Satellite remote sensing derived spatial water utilisation index (wui) for benchmarking of irrigation systems

Water Utilisation Index (WUI) defined as area irrigated per unit volume is a measure of water delivery performance and constitutes one of the important spatial performance indicators of an irrigation system. WUI also forms basis for evaluating the adequacy of seasonal irrigation supplies in an irrigation system (inverse of WUI is delta, i.e. depth of water supplied to a given irrigation unit). In the present study WUI and adequacy indicators were used in benchmarking the performance of Nagarjunasagar Left Canal Command (NSLC) in Andhra Pradesh. Optimised temporal satellite data of rabi season during the years 1990–91 and 1998–99 was used in deriving irrigated crop areas adopting hierarchical classification approach. Paddy is the predominant crop grown and cotton, chillies, sugarcane etc. are the other crops grown in the study area. Equivalent wet area (paddy crop area) was estimated using the operationally used project specific conversion factors. WUI was estimated at disaggregated level viz., distributary, irrigation block, irrigation zone level using the canal discharge data. At project level, WUI estimated to be 65 ha/MCM and 92 ha/MCM during rabi season of 1990–91 and 1998–99 years respectively. A comparison of total irrigated area and discharges corresponding to both the years indicate that irrigation service is extensive and sub optimal during 1998–99 and it is intensive and optimal in 1990–91. It was also observed that WUI is lesser in blocks of with higher Culturable Command Area (CCA) compared to the blocks of lower CCA. All the disaggregated units were ranked into various groups of different levels of water distribution performance. The study demonstrates the utility of WUI as spatial performance indicator and thus useful for benchmarking studies of irrigation command areas. The WUI together with satellite data derived spatial irrigation intensity, crop productivity constitutes important benchmarking indices in irrigation command areas.     

Assessment of Late Blight Induced Diseased Potato Crops: A Case Study for West Bengal District Using Temporal AWiFS and MODIS Data

Remote sensing technology becomes an effective and inexpensive technique for detecting disease in vegetation. In this study, an attempt has been done to discriminate healthy and late blight affected crop using remote sensing based indices such as NDVI and LSWI. NDVI and LSWI spectral profiles between healthy and late blight affected crop shows large difference. Mean difference in reflectance between two acquired dates Jan. 10 and 29, 2009 crop clusters varied from 31.28 % in red band, 7.7 % in NIR band and 6.23 % in SWIR bands in healthy crops while in late blight affected crops it is ?15.5 % in red, 44.4 % in NIR and ?14.61 % in SWIR bands. Negative percentage differences in reflectance indicate reflectance increases from Jan. 10, 2009 to Jan. 29, 2009, while positive difference indicate decrease in reflectance between the two dates. Since potato is an irrigated crop, these differences in reflectance are attributed to prevalent disease at that time. It is found that severely affected areas are Bardhman, Arambag, Bishnupur, Ghatal and Hugli taluka with crop damage areas are 4036.66, 1138.68, 2025.23, 469.15, and 380.08 ha, respectively.     

Assessing the supplementary irrigation for improving crop productivity in water stress region using spatial hydrological model

Water stress during crop cultivation due to inconsistent rainfall is a common phenomenon in maize growing area of Shanmuganadi watershed, located in the semi-arid region of southern peninsular India. The objective is to estimate the supplementary irrigation required to improve the crop productivity during water stress period. Spatial hydrological model, Soil and Water Assessment Tool, has been applied to simulate the watershed hydrology and crop growth for rabi season (October–February) considering the rainfed and irrigated scenarios. The average water stress days of rainfed maize was 60 days with yield of 1.6 t/ha. Irrigated maize with supplementary irrigation of 93–126 mm was resulted in improved yield of 3.8 t/ha with 28 water stress days. The results also suggest that supplemental irrigation can be obtained from groundwater reserves and by adopting early sowing strategy can provide opportunities for improving water productivity in rainfed farming.     

Estimation of damage to agriculture biomass due to Hudhud cyclone and carbon stock assessment in cyclone affected areas using Landsat-8

Developing countries are vulnerable to tropical cyclones due to climatic variability and the frequency and magnitude of some extreme weather and disaster events is likely to increase. Cities and towns situated along the coastal belt of Visakhapatnam district experienced severe damage because of Hudhub cyclone (12 October 2014). The main objective of this research was to identify and quantify the damage to agriculture and vegetation caused by Hudhud cyclone. In this study, landsat-8 satellite data-sets acquired before and after the cyclone have been used; image processing techniques have been carried out to assess the changes of pre- and post-cyclone condition. Economic loss of agriculture crops has been assessed using crop production loss per hectare and total economic loss for agriculture crops in the study area was calculated. Classification results and land use land cover change analysis show that 13.25% of agriculture-Kharif and 31.1% of vegetation was damaged. Crop Biomass was estimated with aid of crop conversion factor for pre- and post-cyclone conditions. Total ‘Above ground biomass’ of the agriculture crop area was estimated at 31.57 t/ha and total loss of biomass was assessed to be 4.2 t/ha. Carbon stock was found to be varying from 0.3 to 8.3 t.C/ha in specific agriculture crops. From the results, it was concluded that Hudhud has done significant damage to the rural and urban areas of Visakhapatnam. The outcome of this study can be used by decision-makers for the release of post disaster relief fund to affected areas.     

Agricultural Area Diversification and Crop Water Demand Analysis: A Remote Sensing and GIS Approach

Large scale adoption of input intensive rice–wheat cropping system in the centrally located Jalandhar district of Indian Punjab has led to over-exploitation of ground water resources, