5 km³ year-1.

Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan

Science.gov (United States)

Huang, Ting-Yin; Yang, Ssu-Yao; Jan, Chyan-Deng

2017-04-01

Soil erosion is a natural process on hillslopes that threats people's life and properties, having a considerable environmental and economic implications for soil degradation, agricultural activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall intensity (I30), is widely used as an indicator to measure the potential risks of soil loss caused by rainfall at a regional scale. This R factor can represent the detachment and entrainment involved in climate conditions on hillslopes, but lack of 30-min rainfall intensity data usually lead to apply this factor more difficult in many regions. In recent years, fixed-interval, hourly rainfall data is readily available and widely used due to the development of automatic weather stations. Here we assess the estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data, and hourly rainfall data obtained from Taipei weather station during 2004 to 2010. Results show that there is a strong correlation among R-factors estimated from different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g., 1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity (ratio of values estimated from the resolution lower than 30-min rainfall data to those estimated from 60-min and hourly rainfall data, respectively) range from 1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as the time resolution increasing from 30-min to 1-min. This paper provides useful information on estimating R-factor when hourly rainfall data is only available.

Darfur: rainfall and conflict

International Nuclear Information System (INIS)

Kevane, Michael; Gray, Leslie

2008-01-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972-2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa

Darfur: rainfall and conflict

Science.gov (United States)

Kevane, Michael; Gray, Leslie

2008-07-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972 2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa.

Hydrologic and Erosional Response to Natural Rainfall and Effects of Conservation and Rehabilitation Measures in a Degraded Dry Sub-Humid Watershed of the Ethiopian Highlands

Science.gov (United States)

McHugh, O. V.; Liu, B. M.; Steenhuis, T. S.

2005-12-01

A good understanding of runoff and erosion under actual field conditions is essential for effective planning of land conservation in the Ethiopian highlands. Hydrologic and sediment yield response to natural rainfall was measured during 3 rainy seasons (2003-2004) at plot and catchment scales with and without conservation practices. Results show that as expected surface runoff generation and erosion rates are significantly influenced by rainfall intensity, land use, scale of measurement, land slope, and the presence or not of conservation measures. Seasonal runoff coefficient and sediment yield were significantly better correlated to number of storms with high 30-minute maximum rainfall intensity (I30 > 20 mm h-1) than to total seasonal rainfall depth. Under conventional management systems cropland on slopes greater than 3 % generated significantly more (over twice) surface runoff and sediment yield compared with shrub and open forest grazing land on steep slopes (34 %). Plot measured surface runoff coefficients (for crop and grazing land uses which cover over 90 % of the catchment area) exceeded total catchment streamflow discharge demonstrating a scale effect. The observed scale effect, a stronger correlation of runoff with maximum rainfall intensity than rainfall depth and average rainfall intensity, and observed significant increases in runoff with steeper land slopes indicate that Hortonian overland flow is the primary runoff generation mechanism in the study zone. Concerning slope effects, cropland on mild slopes produced relatively low seasonal sediment yields (hillside conservation (areas with bench terracing, planted tree seedlings, and small area closure from livestock grazing) resulted in significantly lower catchment peak streamflow discharge and longer duration streamflow compared to a catchment in the same watershed without these measures. Cropland tied ridge and no till conservation practices reduced surface runoff and soil loss during seasons with

The all-year rainfall region of South Africa: Satellite rainfall-estimate perspective

CSIR Research Space (South Africa)

Engelbrecht, CJ

2012-09-01

Full Text Available Climate predictability and variability studies over South Africa typically focus on the summer rainfall region and to a lesser extent on the winter rainfall region. The all-year rainfall region of South Africa, a narrow strip located along the Cape...

Response of conservation measures from small cultivated watersheds, concerning runoff and erosion, under the impact of extreme rainfall events

Science.gov (United States)

Popa, N.

2008-11-01

The study has been made in a representative small watershed with gently to hilly slopes from Tutova Rolling Hills, Romania. The system of conservation measures is represented by stripcroping, bufferstrips, bench terraces, a grassed waterway and a drainage network. The monitoring of hydrological response of agricultural units has been made in two cross sections corresponding to each of the land use type by means of two concrete triangular weirs. The most important soil losses were caused by three extreme rainfall events from August 2004, May 2005 and September 2007. At the date of the first rainfall event, the soil was generally very well protected against erosion by the vegetative cover, excepting parcels that were just ploughed after the mash crop. In that case, it was estimated that the value of soil losses ranged between 20.0 and 24.5 t/ha while for the other crops like corn and soybean, soil losses they were 1.0-1.5 t/ha and 0.5-0.8 t/ha respectively. Damages caused by the rainfall from September 2007 were much more important because at that time about 30% from the entire surface was just prepared for rape seeding. Maximum value of erosion was 95 t/ha on a parcel with 16% slope and 50m length along the slope.

Response of conservation measures from small cultivated watersheds, concerning runoff and erosion, under the impact of extreme rainfall events

International Nuclear Information System (INIS)

Popa, N

2008-01-01

The study has been made in a representative small watershed with gently to hilly slopes from Tutova Rolling Hills, Romania. The system of conservation measures is represented by stripcroping, bufferstrips, bench terraces, a grassed waterway and a drainage network. The monitoring of hydrological response of agricultural units has been made in two cross sections corresponding to each of the land use type by means of two concrete triangular weirs. The most important soil losses were caused by three extreme rainfall events from August 2004, May 2005 and September 2007. At the date of the first rainfall event, the soil was generally very well protected against erosion by the vegetative cover, excepting parcels that were just ploughed after the mash crop. In that case, it was estimated that the value of soil losses ranged between 20.0 and 24.5 t/ha while for the other crops like corn and soybean, soil losses they were 1.0-1.5 t/ha and 0.5-0.8 t/ha respectively. Damages caused by the rainfall from September 2007 were much more important because at that time about 30% from the entire surface was just prepared for rape seeding. Maximum value of erosion was 95 t/ha on a parcel with 16% slope and 50m length along the slope.

A dense camera network for cropland (CropInsight) - developing high spatiotemporal resolution crop Leaf Area Index (LAI) maps through network images and novel satellite data

Science.gov (United States)

Kimm, H.; Guan, K.; Luo, Y.; Peng, J.; Mascaro, J.; Peng, B.

2017-12-01

Monitoring crop growth conditions is of primary interest to crop yield forecasting, food production assessment, and risk management of individual farmers and agribusiness. Despite its importance, there are limited access to field level crop growth/condition information in the public domain. This scarcity of ground truth data also hampers the use of satellite remote sensing for crop monitoring due to the lack of validation. Here, we introduce a new camera network (CropInsight) to monitor crop phenology, growth, and conditions that are designed for the US Corn Belt landscape. Specifically, this network currently includes 40 sites (20 corn and 20 soybean fields) across southern half of the Champaign County, IL ( 800 km2). Its wide distribution and automatic operation enable the network to capture spatiotemporal variations of crop growth condition continuously at the regional scale. At each site, low-maintenance, and high-resolution RGB digital cameras are set up having a downward view from 4.5 m height to take continuous images. In this study, we will use these images and novel satellite data to construct daily LAI map of the Champaign County at 30 m spatial resolution. First, we will estimate LAI from the camera images and evaluate it using the LAI data collected from LAI-2200 (LI-COR, Lincoln, NE). Second, we will develop relationships between the camera-based LAI estimation and vegetation indices derived from a newly developed MODIS-Landsat fusion product (daily, 30 m resolution, RGB + NIR + SWIR bands) and the Planet Lab's high-resolution satellite data (daily, 5 meter, RGB). Finally, we will scale up the above relationships to generate high spatiotemporal resolution crop LAI map for the whole Champaign County. The proposed work has potentials to expand to other agro-ecosystems and to the broader US Corn Belt.

Agricultural water use, crop water footprints and irrigation strategies in the seasonally dry Guanacaste region in Costa Rica

Science.gov (United States)

Morillas, Laura; Johnson, Mark S.; Hund, Silja V.; Steyn, Douw G.

2017-04-01

Agriculture is the main productive sector and a major water-consuming sector in the seasonally-dry Guanacaste region of north-western Costa Rica. Agriculture in the region is intensifying at the same time that seasonal water scarcity is increasing. The climate of this region is characterized by a prolonged dry season from December to March, followed by a bimodal wet season from April to November. The wet season has historically experienced periodic oscillations in rainfall timing and amounts resulting from variations of several large-scale climatic features (El Niño Southern Oscillation, the Pacific Decadal Oscillation, the Atlantic Multidecadal Oscillation and the North Atlantic Oscillation). However, global circulation models now project more recurrent variations in total annual rainfall, changes in rainfall temporal distribution, and increased temperatures in this region. This may result in a lengthening of the dry season and an increase in water scarcity and water-related conflicts as water resources are already limited and disputed in this area. In fact, this region has just undergone a four-year drought over the 2012-2015 period, which has intensified water related conflicts and put agricultural production at risk. In turn, the recent drought has also increased awareness of the local communities regarding the regional threat of water scarcity and the need of a regional water planning. The overall goal of this research is to generate data to characterize water use by the agricultural sector in this region and asses its sustainability in the regional context. Towards this goal, eddy-covariance flux towers were deployed on two extensive farms growing regionally-representative crops (melon/rice rotation and sugarcane) to evaluate, monitor and quantify water use in large-scale farms. The two identically instrumented stations provide continuous measurements of evapotranspiration and CO2 fluxes, and are equipped with additional instrumentation to monitor

Preliminary Investigation on the Behavior of Pore Air Pressure During Rainfall Infiltration

Science.gov (United States)

Ashraf Mohamad Ismail, Mohd; Min, Ng Soon; Hasliza Hamzah, Nur; Hazreek Zainal Abidin, Mohd; Madun, Aziman; Tajudin, Saiful Azhar Ahmad

2018-04-01

This paper focused on the preliminary investigation of pore air pressure behaviour during rainfall infiltration in order to substantiate the mechanism of rainfall induced slope failure. The actual behaviour or pore air pressure during infiltration is yet to be clearly understood as it is regularly assumed as atmospheric. Numerical modelling of one dimensional (1D) soil column was utilized in this study to provide a preliminary insight of this highlighted uncertainty. Parametric study was performed by using rainfall intensities of 1.85 x 10-3m/s and 1.16 x 10-4m/s applied on glass beads to simulate intense and modest rainfall conditions. Analysis results show that the high rainfall intensity causes more development of pore air pressure compared to low rainfall intensity. This is because at high rainfall intensity, the rainwater cannot replace the pore air smoothly thus confining the pore air. Therefore, the effect of pore air pressure has to be taken into consideration particularly during heavy rainfall.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Science.gov (United States)

Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

2018-03-01

The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Directory of Open Access Journals (Sweden)

Hassan Zulkarnain

2018-01-01

Full Text Available The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015 data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM, as compared to Southwest monsoon (SWM. Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Water erosion under simulated rainfall in different soil management systems during soybean growth

OpenAIRE

Engel,Fernando Luis; Bertol,Ildegardis; Mafra,Álvaro Luiz; Cogo,Neroli Pedro

2007-01-01

Soil management influences soil cover by crop residues and plant canopy, affecting water erosion. The objective of this research was to quantify water and soil losses by water erosion under different soil tillage systems applied on a typical aluminic Hapludox soil, in an experiment carried out from April 2003 to May 2004, in the Santa Catarina highland region, Lages, southern Brazil. Simulated rainfall was applied during five soybean cropstages, at the constant intensity of 64.0 mm h-1. Treat...

Coping with Rainfall Variability in Northern Tanzania

DEFF Research Database (Denmark)

Trærup, Sara Lærke Meltofte

2012-01-01

This paper explores a potential relationship between rainfall data and household self-reported harvest shocks and local (spatial) variability of harvest shocks and coping strategies based on a survey of 2700 rural households in the Kagera region of northern Tanzania. In addition, correlations...... of household reported harvest shocks differs significantly between districts and correspond to the observed variability in local climate patterns. Coping strategies are focused on spreading risks and include reduced consumption, casual employment, new crops, external support and the selling of assets....... There are no large differences in applied coping strategies across the region, but district-level data demonstrate how local strategies differ between localities within the districts. The results emphasize that in order to target rural policies and make them efficient, it is important to take into account the local...

Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

Science.gov (United States)

Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

2017-04-01

In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

Evaporative demand and water requirements of the principal crops of the Guadalentin valley (SE Spain) in drought periods

Energy Technology Data Exchange (ETDEWEB)

Sanchez-Toribio, M. I.; Garcia-Marin, R.; Conesa-Garcia, C.; Lopez-Bermudez, F.

2010-07-01

The drought periods that affect the province of Murcia, especially the Guadalentin Valley, are aggravated by an increase in evaporative demand. The aim of the present study was to characterize the increased water demand of woody and herbaceous crops during drought periods in the Guadalentin Valley, an agricultural zone with an excellent climate for specialty crops, which is of great economic importance for Murcia. After defining the drought periods of the last three decades in time and space by means of the standard index of rainfall drought (IESP), several methods were used to determine the reference evapotranspiration (ETo): the Penman-Monteith model (ASCE and FAO models for grass), the Hargreaves method (ETo-ASCE for alfalfa), and ETo using the FAO Radiation method. Finally, the crop water requirements for each to crop type and area of cultivation were estimated using monthly crop coefficients (K{sub c}) and the mean monthly evaporative demand values were obtained by the best fitting method. The increase in the evaporative demand reflected the increased water deficits that occur in the drought years, both in summer and winter (1.23 hm{sup 3} yr{sup -}1). Drought periods are also responsible for reducing the areas dedicated to horticultural crops, because of their high water demands and the additional costs involved, resulting an aggravated socioeconomic position and increased unemployment. (Author) 25 refs.

Analysis of the effect of crops and their management in the process of erosion in the basin of the Cuyaguateje River

International Nuclear Information System (INIS)

Leal Cuba, Zuzell; Diaz Suarez, Jorge; Ruiz Perez, Maria E

2008-01-01

Full text: Surface erosion is one of the environmental problems more serious that the agncultores face throughout the world. In the tropics, this phenomenon takes great dimensions due to the high intensity and large accumulated rainfall registered. Cover vegetable plays an important role in the protection of the soil against erosion. So it is of paramount control its effect. On the basis of this analysis is the realization of this work, which aims to introduce vegetation to the main crop factor present in the basin of the Rio Cuyaguateje, one of the eight prioritized basins of the country, currently affected with serious erosion problems. To estimate the effect of vegetation as a protective cover, used factor model RUSLE vegetation. For the analysis of This factor, the model needs data for coverage and height of the crop development in the time, which were determined for the principal crops of the basin, as well as the methodology for their determination, where you get the models that describe the behavior of these cultures according to the days after planting for the specific conditions of the basin, data that are then processed by the model RUSLE Crop Factor Calculator, obtaining the values of the factor C RUSLE. This calculation indicates according to crop rotation more used by farmers in the study area, a more than 60% soil loss reduction, indicating that crop rotation employee is not more a proper product to which the soil is discovered in the months of greater rainfall. For this proposed planting of beans velvet bean cover that It offers greater coverage in periods of greater erosion of rain and that adapts to these conditions, significantly reducing the soil losses. After the sowing of this culture, through simulations of rain experiments, for this model data obtained, then analysing the results, by comparing the experimental sites for different coverages and bare ground, demonstrating the effectiveness of the sowing of this farming in the protection of soil

High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

Science.gov (United States)

Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis

2012-05-01

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.

Regionalization of monthly rainfall erosivity patternsin Switzerland

Science.gov (United States)

Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

2016-10-01

the total annual rainfall erosivity is identified within four months only (June-September). The highest erosion risk can be expected in July, where not only rainfall erosivity but also erosivity density is high. In addition to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

Reducing Production Basis Risk through Rainfall Intensity Frequency (RIF) Indexes: Global Sensitivity Analysis' Implication on Policy Design

Science.gov (United States)

Muneepeerakul, Chitsomanus; Huffaker, Ray; Munoz-Carpena, Rafael

2016-04-01

The weather index insurance promises financial resilience to farmers struck by harsh weather conditions with swift compensation at affordable premium thanks to its minimal adverse selection and moral hazard. Despite these advantages, the very nature of indexing causes the presence of "production basis risk" that the selected weather indexes and their thresholds do not correspond to actual damages. To reduce basis risk without additional data collection cost, we propose the use of rain intensity and frequency as indexes as it could offer better protection at the lower premium by avoiding basis risk-strike trade-off inherent in the total rainfall index. We present empirical evidences and modeling results that even under the similar cumulative rainfall and temperature environment, yield can significantly differ especially for drought sensitive crops. We further show that deriving the trigger level and payoff function from regression between historical yield and total rainfall data may pose significant basis risk owing to their non-unique relationship in the insured range of rainfall. Lastly, we discuss the design of index insurance in terms of contract specifications based on the results from global sensitivity analysis.

Developing High-resolution Soil Database for Regional Crop Modeling in East Africa

Science.gov (United States)

Han, E.; Ines, A. V. M.

2014-12-01

The most readily available soil data for regional crop modeling in Africa is the World Inventory of Soil Emission potentials (WISE) dataset, which has 1125 soil profiles for the world, but does not extensively cover countries Ethiopia, Kenya, Uganda and Tanzania in East Africa. Another dataset available is the HC27 (Harvest Choice by IFPRI) in a gridded format (10km) but composed of generic soil profiles based on only three criteria (texture, rooting depth, and organic carbon content). In this paper, we present a development and application of a high-resolution (1km), gridded soil database for regional crop modeling in East Africa. Basic soil information is extracted from Africa Soil Information Service (AfSIS), which provides essential soil properties (bulk density, soil organic carbon, soil PH and percentages of sand, silt and clay) for 6 different standardized soil layers (5, 15, 30, 60, 100 and 200 cm) in 1km resolution. Soil hydraulic properties (e.g., field capacity and wilting point) are derived from the AfSIS soil dataset using well-proven pedo-transfer functions and are customized for DSSAT-CSM soil data requirements. The crop model is used to evaluate crop yield forecasts using the new high resolution soil database and compared with WISE and HC27. In this paper we will present also the results of DSSAT loosely coupled with a hydrologic model (VIC) to assimilate root-zone soil moisture. Creating a grid-based soil database, which provides a consistent soil input for two different models (DSSAT and VIC) is a critical part of this work. The created soil database is expected to contribute to future applications of DSSAT crop simulation in East Africa where food security is highly vulnerable.

Identification of climate-resilient integrated nutrient management practices for rice-rice cropping system--an empirical approach to uphold food security.

Science.gov (United States)

Subash, N; Gangwar, B; Singh, Rajbir; Sikka, A K

2015-01-01

Yield datasets of long-term experiments on integrated nutrient management in rice-rice cropping systems were used to investigate the relationship of variability in rainfall, temperature, and integrated nutrient management (INM) practices in rice-rice cropping system in three different agroecological regions of India. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure, green manure, and paddy straw) were compared with farmer's conventional practice. The intraseasonal variations in rice yields are largely driven by rainfall during kharif rice and by temperature during rabi rice. Half of the standard deviation from the average monthly as well as seasonal rainfall during kharif rice and 1 °C increase or decrease from the average maximum and minimum temperature during rabi rice has been taken as the classification of yield groups. The trends in the date of effective onset of monsoon indicate a 36-day delay during the 30-year period at Rajendranagar, which is statistically significant at 95 % confidence level. The mean annual maximum temperature shows an increasing trend in all the study sites. The length of monsoon also showed a shrinking trend in the rate of 40 days during the 30-year study period at Rajendranagar representing a semiarid region. At Bhubaneshwar, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through green manure resulted in an overall average higher increase of 5.1 % in system productivity under both excess and deficit rainfall years and also during the years having seasonal mean maximum temperature ≥35 °C. However, at Jorhat, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through straw resulted in an overall average higher increase of 7.4 % in system productivity, while at Rajendranagar, the application of 75 % NPK through chemical fertilizers and 25 % N through green manusre resulted in an overall average higher increase of

Identification of climate-resilient integrated nutrient management practices for rice-rice cropping system—an empirical approach to uphold food security

Science.gov (United States)

Subash, N.; Gangwar, B.; Singh, Rajbir; Sikka, A. K.

2015-01-01

Yield datasets of long-term experiments on integrated nutrient management in rice-rice cropping systems were used to investigate the relationship of variability in rainfall, temperature, and integrated nutrient management (INM) practices in rice-rice cropping system in three different agroecological regions of India. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure, green manure, and paddy straw) were compared with farmer's conventional practice. The intraseasonal variations in rice yields are largely driven by rainfall during kharif rice and by temperature during rabi rice. Half of the standard deviation from the average monthly as well as seasonal rainfall during kharif rice and 1 °C increase or decrease from the average maximum and minimum temperature during rabi rice has been taken as the classification of yield groups. The trends in the date of effective onset of monsoon indicate a 36-day delay during the 30-year period at Rajendranagar, which is statistically significant at 95 % confidence level. The mean annual maximum temperature shows an increasing trend in all the study sites. The length of monsoon also showed a shrinking trend in the rate of 40 days during the 30-year study period at Rajendranagar representing a semiarid region. At Bhubaneshwar, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through green manure resulted in an overall average higher increase of 5.1 % in system productivity under both excess and deficit rainfall years and also during the years having seasonal mean maximum temperature ≥35 °C. However, at Jorhat, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through straw resulted in an overall average higher increase of 7.4 % in system productivity, while at Rajendranagar, the application of 75 % NPK through chemical fertilizers and 25 % N through green manusre resulted in an overall average higher increase of

Crop Upgrading Strategies and Modelling for Rainfed Cereals in a Semi-Arid Climate—A Review

Directory of Open Access Journals (Sweden)

Festo Richard Silungwe

2018-03-01

Full Text Available Spatiotemporal rainfall variability and low soil fertility are the primary crop production challenges facing poor farmers in semi-arid environments. However, there are few solutions for addressing these challenges. The literature provides several crop upgrading strategies (UPS for improving crop yields, and biophysical models are used to simulate these strategies. However, the suitability of UPS is limited by systemization of their areas of application and the need to cope with the challenges faced by poor farmers. In this study, we reviewed 187 papers from peer-reviewed journals, conferences and reports that discuss UPS suitable for cereals and biophysical models used to assist in the selection of UPS in semi-arid areas. We found that four UPS were the most suitable, namely tied ridges, microdose fertilization, varying sowing dates, and field scattering. The DSSAT, APSIM and AquaCrop models adequately simulate these UPS. This work provides a systemization of crop UPS and models in semi-arid areas that can be applied by scientists and planners.

Heavy rainfall equations for Santa Catarina, Brazil

Directory of Open Access Journals (Sweden)

Álvaro José Back

2011-12-01

Full Text Available Knowledge of intensity-duration-frequency (IDF relationships of rainfall events is extremely important to determine the dimensions of surface drainage structures and soil erosion control. The purpose of this study was to obtain IDF equations of 13 rain gauge stations in the state of Santa Catarina in Brazil: Chapecó, Urussanga, Campos Novos, Florianópolis, Lages, Caçador, Itajaí, Itá, Ponte Serrada, Porto União, Videira, Laguna and São Joaquim. The daily rainfall data charts of each station were digitized and then the annual maximum rainfall series were determined for durations ranging from 5 to 1440 min. Based on these, with the Gumbel-Chow distribution, the maximum rainfall was estimated for durations ranging from 5 min to 24 h, considering return periods of 2, 5, 10, 20, 25, 50, and 100 years,. Data agreement with the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test, at 5 % significance level. For each rain gauge station, two IDF equations of rainfall events were adjusted, one for durations from 5 to 120 min and the other from 120 to 1440 min. The results show a high variability in maximum intensity of rainfall events among the studied stations. Highest values of coefficients of variation in the annual maximum series of rainfall were observed for durations of over 600 min at the stations of the coastal region of Santa Catarina.

Assessing the Challenges in Successful Implementation and Adoption of Crop Insurance in Thailand

Directory of Open Access Journals (Sweden)

Shweta Sinha

2016-12-01

Full Text Available The purpose of this paper is to assess the gaps in the adoption of crop insurance in Thailand and suggest possible solutions relating to policy support and framework, implementation mechanisms, technology adoption, and awareness amongst farmers. The methodology includes a literature review, interaction with officials, rice experts and insurance experts, and discussion with farmers. A study was undertaken at province level to assess the impact of using rainfall index as a threshold. Additionally, focused group discussions (FGD were conducted with rice farmers at the village level. Key issues targeted in the FGD were to understand the behavior and practices during droughts, impact of drought on crop yield, methods already in use to reduce the impact, such as plantation of drought-resistant rice, and the adoption of crop insurance. Data availability is a challenge and has led to withdrawal of Weather Index Insurance (WII in 2015. WII have threshold levels based on historical rainfall. Adoption of coping mechanisms, such as drought-resistant rice and irrigation increases the chances of adverse selection. In absence of ground based weather data, a combination of satellite agriculture drought information can be used to make crop insurance more attractive as it would help in reducing basis risk and improving insurers and farmers’ confidence in the product. Discussion with farmers, insurance companies, and the Bank of Agriculture and Agricultural Cooperatives (BAAC in Thailand suggested low awareness among farmers about the potential benefits of weather index insurance products. Relatively low compensation is also an obstacle. Proper marketing and awareness raising campaigns should also accompany the introduction of index-based insurance products.

Spatiotemporal Dynamics of Whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Commercial Watermelon Crops.

Science.gov (United States)

Lima, Carlos H O; Sarmento, Renato A; Galdino, Tarcísio V S; Pereira, Poliana S; Silva, Joedna; Souza, Danival J; Dos Santos, Gil R; Costa, Thiago L; Picanço, Marcelo C

2018-04-16

Spatiotemporal dynamics studies of crop pests enable the determination of the colonization pattern and dispersion of these insects in the landscape. Geostatistics is an efficient tool for these studies: to determine the spatial distribution pattern of the pest in the crops and to make maps that represent this situation. Analysis of these maps across the development of plants can be used as a tool in precision agriculture programs. Watermelon, Citrullus lanatus (Thunb.) Matsum. and Nakai (Cucurbitales: Cucurbitaceae), is the second most consumed fruit in the world, and the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is one of the most important pests of this crop. Thus, the objective of this work was to determine the spatiotemporal distribution of B. tabaci in commercial watermelon crops using geostatistics. For 2 yr, we monitored adult whitefly densities in eight watermelon crops in a tropical climate region. The location of the samples and other crops in the landscape was georeferenced. Experimental data were submitted to geostatistical analysis. The colonization of B. tabaci had two patterns. In the first, the colonization started at the outermost parts of the crop. In the second, the insects occupied the whole area of the crop since the beginning of cultivation. The maximum distance between sites of watermelon crops in which spatial dependence of B. tabaci densities was observed was 19.69 m. The adult B. tabaci densities in the eight watermelon fields were positively correlated with rainfall and relative humidity, whereas wind speed negatively affected whiteflies population.

Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques

Science.gov (United States)

Machiwal, Deepesh; Gupta, Ankit; Jha, Madan Kumar; Kamble, Trupti

2018-04-01

This study investigated trends in 35 years (1979-2013) temperature (maximum, Tmax and minimum, Tmin) and rainfall at annual and seasonal (pre-monsoon, monsoon, post-monsoon, and winter) scales for 31 grid points in a coastal arid region of India. Box-whisker plots of annual temperature and rainfall time series depict systematic spatial gradients. Trends were examined by applying eight tests, such as Kendall rank correlation (KRC), Spearman rank order correlation (SROC), Mann-Kendall (MK), four modified MK tests, and innovative trend analysis (ITA). Trend magnitudes were quantified by Sen's slope estimator, and a new method was adopted to assess the significance of linear trends in MK-test statistics. It was found that the significant serial correlation is prominent in the annual and post-monsoon Tmax and Tmin, and pre-monsoon Tmin. The KRC and MK tests yielded similar results in close resemblance with the SROC test. The performance of two modified MK tests considering variance-correction approaches was found superior to the KRC, MK, modified MK with pre-whitening, and ITA tests. The performance of original MK test is poor due to the presence of serial correlation, whereas the ITA method is over-sensitive in identifying trends. Significantly increasing trends are more prominent in Tmin than Tmax. Further, both the annual and monsoon rainfall time series have a significantly increasing trend of 9 mm year-1. The sequential significance of linear trend in MK test-statistics is very strong (R 2 ≥ 0.90) in the annual and pre-monsoon Tmin (90% grid points), and strong (R 2 ≥ 0.75) in monsoon Tmax (68% grid points), monsoon, post-monsoon, and winter Tmin (respectively 65, 55, and 48% grid points), as well as in the annual and monsoon rainfalls (respectively 68 and 61% grid points). Finally, this study recommends use of variance-corrected MK test for the precise identification of trends. It is emphasized that the rising Tmax may hamper crop growth due to enhanced

Crop rotation in the Valle Calido del Alto Magdalena a sustainable focus of high yield

International Nuclear Information System (INIS)

Alfaro Rodriguez, Ricardo; Maria Caicedo, Antonio; Amezquita Collazos, Edgar; Castro Franco, Hugo Eduardo

1996-01-01

Experiments were carried out during five years at the Nataima Research Center, located at 431 m.a.s.l, with average temperature of 28 Celsius degrades and annual rainfall of 1274 Boyaca mm, on a soil classified as Arenic Haplustalf, to evaluate different crops rotation based on rice and sorghum; the combinations used were as follows; rice-rice (R-R), rice-- soybean (R-SY), rice-crotalaria-sorghum (R-C-S), sorghum-sorghum (S-S), sorghum-soybean (S-SY) and cotton-sorghum (Al-S). Simultaneously it was evaluated the response to four nitrogen levels, which allowed to find out yield functions and optimum economical. The rotations S-SY, R-SY and AI-S have been the best qualified from an environmental perspective. Sorghum-soybean rotation presents increases in yield compared with expected values, which allows thinking that it is a truly sustainable rotation. This rotation also had an excellent profitability and for that reason is considered the best option within the goals of this work

Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

Science.gov (United States)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2017-12-01

In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

Crop scheduling improvements for rainfed agriculture in the high jungle of Peru

Directory of Open Access Journals (Sweden)

Enrique Meseth

2014-12-01

Full Text Available This work was aimed to improve the water management for agriculture by applying efficient crop schedules in Vilcabamba and similar areas of the high jungle, which can satisfy most of the water requirements with rainfed agriculture to maximize the crops yield. For this purpose, two field practices were carried out during the dry (September 2012 and wet season (February 2013 to measure rivers and canals flows with the velocity/area method; 19 soil samples were collected on-site and analyzed, presenting prevalent sandy loam and loam textures. Cropwat program was used to estimate crop water requirements and scheme irrigation requirements, resulting in a maximum flow capacity of 1.72 l s-1 in May, during the dry season. The flow capacity can be satisfied, since small ditches convey approximately 2 to 6 l s-1 on the same season. The research findings indicate that rainfed farming can be practised, yet an initial pre-irrigation needs to be applied, for crops should not be water stressed. However, if soil is not pre-irrigated the production can be affected, with vegetables and potato crop yields being reduced by 4.7% and 1.4% respectively. To minimize these effects, both crops are suggested to be sowed one month later, adapting their growth period to the rainy season.

Harvesting Robots for High-value Crops: State-of-the-art Review and Challenges Ahead

NARCIS (Netherlands)

Bac, C.W.; Henten, van E.; Hemming, J.; Edan, Y.

2014-01-01

This review article analyzes state-of-the-art and future perspectives for harvesting robots in high-value crops. The objectives were to characterize the crop environment relevant for robotic harvesting, to perform a literature review on the state-of-the-art of harvesting robots using quantitative

Temporal characteristics of rainfall events under three climate types in Slovenia

Science.gov (United States)

Dolšak, Domen; Bezak, Nejc; Šraj, Mojca

2016-10-01

Temporal rainfall distribution can often have significant influence on other hydrological processes such as runoff generation or rainfall interception. High-frequency rainfall data from 30 stations in Slovenia were analysed in order to improve the knowledge about the temporal rainfall distribution within a rainfall event. Using the pre-processed rainfall data Huff curves were determined and the binary shape code (BSC) methodology was applied. Although Slovenia covers only about 20,000 km2, results indicate large temporal and spatial variability in the precipitation pattern of the analysed stations, which is in agreement with the different Slovenian climate types: sub-Mediterranean, temperate continental, and mountain climate. Statistically significant correlation was identified between the most frequent BSC types, mean annual precipitation, and rainfall erosivity for individual rainfall stations. Moreover, different temporal rainfall distributions were observed for rainfall events with shorter duration (less than 12 h) than those with longer duration (more than 24 h). Using the analysis of the Huff curves it was shown that the variability in the Huff curves decreases with increasing rainfall duration. Thus, it seems that for shorter duration convective storms a more diverse temporal rainfall distribution can be expected than for the longer duration frontal precipitation where temporal rainfall distribution shows less variability.

Rainfall over Friuli-Venezia Giulia: High amounts and strong geographical gradients

Science.gov (United States)

Ceschia, M.; Micheletti, St.; Carniel, R.

1991-12-01

The precipitation distribution over Friuli-Venezia Giulia — the easternmost region of Northern Italy extending from the Adriatic Sea to the Alps — has been studied. Monthly rainfall data over the region and the bordering areas of Veneto and Slovenia during the period from 1951 to 1986 have been analyzed by standard statistical methods, including cluster analysis. The overall results emphasize a distribution with rainfall increasing from the sea to the prealpine areas. The highest precipitations were recorded over the Musi-Canin range, with average values exceeding 3 200 mm per year. Noteworthy is the unforeseen subdivision of the region by the clustering procedure by means of the Angot index.

Forty years experience in developing and using rainfall simulators under tropical and Mediterranean conditions

Science.gov (United States)

Pla-Sentís, Ildefonso; Nacci, Silvana

2010-05-01

Rainfall simulation has been used as a practical tool for evaluating the interaction of falling water drops on the soil surface, to measure both stability of soil aggregates to drop impact and water infiltration rates. In both cases it is tried to simulate the effects of natural rainfall, which usually occurs at very different, variable and erratic rates and intensities. One of the main arguments against the use of rainfall simulators is the difficulty to reproduce the size, final velocity and kinetic energy of the drops in natural rainfall. Since the early 70´s we have been developing and using different kinds of rainfall simulators, both at laboratory and field levels, and under tropical and Mediterranean soil and climate conditions, in flat and sloping lands. They have been mainly used to evaluate the relative effects of different land use and management, including different cropping systems, tillage practices, surface soil conditioning, surface covers, etc. on soil water infiltration, on runoff and on erosion. Our experience is that in any case it is impossible to reproduce the variable size distribution and terminal velocity of raindrops, and the variable changes in intensity of natural storms, under a particular climate condition. In spite of this, with the use of rainfall simulators it is possible to obtain very good information, which if it is properly interpreted in relation to each particular condition (land and crop management, rainfall characteristics, measurement conditions, etc.) may be used as one of the parameters for deducing and modelling soil water balance and soil moisture regime under different land use and management and variable climate conditions. Due to the possibility for a better control of the intensity of simulated rainfall and of the size of water drops, and the possibility to make more repeated measurements under very variable soil and land conditions, both in the laboratory and specially in the field, the better results have been

Impact of rainfall patterns and frequency on the export of pesticides and heavy-metals from agricultural soils.

Science.gov (United States)

Meite, Fatima; Alvarez-Zaldívar, Pablo; Crochet, Alexandre; Wiegert, Charline; Payraudeau, Sylvain; Imfeld, Gwenaël

2018-03-01

The combined influence of soil characteristics, pollutant aging and rainfall patterns on the export of pollutants from topsoils is poorly understood. We used laboratory experiments and parsimonious modeling to evaluate the impact of rainfall characteristics on the ponding and the leaching of a pollutant mixture from topsoils. The mixture included the fungicide metalaxyl, the herbicide S-metolachlor, as well as copper (Cu) and zinc (Zn). Four rainfall patterns, which differed in their durations and intensities, were applied twice successively with a 7days interval on each soil type. To evaluate the influence of soil type and aging, experiments included crop and vineyard soils and two stages of pollutant aging (0 and 10days). The global export of pollutants was significantly controlled by the rainfall duration and frequency (Pexport of metalaxyl (44.5±21.5% of the initial mass spiked in the soils), S-metolachlor (8.1±3.1%) and Cu (3.1±0.3%). Soil compaction caused by the first rainfall reduced in the second rainfall the leaching of remaining metalaxyl, S-metolachlor, Cu and Zn by 2.4-, 2.9-, 30- and 50-fold, respectively. In contrast, soil characteristics and aging had less influence on pollutant mass export. The soil type significantly influenced the leaching of Zn, while short-term aging impacted Cu leaching. Our results suggest that rainfall characteristics predominantly control export patterns of metalaxyl and S-metolachlor, in particular when the aging period is short. We anticipate our study to be a starting point for more systematic evaluation of the dissolved pollutant ponding/leaching partitioning and the export of pollutant mixtures from different soil types in relation to rainfall patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

The Relationship between El nino Southern Oscillation (ENSO) Phenomenon and Seasonal Precipitation Variability in Eastern Kenya with Special Reference to Katumani: Its Implication to Crop Production

International Nuclear Information System (INIS)

Kitheka, S.K

1999-01-01

Climatic variability has been defined as a major limitation to agricultural production in semi arid Kenya. The major difficulty to both farmers and research community, has been the inability to to predict seasonal rainfall prior to the season onset. Although several researches have attempted and made advances in predicting rainfall amount, solutions to the problem have not been achieved. This study has examined and related rainfall at Katumani with the El Nino-Southern Oscillation (ENSO) phenomenon. Rainfall variations during different phases of ENSO were established. Some advances in the early prediction of March-May and October -January rains for, both, the warm and cold phases of ENSO have been made. Crop production is closely related to the rainfall and therefore a need for revision of agronomic recommendation to tie them with rainfall variation

Environmental Change: Precipitation and N, P, K, mg Fertilization Influences on Crop Yield Under Temperate Climate Conditions

Science.gov (United States)

László Phd, Dd. M.

2009-04-01

. These crops are demanding indicator of soil nutrient status also. Have a particularly high requirement for supply of soil nitrogen, phosphorus, potassium and magnesium. From 1962 to 1990 this paper describes climate-rainfall-change and N, P, K and Mg-mineral fertilisation effects on rye, potato and winter wheat yield on a acidic sandy brown forest soil at long term experiment scale under temperate climate conditions at Hungary. Material and Method: The effect of rainfall quantity and distribution on certain crop fertilisation factors (N, P, K, Mg and yield) were studied in a long-term field experiment on acidic sandy brown forest soil at North-Eastern Hungary set up in 1962 and 2002. Ploughed layer of the experiment soil had a pH(KCl) 4.5, humus 0.5%, CEC 5-10 mgeq 100 g-1. The topsoil was poor in all four macronutrients N, P, K and Mg. Rye, potato and winter wheat experiments involved 2x2x16x8 = 512, 2x2x16x8 = 512 and 2x16x4 = 128 plots. The gross and net plot size was 10x5 = 50 m2 and 35.5 m2. The experimental designe was split-split-plot. Average treatments were rye N:45 kg, P2O5:24, K2O:40, MgO:7.5 kg ha-1 year-1, potato N:75 kg, P2O5:24, K2O:75, MgO:15 kg ha-1 year-1, winter wheat N:45 kg, P2O5:24, K2O:40, MgO:7.5 kg ha-1 year-1 from 1962 to 1980 and N:75 kg, P2O5:90, K2O:90, MgO:140 kg ha-1 year-1 from 1981 to 1990 in the form of 25% calcium ammonium nitrate, 18% superphosphate, 40% potassium chloride, and magnesium sulphate. The groundwater table was at a depth of 2-3 m. Ecological (rainfall) and experimental data bases were estimated by Hungarian traditional [6] and RISSAC-HAS [3] standards and MANOVA (SPSS). Results: Climate-rainfall-change and mineral fertilisation effects on rye yield a. Experimental years were characterised by frequent extremes of precipitation variabilities and changes. One year had an 450 mm average rainfall (1966), one year had a more humid (1970) and three years had a very dry (1964, 1968, 1972) character. b. Weather anomalies as

Forecasting wheat and barley crop production in arid and semi-arid regions using remotely sensed primary productivity and crop phenology: A case study in Iraq.

Science.gov (United States)

Qader, Sarchil Hama; Dash, Jadunandan; Atkinson, Peter M

2018-02-01

Crop production and yield estimation using remotely sensed data have been studied widely, but such information is generally scarce in arid and semi-arid regions. In these regions, inter-annual variation in climatic factors (such as rainfall) combined with anthropogenic factors (such as civil war) pose major risks to food security. Thus, an operational crop production estimation and forecasting system is required to help decision-makers to make early estimates of potential food availability. Data from NASA's MODIS with official crop statistics were combined to develop an empirical regression-based model to forecast winter wheat and barley production in Iraq. The study explores remotely sensed indices representing crop productivity over the crop growing season to find the optimal correlation with crop production. The potential of three different remotely sensed indices, and information related to the phenology of crops, for forecasting crop production at the governorate level was tested and their results were validated using the leave-one-year-out approach. Despite testing several methodological approaches, and extensive spatio-temporal analysis, this paper depicts the difficulty in estimating crop yield on an annual base using current satellite low-resolution data. However, more precise estimates of crop production were possible. The result of the current research implies that the date of the maximum vegetation index (VI) offered the most accurate forecast of crop production with an average R 2 =0.70 compared to the date of MODIS EVI (Avg R 2 =0.68) and a NPP (Avg R 2 =0.66). When winter wheat and barley production were forecasted using NDVI, EVI and NPP and compared to official statistics, the relative error ranged from -20 to 20%, -45 to 28% and -48 to 22%, respectively. The research indicated that remotely sensed indices could characterize and forecast crop production more accurately than simple cropping area, which was treated as a null model against which to

Cropping Systems and Climate Change in Humid Subtropical Environments

Directory of Open Access Journals (Sweden)

Ixchel M. Hernandez-Ochoa

2018-02-01

Full Text Available In the future, climate change will challenge food security by threatening crop production. Humid subtropical regions play an important role in global food security, with crop rotations often including wheat (winter crop and soybean and maize (summer crops. Over the last 30 years, the humid subtropics in the Northern Hemisphere have experienced a stronger warming trend than in the Southern Hemisphere, and the trend is projected to continue throughout the mid- and end of century. Past rainfall trends range, from increases up to 4% per decade in Southeast China to −3% decadal decline in East Australia; a similar trend is projected in the future. Climate change impact studies suggest that by the middle and end of the century, wheat yields may not change, or they will increase up to 17%. Soybean yields will increase between 3% and 41%, while maize yields will increase by 30% or decline by −40%. These wide-ranging climate change impacts are partly due to the region-specific projections, but also due to different global climate models, climate change scenarios, single-model uncertainties, and cropping system assumptions, making it difficult to make conclusions from these impact studies and develop adaptation strategies. Additionally, most of the crop models used in these studies do not include major common stresses in this environment, such as heat, frost, excess water, pests, and diseases. Standard protocols and impact assessments across the humid subtropical regions are needed to understand climate change impacts and prepare for adaptation strategies.

Irrigation as an Adaptation Strategy to Climate Change: The Relative Influence of Groundwater and Canal Irrigation on Winter Crop Production and its Sensitivity to Weather Variability in India

Science.gov (United States)

Jain, M.; Fishman, R.; Mondal, P.; Galford, G. L.; Naeem, S.; Modi, V.; DeFries, R. S.

2014-12-01

India is a hotspot for food security issues over the upcoming decades, due to increasing population pressures, groundwater depletion, and climate change. Investing in additional irrigation infrastructure may bolster food security, however, the relative influence of different types of irrigation (e.g. groundwater versus canal) on agricultural production remains unclear. One reason that the relative impact of different irrigation strategies on agricultural production has not been analyzed across India is because national-scale data on crop production and the types of irrigation technologies used are typically available at too coarse of spatial and temporal resolutions to answer this question adequately. Thus, we develop a novel algorithm to map cropped area across India at a 1 x 1 km scale using MODIS satellite data, and link these high-resolution cropped area maps with village-level data (n = 600,000) on irrigation. This allowed us to assess the relative impact of groundwater (i.e. dug, shallow, and deep wells) and canal irrigation (i.e. surface lift and flow canals) on winter cropped area and its sensitivity to rainfall across India at the village-scale from 2000 to 2006. We find that deep well irrigation is both associated with the greatest amount of winter cropped area, and is also the least sensitive to monsoon and winter rainfall variability. However, the effectiveness of deep well irrigation varies across India, with the greatest benefits seen in the regions that are most at risk for losing groundwater as a possible source of irrigation over the upcoming decades (e.g. Northwest India). This work highlights the need to develop ways to use remaining groundwater more efficiently (e.g. drip irrigation, less water-intensive crops) given that canal irrigation is not an adequate substitute, particularly in the regions that are facing the greatest levels of groundwater depletion.

Mapping Multi-Cropped Land Use to Estimate Water Demand Using the California Pesticide Reporting Database

Science.gov (United States)

Henson, W.; Baillie, M. N.; Martin, D.

2017-12-01

Detailed and dynamic land-use data is one of the biggest data deficiencies facing food and water security issues. Better land-use data results in improved integrated hydrologic models that are needed to look at the feedback between land and water use, specifically for adequately representing changes and dynamics in rainfall-runoff, urban and agricultural water demands, and surface fluxes of water (e.g., evapotranspiration, runoff, and infiltration). Currently, land-use data typically are compiled from annual (e.g., Crop Scape) or multi-year composites if mapped at all. While this approach provides information about interannual land-use practices, it does not capture the dynamic changes in highly developed agricultural lands prevalent in California agriculture such as (1) dynamic land-use changes from high frequency multi-crop rotations and (2) uncertainty in sub-annual crop distribution, planting times, and cropped areas. California has collected spatially distributed data for agricultural pesticide use since 1974 through the California Pesticide Information Portal (CalPIP). A method leveraging the CalPIP database has been developed to provide vital information about dynamic agricultural land use (e.g., crop distribution and planting times) and water demand issues in Salinas Valley, California, along the central coast. This 7 billion dollar/year agricultural area produces up to 50% of U.S. lettuce and broccoli. Therefore, effective and sustainable water resource development in the area must balance the needs of this essential industry, other beneficial uses, and the environment. This new tool provides a way to provide more dynamic crop data in hydrologic models. While the current application focuses on the Salinas Valley, the methods are extensible to all of California and other states with similar pesticide reporting. The improvements in representing variability in crop patterns and associated water demands increase our understanding of land-use change and

Predicting of soil erosion with regarding to rainfall erosivity and soil erodibility

Science.gov (United States)

Suif, Zuliziana; Razak, Mohd Amirun Anis Ab; Ahmad, Nordila

2018-02-01

The soil along the hill and slope are wearing away due to erosion and it can take place due to occurrence of weak and heavy rainfall. The aim of this study is to predict the soil erosion degree in Universiti Pertahanan Nasional Malaysia (UPNM) area focused on two major factor which is soil erodibility and rainfall erosivity. Soil erodibility is the possibilities of soil to detach and carried away during rainfall and runoff. The "ROM" scale was used in this study to determine the degree of soil erodibility, namely low, moderate, high, and very high. As for rainfall erosivity, the erosive power caused by rainfall that cause soil loss. A daily rainfall data collected from January to April was analyzed by using ROSE index classification to identify the potential risk of soil erosion. The result shows that the soil erodibilty are moderate at MTD`s hill, high at behind of block Lestari and Landslide MTD hill, and critical at behind the mess cadet. While, the highest rainfall erosivity was recorded in March and April. Overall, this study would benefit the organization greatly in saving cost in landslide protection as relevant authorities can take early measures repairing the most affected area of soil erosion.

High-frequency DOC and nitrate measurements provide new insights into their export and their relationships to rainfall-runoff processes

Science.gov (United States)

Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus

2015-04-01

Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of

Soil Hydrological Attributes of an Integrated Crop-Livestock Agroecosystem: Increased Adaptation through Resistance to Soil Change

International Nuclear Information System (INIS)

Liebig, M.A; Tanaka, D.L; Kronberg, S.L; Karn, J.F; Scholljegerdes, E.J

2011-01-01

Integrated crop-livestock systems have been purported to have significant agronomic and environmental benefits compared to specialized, single-enterprise production systems. However, concerns exist regarding the effect of livestock in integrated systems to cause soil compaction, thereby decreasing infiltration of water into soil. Such concerns are compounded by projections of more frequent high-intensity rainfall events from anticipated climate change, which would act to increase surface runoff and soil erosion. A study was conducted to evaluate the effects of residue management, frequency of hoof traffic, season, and production system (e.g., integrated annual cropping versus perennial grass) on infiltration rates from 2001 through 2008 in central North Dakota, USA. Imposed treatments had no effect on infiltration rate at three, six, and nine years after study establishment, implying that agricultural producers should not be concerned with inhibited infiltration in integrated annual cropping systems, where winter grazing is used. The use of no-till management, coupled with annual freeze/thaw and wet/dry cycles, likely conferred an inherent resistance to change in near-surface soil properties affecting soil hydrological attributes. Accordingly, caution should be exercised in applying these results to other regions or management systems.

Projected changes of rainfall seasonality and dry spells in a high greenhouse gas emissions scenario

OpenAIRE

Pascale, Salvatore; Lucarini, Valerio; Feng, Xue; Porporato, Amilcare; ul Hasson, Shabeh

2016-01-01

In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models contributing to Coupled Model Intercomparison Project 5 (CMIP5). We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to qu...

Analysis of Spatiotemporal Statistical Properties of Rainfall in the Phoenix Metropolitan Area

Science.gov (United States)

Mascaro, G.

2016-12-01

The analysis of the rainfall statistical properties at multiple spatiotemporal scales is a necessary preliminary step to support modeling of urban hydrology, including flood prediction and simulation of impacts of land use changes. In this contribution, the rainfall statistical properties are analyzed in the Phoenix Metropolitan area and its surroundings ( 29600 km2) in Arizona using observations from 310 gauges of the Flood Control District of the Maricopa County network. Different techniques are applied to investigate the rainfall properties at temporal scales from 1 min to years and to quantify the associated spatial variability. Results reveal the following. The rainfall regime is characterized by high interannual variability, which is partially explained by teleconnections with El Niño Southern Oscillation, and marked seasonality, with two maxima in the monsoon season from July to September and in winter from November to March. Elevation has a significant control on seasonal rainfall accumulation, strength of thermal convective activity during the monsoon, and peak occurrence of the rainfall diurnal cycle present in summer. The spatial correlation of wintertime rainfall is high even at short aggregation times (cells).

Accuracy of rainfall measurement for scales of hydrological interest

Directory of Open Access Journals (Sweden)

S. J. Wood

2000-01-01

Full Text Available The dense network of 49 raingauges over the 135 km2 Brue catchment in Somerset, England is used to examine the accuracy of rainfall estimates obtained from raingauges and from weather radar. Methods for data quality control and classification of precipitation types are first described. A super-dense network comprising eight gauges within a 2 km grid square is employed to obtain a 'true value' of rainfall against which the 2 km radar grid and a single 'typical gauge' estimate can be compared. Accuracy is assessed as a function of rainfall intensity, for different periods of time-integration (15 minutes, 1 hour and 1 day and for two 8-gauge networks in areas of low and high relief. In a similar way, the catchment gauge network is used to provide the 'true catchment rainfall' and the accuracy of a radar estimate (an area-weighted average of radar pixel values and a single 'typical gauge' estimate of catchment rainfall evaluated as a function of rainfall intensity. A single gauge gives a standard error of estimate for rainfall in a 2 km square and over the catchment of 33% and 65% respectively, at rain rates of 4 mm in 15 minutes. Radar data at 2 km resolution give corresponding errors of 50% and 55%. This illustrates the benefit of using radar when estimating catchment scale rainfall. A companion paper (Wood et al., 2000 considers the accuracy of rainfall estimates obtained using raingauge and radar in combination. Keywords: rainfall, accuracy, raingauge, radar

Olive Cultivation in the Southern Hemisphere: Flowering, Water Requirements and Oil Quality Responses to New Crop Environments

Science.gov (United States)

Torres, Mariela; Pierantozzi, Pierluigi; Searles, Peter; Rousseaux, M. Cecilia; García-Inza, Georgina; Miserere, Andrea; Bodoira, Romina; Contreras, Cibeles; Maestri, Damián

2017-01-01

Olive (Olea europaea L.) is a crop well adapted to the environmental conditions prevailing in the Mediterranean Basin. Nevertheless, the increasing international demand for olive oil and table olives in the last two decades has led to expansion of olive cultivation in some countries of the southern hemisphere, notably in Argentina, Chile, Perú and Australia. While the percentage of world production represented by these countries is still low, many of the new production regions do not have typical Mediterranean climates, and some are located at subtropical latitudes where there is relatively little information about crop function. Thus, the primary objective of this review was to assess recently published scientific literature on olive cultivation in these new crop environments. The review focuses on three main aspects: (a) chilling requirements for flowering, (b) water requirements and irrigation management, and (c) environmental effects on fruit oil concentration and quality. In many arid and semiarid regions of South America, temperatures are high and rainfall is low in the winter and early spring months compared to conditions in much of the Mediterranean Basin. High temperatures have often been found to have detrimental effects on olive flowering in many olive cultivars that have been introduced to South America, and a better understanding of chilling requirements is needed. Lack of rainfall in the winter and spring also has resulted in an urgent need to evaluate water requirements from the flower differentiation period in the winter to early fruit bearing. Additionally, in some olive growing areas of South America and Australia, high early season temperatures affect the timing of phenological events such that the onset of oil synthesis occurs sooner than in the Mediterranean Basin with most oil accumulation taking place in the summer when temperatures are very high. Increasing mean daily temperatures have been demonstrated to decrease fruit oil concentration

MAIZE YIELD AND ITS STABILITY AS AFFECTED BY TILLAGE AND CROP RESIDUE MANAGEMENT IN THE EASTERN ROMANIAN DANUBE PLAIN

Directory of Open Access Journals (Sweden)

Alexandru COCIU

2015-10-01

Full Text Available Rainfed crop management systems need to be optimized to provide more resilient options in order to cope with projected climatic scenarios which are forecasting a decrease in mean precipitation and more frequent extreme drought periods in the Eastern Romanian Danube Plain. This research, carried out in the period of 2011-2014, had as main purpose the determination of influence of tillage practices and residue management on rainfall use efficiency, maize yield and its stability, in order to evaluate the advantages of conservation agriculture (CA in the time of stabilization of direct seeding effects, in comparison with traditional chisel tillage. The maize grain yields are presented for each crop management practices, as follows: (1 chisel tillage, retained crop residues being chopped and incorporated (ciz; (2 zero tillage, retained crop residue chopped and kept on the field in short flat condition (rvt; (3 zero tillage, crop residues kept on the field in short root-anchored condition (1/2rva, and (4 zero tillage, crop residues kept on the field in tall root-anchored condition (1/1rva. In 2012, a year with prolonged drought during vegetative growth, yield differences between zero tillage with short root-anchored residue retention (1/2rva and chisel tillage with residue incorporation (ciz were positive, up to 840 kg ha-1. In average over 2011-2014, conservation agriculture (CA practices had a yield advantage over traditional chisel tillage practice. Zero tillage with residue retention used rainfall more efficiently so suggesting that it is a more resilient agronomic system than traditional (conventional practices involving chisel tillage with residue incorporation.

Preliminary investigations to assess the usefulness of Be-7 as a radiotracer in soil covered by vegetation [Activities of the Soil and Water Management and Crop Nutrition Laboratory, Seibersdorf

Energy Technology Data Exchange (ETDEWEB)

Iurian, Andra-Rada [Faculty of Environmental Science and Engineering, Babes-Bolyai University, Cluj-Napoca (Romania); Dercon, Gerd; Adu-Gyamfi, Joseph; Mabit, Lionel [Soil and Water Management and Crop Nutrition Laboratory, Joint FAO/IAEA Division for Nuclear Techniques in Food and Agriculture, Seibersdorf (Austria); Kis-Benedek, Gyula; Ceccatelli, Alessia; Tarjan, Sandor [3Terrestrial Environment Laboratory, IAEA Environment Laboratories, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Seibersdorf (Austria); Blake, William [School of Geography, University of Plymouth, Plymouth (United Kingdom); others, and

2014-07-15

Different factors may affect the extent of radionuclides’ interception by plants and therewith their inventories in soil covered areas. In particular, there is interest in assessing the impact of the vegetation factor for different soil coverage conditions, when using {sup 7}Be as radiotracer of soil redistribution in cropped farmland. Our results suggest that {sup 7}Be foliar interception of bean plants is likely to affect the radionuclide inventories and their spatial uniformity in covered soil. Reliable results on short-term erosion using {sup 7}Be can be obtained in cropped farmland with limited cover, but only when taking into account the interception factor. The impact of the interception factor is highly dependent on rainfall intensity and duration, crop species and the growing stage of the plants. Further investigations into these variables are required.

Preliminary investigations to assess the usefulness of Be-7 as a radiotracer in soil covered by vegetation [Activities of the Soil and Water Management and Crop Nutrition Laboratory, Seibersdorf

International Nuclear Information System (INIS)

Iurian, Andra-Rada; Dercon, Gerd; Adu-Gyamfi, Joseph; Mabit, Lionel; Kis-Benedek, Gyula; Ceccatelli, Alessia; Tarjan, Sandor; Blake, William

2014-01-01

Different factors may affect the extent of radionuclides’ interception by plants and therewith their inventories in soil covered areas. In particular, there is interest in assessing the impact of the vegetation factor for different soil coverage conditions, when using 7 Be as radiotracer of soil redistribution in cropped farmland. Our results suggest that 7 Be foliar interception of bean plants is likely to affect the radionuclide inventories and their spatial uniformity in covered soil. Reliable results on short-term erosion using 7 Be can be obtained in cropped farmland with limited cover, but only when taking into account the interception factor. The impact of the interception factor is highly dependent on rainfall intensity and duration, crop species and the growing stage of the plants. Further investigations into these variables are required

Crop yield response to climate change varies with cropping intensity.

Science.gov (United States)

Challinor, Andrew J; Parkes, Ben; Ramirez-Villegas, Julian

2015-04-01

Projections of the response of crop yield to climate change at different spatial scales are known to vary. However, understanding of the causes of systematic differences across scale is limited. Here, we hypothesize that heterogeneous cropping intensity is one source of scale dependency. Analysis of observed global data and regional crop modelling demonstrate that areas of high vs. low cropping intensity can have systematically different yields, in both observations and simulations. Analysis of global crop data suggests that heterogeneity in cropping intensity is a likely source of scale dependency for a number of crops across the globe. Further crop modelling and a meta-analysis of projected tropical maize yields are used to assess the implications for climate change assessments. The results show that scale dependency is a potential source of systematic bias. We conclude that spatially comprehensive assessments of climate impacts based on yield alone, without accounting for cropping intensity, are prone to systematic overestimation of climate impacts. The findings therefore suggest a need for greater attention to crop suitability and land use change when assessing the impacts of climate change. © 2015 John Wiley & Sons Ltd.

Finger millet: An alternative crop for the Southern High Plains

Science.gov (United States)

In the Southern High Plains, dairies are expanding to take advantage of favorable climatic conditions. Currently, corn (Zea mays L.) and forage sorghum [Sorghum bicolor (L.) Moench] are the two major crops grown in the region to meet silage demands for the expanding dairy industry, but they have rel...

Climate change, climate variability and adaptation options in smallholder cropping systems of the Sudano - Sahel region in West Africa

NARCIS (Netherlands)

Traore, B.

2014-01-01

Key words: crop production, maize, millet, sorghum, cotton, fertilizer, rainfall, temperature, APSIM, Mali,

In the Sudano-Sahelian zone of West Africa (SSWA) agricultural production remains the main source of livelihood for rural communities, providing employment to more than 60

Prediction of Rainfall-Induced Landslides

Science.gov (United States)

Nadim, F.; Sandersen, F.

2009-12-01

Rainfall-induced landslides can be triggered by two main mechanisms: shear failure due to build-up of pore water pressure and erosion by surface water runoff when flow velocity exceeds a critical value. Field measurements indicate that, in the initial phase, the slip surface of a landslide often occurs along the top of a relatively impermeable layer located at some depth within the soil profile, e.g. at the contact with a shallow underlying bedrock or parent rock. The shear strength along this surface and hence the stability of the slope is governed by the pore water pressure. The pore pressure is in turn controlled by water seepage through the slope, either from infiltrated rain, or from groundwater that follows bedrock joints and soil layers with high permeability. When the infiltration rate of the underlying layer is too low for further downward penetration of water or when a wetting front is produced, pore water pressure builds up, reducing the soil shear strength. During high intensity rainfall, surface water runoff will exert shear stresses on the bed material. De-pending on the grain size distribution and specific gravity of the material, erosion might occur when the flow velocity exceeds a critical value. As erosion progresses and sediment concentration increases, the flow regime may become unstable with heavy erosion at high flow velocity locations triggering a debris flow. In many cases, previous landslides along steep gully walls have fed an abundance of loose soil material into the gullies. Landslides along gully walls that obstruct the water transport may also trigger debris flows when the landslide-dam collapses, creating a surge downstream. Both the long-duration (1 or more days) and short-duration precipitation (of the order of 1 hour) are significant in the triggering of shallow landslides, since the critical short-duration rainfall intensity reduces as the antecedent accumulated rainfall increases. Experiences in Norway indicate that the maxi

Leaching variations of heavy metals in chelator-assisted phytoextraction by Zea mays L. exposed to acid rainfall.

Science.gov (United States)

Lu, Yayin; Luo, Dinggui; Liu, Lirong; Tan, Zicong; Lai, An; Liu, Guowei; Li, Junhui; Long, Jianyou; Huang, Xuexia; Chen, Yongheng

2017-11-01

Chelant-enhanced phytoextraction method has been put forward as an effective soil remediation method, whereas the heavy metal leaching could not be ignored. In this study, a cropping-leaching experiment, using soil columns, was applied to study the metal leaching variations during assisted phytoextraction of Cd- and Pb-polluted soils, using seedlings of Zea mays, applying three different chelators (EDTA, EDDS, and rhamnolipid), and artificial rainfall (acid rainfall or normal rainfall). It showed that artificial rainfall, especially artificial acid rain, after chelator application led to the increase of heavy metals in the leaching solution. EDTA increased both Cd and Pb concentrations in the leaching solution, obviously, whereas EDDS and rhamnolipid increased Cd concentration but not Pb. The amount of Cd and Pb decreased as the leaching solution increased, the patterns as well matched LRMs (linear regression models), with R-square (R 2 ) higher than 90 and 82% for Cd and Pb, respectively. The maximum cumulative Cd and Pb in the leaching solutions were 18.44 and 16.68%, respectively, which was amended by EDTA and acid rainwater (pH 4.5), and followed by EDDS (pH 4.5), EDDS (pH 6.5), rhamnolipid (0.5 g kg -1 soil, pH 4.5), and rhamnolipid (pH 6.5).

Hydrological Evaluation of TRMM Rainfall over the Upper Senegal River Basin

Directory of Open Access Journals (Sweden)

Ansoumana Bodian

2016-04-01

Full Text Available The availability of climatic data, especially on a daily time step, has become very rare in West Africa over the last few years due to the high costs of climate data monitoring. This scarcity of climatic data is a huge obstacle to conduct hydrological studies over some watersheds. In this context, our study aimed to evaluate the capacity of Tropical Rainfall Measuring Mission (TRMM satellite data to simulate the observed runoffs over the Bafing (the main important tributary of the Senegal River before their potential integration in hydrological studies. The conceptual hydrological model GR4J (modèle du Génie Rural (Agricultural Engineering Model à 4 paramètres Journalier (4 parameters Daily has been used, calibrated and validated over the 1961–1997 period with rainfall and Potential Evapotranspiration (PET as inputs. Then, the parameters that best reflect the rainfall-runoff relation, obtained during the cross-calibration-validation phase, were used to simulate runoff over the 1998–2004 period using observed and TRMM rainfalls. The findings of this study show that there is a high consistency between satellite-based estimates and ground-based observations of rainfall. Over the 1998–2004 simulation period, the two rainfall data series show quite satisfactorily results. The output hydrographs from satellite-based estimates and ground-based observations of rainfall coincide quite well with the shape of observed hydrographs with Nash-Sutcliffe Efficiency coefficient (NSE of 0.88 and 0.80 for observed rainfalls and TRMM rainfalls, respectively.

Winter cover crops as a best management practice for reducing nitrogen leaching

Science.gov (United States)

Ritter, W. F.; Scarborough, R. W.; Chirnside, A. E. M.

1998-10-01

The role of rye as a winter cover crop to reduce nitrate leaching was investigated over a three-year period on a loamy sand soil. A cover crop was planted after corn in the early fall and killed in late March or early April the following spring. No-tillage and conventional tillage systems were compared on large plots with irrigated corn. A replicated randomized block design experiment was conducted on small plots to evaluate a rye cover crop under no-tillage and conventional tillage and with commercial fertilizer, poultry manure and composted poultry manure as nitrogen fertilizer sources. Nitrogen uptake by the cover crop along with nitrate concentrations in groundwater and the soil profile (0-150 cm) were measured on the large plots. Soil nitrate concentrations and nitrogen uptake by the cover crop were measured on the small plots. There was no significant difference in nitrate concentrations in the groundwater or soil profile with and without a cover crop in either no-tillage or conventional tillage. Annual amounts of nitrate-N leached to the water-table varied from 136.0 to 190.1 kg/ha in 1989 and from 82.4 to 116.2 kg/ha in 1991. Nitrate leaching rates were somewhat lower with a cover crop in 1989, but not in 1990. There was no statistically significant difference in corn grain yields between the cover crop and non-cover crop treatments. The planting date and adequate rainfall are very important in maximizing nitrogen uptake in the fall with a rye cover crop. On the Delmarva Peninsula, the cover crop should probably be planted by October 1 to maximize nitrogen uptake rates in the fall. On loamy sand soils, rye winter cover crops cannot be counted on as a best management practice for reducing nitrate leaching in the Mid-Atlantic states.

A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

Science.gov (United States)

Negri, A. J.; Xu, L.; Adler, R. F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The development of a satellite infrared technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall in Amazonia are presented. The Convective-Stratiform. Technique, calibrated by coincident, physically retrieved rain rates from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI), is applied during January to April 1999 over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. Results compare well (a one-hour lag) with the diurnal cycle derived from Tropical Ocean-Global Atmosphere (TOGA) radar-estimated rainfall in Rondonia. The satellite estimates reveal that the convective rain constitutes, in the mean, 24% of the rain area while accounting for 67% of the rain volume. The effects of geography (rivers, lakes, coasts) and topography on the diurnal cycle of convection are examined. In particular, the Amazon River, downstream of Manaus, is shown to both enhance early morning rainfall and inhibit afternoon convection. Monthly estimates from this technique, dubbed CST/TMI, are verified over a dense rain gage network in the state of Ceara, in northeast Brazil. The CST/TMI showed a high bias equal to +33% of the gage mean, indicating that possibly the TMI estimates alone are also high. The root mean square difference (after removal of the bias) equaled 36.6% of the gage mean. The correlation coefficient was 0.77 based on 72 station-months.

How efficiently do corn- and soybean-based cropping systems use water? A systems modeling analysis.

Science.gov (United States)

Dietzel, Ranae; Liebman, Matt; Ewing, Robert; Helmers, Matt; Horton, Robert; Jarchow, Meghann; Archontoulis, Sotirios

2016-02-01

Agricultural systems are being challenged to decrease water use and increase production while climate becomes more variable and the world's population grows. Low water use efficiency is traditionally characterized by high water use relative to low grain production and usually occurs under dry conditions. However, when a cropping system fails to take advantage of available water during wet conditions, this is also an inefficiency and is often detrimental to the environment. Here, we provide a systems-level definition of water use efficiency (sWUE) that addresses both production and environmental quality goals through incorporating all major system water losses (evapotranspiration, drainage, and runoff). We extensively calibrated and tested the Agricultural Production Systems sIMulator (APSIM) using 6 years of continuous crop and soil measurements in corn- and soybean-based cropping systems in central Iowa, USA. We then used the model to determine water use, loss, and grain production in each system and calculated sWUE in years that experienced drought, flood, or historically average precipitation. Systems water use efficiency was found to be greatest during years with average precipitation. Simulation analysis using 28 years of historical precipitation data, plus the same dataset with ± 15% variation in daily precipitation, showed that in this region, 430 mm of seasonal (planting to harvesting) rainfall resulted in the optimum sWUE for corn, and 317 mm for soybean. Above these precipitation levels, the corn and soybean yields did not increase further, but the water loss from the system via runoff and drainage increased substantially, leading to a high likelihood of soil, nutrient, and pesticide movement from the field to waterways. As the Midwestern United States is predicted to experience more frequent drought and flood, inefficiency of cropping systems water use will also increase. This work provides a framework to concurrently evaluate production and

Orthology Guided Assembly in highly heterozygous crops

DEFF Research Database (Denmark)

Ruttink, Tom; Sterck, Lieven; Rohde, Antje

2013-01-01

to outbreeding crop species hamper De Bruijn Graph-based de novo assembly algorithms, causing transcript fragmentation and the redundant assembly of allelic contigs. If multiple genotypes are sequenced to study genetic diversity, primary de novo assembly is best performed per genotype to limit the level......Despite current advances in next-generation sequencing data analysis procedures, de novo assembly of a reference sequence required for SNP discovery and expression analysis is still a major challenge in genetically uncharacterized, highly heterozygous species. High levels of polymorphism inherent...... of polymorphism and avoid transcript fragmentation. Here, we propose an Orthology Guided Assembly procedure that first uses sequence similarity (tBLASTn) to proteins of a model species to select allelic and fragmented contigs from all genotypes and then performs CAP3 clustering on a gene-by-gene basis. Thus, we...

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren; Korup Andersen, Aske; Larsen, Anders Badsberg

2017-01-01

Continuous and long rainfall series are a necessity in rural and urban hydrology for analysis and design purposes. Local historical point rainfall series often cover several decades, which makes it possible to estimate rainfall means at different timescales, and to assess return periods of extreme...... includes climate changes projected to a specific future period. This paper presents a framework for resampling of historical point rainfall series in order to generate synthetic rainfall series, which has the same statistical properties as an original series. Using a number of key target predictions...... for the future climate, such as winter and summer precipitation, and representation of extreme events, the resampled historical series are projected to represent rainfall properties in a future climate. Climate-projected rainfall series are simulated by brute force randomization of model parameters, which leads...

Genetic approach to the development of crop production systems on savanna soils of the Eastern plains of Colombia

International Nuclear Information System (INIS)

Valencia R, Ruben Alfredo; Leal Monsalve, Dario

1996-01-01

The savanna region of the eastern plains of Colombia is characterized by its low fertility with reduced soil content of calcium (Ca), magnesium (Mg), potassium (K), phosphorus (P) and sulfur (S); low pH; high exchangeable aluminum (Al); high al saturation and high soil fragility, however these acid soils offer several advantages which make them ideal for sustainable agriculture, such as 1) abundant and adequate rainfall distribution from April to November, 2) flat topography, 3) good physical soil characteristics and, 4) large potential area. The eastern plains of Colombia comprise about 26 million hectares, 53% of them have good drainage and are currently under extensive cattle grazing systems with no or little technology practices and inherent low productivity. Low cost soil management technology is needed to utilize efficient/y these vast areas. Key technology components must include the identification of suitable crop species and cultivars that can tolerate al and absorb N in the presence of excess Al. Research on crop production systems to incorporate this huge area into food production has been led by ICA and CORPOICA toward the generation of crop varieties suitable to acid soil conditions and the development of adequate technology practices to preserve the ecosystem. The goal of the systemic approach is to develop sustainable technology with the participation of a multidisciplinary group

Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

Science.gov (United States)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

Science.gov (United States)

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

2018-02-01

Accurate and long-term rainfall estimates are the main inputs for several applications, from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale, and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two state-of-the-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modeled data set (ERA-Interim). A quality check is carried out on a global scale at 1° of spatial sampling and 5 days of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), root mean square difference (RMSD, median value test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.The SM2RAIN-CCI rainfall data set is freely available at https://doi.org/10.5281/zenodo.846259.

The Effect of Rainfall Patterns on the Mechanisms of Shallow Slope Failure

Directory of Open Access Journals (Sweden)

Muhammad Suradi

2014-04-01

Full Text Available This paper examines how rainfall patterns affect the mechanisms of shallow slope failure. Numerical modelling, utilising the commercial software SVFlux and SVSlope, was carried out for a coupled analysis of rainfall-induced slope seepage and instability, with reference to a shallow landslide took place in Jabiru, Northern Territory (NT Australia in 2007. Rainfall events were varied in terms of pattern in this analysis. The results revealed that slopes are sensitive to rainfall pattern when the rainfall intensity has a high degree of fluctuation at around the same value as that of saturated hydraulic conductivity. Average rainfall intensity at the beginning of a rainfall period plays a primary role in determining the rate of decrease in initial factor of safety (Fi towards minimum factor of safety (Fmin. The effect of rainfall events on the slope instability is attributed to the amount of rainwater infiltration into slope associated with rainfall pattern.

Evaluation benefits of rainwater harvesting using infiltration pits in rainfed cropping systems: Preliminary results from Rushinga district, Zimbabwe

NARCIS (Netherlands)

Nyakudya, I.W.; Stroosnijder, L.; Chimweta, M.; Nyagumbo, I.

2012-01-01

ABSTRACT Occurrence of dry spells during the rainfall season is the major cause of crop failure in semi-arid areas. Rainwater harvesting (RWH) is regarded as a viable option for mitigating these dry spells. However, benefits of most RWH systems have not been adequately quantified. The objective of

Validation and correction of rainfall data from the WegenerNet high density network in southeast Austria

Science.gov (United States)

O, Sungmin; Foelsche, U.; Kirchengast, G.; Fuchsberger, J.

2018-01-01

Eight years of daily rainfall data from WegenerNet were analyzed by comparison with data from Austrian national weather stations. WegenerNet includes 153 ground level weather stations in an area of about 15 km × 20 km in the Feldbach region in southeast Austria. Rainfall has been measured by tipping bucket gauges at 150 stations of the network since the beginning of 2007. Since rain gauge measurements are considered close to true rainfall, there are increasing needs for WegenerNet data for the validation of rainfall data products such as remote sensing based estimates or model outputs. Serving these needs, this paper aims at providing a clearer interpretation on WegenerNet rainfall data for users in hydro-meteorological communities. Five clusters - a cluster consists of one national weather station and its four closest WegenerNet stations - allowed us close comparison of datasets between the stations. Linear regression analysis and error estimation with statistical indices were conducted to quantitatively evaluate the WegenerNet daily rainfall data. It was found that rainfall data between the stations show good linear relationships with an average correlation coefficient (r) of 0.97 , while WegenerNet sensors tend to underestimate rainfall according to the regression slope (0.87). For the five clusters investigated, the bias and relative bias were - 0.97 mm d-1 and - 11.5 % on average (except data from new sensors). The average of bias and relative bias, however, could be reduced by about 80 % through a simple linear regression-slope correction, with the assumption that the underestimation in WegenerNet data was caused by systematic errors. The results from the study have been employed to improve WegenerNet data for user applications so that a new version of the data (v5) is now available at the WegenerNet data portal (www.wegenernet.org).

Critical Phenomena of Rainfall in Ecuador

Science.gov (United States)

Serrano, Sh.; Vasquez, N.; Jacome, P.; Basile, L.

2014-02-01

Self-organized criticality (SOC) is characterized by a power law behavior over complex systems like earthquakes and avalanches. We study rainfall using data of one day, 3 hours and 10 min temporal resolution from INAMHI (Instituto Nacional de Meteorologia e Hidrologia) station at Izobamba, DMQ (Metropolitan District of Quito), satellite data over Ecuador from Tropical Rainfall Measure Mission (TRMM,) and REMMAQ (Red Metropolitana de Monitoreo Atmosferico de Quito) meteorological stations over, respectively. Our results show a power law behavior of the number of rain events versus mm of rainfall measured for the high resolution case (10 min), and as the resolution decreases this behavior gets lost. This statistical property is the fingerprint of a self-organized critical process (Peter and Christensen, 2002) and may serve as a benchmark for models of precipitation based in phase transitions between water vapor and precipitation (Peter and Neeling, 2006).

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

OpenAIRE

Carolien Toté; Domingos Patricio; Hendrik Boogaard; Raymond van der Wijngaart; Elena Tarnavsky; Chris Funk

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Cl...

The Empowerment Strategy for The Food Crop Farmers in Anticipating The Climate Change

Directory of Open Access Journals (Sweden)

Efriyani Sumastuti

2015-12-01

Full Text Available In Indonesia, the climate change and the global warming like changes in the pattern and distribution of the rainfall give impacts on agricultural production at large, especially in the food crops. These also cause droughts, floods, landslides, forest fires, rising temperatures in urban areas, and rising sea levels. The above impacts are felt by the farmers because those can lead to a decrease in production even the crop failure. This research aims to develop an empowerment strategy of the food crop farmers in anticipating the climate change in Central Java. The data used is the primary data obtained through in-depth interviews with key-person and the Focus Group Discussion (FGD. The Analysis Hierarchy Process (AHP is conducted to determine the program priorities and strate gies. The result of research shows that anticipating the climate change should be synergistically conducted in four aspects: human resources, technology, institutional and production, by involving various groups in the society. Various groups can be grouped into academics, businessmen / private sectors, government and community of food crop farmers / society.

Deterministic Approach for Estimating Critical Rainfall Threshold of Rainfall-induced Landslide in Taiwan

Science.gov (United States)

Chung, Ming-Chien; Tan, Chih-Hao; Chen, Mien-Min; Su, Tai-Wei

2013-04-01

Taiwan is an active mountain belt created by the oblique collision between the northern Luzon arc and the Asian continental margin. The inherent complexities of geological nature create numerous discontinuities through rock masses and relatively steep hillside on the island. In recent years, the increase in the frequency and intensity of extreme natural events due to global warming or climate change brought significant landslides. The causes of landslides in these slopes are attributed to a number of factors. As is well known, rainfall is one of the most significant triggering factors for landslide occurrence. In general, the rainfall infiltration results in changing the suction and the moisture of soil, raising the unit weight of soil, and reducing the shear strength of soil in the colluvium of landslide. The stability of landslide is closely related to the groundwater pressure in response to rainfall infiltration, the geological and topographical conditions, and the physical and mechanical parameters. To assess the potential susceptibility to landslide, an effective modeling of rainfall-induced landslide is essential. In this paper, a deterministic approach is adopted to estimate the critical rainfall threshold of the rainfall-induced landslide. The critical rainfall threshold is defined as the accumulated rainfall while the safety factor of the slope is equal to 1.0. First, the process of deterministic approach establishes the hydrogeological conceptual model of the slope based on a series of in-situ investigations, including geological drilling, surface geological investigation, geophysical investigation, and borehole explorations. The material strength and hydraulic properties of the model were given by the field and laboratory tests. Second, the hydraulic and mechanical parameters of the model are calibrated with the long-term monitoring data. Furthermore, a two-dimensional numerical program, GeoStudio, was employed to perform the modelling practice. Finally

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

Directory of Open Access Journals (Sweden)

Carolien Toté

2015-02-01

Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

Science.gov (United States)

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

The rainfall plot: its motivation, characteristics and pitfalls.

Science.gov (United States)

Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

2017-05-18

A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

Solar Variability Controls on Rainfall in the Last Millennia: Evidence from a Highly Resolved Stalagmite Record from DeSoto Caverns (USA)

Science.gov (United States)

Aharon, P.; Lambert, W.; Hellstrom, J.

2009-12-01

Moisture transport from the Gulf of Mexico (GOM) inland has a considerable influence on both regional and continental rainfall patterns. Recent episodes of drought in the Southeastern USA exposed the vulnerability of the regional infrastructure to climate changes and gave rise to inter-state “water wars”. In order to better understand the cause of these periodic droughts and their controlling climate factors we have initiated a study of stalagmites from the DeSoto Caverns (Alabama, USA) that intersect the moisture flow from GOM. Combination of unusually high growth rates (up to 2 mm/decade), prominent dark and light seasonal layers, pristine aragonite mineralogy, precise U/Th dates acquired from mg-size samples and tight sampling (n=195) afforded generation of biannual (δ18O and δ13C of exceptional clarity spanning the last 700 yrs. The stalagmite (DSSG1) top yields isotope values (δ18O=-5.5 per-mill VPDB; δ13C=-10.1 per-mill VPDB) that are in good agreement with the predicted equilibrium isotope values. The oxygen and carbon isotope records exhibit a number of alternating negative and positive phase changes of correspond exactly with the Sun quiescence periods known as Dalton, Maunder, Spörer and Wolf Minima, and are corroborated by agreement with the positive shifts in atmospheric radiocarbon levels. Using a forward model we interpret the positive and negative δ18O and δ13C shifts during solar maxima and minima, respectively, as being primarily an expression of rapid shifts in rainfall sourced from GOM moisture and alternating between low and high rainfall intervals. The low and high rainfall intervals discerned in the stalagmite correspond to contemporaneous SST rise and fall in GOM and the Caribbean of about 1 oC amplitude. We suggest that small but measurable SST changes in the Western Hemisphere Warm Pool (WHWP), controlled by solar radiation changes between maxima and minima cycles, have a pronounced effect on the continental rainfall pattern. The

Climatic, Edaphic Factors and Cropping History Help Predict Click Beetle (Coleoptera: Elateridae) (Agriotes spp.) Abundance.

Science.gov (United States)

Kozina, A; Lemic, D; Bazok, R; Mikac, K M; Mclean, C M; Ivezić, M; Igrc Barčić, J

2015-01-01

It is assumed that the abundance of Agriotes wireworms (Coleoptera: Elateridae) is affected by agro-ecological factors such as climatic and edaphic factors and the crop/previous crop grown at the sites investigated. The aim of this study, conducted in three different geographic counties in Croatia from 2007 to 2009, was to determine the factors that influence the abundance of adult click beetle of the species Agriotes brevis Cand., Agriotes lineatus (L.), Agriotes obscurus (L.), Agriotes sputator (L.), and Agriotes ustulatus Schall. The mean annual air temperature, total rainfall, percentage of coarse and fine sand, coarse and fine silt and clay, the soil pH, and humus were investigated as potential factors that may influence abundance. Adult click beetle emergence was monitored using sex pheromone traps (YATLORf and VARb3). Exploratory data analysis was preformed via regression tree models and regional differences in Agriotes species' abundance were predicted based on the agro-ecological factors measured. It was found that the best overall predictor of A. brevis abundance was the previous crop grown. Conversely, the best predictor of A. lineatus abundance was the current crop being grown and the percentage of humus. The best predictor of A. obscurus abundance was soil pH in KCl. The best predictor of A. sputator abundance was rainfall. Finally, the best predictors of A. ustulatus abundance were soil pH in KCl and humus. These results may be useful in regional pest control programs or for predicting future outbreaks of these species. © The Author 2015. Published by Oxford University Press on behalf of the Entomological Society of America.

Soil Water Improvements with the Long Term Use of a Winter Rye Cover Crop

Science.gov (United States)

Basche, A.; Kaspar, T.; Archontoulis, S.; Jaynes, D. B.; Sauer, T. J.; Parkin, T.; Miguez, F.

2015-12-01

The Midwestern United States, a region that produces one-third of maize and one-quarter of soybeans globally, is projected to experience increasing rainfall variability with future climate change. One approach to mitigate climate impacts is to utilize crop and soil management practices that enhance soil water storage, reducing the risks of flooding and runoff as well as drought-induced crop water stress. While some research indicates that a winter cover crop in a maize-soybean rotation increases soil water, producers continue to be concerned that water use by cover crops will reduce water for a following cash crop. We analyzed continuous in-field soil moisture measurements over from 2008-2014 at a Central Iowa research site that has included a winter rye cover crop in a maize-soybean rotation for thirteen years. This period of study included years in the top third of wettest years on record (2008, 2010, 2014) as well as years in the bottom third of driest years (2012, 2013). We found the cover crop treatment to have significantly higher soil water storage from 2012-2014 when compared to the no cover crop treatment and in most years greater soil water content later in the growing season when a cover crop was present. We further found that the winter rye cover crop significantly increased the field capacity water content and plant available water compared to the no cover crop treatment. Finally, in 2012 and 2013, we measured maize and soybean biomass every 2-3 weeks and did not see treatment differences in crop growth, leaf area or nitrogen uptake. Final crop yields were not statistically different between the cover and no cover crop treatment in any of the years of this analysis. This research indicates that the long-term use of a winter rye cover crop can improve soil water dynamics without sacrificing cash crop growth.

Effect of soil warming and rainfall patterns on soil N cycling in northern Europe

DEFF Research Database (Denmark)

Patil, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

2010-01-01

. These changes may affect soil moisture regimes, soil water drainage, soil nitrogen (N) availability and N leaching to aquatic environment and N2O emissions to atmosphere. Thus it is important to study the effects of increased soil temperature and varying rainfall patterns on soil N cycling in arable land from...... temperate climates, which is a major source of N pollution. An open-field lysimeter study was carried out during 2008-2009 in Denmark on loamy sand soil (Typic Hapludult) with three factors: number of rainy days, rainfall amount and soil warming. Number of rainy days included the mean monthly rainy days...... by 5 °C at 0.1 m depth as ‘heated' and non-heated as ‘control' treatments. Automated mobile rain-out shelter and irrigation system, and insulated buried heating cables were used to impose the treatments. Soil warming, compared with unheated control, advanced winter wheat crop development, and increased...

Quantification of tillage, plant cover, and cumulative rainfall effects on soil surface microrelief by statistical, geostatistical and fractal indices

Science.gov (United States)

Paz-Ferreiro, J.; Bertol, I.; Vidal Vázquez, E.

2008-07-01

Changes in soil surface microrelief with cumulative rainfall under different tillage systems and crop cover conditions were investigated in southern Brazil. Surface cover was none (fallow) or the crop succession maize followed by oats. Tillage treatments were: 1) conventional tillage on bare soil (BS), 2) conventional tillage (CT), 3) minimum tillage (MT) and 4) no tillage (NT) under maize and oats. Measurements were taken with a manual relief meter on small rectangular grids of 0.234 and 0.156 m2, throughout growing season of maize and oats, respectively. Each data set consisted of 200 point height readings, the size of the smallest cells being 3×5 cm during maize and 2×5 cm during oats growth periods. Random Roughness (RR), Limiting Difference (LD), Limiting Slope (LS) and two fractal parameters, fractal dimension (D) and crossover length (l) were estimated from the measured microtopographic data sets. Indices describing the vertical component of soil roughness such as RR, LD and l generally decreased with cumulative rain in the BS treatment, left fallow, and in the CT and MT treatments under maize and oats canopy. However, these indices were not substantially affected by cumulative rain in the NT treatment, whose surface was protected with previous crop residues. Roughness decay from initial values was larger in the BS treatment than in CT and MT treatments. Moreover, roughness decay generally tended to be faster under maize than under oats. The RR and LD indices decreased quadratically, while the l index decreased exponentially in the tilled, BS, CT and MT treatments. Crossover length was sensitive to differences in soil roughness conditions allowing a description of microrelief decay due to rainfall in the tilled treatments, although better correlations between cumulative rainfall and the most commonly used indices RR and LD were obtained. At the studied scale, parameters l and D have been found to be useful in interpreting the configuration properties of

Long term high resolution rainfall runoff observations for improved water balance uncertainty and database QA-QC in the Walnut Gulch Experimental Watershed.

Science.gov (United States)

Bitew, M. M.; Goodrich, D. C.; Demaria, E.; Heilman, P.; Kautz, M. A.

2017-12-01

Walnut Gulch is a semi-arid environment experimental watershed and Long Term Agro-ecosystem Research (LTAR) site managed by USDA-ARS Southwest Watershed Research Center for which high-resolution long-term hydro-climatic data are available across its 150 km2 drainage area. In this study, we present the analysis of 50 years of continuous hourly rainfall data to evaluate runoff control and generation processes for improving the QA-QC plans of Walnut Gulch to create high-quality data set that is critical for reducing water balance uncertainties. Multiple linear regression models were developed to relate rainfall properties, runoff characteristics and watershed properties. The rainfall properties were summarized to event based total depth, maximum intensity, duration, the location of the storm center with respect to the outlet, and storm size normalized to watershed area. We evaluated the interaction between the runoff and rainfall and runoff as antecedent moisture condition (AMC), antecedent runoff condition (ARC) and, runoff depth and duration for each rainfall events. We summarized each of the watershed properties such as contributing area, slope, shape, channel length, stream density, channel flow area, and percent of the area of retention stock ponds for each of the nested catchments in Walnut Gulch. The evaluation of the model using basic and categorical statistics showed good predictive skill throughout the watersheds. The model produced correlation coefficients ranging from 0.4-0.94, Nash efficiency coefficients up to 0.77, and Kling-Gupta coefficients ranging from 0.4 to 0.98. The model predicted 92% of all runoff generations and 98% of no-runoff across all sub-watersheds in Walnut Gulch. The regression model also indicated good potential to complement the QA-QC procedures in place for Walnut Gulch dataset publications developed over the years since the 1960s through identification of inconsistencies in rainfall and runoff relations.

Crop insurance evaluation in response to extreme events

Science.gov (United States)

Moriondo, Marco; Ferrise, Roberto; Bindi, Marco

2013-04-01

Crop yield insurance has been indicated as a tool to manage the uncertainties of crop yields (Sherrick et al., 2004) but the changes in crop yield variability as expected in the near future should be carefully considered for a better quantitative assessment of farmer's revenue risk and insurance values in a climatic change regime (Moriondo et al., 2011). Under this point of view, mechanistic crop growth models coupled to the output of General/Regional Circulation Models (GCMs, RCMs) offer a valuable tool to evaluate crop responses to climatic change and this approach has been extensively used to describe crop yield distribution in response to climatic change considering changes in both mean climate and variability. In this work, we studied the effect of a warmer climate on crop yield distribution of durum wheat (Triticum turgidum L. subsp durum) in order to assess the economic significance of climatic change in a risk decision context. Specifically, the outputs of 6 RCMs (Tmin, Tmax, Rainfall, Global Radiation) (van der Linden and Mitchell 2009) have been statistically downscaled by a stochastic weather generator over eight sites across the Mediterranean basin and used to feed the crop growth model Sirius Quality. Three time slices were considered i) the present period PP (average of the period 1975-1990, [CO2]=350 ppm), 2020 (average of the period 2010-2030, SRES scenario A1b, [CO2]=415 ppm) and 2040 (average of the period 2030-2050, SRES scenario A1b, [CO2]=480 ppm). The effect of extreme climate events (i.e. heat stress at anthesis stage) was also considered. The outputs of these simulations were used to estimate the expected payout per hectare from insurance triggered when yields fall below a specific threshold defined as "the insured yield". For each site, the threshold was calculated as a fraction (70%) of the median of yield distribution under PP that represents the percentage of median yield above which indemnity payments are triggered. The results

Radar rainfall image repair techniques

Directory of Open Access Journals (Sweden)

Stephen M. Wesson

2004-01-01

Full Text Available There are various quality problems associated with radar rainfall data viewed in images that include ground clutter, beam blocking and anomalous propagation, to name a few. To obtain the best rainfall estimate possible, techniques for removing ground clutter (non-meteorological echoes that influence radar data quality on 2-D radar rainfall image data sets are presented here. These techniques concentrate on repairing the images in both a computationally fast and accurate manner, and are nearest neighbour techniques of two sub-types: Individual Target and Border Tracing. The contaminated data is estimated through Kriging, considered the optimal technique for the spatial interpolation of Gaussian data, where the 'screening effect' that occurs with the Kriging weighting distribution around target points is exploited to ensure computational efficiency. Matrix rank reduction techniques in combination with Singular Value Decomposition (SVD are also suggested for finding an efficient solution to the Kriging Equations which can cope with near singular systems. Rainfall estimation at ground level from radar rainfall volume scan data is of interest and importance in earth bound applications such as hydrology and agriculture. As an extension of the above, Ordinary Kriging is applied to three-dimensional radar rainfall data to estimate rainfall rate at ground level. Keywords: ground clutter, data infilling, Ordinary Kriging, nearest neighbours, Singular Value Decomposition, border tracing, computation time, ground level rainfall estimation

Thermodynamic ocean-atmosphere Coupling and the Predictability of Nordeste rainfall

Science.gov (United States)

Chang, P.; Saravanan, R.; Giannini, A.

2003-04-01

The interannual variability of rainfall in the northeastern region of Brazil, or Nordeste, is known to be very strongly correlated with sea surface temperature (SST) variability, of Atlantic and Pacific origin. For this reason the potential predictability of Nordeste rainfall is high. The current generation of state-of-the-art atmospheric models can replicate the observed rainfall variability with high skill when forced with the observed record of SST variability. The correlation between observed and modeled indices of Nordeste rainfall, in the AMIP-style integrations with two such models (NSIPP and CCM3) analyzed here, is of the order of 0.8, i.e. the models explain about 2/3 of the observed variability. Assuming that thermodynamic, ocean-atmosphere heat exchange plays the dominant role in tropical Atlantic SST variability on the seasonal to interannual time scale, we analyze its role in Nordeste rainfall predictability using an atmospheric general circulation model coupled to a slab ocean model. Predictability experiments initialized with observed December SST show that thermodynamic coupling plays a significant role in enhancing the persistence of SST anomalies, both in the tropical Pacific and in the tropical Atlantic. We show that thermodynamic coupling is sufficient to provide fairly accurate forecasts of tropical Atlantic SST in the boreal spring that are significantly better than the persistence forecasts. The consequences for the prediction of Nordeste rainfall are analyzed.

Heavy rainfall in Mediterranean cyclones. Part I: contribution of deep convection and warm conveyor belt

Science.gov (United States)

Flaounas, Emmanouil; Kotroni, Vassiliki; Lagouvardos, Konstantinos; Gray, Suzanne L.; Rysman, Jean-François; Claud, Chantal

2018-04-01

In this study, we provide an insight to the role of deep convection (DC) and the warm conveyor belt (WCB) as leading processes to Mediterranean cyclones' heavy rainfall. To this end, we use reanalysis data, lighting and satellite observations to quantify the relative contribution of DC and the WCB to cyclone rainfall, as well as to analyse the spatial and temporal variability of these processes with respect to the cyclone centre and life cycle. Results for the period 2005-2015 show that the relationship between cyclone rainfall and intensity has high variability and demonstrate that even intense cyclones may produce low rainfall amounts. However, when considering rainfall averages for cyclone intensity bins, a linear relationship was found. We focus on the 500 most intense tracked cyclones (responsible for about 40-50% of the total 11-year Mediterranean rainfall) and distinguish between the ones producing high and low rainfall amounts. DC and the WCB are found to be the main cause of rainfall for the former (producing up to 70% of cyclone rainfall), while, for the latter, DC and the WCB play a secondary role (producing up to 50% of rainfall). Further analysis showed that rainfall due to DC tends to occur close to the cyclones' centre and to their eastern sides, while the WCBs tend to produce rainfall towards the northeast. In fact, about 30% of rainfall produced by DC overlaps with rainfall produced by WCBs but this represents only about 8% of rainfall produced by WCBs. This suggests that a considerable percentage of DC is associated with embedded convection in WCBs. Finally, DC was found to be able to produce higher rain rates than WCBs, exceeding 50 mm in 3-h accumulated rainfall compared to a maximum of the order of 40 mm for WCBs. Our results demonstrate in a climatological framework the relationship between cyclone intensity and processes that lead to heavy rainfall, one of the most prominent environmental risks in the Mediterranean. Therefore, we set

Rainfall characteristics and thresholds for periglacial debris flows in the Parlung Zangbo Basin, southeast Tibetan Plateau

Science.gov (United States)

Deng, Mingfeng; Chen, Ningsheng; Ding, Haitao

2018-02-01

The Parlung Zangbo Basin in the southeastern Tibet Plateau is affected by the summer monsoon from the Indian Ocean, which produces large rainfall gradients in the basin. Rainfall data during 2012-2015 from five new meteorological stations are used to analyse the rainfall characteristics. The daily rainfall, rainfall duration, mean rainfall intensity, and peak rainfall intensity are consistent, but sometimes contrasting. For example, these values decrease with increasing altitude, and the gradient is large downstream and small upstream, respectively. Moreover, the rainfall intensity peaks between 01:00 and 06:00 and increases during the afternoon. Based on the analysis of 14 debris flow cases in the basin, differences in the rainfall threshold differ depending on the location as sediment varieties. The sediment in the middle portions of the basin is wet and well structured; thus, long-duration, high-intensity rainfall is required to generate debris flows. Ravels in the upstream area are arid and not well structured, and short-duration rainfall is required to trigger debris flows. Between the above two locations, either long-duration, low-intensity rainfall or short-duration, high-intensity rainfall could provoke debris flows. Clearly, differences in rainfall characteristics and rainfall thresholds that are associated with the location must be considered in debris flow monitoring and warnings.

Grand challenges for crop science

Science.gov (United States)

Crop science is a highly integrative science using the disciplines of conventional plant breeding, transgenic crop improvement, plant physiology, and cropping system sciences to develop improved varieties of agronomic, turf, and forage crops to produce feed, food, fuel, and fiber for our world's gro...

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

Science.gov (United States)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

Science.gov (United States)

Zorzetto, E.; Marani, M.

2017-12-01

The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

Rainfall erosivity map for Ghana

International Nuclear Information System (INIS)

Oduro Afriyie, K.

1995-10-01

Monthly rainfall data, spanning over a period of more than thirty years, were used to compute rainfall erosivity indices for various stations in Ghana, using the Fournier index, c, defined as p 2 /P, where p is the rainfall amount in the wettest month and P is the annual rainfall amount. Values of the rainfall erosivity indices ranged from 24.5 mm at Sunyani in the mid-portion of Ghana to 180.9 mm at Axim in the south western coastal portion. The indices were used to construct a rainfall erosivity map for the country. The map revealed that Ghana may be broadly divided into five major erosion risk zones. The middle sector of Ghana is generally in the low erosion risk zone; the northern sector is in the moderate to severe erosion risk zone, while the coastal sector is in the severe to extreme severe erosion risk zone. (author). 11 refs, 1 fig., 1 tab

Spatial Scaling of Global Rainfall and Flood Extremes

Science.gov (United States)

Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

2014-05-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

What rainfall events trigger landslides on the West Coast US?

Science.gov (United States)

Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

2016-04-01

A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

Science.gov (United States)

Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

2014-12-01

The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are

Do we really use rainfall observations consistent with reality in hydrological modelling?

Science.gov (United States)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

Spatial dependence of extreme rainfall

Science.gov (United States)

Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

2017-05-01

This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

Topgrass. A trial of the suitability of switchgrass and reed canary grass as biofuel crops under UK conditions. 4th interim report

Energy Technology Data Exchange (ETDEWEB)

Riche, A.B.

2004-04-01

This report summarises the results of the Topgrass project growing miscanthus, switchgrass and reed canary grass at nine UK sites and covers a one year period between the winter harvesting of the plots in 2002/3 and 2003/4. Details are given of the rainfall, air temperature and solar radiation; crop monitoring for pests, diseases and weeds; crop measurements; and a comparison of all sites. Appendices present individual site diaries and individual site operations and costs.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

Science.gov (United States)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water

The modification of the typhoon rainfall climatology model in Taiwan

Directory of Open Access Journals (Sweden)

C.-S. Lee

2013-01-01

Full Text Available This study is focused on the modification of a typhoon rainfall climatological model, by using the dataset up to 2006 and including data collected from rain gauge stations established after the 921 earthquake (1999. Subsequently, the climatology rainfall models for westward- and northward-moving typhoons are established by using the typhoon track classification from the Central Weather Bureau. These models are also evaluated and examined using dependent cases collected between 1989 and 2006 and independent cases collected from 2007 to 2011. For the dependent cases, the average total rainfall at all rain gauge stations forecasted using the climatology rainfall models for westward- (W-TRCM12 and northward-moving (N-TRCM12 typhoons is superior to that obtained using the original climatological model (TRCM06. Model W-TRCM12 significantly improves the precipitation underestimation of model TRCM06. The independent cases show that model W-TRCM12 provides better accumulated rainfall forecasts and distributions than model TRCM06. A climatological model for accompanied northeastern monsoons (A-TRCM12 for special typhoon types has also been established. The current A-TRCM12 model only contains five historical cases and various typhoon combinations can cause precipitation in different regions. Therefore, precipitation is likely to be significantly overestimated and high false alarm ratios are likely to occur in specific regions. For example, model A-TRCM12 significantly overestimates the rainfall forecast for Typhoon Mitag, an independent case from 2007. However, it has a higher probability of detection than model TRCM06. From a disaster prevention perspective, a high probability of detection is much more important than a high false alarm ratio. The modified models can contribute significantly to operational forecast.

Periods of high intensity rainfall and the safety of the Angra dos Reis nuclear power plant

International Nuclear Information System (INIS)

Nicolli, D.

1993-01-01

The high precipitation rates aggravate the consequences of hypothetical accidental releases of radioactive material from the Angra dos Reis Nuclear Power Plant (NPP), as determined by probabilistic risk assessment. A 30-year rainfall series was analysed, aiming at calculating the probability of occurring a given amount q of precipitation during a certain period of n days. The nine highest precipitation amounts have also been determined. The results show there was a rainier climate in the '50 s and '60 s than in the '70 s and '80 s. The risk of catastrophic landslide has been enhanced as an environmental impact of the construction of the Rio-Santos highway and NPP which have not yet gone through an abnormal rainfall period. It has been suggested that criteria should be established to reduce the nuclear power and shut down the reactor when the precipitation accumulates to a dangerous limit. (author)

RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM

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Celso A. G. Santos

2016-01-01

Full Text Available The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009 from a raingauge and also using daily rainfall data (1998–2013 from the Tropical Rainfall Measuring Mission (TRMM. The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256– 512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.

Quantifying rainfall-runoff relationships on the Mieso Hypo Calcic ...

African Journals Online (AJOL)

The mean annual rainfall at Mieso is 738 mm. The soil is a Hypo Calcic Vertisol with a high clay and silt content and is very susceptible to crusting. To achieve the objective of the study, rainfall-runoff measurements were made during 2003 and 2004 on 2 m x 2 m plots provided with a runoff measuring system, and replicated ...

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

Science.gov (United States)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

Lixiviação de potássio da palha de espécies de cobertura de solo de acordo com a quantidade de chuva aplicada Potassium leaching from green cover crop residues as affected by rainfall amount

Directory of Open Access Journals (Sweden)

C. A. Rosolem

2003-04-01

Full Text Available Os restos vegetais deixados na superfície do solo em sistemas de semeadura direta, além de proteger o solo da erosão, constituem considerável reserva de nutrientes que podem ser disponibilizados para a cultura principal, subseqüente. Avaliou-se a lixiviação de K da palha de seis espécies vegetais com potencial de uso como plantas para cobertura do solo de acordo com a quantidade de chuva recebida após o manejo. Milheto (Pennisetum americanum, var. BN-2, sorgo de guiné (Sorghum vulgare, aveia preta (Avena strigosa, triticale (Triticum secale, crotalária juncea (Crotalaria juncea e braquiária (Brachiaria decumbens foram cultivados em vasos com terra, em casa de vegetação, em Botucatu (SP. Aos 45 dias da emergência, as plantas foram cortadas na altura do colo, secas em estufa e submetidas a chuvas simuladas de 4,4, 8,7, 17,4, 34,9 e 69,8 mm, considerando uma quantidade de palha equivalente a 8,0 t ha-1. A máxima retenção de água pela palha corresponde a uma lâmina de até 3,0 mm, independentemente da espécie, praticamente não ocorrendo lixiviação do potássio com chuvas da ordem de 5 mm. A máxima liberação de K por unidade de chuva ocorre com lâminas de até 20 mm, decrescendo a partir deste ponto. A quantidade de K liberado da palha logo após o manejo depende da espécie vegetal, não ultrapassando, no entanto, 24 kg ha-1 com chuvas da ordem de 70 mm, apresentando correlação positiva com a concentração do nutriente no tecido vegetal. O triticale e a aveia são mais eficientes na ciclagem do potássio.Besides protecting soil from erosion, plant residues left on the soil surface by green cover crops in no-till cropping systems represent a considerable nutrient source of nutrients that can be made available for the following crop. Potassium leaching from the straw of six cover crop species was evaluated, in relation to the amount of rain on the residues. Pearl millet (Pennisetum americanum, guinea sorghum (Sorghum

Ecosystem and Community Responses to Rainfall Manipulations in Shrublands Depends on Dominant Vegetation Cover

Science.gov (United States)

Esch, E. H.; Lipson, D.; Kim, J. B.; Cleland, E. E.

2014-12-01

Southern California is predicted to face decreasing precipitation with increased interannual variability in the coming century. Native shrublands in this area are increasingly invaded by exotic annual grasses, though invasion dynamics can vary by rainfall scenario, with wet years generally associated with high invasion pressure. Interplay between rainfall and invasion scenarios can influence carbon stocks and community composition. Here we asked how invasion alters ecosystem and community responses in drought versus high rainfall scenarios, as quantified by community identity, biomass production, and the normalized difference vegetation index (NDVI). To do this, we performed a rainfall manipulation experiment with paired plots dominated either by native shrubs or exotic herbaceous species, subjected to treatments of 50%, 100%, or 150% of ambient rainfall. The study site was located in a coastal sage scrub ecosystem, with patches dominated by native shrubs and exotic grasses located in San Diego County, USA. During two growing seasons, we found that native, herbaceous biomass production was significantly affected by rainfall treatment (p<0.05 for both years), though was not affected by dominant community composition. Photosynthetic biomass production of shrub species also varied by treatment (p=0.035). Exotic biomass production showed a significant interaction between dominant community composition and rainfall treatment, and both individual effects (p<0.001 for all). NDVI showed similar results, but also indicated the importance of rainfall timing on overall biomass production between years. Community composition data showed certain species, of both native and exotic identities, segregating by treatment. These results indicate that exotic species are more sensitive to rainfall, and that increased rainfall may promote greater carbon storage in annual dominated communities when compared to shrub dominated communities in high rainfall years, but with drought, this

Organic carbon exportation in a tobacco cropped watershed

Science.gov (United States)

de Mello, N.; Merten, G.; Pontarolo, E.

2009-04-01

data was obtained by simulated rainfall, at the hillslope scale, the information assessed was the sediments movement and the carbon enrichment ratio, by the use of collectors positioned in different segments of the catena (upper, mid and down slope position). Each catchment was provided with a Parshall flume with a collecting tank to contain the runoff and sediments losses of each rainfall event. The soil management systems were conventional tillage, minimum tillage and no tillage. An area with native vegetation was also evaluated. The results were compared by regression analysis (small plots) multivariate statistical analysis (hillslope) and the set of all data was analyzed through the elaboration of bayesian network. In small plots scale, under simulated rainfall, only the no tillage, when evaluated at the end of tobacco cropping differed from the others management systems to OC exportation. The exportation was smallest then the others for all OC fractions evaluated (CAM, POC and DOC). During others stages of tobacco cropping, there was not statistical differences. In the hillslope scale it was observed that the sediments movement in conventional tillage areas was more influenced by the format of the hillside (concave or convex) that in areas under no tillage and minimum tillage. Among the areas under conventional tillage, the OC exportation rate was higher in concave areas than in convex areas. Thus, the losses of CAM and POC were higher in the areas under conventional tillage than under no tillage or minimum tillage only in the recently converted areas from native vegetation or prairies to agriculture under conventional soil management. The exportation of DOC, observed in the Parshall flumes, was always higher in the area under no tillage, followed by the native vegetation and then the conventional tillage. The conventional tillage area had a trend of concentration of DOC exportation, which tended to be higher in the period immediately after the soil mobilization

Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

Science.gov (United States)

Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.

2009-04-01

Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.

Rainfall spatiotemporal variability relation to wetlands hydroperiods

Science.gov (United States)

Serrano-Hidalgo, Carmen; Guardiola-Albert, Carolina; Fernandez-Naranjo, Nuria

2017-04-01

Doñana natural space (Southwestern Spain) is one of the largest protected wetlands in Europe. The wide marshes present in this natural space have such ecological value that this wetland has been declared a Ramsar reserve in 1982. Apart from the extensive marsh, there are also small lagoons and seasonally flooded areas which are likewise essential to maintain a wide variety of valuable habitats. Hydroperiod, the length of time each point remains flooded along an annual cycle, is a critical ecological parameter that shapes aquatic plants and animals distribution and determines available habitat for many of the living organisms in the marshes. Recently, there have been published two different works estimating the hydroperiod of Doñana lagoons with Landsat Time Series images (Cifuentes et al., 2015; Díaz-Delgado et al., 2016). In both works the flooding cycle hydroperiod in Doñana marshes reveals a flooding regime mainly driven by rainfall, evapotranspiration, topography and local hydrological management actions. The correlation found between rainfall and hydroperiod is studied differently in both works. While in one the rainfall is taken from one raingauge (Cifuentes et al., 2015), the one performed by Díaz-Delgado (2016) uses annual rainfall maps interpolated with the inverse of the distance method. The rainfall spatiotemporal variability in this area can be highly significant; however the amount of this importance has not been quantified at the moment. In the present work the geostatistical tool known as spatiotemporal variogram is used to study the rainfall spatiotemporal variability. The spacetime package implemented in R (Pebesma, 2012) facilities its computation from a high rainfall data base of more than 100 raingauges from 1950 to 2016. With the aid of these variograms the rainfall spatiotemporal variability is quantified. The principal aim of the present work is the study of the relation between the rainfall spatiotemporal variability and the

Challenges to Rainfall-Runoff and Transit Time Distribution Modeling Within the Southeastern Coastal Plain, USA

Science.gov (United States)

Decker, P.; Cohen, M. J.; Jawitz, J. W.

2017-12-01

Previous hydrologic studies primarily focus on processes related to montane catchments with significant runoff ratios, low evapotranspiration rates, and reasonably short travel times. There is a significant lack of research for hydrologic processes occurring within the United States Southeastern Coastal Plain landscape where low-relief and high rates of evapotranspiration impact water fluxes. Hydrologic modeling efforts within this region may elucidate possible interactions and timescales of solute travel where much of the landscape is managed for agricultural crops, namely plantation forestry. A long-term paired watershed study carried out in northern Florida monitored two second-order blackwater streams for five years. Rainfall-runoff models for both catchments were created using daily discharge, precipitation, and modeled evapotranspiration as input parameters. Best fit occurred (NSE = 0.8) when the catchments were modeled as two-storage (shallow and deep) reservoirs in parallel and overland flow was allowed to contribute to streamflow in periods were shallow groundwater storage was at capacity. In addition, streamflow and rainfall chloride concentrations were used to model in-variable transit time distributions using spectral methods. In both catchments this transit time was unresolvable because output spectral power exceeded input spectral power, a result assumed to be driven by the evaporative demand of the region. A modeled chloride time series from random input concentration and modeled output through the rainfall-runoff model was used to alter the evaporation ratio. Once evaporation rates equaled known rates found in cool, high-relief catchments, spectral analysis illustrated higher input spectral power and therefore resolvable transit times. Findings from this study illustrate significant effects from evaporation within the catchment - often exceeding the signal from the background catchment process itself. Calculations illustrate a proposed mean transit

Measuring urban rainfall using microwave links from commercial cellular communication networks

NARCIS (Netherlands)

Overeem, A.; Leijnse, H.; Uijlenhoet, R.

2011-01-01

The estimation of rainfall using commercial microwave links is a new and promising measurement technique. Commercial link networks cover large parts of the land surface of the earth and have a high density, particularly in urban areas. Rainfall attenuates the electromagnetic signals transmitted

How is rainfall interception in urban area affected by meteorological parameters?

Science.gov (United States)

Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

2017-04-01

Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be

Life Cycle Assessment of a Highly Diverse Vegetable Multi-Cropping System in Fengqiu County, China

Directory of Open Access Journals (Sweden)

Li Li

2018-03-01

Full Text Available Agricultural biodiversity usually leads to greater sustainability in production practices. To understand the environmental implications of the development of village-level multi-cropping in rural China, we compared the environmental impact of a highly diverse vegetable multi-cropping system to a conventional wheat/maize rotation system based on the method of life cycle assessment (LCA. Using household level cultivation data, this study examined the gate-to-gate environmental impacts of on-site cultivation practices relating to the production of 10,000 nutrient equivalent units. Results show that vegetable multi-cropping resulted in decreased average land requirement, and diesel, water and electricity usage by 69.8%, 62.2%, 71.7%, and 63.4%, respectively, while average nitrogen (Total N, phosphorus (P2O5, and potassium (K2O usage in vegetable multi-cropping systems decreased by 16.3%, 42.1%, and 75.8%, respectively. Additional corresponding effects led to a decrease in the total global warming, eutrophication, and acidification potentials from external inputs by 21.6%, 16.7%, and 16.2% of the entire system, respectively. Moreover, the midpoint human toxicity potential from pesticide usage of the vegetable multi-cropping system was lower than that of the conventional system. However, the midpoint eco-toxicity potential from pesticide usage was higher due to certain highly toxic substances, and both human and eco-toxicity potentials from heavy metals were all higher by a few orders of magnitudes. Thus, to mitigate these detrimental consequences, some related measures are proposed for sustainable practices in the future implementation of multi-cropping systems.

Dryland orchard development in southern Tamil Nadu

International Nuclear Information System (INIS)

Mohandas, S.; Marimuthu, R.; Karthikeyan, M.

2002-01-01

With low annual rainfall and high potential of evaporation in southern districts of Tamil Nadu, it is difficult to grow the crops, successfully. Drylands of this tract are vulnerable to high radiation, high temperature and variable rainfall. Hence, dryfarming has become a risky enterprise in this zone and all the above factors altogether reduce the choice of agricultural crops. Considering the magnitude of the area and it's untapped potential, which offers enormous scope for dryland horticulture in this region and thereby improving the soil productivity for other crops too

Biotech crops: imperative for achieving the millenium development goals and sustainability of agriculture in the climate change era.

Science.gov (United States)

Husaini, Amjad M; Tuteja, Narendra

2013-01-01

Biotechnological intervention in the development of crops has opened new vistas in agriculture. Central to the accomplishment of the Millennium Development Goals (MDGs), biotech-agriculture is essential in meeting these targets. Biotech crops have already made modest contributions toward ensuring food and nutrition security by reducing losses and increasing productivity, with less pesticide input. These crops could help address some of the major challenges in agriculture-based economies created by climate change. Projections of global climate change expect the concentration of greenhouse gases to increase, aridization of the environment to increase, temperature fluctuations to occur sharply and frequently, and spatial and temporal distribution of rainfall to be disturbed-all of which will increase abiotic stress-related challenges to crops. Countering these challenges and to meet the food requirement of the ever-increasing world population (expected to reach 9 billion by 2030) we need to (1) develop and use biotech crops for mitigating adverse climatic changes; (2) develop biotech crops resilient to adverse environmental conditions; and (3) address the issues/non-issues raised by NGO's and educate the masses about the benefits of biotech crops.

Mapping monthly rainfall erosivity in Europe.

Science.gov (United States)

Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

2017-02-01

Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be

Persistence Characteristics of Australian Rainfall Anomalies

Science.gov (United States)

Simmonds, Ian; Hope, Pandora

1997-05-01

Using 79 years (1913-1991) of Australian monthly precipitation data we examined the nature of the persistence of rainfall anomalies. Analyses were performed for four climate regions covering the country, as well as for the entire Australian continent. We show that rainfall over these regions has high temporal variability and that annual rainfall amounts over all five sectors vary in phase and are, with the exception of the north-west region, significantly correlated with the Southern Oscillation Index (SOI). These relationships were particularly strong during the spring season.It is demonstrated that Australian rainfall exhibits statistically significant persistence on monthly, seasonal, and (to a limited extent) annual time-scales, up to lags of 3 months and one season and 1 year. The persistence showed strong seasonal dependence, with each of the five regions showing memory out to 4 or 5 months from winter and spring. Many aspects of climate in the Australasian region are known to have undergone considerable changes about 1950. We show this to be true for persistence also; its characteristics identified for the entire record were present during the 1951--1980 period, but virtually disappeared in the previous 30-year period.Much of the seasonal distribution of rainfall persistence on monthly time-scales, particularly in the east, is due to the influence of the SOI. However, most of the persistence identified in winter and spring in the north-west is independent of the ENSO phenomenon.Rainfall anomalies following extreme dry and wet months, seasons and years (lowest and highest two deciles) persisted more than would be expected by chance. For monthly extreme events this was more marked in the winter semester for the wet events, except in the south-east region. In general, less persistence was found for the extreme seasons. Although the persistence of dry years was less than would have been expected by chance, the wet years appear to display persistence.

Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

Science.gov (United States)

Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo

2013-04-01

performed. Then hydrologic component of the runoff hydrographs, peak flows and total runoffs from the estimated rainfall and the observed rainfall are compared. The results show that hydrologic components have high fluctuations depending on storm rainfall event. Thus, it is necessary to choose appropriate radar rainfall data derived from the above radar rainfall transform formulas to analyze the runoff of radar rainfall. The simulated hydrograph by radar in the three basins of agricultural areas is more similar to the observed hydrograph than the other three basins of mountainous areas. Especially the peak flow and shape of hydrograph of the agricultural areas is much closer to the observed ones than that of mountainous areas. This result comes from the difference of radar rainfall depending on the basin elevation. Therefore we need the examination of radar rainfall transform formulas following rainfall event and runoff analysis based on basin elevation for the improvement of radar rainfall application. Acknowledgment This study was financially supported by the Construction Technology Innovation Program(08-Tech-Inovation-F01) through the Research Center of Flood Defence Technology for Next Generation in Korea Institute of Construction & Transportation Technology Evaluation and Planning(KICTEP) of Ministry of Land, Transport and Maritime Affairs(MLTM)

Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

Science.gov (United States)

Kakar, Ramesh; Adler, Robert; Smith, Eric; Starr, David OC. (Technical Monitor)

2001-01-01

Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

Rainfall Climatology over Asir Region, Saudi Arabia

Science.gov (United States)

Sharif, H.; Furl, C.; Al-Zahrani, M.

2012-04-01

Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

Crop yields response to water pressures in the Ebro basin in Spain: risk and water policy implications

Science.gov (United States)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2011-02-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro river basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

Risk of water scarcity and water policy implications for crop production in the Ebro Basin in Spain

Science.gov (United States)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2010-08-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro River Basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

Simulation of Tropical Rainfall Variability

Science.gov (United States)

Bader, J.; Latif, M.

2002-12-01

The impact of sea surface temperature (SST) - especially the role of the tropical Atlantic meridional SST gradient and the El Nino-Southern Oscillation - on precipitation is investigated with the atmospheric general circulation model ECHAM4/T42. Ensemble experiments - driven with observed SST - show that Atlantic SST has a significant influence on precipitation over West Africa and northeast Brazil. SST sensitivity experiments were performed in which the climatological SST was enhanced or decreased by one Kelvin in certain ocean areas. Changing SST in the eastern tropical Atlantic caused only significant changes along the Guinea Coast, with a positive anomaly (SSTA) increasing rainfall and a negative SSTA reducing it. The response was nearly linear. Changing SST in other ocean areas caused significant changes over West Africa, especially in the Sahel area. The response is found to be non linear, with only negative SSTA leading to significant reduction in Sahel rainfall. Also, the impact of the SSTAs from the different ocean regions was not additive with respect to the rainfall. The influence of SST on precipitation over northeast Brazil (Nordeste) was also investigated. Three experiments were performed in which the climatological SST was enhanced/decreased or decreased/enhanced by one Kelvin in the North/South Atlantic and increased by two Kelvin in the Nino3 ocean area. All experiments caused significant changes over Nordeste, with an enhanced/reduced SST gradient in the Atlantic increasing/reducing rainfall. The response was nearly linear. The main effect of the Atlantic SST gradient was a shift of the ITCZ, caused by trade wind changes. The ''El Nino'' event generates a significant reduction in Nordeste rainfall. A significant positive SLP anomaly occurs in northeast Brazil which may be associated with the descending branch of the Walker circulation. Also a significant positive SLP over the Atlantic from 30S to 10N north occurs. This results in a reduced SLP

Karst Aquifer in Qatar and its bearing on Natural Rainfall Recharge

Science.gov (United States)

Baalousha, Husam; Ackerer, Philippe

2017-04-01

Qatar is an arid country with little rainfall and high evaporation. Surface water is non-existent so aquifer is the only source of natural water. The annual long-term averages of rainfall and evaporation are 80 mm and more than 2000 mm, respectively. Despite the low rainfall and high evaporation, natural recharge from rainfall occurs at an average of approximately 50 million m3 per year. Rainfall recharge in Qatar takes in land depressions that occur all over the country. These depressions are a result of land collapse due to sinkholes and cavity in the limestone formation. In the northern part of the country, karst features occur as a result of dissolution of limestone, which leads to land depressions. Results of this study shows groundwater recharge occurs in land depression areas, especially in the northern part of the country, where surface runoff accumulates in these land depressions and recharges the aquifer. This paper was made possible by NPRP grant # [NPRP 9-030-1-008] from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the author[s]."

Projected Changes in Seasonal Mean Temperature and Rainfall (2011-2040) in Cagayan Valley, Philippines

Science.gov (United States)

Basconcillo, J. Q.; Lucero, A. J. R.; Solis, A. S.; Kanamaru, H.; Sandoval, R. S.; Bautista, E. U.

2014-12-01

Among Filipinos, a meal is most often considered incomplete without rice. There is a high regard for rice in the entire archipelago that in 2012, the country's rice production was accounted to more than 18 million tons with an equivalent harvested area of 4.7 million hectares. This means that from the 5.4 million hectares of arable land in the Philippines, 11 percent are found and being utilized for rice production in Cagayan Valley (CV). In the same year, more than 13 percent of the country's total annual rice production was produced in CV. Rice production also provides employment to 844,000 persons (out of 1.4 million persons) which suggest that occupation and livelihood in Cagayan Valley are strongly anchored in rice production. These figures outline the imaginable vulnerability of rice production in CV amidst varying issues such as land conversion, urbanization, increase in population, retention of farming households, and climate change. While all these issues are of equal importance, this paper is directed towards the understanding the projected changes in seasonal rainfall and mean temperature (2011-2040). It is envisioned by this study that a successful climate change adaptation starts with the provision of climate projections hence this paper's objective to investigate on the changes in climate patterns and extreme events. Projected changes are zonally limited to the Provinces of Cagayan, Isabela, Nueva Vizcaya, and Quirino based on the statistical downscaling of three global climate models (BCM2, CNCM3, and MPEH5) and two emission scenarios (A1B and A2). With the idea that rainfall and temperature varies with topography, the AURELHY technique was utilized in interpolating climate projections. Results obtained from the statistical downscaling showed that there will be significant climate changes from 2011-2040 in terms of rainfall and mean temperature. There are also indications of increasing frequency of extreme 24-hour rainfall and number of dry days

Physiological and Agronomic Performance of the Coffee Crop in the Context of Climate Change and Global Warming: A Review.

Science.gov (United States)

DaMatta, Fábio M; Avila, Rodrigo T; Cardoso, Amanda A; Martins, Samuel C V; Ramalho, José C

2018-05-30

Coffee is one of the most important global crops and provides a livelihood to millions of people living in developing countries. Coffee species have been described as being highly sensitive to climate change, as largely deduced from modeling studies based on predictions of rising temperatures and changing rainfall patterns. Here, we discuss the physiological responses of the coffee tree in the context of present and ongoing climate changes, including drought, heat, and light stresses, and interactions between these factors. We also summarize recent insights on the physiological and agronomic performance of coffee at elevated atmospheric CO 2 concentrations and highlight the key role of CO 2 in mitigating the harmful effects of heat stress. Evidence is shown suggesting that warming, per se, may be less harmful to coffee suitability than previously estimated, at least under the conditions of an adequate water supply. Finally, we discuss several mitigation strategies to improve crop performance in a changing world.

An assessment of crop water deficits of the plants growing on the Małopolska Upland (Poland

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Kowalczyk Agnieszka

2016-06-01

Full Text Available The problem of water scarcity is unfavourable for the economy, with the most significant water deficits felt by agriculture. In Poland water deficits in agriculture are occurring more frequently, causing losses in yield, not only in the Lowland areas but also in the Uplands. This paper presents an assessment of the water deficits at various excedance probability levels for four varieties of field crop and for soil types with various water retention capacity, which occur in the Małopolska Upland. Calculations were performed by balancing the amount of available soil water in the root zone. The study was based on the meteorological data from the Institute of Meteorology and Water Management for the years 1971–2010. Daily precipitation data from six rainfall stations: Borusowa, Igołomia, Książ Wielki, Miechów, Olewin and Sielec was utilised as well as average decadal air temperature, water vapour pressure, wind speed and sunshine hours from the meteorological station at Kraków–Balice. The water deficits at an excedance probability level of 20% fluctuated during the growing season from 5 mm (Phaeozems to 190 mm (Leptosols. In the Małopolska Upland in soils with a medium capacity to retain water (110–160 mm, water deficits have occurred even in years of average rainfall (with probability 50%. This study confirms the considerable impact of the high variability of the soil and pluvial conditions in the region on the water deficits of the field crops.

Rainfall control of debris-flow triggering in the Réal Torrent, Southern French Prealps

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Bel, Coraline; Liébault, Frédéric; Navratil, Oldrich; Eckert, Nicolas; Bellot, Hervé; Fontaine, Firmin; Laigle, Dominique

2017-08-01

This paper investigates the occurrence of debris flow due to rainfall forcing in the Réal Torrent, a very active debris flow-prone catchment in the Southern French Prealps. The study is supported by a 4-year record of flow responses and rainfall events, from three high-frequency monitoring stations equipped with geophones, flow stage sensors, digital cameras, and rain gauges measuring rainfall at 5-min intervals. The classic method of rainfall intensity-duration (ID) threshold was used, and a specific emphasis was placed on the objective identification of rainfall events, as well as on the discrimination of flow responses observed above the ID threshold. The results show that parameters used to identify rainfall events significantly affect the ID threshold and are likely to explain part of the threshold variability reported in the literature. This is especially the case regarding the minimum duration of rain interruption (MDRI) between two distinct rainfall events. In the Réal Torrent, a 3-h MDRI appears to be representative of the local rainfall regime. A systematic increase in the ID threshold with drainage area was also observed from the comparison of the three stations, as well as from the compilation of data from experimental debris-flow catchments. A logistic regression used to separate flow responses above the ID threshold, revealed that the best predictors are the 5-min maximum rainfall intensity, the 48-h antecedent rainfall, the rainfall amount and the number of days elapsed since the end of winter (used as a proxy of sediment supply). This emphasizes the critical role played by short intense rainfall sequences that are only detectable using high time-resolution rainfall records. It also highlights the significant influence of antecedent conditions and the seasonal fluctuations of sediment supply.

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China.

Science.gov (United States)

Wang, Lai; Zhong, Chonggao; Gao, Pengxiang; Xi, Weimin; Zhang, Shuoxin

2015-01-01

Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia) monoculture system (JRMS), a wheat (Triticum aestivum) monoculture system (TAMS), and a walnut-wheat alley cropping system (JTACS) over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0-40 cm soil depth. Within JTACS, the speed of the wetting front's downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world.

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China.

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Lai Wang

Full Text Available Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia monoculture system (JRMS, a wheat (Triticum aestivum monoculture system (TAMS, and a walnut-wheat alley cropping system (JTACS over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0-40 cm soil depth. Within JTACS, the speed of the wetting front's downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world.

Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

Science.gov (United States)

Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

2012-04-01

During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

Conditions for the Occurrence of Slaking and Other Disaggregation Processes under Rainfall

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Frédéric Darboux

2016-07-01

Full Text Available Under rainfall conditions, aggregates may suffer breakdown by different mechanisms. Slaking is a very efficient breakdown mechanism. However, its occurrence under rainfall conditions has not been demonstrated. Therefore, the aim of this study was to evaluate the occurrence of slaking under rain. Two soils with silt loam (SL and clay loam (CL textures were analyzed. Two classes of aggregates were utilized: 1–3 mm and 3–5 mm. The aggregates were submitted to stability tests and to high intensity (90 mm·h−1 and low intensity (28 mm·h−1 rainfalls, and different kinetic energy impacts (large and small raindrops using a rainfall simulator. The fragment size distributions were determined both after the stability tests and rainfall simulations, with the calculation of the mean weighted diameter (MWD. After the stability tests the SL presented smaller MWDs for all stability tests when compared to the CL. In both soils the lowest MWD was obtained using the fast wetting test, showing they were sensitive to slaking. For both soils and the two aggregate classes evaluated, the MWDs were recorded from the early beginning of the rainfall event under the four rainfall conditions. The occurrence of slaking in the evaluated soils was not verified under the simulated rainfall conditions studied. The early disaggregation was strongly related to the cumulative kinetic energy, advocating for the occurrence of mechanical breakdown. Because slaking requires a very high wetting rate on initially dry aggregates, it seems unlikely to occur under field conditions, except perhaps for furrow irrigation.

Parametric study on the effect of rainfall pattern to slope stability

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Hakim Sagitaningrum Fathiyah

2017-01-01

Full Text Available Landslide in Indonesia usually occurs during the rainy seasons. Previous studies showed that rainfall infiltration has a great effect on the factor of safety (FS of slopes. This research focused on the effect of rainfall pattern on the FS of unsaturated slope with different slope angle i.e.: 30°, 45°, and 60°. Three different rainfall patterns, which are normal, advanced, and delayed were considered in the analysis. The effects of low or high hydraulic conductivity of the soil are also observed. The analyses were conducted with SEEP/W for the seepage and SLOPE/W for the slope stability. It is found that the lowest FS for gentle slope is reached under the application of advanced rainfall pattern and the lowest FS for steep slope is reached under the application of delayed rainfall pattern. Reduction of FS is known to be the largest for gentle slope rather than steep slope due to negative pore water pressure reduction and the rising of ground water level. The largest FS reduction caused by rainfall was achieved for gentle slope under advanced rainfall pattern.

An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

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Margaret Wambui Kimani

2017-05-01

Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

Crop residue inventory estimates for Texas High Plains cotton

Science.gov (United States)

Interest in the use of cotton crop by-products for the production of bio-fuels and value-added products is increasing. Research documenting the availability of cotton crop by-products after machine harvest is needed. The objectives of this work were to document the total biomass production for moder...

Impacts of ridge-furrow rainfall concentration systems and mulches on corn growth and yield in the semiarid region of China.

Science.gov (United States)

Ren, Xiao-Long; Zhang, Peng; Chen, Xiao-Li; Jia, Zhi-Kuan

2016-08-01

Plastic-covered ridge-furrow farming systems for rainfall concentration (RC) improve the water availability for crops and increase the water use efficiency (WUE), thereby stabilizing high yields. In this study, we optimized the mulching patterns for RC planting to mitigate the risks of drought during crop production in semiarid agricultural areas. We conducted a 4-year field study to determine the RC effects on corn production of mulching in furrows with 8% biodegradable films (RCSB ), liquid film (RCSL ), bare furrow (RCSN ) and conventional flat (CF) farming. We found that RC significantly (P > 0.05) increased the soil moisture in the top 0-100 cm layer and the topsoil temperature (0-20 cm) during the corn-growing period. Mulching with different materials in planting furrows further improved the rain-harvesting, moisture-retaining and yield-increasing effects of RC planting. Compared with CF, the 4-year average total dry matter amount per plant for RCSB , RCSL and RCSN treatments increased by 42.1%, 30.8% and 17.2%, respectively. The grain yield increased by 59.7%, 53.4% and 32.6%, respectively. Plastic-covered ridge and furrow mulched with biodegradable film and liquid film is recommended for use in the semiarid Loess Plateau of China to alleviate the effects of drought on crop production. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh; Chowdary, Jasti S.; Srinivas, G; Gnanaseelan, C; Parekh, Anant; Attada, Raju; Rama Krishna, S S V S

2018-01-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

Science.gov (United States)

Konda, Gopinadh; Chowdary, J. S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Rama Krishna, S. S. V. S.

2018-06-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

KAUST Repository

Konda, Gopinadh

2018-05-22

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

Giving sustainable agriculture really good odds through innovative rainfall index insurance

Science.gov (United States)

Muneepeerakul, C. P.; Muneepeerakul, R.

2017-12-01

Population growth, increasing demands for food, and increasingly uncertain and limited water availability amidst competing demands for water by other users and the environment call for a novel approach to manage water in food production systems to be developed now. Tapping into broad popularity of crop insurance as a risk management intervention, we propose an innovative rainfall index insurance program as a novel systems approach that addresses water conservation in food production systems by exploiting two common currencies that tie the food production systems and others together, namely water and money. Our novel methodology allows for optimizing diverse farm and financial strategies together, revealing strategy portfolios that result in greater water use efficiency and higher incomes at a lower level of water use. Furthermore, it allows targeted interventions to achieve reduction in irrigation water, while providing financial protection to farmers against the increasing uncertainty in water availability. Not only would such a tool result in efficiently less use of water, it would also encourage diversification in farm practices, which reduces the farm's vulnerability against crop price volatility and pest or disease outbreaks and contributes to more sustainable agriculture.

Predicting watershed acidification under alternate rainfall conditions

International Nuclear Information System (INIS)

Huntington, T.G.

1996-01-01

The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, USA using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soilwater flux will result in larger increases in soil-adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distributions of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading. 29 refs., 7 figs., 4 tabs

Influence of Changing Rainfall Patterns on the Yield of Rambutan (Nephelium lappaceum L. and Selection of Genotypes in Known Drought-tolerant Fruit Species for Climate Change Adaptation

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Pablito M. Magdalita

2015-06-01

Full Text Available In fruit crop production, rainfall, water stress, temperature, and wind are key variables for success, and the present changes in rainfall patterns could affect the flowering and yield of the rambutan (Nephelium lappaceum L. Other fruit species like macopa (Syzygium samarangense, siniguelas (Spondias purpurea, and native santol or cotton fruit (Sandoricum koetjape remain productive despite extreme climatic changes. This study assessed the influence of rainfall on rambutan yield and evaluated and selected tree genotypes of known drought-tolerant fruit species. Rambutan yield in a selected farm in Calauan, Laguna, Philippines, dropped remarkably from 152.2 kg/tree in 2008 to 8.6 kg/tree in 2009. This reduction could be attributed to the high rainfall in April 2009 at 334.4 mm, and possibly other environmental factors like temperature, relative humidity, solar radiation, and strong wind. Furthermore, wet months in 2009 also inhibited the flowering of rambutan. However, a low yield obtained in 2010 at 45.5 kg/tree could be partly attributed to the very low rainfall in May 2010 at only 9.1 mm. On the other hand, in relation to changing climate, selection of tree genotypes for use as varieties in known drought- and flood-tolerant fruit species based on important fruit qualities like sweetness, juiciness, and high edible portion was done. Among 103 macopa genotypes, Mc-13, 43, and 91 were selected and the best (i.e. , Mc-13 had sweet (7.15 °Brix and crispy fruits weighing 49.44 g, creamy white (RHCC 155 A, and had high edible portion (EP, 93.22%. Among 114 siniguelas genotypes, Sg-41, 42 and 105 were selected and the best selection (i.e., Sg-41, had sweet (12.50 °Brix and juicy fruit weighing 20.42 g, ruby red (RHCC 59 A, and had high EP (83.27%. Among 101 native santol genotypes, Sn-47, 59, and 74 were selected and the best selection (i.e. , Sn-59 had relatively sweet (5.56 °Brix and juicy fruits weighing 51.96 g, maize yellow (RHCC 21 B, and had

Spatio-temporal trends of rainfall across Indian river basins

Science.gov (United States)

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

2018-04-01

Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

Rainfall Modification by Urban Areas: New Perspectives from TRMM

Science.gov (United States)

Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

2002-01-01

Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Estimating Hydrologic Fluxes, Crop Water Use, and Agricultural Land Area in China using Data Assimilation

Science.gov (United States)

Smith, Tiziana; McLaughlin, Dennis B.; Hoisungwan, Piyatida

2016-04-01

Crop production has significantly altered the terrestrial environment by changing land use and by altering the water cycle through both co-opted rainfall and surface water withdrawals. As the world's population continues to grow and individual diets become more resource-intensive, the demand for food - and the land and water necessary to produce it - will continue to increase. High-resolution quantitative data about water availability, water use, and agricultural land use are needed to develop sustainable water and agricultural planning and policies. However, existing data covering large areas with high resolution are susceptible to errors and can be physically inconsistent. China is an example of a large area where food demand is expected to increase and a lack of data clouds the resource management dialogue. Some assert that China will have insufficient land and water resources to feed itself, posing a threat to global food security if they seek to increase food imports. Others believe resources are plentiful. Without quantitative data, it is difficult to discern if these concerns are realistic or overly dramatized. This research presents a quantitative approach using data assimilation techniques to characterize hydrologic fluxes, crop water use (defined as crop evapotranspiration), and agricultural land use at 0.5 by 0.5 degree resolution and applies the methodology in China using data from around the year 2000. The approach uses the principles of water balance and of crop water requirements to assimilate existing data with a least-squares estimation technique, producing new estimates of water and land use variables that are physically consistent while minimizing differences from measured data. We argue that this technique for estimating water fluxes and agricultural land use can provide a useful basis for resource management modeling and policy, both in China and around the world.

Comparison and Evolution of Extreme Rainfall-Induced Landslides in Taiwan

Directory of Open Access Journals (Sweden)

Chunhung WU

2017-11-01

Full Text Available This study analyzed the characteristics of, and locations prone to, extreme rainfall-induced landslides in three watersheds in Taiwan, as well as the long-term evolution of landslides in the Laonong River watershed (LRW, based on multiannual landslide inventories during 2003–2014. Extreme rainfall-induced landslides were centralized beside sinuous or meandering reaches, especially those with large sediment deposition. Landslide-prone strata during extreme rainfall events were sandstone and siltstone. Large-scale landslides were likely to occur when the maximum 6-h accumulated rainfall exceeded 420 mm. All of the large-scale landslides induced by short-duration and high-intensity rainfall developed from historical small-scale landslides beside the sinuous or meandering reaches or in the source area of rivers. However, most of the large-scale landslides induced by long-duration and high-intensity rainfall were new but were still located beside sinuous or meandering reaches or near the source. The frequency density of landslides under long-duration and high-intensity rainfall was larger by one order than those under short-duration rainfall, and the β values in the landslide frequency density-area analysis ranged from 1.22 to 1.348. The number of downslope landslides was three times larger than those of midslope and upslope landslides. The extreme rainfall-induced landslides occurred in the erosion gullies upstream of the watersheds, whereas those beside rivers were downstream. Analysis of the long-term evolution of landslides in the LRW showed that the geological setting, sinuousness of reaches, and sediment yield volume determined their location and evolution. Small-scale landslides constituted 71.9–96.2% of the total cases from 2003 to 2014, and were more easily induced after Typhoon Morakot (2009. The frequency density of landslides after Morakot was greater by one order than before, with 61% to 68% of total landslides located in the

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

Science.gov (United States)

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

An assessment of the performance of global rainfall estimates without ground-based observations

Directory of Open Access Journals (Sweden)

C. Massari

2017-09-01

Full Text Available Satellite-based rainfall estimates over land have great potential for a wide range of applications, but their validation is challenging due to the scarcity of ground-based observations of rainfall in many areas of the planet. Recent studies have suggested the use of triple collocation (TC to characterize uncertainties associated with rainfall estimates by using three collocated rainfall products. However, TC requires the simultaneous availability of three products with mutually uncorrelated errors, a requirement which is difficult to satisfy with current global precipitation data sets. In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS, showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth of the aforementioned products without using a ground benchmark data set. The analysis is carried out during the period 2007–2012 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern

Pruning for crop regulation in high density guava (Psidium guajava L.) plantation

Energy Technology Data Exchange (ETDEWEB)

Thakre, M.; Lal, S.; Uniyal, S.; Goswami, A.K. Prakash. P.

2016-11-01

High density management and crop regulation are two important aspects in guava (Psidium guajava L.) production. Therefore, to find out the economic way of managing high density planting and crop regulation, the present work was carried out on 6-year-old guava trees of cv. Pant Prabhat under double-hedge row system of planting during 2009-10 and 2010-11. Seven different forms of pruning [FBT: flower bud thinning by hand, FBTT: flower bud thinning by hand followed by removal of terminal one leaf pair, RLFO: removal of leaves and flower buds by hand, retaining one leaf pair at the top, RLF: removal of all leaves and flowers by hand, OLPS: one leaf pair shoot pruning, FSP: full shoot pruning, OLPF: one leaf pair pruning of fruited shoots only] were studied along with control (C).Minimum annual increase in tree volume (6.764 m3) was recorded with the treatment OLPF, which was 2.31 times less than the control (15.682 m3). Highest yield during winter season (55.30 kg/tree) and total yield (59.87 kg/tree) was obtained from treatment OLPF. One leaf pair pruning of fruited shoots only (OLPF) was also found profitable among other treatments by recording cost:benefit ratio of 1:2.96. This treatment also recorded the highest return distributed in rainy as well as in winter season. On the basis of findings it can be concluded that one leaf pair pruning of fruited shoots only is suitable for profitable high density management as well as crop regulation of guava in farmer friendly manner. (Author)

Parametric study on the effect of rainfall pattern to slope stability

OpenAIRE

Hakim Sagitaningrum Fathiyah; Bahsan Erly

2017-01-01

Landslide in Indonesia usually occurs during the rainy seasons. Previous studies showed that rainfall infiltration has a great effect on the factor of safety (FS) of slopes. This research focused on the effect of rainfall pattern on the FS of unsaturated slope with different slope angle i.e.: 30°, 45°, and 60°. Three different rainfall patterns, which are normal, advanced, and delayed were considered in the analysis. The effects of low or high hydraulic conductivity of the soil are also obser...

Vicia narbonensis-Avena strigosa mixture, a viable alternative in rainfed cropping systems under Mediterranean conditions

Energy Technology Data Exchange (ETDEWEB)

Pedraza, V.; Perea, F.; Saavedra, M.; Fuentes, C.; Alcántara, C.

2017-07-01

The demand of vegetable protein for animal feed and the need to diversify the crop rotation in rainfed Mediterranean climates has led to study the viability as new forage crop of the Vicia narbonensis-Avena strigosa mixture. Therefore, a 3-year field trial was conducted at two different and representative locations of the area to evaluate the capacity of both species to form a balanced mixture and to define its potential for high yield and forage quality. Different seeding ratios (65:35, 50:50 and 35:65) were compared with their pure stands and the standard mixture Avena sativa-Vicia sativa (65:35). Forage mixtures establishment and growth varied according to the environmental conditions with a negative influence of a dry year 1 for legumes (<300 mm) and a wet year 2 for oats (>630 mm). However, competition ratio indicated that there were not significant differences between mixed treatments, displaying intermediate ground coverage values, dry matter yield and crude protein regarding pure stands. Higher dry matter yield than control mixture in addition to similar crude protein, acid-detergent fibre, neutral-detergent fibre and digestible dry matter values, were produced at 35:65 in dry years and 65:35 and 50:50 in rainy years with loamy and clay soils, respectively. The appropriate development of both species in the mixture at different soil and rainfall conditions, as well as a good yield often higher than control mixture and a great forage quality, confirm to the narbon bean-black oat mixture as a viable and profitable crop alternative in rainfed cropping systems under Mediterranean conditions.

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

Science.gov (United States)

Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

2017-04-01

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

Carbon isotope discrimination as a selection tool for high water use efficiency and high crop yields

International Nuclear Information System (INIS)

Kumarasinghe, K.S.; Kirda, C.; Bowen, G.D.; Zapata, F.; Awonaike, K.O.; Holmgren, E.; Arslan, A.; De Bisbal, E.C.; Mohamed, A.R.A.G.; Montenegro, A.

1996-01-01

Results of back-up research conducted at the FAO/IAEA Agriculture and Biotechnology Laboratory in support of the FAO/IAEA Co-ordinated Research Programme on the Use of Isotope Studies on Increasing and Stabilizing Plant Productivity in Low Phosphate and Semi-arid and Sub-humid Soils of the Tropics and Sub-tropics, are presented here. Neutron probe measurements confirmed the earlier reports of a strong correlation of Δ with grain yield and water use efficiency of wheat. High soil gypsum content and soil salinity, a wide spread problem in soils of arid and semi-arid climatic zones, do not interfere with the association of Δ with crop yields, provided plants are grown in similar soil water status and soil fertility level. Results of a glasshouse experiment using selected cowpea genotypes showed that Δ values measured at flowering stage positively correlated with total dry matter production and percent N 2 derived from atmosphere (%Ndfa), contributing to an earlier report from the laboratory that it may be possible to use Δ values for screening of leguminous crops for high N 2 fixation potential. 13 C isotope discrimination in the leaves of Gliricidia sepium was measured to examine if the technique could be extended to studies with trees. Results of a glasshouse experiment with 18 provenances of Gliricidia sepium showed highly significant correlations of Δ with total dry matter production, water use efficiency and total N accumulated through biological nitrogen fixation. Although the correlation of Δ with water use efficiency and dry matter yield are relatively clear and better understood, the correlation with nitrogen fixation still needs a closer examination under different environmental conditions and with different species. While 13 C isotope discrimination may be a valuable tool for identifying annual crops with high water use efficiency and high yield potential, it may be more attractive for tree species considering the long growth periods taken for trees

An artificial neural network model for rainfall forecasting in Bangkok, Thailand

Directory of Open Access Journals (Sweden)

N. Q. Hung

2009-08-01

Full Text Available This paper presents a new approach using an Artificial Neural Network technique to improve rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of hourly data from 75 rain gauge stations in the area were used to develop the ANN model. The developed ANN model is being applied for real time rainfall forecasting and flood management in Bangkok, Thailand. Aimed at providing forecasts in a near real time schedule, different network types were tested with different kinds of input information. Preliminary tests showed that a generalized feedforward ANN model using hyperbolic tangent transfer function achieved the best generalization of rainfall. Especially, the use of a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness, the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input data, advanced ANN model to apply with continuous data containing rainy and non-rainy period, allowed model to issue forecast at any moment. Additionally, forecasts by ANN model were compared to the convenient approach namely simple persistent method. Results show that ANN forecasts have superiority over the ones obtained by the persistent model. Rainfall forecasts for Bangkok from 1 to 3 h ahead were highly satisfactory. Sensitivity analysis indicated that the most important input parameter besides rainfall itself is the wet bulb temperature in forecasting rainfall.

Measuring the economic impact of climate change on major South African field crops: a Ricardian approach

Science.gov (United States)

Gbetibouo, G. A.; Hassan, R. M.

2005-07-01

This study employed a Ricardian model to measure the impact of climate change on South Africa's field crops and analysed potential future impacts of further changes in the climate. A regression of farm net revenue on climate, soil and other socio-economic variables was conducted to capture farmer-adapted responses to climate variations. The analysis was based on agricultural data for seven field crops (maize, wheat, sorghum, sugarcane, groundnut, sunflower and soybean), climate and edaphic data across 300 districts in South Africa. Results indicate that production of field crops was sensitive to marginal changes in temperature as compared to changes in precipitation. Temperature rise positively affects net revenue whereas the effect of reduction in rainfall is negative. The study also highlights the importance of season and location in dealing with climate change showing that the spatial distribution of climate change impact and consequently needed adaptations will not be uniform across the different agro-ecological regions of South Africa. Results of simulations of climate change scenarios indicate many impacts that would induce (or require) very distinct shifts in farming practices and patterns in different regions. Those include major shifts in crop calendars and growing seasons, switching between crops to the possibility of complete disappearance of some field crops from some region.

Entropy of stable seasonal rainfall distribution in Kelantan

Science.gov (United States)

Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

2017-05-01

Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

Stochastic modelling of daily rainfall sequences

NARCIS (Netherlands)

Buishand, T.A.

1977-01-01

Rainfall series of different climatic regions were analysed with the aim of generating daily rainfall sequences. A survey of the data is given in I, 1. When analysing daily rainfall sequences one must be aware of the following points:
a. Seasonality. Because of seasonal variation

Characterization of Future Caribbean Rainfall and Temperature Extremes across Rainfall Zones

Directory of Open Access Journals (Sweden)

Natalie Melissa McLean

2015-01-01

Full Text Available End-of-century changes in Caribbean climate extremes are derived from the Providing Regional Climate for Impact Studies (PRECIS regional climate model (RCM under the A2 and B2 emission scenarios across five rainfall zones. Trends in rainfall, maximum temperature, and minimum temperature extremes from the RCM are validated against meteorological stations over 1979–1989. The model displays greater skill at representing trends in consecutive wet days (CWD and extreme rainfall (R95P than consecutive dry days (CDD, wet days (R10, and maximum 5-day precipitation (RX5. Trends in warm nights, cool days, and warm days were generally well reproduced. Projections for 2071–2099 relative to 1961–1989 are obtained from the ECHAM5 driven RCM. Northern and eastern zones are projected to experience more intense rainfall under A2 and B2. There is less consensus across scenarios with respect to changes in the dry and wet spell lengths. However, there is indication that a drying trend may be manifest over zone 5 (Trinidad and northern Guyana. Changes in the extreme temperature indices generally suggest a warmer Caribbean towards the end of century across both scenarios with the strongest changes over zone 4 (eastern Caribbean.

Investigation of Rainfall-Runoff Processes and Soil Moisture Dynamics in Grassland Plots under Simulated Rainfall Conditions

Directory of Open Access Journals (Sweden)

Nana Zhao

2014-09-01

Full Text Available The characteristics of rainfall-runoff are important aspects of hydrological processes. In this study, rainfall-runoff processes and soil moisture dynamics at different soil depths and slope positions of grassland with two different row spacings (5 cm and 10 cm, respectively, referred to as R5 and R10 were analyzed, by means of a solution of rainfall simulation experiments. Bare land was also considered as a comparison. The results showed that the mechanism of runoff generation was mainly excess infiltration overland flow. The surface runoff amount of R5 plot was greater than that of R10, while the interflow amount of R10 was larger than that of R5 plot, although the differences of the subsurface runoff processes between plots R5 and R10 were little. The effects of rainfall intensity on the surface runoff were significant, but not obvious on the interflow and recession curve, which can be described as a simple exponential equation, with a fitting degree of up to 0.854–0.996. The response of soil moisture to rainfall and evapotranspiration was mainly in the 0–20 cm layer, and the response at the 40 cm layer to rainfall was slower and generally occurred after the rainfall stopped. The upper slope generally responded fastest to rainfall, and the foot of the slope was the slowest. The results presented here could provide insights into understanding the surface and subsurface runoff processes and soil moisture dynamics for grasslands in semi-arid regions.

Rainfall Stochastic models

Science.gov (United States)

Campo, M. A.; Lopez, J. J.; Rebole, J. P.

2012-04-01

This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series

Improved rainfall-runoff approach using lumped and conceptual modelling

OpenAIRE

Durán Barroso, Pablo

2016-01-01

Rainfall-runoff quantification is one of the most important tasks in both engineering and watershed management as it allows to identify, forecast and explain watershed response. The division of the rainfall depth between infiltration and runoff has a high level of complexity due to the spatial heterogeneity in real catchments and the temporal precipitation variability, which provide scale effects on the overall runoff volumes. The Natural Resources Conservation Service Curve Number (NRCS CN) ...

Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

Science.gov (United States)

Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951-2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October-December (OND) and March-May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

Radar rainfall estimation for the identification of debris-flow precipitation thresholds

Science.gov (United States)

Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

2014-05-01

Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial

Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

Science.gov (United States)

Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

2013-12-01

Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

Population fluctuation of Empoasca sp. (Hemiptera: Cicadellidae in a physic nut crop in Mato Grosso do Sul

Directory of Open Access Journals (Sweden)

Denisar Paggioli de Carvalho

2016-01-01

Full Text Available Physic nut (Jatropha curcas L. is an oilseed, semi-evergreen shrub or small tree of the Euphorbiaceae family, whose seeds contain oil that can be processed into a high quality biofuel. However, there have been reports of arthropods feeding from its leaves, including the green leafhopper Empoasca sp. (Hemiptera: Cicadellidae. The large numbers of this insect, observed in certain periods of the year in many regions of Brazil, are causing damage to the oilseed crops. This study aims at evaluating the fluctuation in green leafhopper population in a physic nut crop in Dourados, Mato Grosso do Sul, to assess possible correlations with rainfall, maximum, average and minimum temperatures. This evaluation was conducted between March 2011 and July 2012. The largest Empoasca sp. populations were recorded in May and June, 2011, and between February and May, 2012. No significant correlation was observed between the weather parameters analyzed and the fluctuation in the Hemiptera population, but there was a trend toward higher population density during the warmer and rainier months.

Connecting Digital Repeat Photography to Ecosystem Fluxes in Inland Pacific Northwest, US Cropping Systems

Science.gov (United States)

Russell, E.; Chi, J.; Waldo, S.; Pressley, S. N.; Lamb, B. K.; Pan, W.

2017-12-01

Diurnal and seasonal gas fluxes vary by crop growth stage. Digital cameras are increasingly being used to monitor inter-annual changes in vegetation phenology in a variety of ecosystems. These cameras are not designed as scientific instruments but the information they gather can add value to established measurement techniques (i.e. eddy covariance). This work combined deconstructed digital images with eddy covariance data from five agricultural sites (1 fallow, 4 cropped) in the inland Pacific Northwest, USA. The data were broken down with respect to crop stage and management activities. The fallow field highlighted the camera response to changing net radiation, illumination, and rainfall. At the cropped sites, the net ecosystem exchange, gross primary production, and evapotranspiration were correlated with the greenness and redness values derived from the images over the growing season. However, the color values do not change quickly enough to respond to day-to-day variability in the flux exchange as the two measurement types are based on different processes. The management practices and changes in phenology through the growing season were not visible within the camera data though the camera did capture the general evolution of the ecosystem fluxes.

The Crop Journal: A new scientific journal for the global crop science community

Directory of Open Access Journals (Sweden)

Jianmin Wan

2013-10-01

Full Text Available As global population increases and demands for food supplies become greater, we face great challenges in providing more products and in larger quantities from less arable land. Crop science has gained increasing importance in meeting these challenges and results of scientific research must be communicated worldwide on a regular basis. In many countries, however, crop scientists have to publish the results of their investigations in national journals with heterogeneous contents and in their native languages. As a consequence, valuable work often remains unknown to scientists elsewhere. As a big country with a large number of crop scientists, China has a wide range of climatic and ecological environments, diverse plant species and cropping systems, and different regional needs for food supplies, which justify the recent decision by the Crop Science Society of China and the Institute of Crop Science within the Chinese Academy of Agricultural Sciences, to launch a new communication channel, The Crop Journal. The goal of The Crop Journal is to meet an urgent need for a major Asia-based journal that covers the diverse fields of crop science. Our aim is to create a vital and thought-provoking journal that will highlight state-of-the-art original work and reviews by high-profile crop scientists and investigative groups throughout the world — a journal that will respond to the needs of specialists in strategic crop research. We will work with scientific and publishing colleagues worldwide, using The Plant Journal and Crop Science as models, to establish The Crop Journal as a broadly based high quality journal and a premier forum for issues in crop science. The Crop Journal will cover a wide range of topics, including crop genetics, breeding, agronomy, crop physiology, germplasm resources, grain chemistry, grain storage and processing, crop management practices, crop biotechnology, and biomathematics. The journal also encourages the submission of review

ICUD-0471 Weather radar rainfall for design of urban storm water systems

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Wright, D. B.; Nielsen, Jesper Ellerbæk

2017-01-01

Long continuous series of high-resolution radar rainfall series provides valuable information on spatial and temporal variability of rainfall, which can be used in design of urban drainage systems. In design of especially large drainage systems with complex flow patterns (and potentially surface ...

Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM for Rainfall Variability over the Pacific Slope and Coast of Ecuador

Directory of Open Access Journals (Sweden)

Bolívar Erazo

2018-02-01

Full Text Available A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC. A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC dataset, the Climatic Research Unit–University of East Anglia (CRU dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7 dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7% but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%. The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7% and CRU (102.3 and −2.3% products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event over the EPSC and specifically towards the center-south of the EPSC (Guayas basin but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

Rainfall: Features and Variations over Saudi Arabia, A Review

Directory of Open Access Journals (Sweden)

Hosny Hasanean

2015-08-01

rainfall will remain the lowest.The climate in the SA is instructed by the El Niño Southern Oscillation (ENSO and other circulations such as centers of high and low pressure, the North Atlantic Oscillation (NAO and SOI. Strength and oscillation of subtropical jet stream play a big role in pulling hot, dry air masses of SA.

Long term variations of extreme rainfall in Denmark and southern Sweden

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

2015-01-01

A high number of studies have detected changes in the observed heavy rainfall in Northern and Central Europe, all adding to the debate on anthropogenic climate change and its potential impact on rainfall extremes. However, it is equally relevant to understand natural variations on which...... the anthropogenic changes are imposed. This study identifies multi-decadal variations in daily rainfall extremes from Denmark and southern Sweden, with a recurrence level relevant for flood hazard analysis. Based on smoothed series it is concluded that the frequency of the extreme events shows both a general...

Conditional probability of intense rainfall producing high ground concentrations from radioactive plumes

International Nuclear Information System (INIS)

Wayland, J.R.

1977-03-01

The overlap of the expanding plume of radioactive material from a hypothetical nuclear accident with rainstorms over dense population areas is considered. The conditional probability of the occurrence of hot spots from intense cellular rainfall is presented

Multisite rainfall downscaling and disaggregation in a tropical urban area

Science.gov (United States)

Lu, Y.; Qin, X. S.

2014-02-01

A systematic downscaling-disaggregation study was conducted over Singapore Island, with an aim to generate high spatial and temporal resolution rainfall data under future climate-change conditions. The study consisted of two major components. The first part was to perform an inter-comparison of various alternatives of downscaling and disaggregation methods based on observed data. This included (i) single-site generalized linear model (GLM) plus K-nearest neighbor (KNN) (S-G-K) vs. multisite GLM (M-G) for spatial downscaling, (ii) HYETOS vs. KNN for single-site disaggregation, and (iii) KNN vs. MuDRain (Multivariate Rainfall Disaggregation tool) for multisite disaggregation. The results revealed that, for multisite downscaling, M-G performs better than S-G-K in covering the observed data with a lower RMSE value; for single-site disaggregation, KNN could better keep the basic statistics (i.e. standard deviation, lag-1 autocorrelation and probability of wet hour) than HYETOS; for multisite disaggregation, MuDRain outperformed KNN in fitting interstation correlations. In the second part of the study, an integrated downscaling-disaggregation framework based on M-G, KNN, and MuDRain was used to generate hourly rainfall at multiple sites. The results indicated that the downscaled and disaggregated rainfall data based on multiple ensembles from HadCM3 for the period from 1980 to 2010 could well cover the observed mean rainfall amount and extreme data, and also reasonably keep the spatial correlations both at daily and hourly timescales. The framework was also used to project future rainfall conditions under HadCM3 SRES A2 and B2 scenarios. It was indicated that the annual rainfall amount could reduce up to 5% at the end of this century, but the rainfall of wet season and extreme hourly rainfall could notably increase.

Climate protection and energy crops. Potential for greenhouse gas emission reduction through crop rotation and crop planning

International Nuclear Information System (INIS)

Eckner, Jens; Peter, Christiane; Vetter, Armin

2015-01-01

The EVA project compares nationwide energy crops and crop rotations on site-specific productivity. In addition to agronomic suitability for cultivation economic and environmental benefits and consequences are analyzed and evaluated. As part of sustainability assessment of the tested cultivation options LCAs are established. The model MiLA developed in the project uses empirical test data and site parameters to prepare the inventory balances. At selected locations different cultivation and fertilization regimes are examined comparatively. In the comparison of individual crops and crop rotation combinations cultivation of W.Triticale-GPS at the cereals favor location Dornburg causes the lowest productrelated GHG-emissions. Due to the efficient implementation of nitrogen and the substrate properties of maize is the cultivation despite high area-related emissions and N-expenses at a low level of emissions. Because of the intensity the two culture systems offer lower emissions savings potentials with high area efficiency. Extensification with perennial alfalfagrass at low nitrogen effort and adequate yield performance show low product-related emissions. Closing the nutrient cycles through a recirculation of digestates instead of using mineral fertilization has a climate-friendly effect. Adapted intensifies of processing or reduced tillage decrease diesel consumption and their related emissions.

Simulation of boreal Summer Monsoon Rainfall using CFSV2_SSiB model: sensitivity to Land Use Land Cover (LULC)

Science.gov (United States)

Chilukoti, N.; Xue, Y.

2016-12-01

The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations

Molecular, Genetic and Agronomic Approaches to Utilizing Pulses as Cover Crops and Green Manure into Cropping Systems.

Science.gov (United States)

Tani, Eleni; Abraham, Eleni; Chachalis, Demosthenis; Travlos, Ilias

2017-06-05

Cover crops constitute one of the most promising agronomic practices towards a more sustainable agriculture. Their beneficial effects on main crops, soil and environment are many and various, while risks and disadvantages may also appear. Several legumes show a high potential but further research is required in order to suggest the optimal legume cover crops for each case in terms of their productivity and ability to suppress weeds. The additional cost associated with cover crops should also be addressed and in this context the use of grain legumes such as cowpea, faba bean and pea could be of high interest. Some of the aspects of these grain legumes as far as their use as cover crops, their genetic diversity and their breeding using conventional and molecular approaches are discussed in the present review. The specific species seem to have a high potential for use as cover crops, especially if their noticeable genetic diversity is exploited and their breeding focuses on several desirable traits.

Molecular, Genetic and Agronomic Approaches to Utilizing Pulses as Cover Crops and Green Manure into Cropping Systems

Science.gov (United States)

Tani, Eleni; Abraham, Eleni; Chachalis, Demosthenis; Travlos, Ilias

2017-01-01

Cover crops constitute one of the most promising agronomic practices towards a more sustainable agriculture. Their beneficial effects on main crops, soil and environment are many and various, while risks and disadvantages may also appear. Several legumes show a high potential but further research is required in order to suggest the optimal legume cover crops for each case in terms of their productivity and ability to suppress weeds. The additional cost associated with cover crops should also be addressed and in this context the use of grain legumes such as cowpea, faba bean and pea could be of high interest. Some of the aspects of these grain legumes as far as their use as cover crops, their genetic diversity and their breeding using conventional and molecular approaches are discussed in the present review. The specific species seem to have a high potential for use as cover crops, especially if their noticeable genetic diversity is exploited and their breeding focuses on several desirable traits. PMID:28587254

Rainfall simulators - innovations seeking rainfall uniformity and automatic flow rate measurements

Science.gov (United States)

Bauer, Miroslav; Kavka, Petr; Strouhal, Luděk; Dostál, Tomáš; Krása, Josef

2016-04-01

Field rainfall simulators are used worldwide for many experimental purposes, such as runoff generation and soil erosion research. At CTU in Prague a laboratory simulator with swinging nozzles VeeJet has been operated since 2001. Since 2012 an additional terrain simulator is being used with 4 fixed FullJet 40WSQ nozzles with 2,4 m spacing and operating over two simultaneously sprinkled experimental plots sizing 8x2 and 1x1 m. In parallel to other research projects a specific problem was solved: improving rainfall spatial uniformity and overall intensity and surface runoff measurements. These fundamental variables significantly affect investigated processes as well as resulting water balance of the plot, therefore they need to be determined as accurately as possible. Although the original nozzles setting produced (commonly used) Christiansen uniformity index CU over 80 %, detailed measurements proved this index insufficient and showed many unrequired rainfall extremes within the plot. Moreover the number of rainfall intensity scenarios was limited and some of them required problematic multi-pressure operation of the water distribution system. Therefore the simulator was subjected to many substantial changes in 2015. Innovations ranged from pump intensification to control unit upgrade. As essential change was considered increase in number of nozzles to 9 in total and reducing their spacing to 1,2 m. However new uniformity measurements did not bring any significant improvement. Tested scenarios showed equal standard deviations of interpolated intensity rasters and equal or slightly lower CU index. Imperfections of sprinkling nozzles were found to be the limiting factor. Still many other benefits were brought with the new setup. Whole experimental plot 10x2 m is better covered with the rainfall while the water consumption is retained. Nozzles are triggered in triplets, which enables more rainfall intensity scenarios. Water distribution system is more stable due to

Interaction of turbine-generated turbulence with agricultural crops: Conceptual framework and preliminary results

Science.gov (United States)

Takle, E. S.; Rajewski, D. A.; Segal, M.; Elmore, R.; Hatfield, J.; Prueger, J. H.; Taylor, S. E.

2009-12-01

The US Midwest is a unique location for wind power production because wind farms in this region, unlike any other, are co-located within major agricultural production systems that are among the most highly productive in the world. Iowa has over 3,000 MW of installed power in wind farms typically consisting of 75-120 turbines positioned within agricultural fields with irregular spacing but inter-turbine distances in some cases less than 300 m. Wind turbines extract energy from the ambient flow and change mean and turbulent characteristics of wind flow over and within the crop canopy. Turbulent exchange of air from within the crop canopy regulates vertical fluxes of heat, moisture, momentum, and CO2. Changes in wind speed and turbulence structure by wind farms and isolated wind turbines will influence crop growth, productivity, and seed quality in unknown ways. For instance, enhanced vertical fluxes of heat and moisture may help cool the crop on hot summer days (beneficial) but may enhance loss of soil moisture (detrimental). Faster drying of dew from the crop in the morning reduces leaf wetness, which is a condition favoring growth of fungus, mold and toxins. Corn and soybeans typically draw down ambient CO2 levels by 15-20% during the day in the peak growing season, providing an opportunity to enhance downward fluxes of CO2 into the crop canopy by turbine-induced turbulence. Reduction of high winds and resulting leaf shredding and stalk lodging are documented positive effects of agricultural shelterbelts and may be benefits of turbines as well. Enhanced surface evaporation during fall dry-down would improve seed readiness for storage and reduce artificial drying costs. Modification of surface wind convergence/divergence patterns may enhance convection and change rainfall patterns and modify snow deposition, melting, and soil-moisture-recharge in winter. Wind machines are widely used in orchards and vineyards for avoiding killing freezes, but turbine benefits for

Harvester development for new high yielding SRC crops and markets

Energy Technology Data Exchange (ETDEWEB)

Paulson, Mark

2005-07-01

This report describes the development of harvesting equipment for short rotation cultivation (SRC) crops produced in the UK that can produce fuel to a required specification in a single pass at a cost that is profitable for the grower while minimising the cost of the product. Details are given of the manufacture and installation of new components for large crop harvesting, and production of fuel suitable for co-firing in a coal combustion system using pulverised fuel and fuel suitable for gasification. The development of the drive chain to cope with the higher yielding crops, field tests on SRC crops, and determination of the most economic harvesting system are discussed along with the remanufacture of the chipping drum, and production of market chip samples. Harvesting guidance and an economic analysis of harvesting systems are presented.

Harvester development for new high yielding SRC crops and markets

International Nuclear Information System (INIS)

Paulson, Mark

2005-01-01

This report describes the development of harvesting equipment for short rotation cultivation (SRC) crops produced in the UK that can produce fuel to a required specification in a single pass at a cost that is profitable for the grower while minimising the cost of the product. Details are given of the manufacture and installation of new components for large crop harvesting, and production of fuel suitable for co-firing in a coal combustion system using pulverised fuel and fuel suitable for gasification. The development of the drive chain to cope with the higher yielding crops, field tests on SRC crops, and determination of the most economic harvesting system are discussed along with the remanufacture of the chipping drum, and production of market chip samples. Harvesting guidance and an economic analysis of harvesting systems are presented

Combining Biophysical and Price Simulations to Assess the Economics of Long-Term Crop Rotations

OpenAIRE

Murray-Prior, Roy B.; Whish, J.; Carberry, Peter S.; Dalgleish, N.

2003-01-01

Biophysical simulation models (e.g. APSIM) using historical rainfall data are increasingly being used to provide yield and other data on crop rotations in various regions of Australia. However, to analyse the economics of these rotations it is desirable to incorporate the other main driver of profitability, price variation. Because the context was that APSIM was being used to simulate an existing trial site being monitored by a farmer group Gross Margin output was considered most appropriate....

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

Science.gov (United States)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

Applying Spatially Distributed Rainfall to a Hydrological Model in a Tropical Watershed, Manoa Watershed, in Hawaii

Science.gov (United States)

Huang, Y. F.; Tsang, Y. P.

2017-12-01

Rainfall in Hawaii is characterized with high spatial and temporal variability. In the south side of Oahu, the Manoa watershed, with an area of 11 km2, has the annual maximum rainfall of 3900mm and the minimum rainfall of 1000 mm. Despite this high spatial heterogeneity, the rain gage network seems insufficiently capture this pattern. When simulating stream flow and predicting floods with hydrological models in Hawaii, the model performance is often unsatisfactory because of inadequate representation of rainfall data. Longman et al. (in prep.) have developed the spatially distributed daily rainfall across the Hawaiian Islands by applying ordinary kriging, yet these data have not been applied to hydrological models. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the streamflow simulation by applying spatially-distributed rainfall in the Manoa watershed. We first used point daily-rainfall at Lyon Arboretum from National Center of Environmental Information (NCEI) as the uniform rainfall input. Secondly, we summarized sub-watershed mean rainfall from the daily spatial-statistical rainfall. Both rainfall data are available from 1999 to 2014. The SWAT was set up for five-year warm-up, nine-year calibration, and two-year validation. The model parameters were calibrated and validated with four U.S. Geological Survey stream gages. We compared the calibrated watershed parameters, characteristics, and assess the streamflow hydrographs from these two rainfall inputs. The differences and improvement of using spatially distributed rainfall input in SWAT were discussed. In addition to improving the model by the representation of rainfall, this study helped us having a better understanding of the watershed hydrological response in Hawaii.

Effects of Rainfall-Induced Topsoil Structure Changes on Root-Zone Moisture Regime during the Dry Period

Science.gov (United States)

Wang, Feng; Chen, Jiazhou; Lin, Lirong

2018-01-01

Rainfall erosion and subsequent intermittent drought are serious barriers for agricultural production in the subtropical red soil region of China. Although it is widely recognized that rainfall-induced soil structure degradation reduced soil water storage and water-holding capacity, the effects of variation of the rainfall-induced topsoil structure on the subsequent soil water regime during the dry period is still rarely considered. The objective of this study was to ascertain the way of rainfall-induced topsoil structure changes on the subsequent soil water regime during the dry period. In a three-year-long experiment, six practices (CK, only crop; SM, straw mulching; PAM, polyacrylamide surface application; B, contour Bahia-grass strip; SPAM, straw mulching and polyacrylamide surface application; and BPAM, contour Bahia-grass strip and polyacrylamide surface application) were conducted at an 8° farmland with planting summer maize resulting in different topsoil structure and root-zone moisture, to establish and reveal the quantitatively relationship between the factors of topsoil structure and soil drought. Rainfall erosion significantly increased the soil crust coverage, and decreased the WSA 0.25, 0-30 mm soil porosity and mean pore size. There was no significant difference during the raining stage of root-zone water storage between CK and other practices. An index of soil drought intensity ( I) and degree ( D) was established using soil water loss rate and soil drought severity. The larger value of I means a higher rate of water loss. The larger value of D means more severe drought. During the dry period, I and D were significantly higher in CK than in other practices. I and D had significantly positively correlation with the crust size and crust coverage, and negatively with WSA 0.25, 15-30 mm soil porosity and mean pore size. Among of soil structure factors, the soil porosity had the largest effect on I and D. The rainfall-induced topsoil structure changes

Can biofuel crops alleviate tribal poverty in India's drylands?

International Nuclear Information System (INIS)

Agoramoorthy, Govindasamy; Hsu, Minna J.; Chaudhary, Sunita; Shieh, Po-Chuen

2009-01-01

The on-going climate change concerns have stimulated heavy interest in biofuels, and supporters of biofuels hail that they are considered naturally carbon-neutral. Critiques on the other hand cry that the large-scale production of biofuels can not only strain agricultural resources, but also threaten future food security. People who live in the drylands of India are often faced with challenges and constraints of poverty. Foremost among the challenges are the marginal environmental conditions for agriculture, often influenced by low and erratic rainfall, frequent droughts, poor soil condition, unreliable irrigation water supply, and rural migration to urban areas in search of work. In this paper, we have analyzed a case study of community lift irrigation practiced in India and its impact in boosting agricultural productivity and enhancing local food security. The lift-irrigation model practiced in the drylands of India to grow food crops can be adopted for the expansion of biofuel crops that has the potential to eradicate poverty among farming communities if appropriate sustainable development measures are carefully implemented. (author)

Grid-cell-based crop water accounting for the famine early warning system

Science.gov (United States)

Verdin, James; Klaver, Robert

2002-06-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996-97 and 1997-98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996-97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline. Published in 2002 by John Wiley & Sons, Ltd.

Variability of rainfall over small areas

Science.gov (United States)

Runnels, R. C.

1983-01-01

A preliminary investigation was made to determine estimates of the number of raingauges needed in order to measure the variability of rainfall in time and space over small areas (approximately 40 sq miles). The literature on rainfall variability was examined and the types of empirical relationships used to relate rainfall variations to meteorological and catchment-area characteristics were considered. Relations between the coefficient of variation and areal-mean rainfall and area have been used by several investigators. These parameters seemed reasonable ones to use in any future study of rainfall variations. From a knowledge of an appropriate coefficient of variation (determined by the above-mentioned relations) the number rain gauges needed for the precise determination of areal-mean rainfall may be calculated by statistical estimation theory. The number gauges needed to measure the coefficient of variation over a 40 sq miles area, with varying degrees of error, was found to range from 264 (10% error, mean precipitation = 0.1 in) to about 2 (100% error, mean precipitation = 0.1 in).

Analysis of rainfall infiltration law in unsaturated soil slope.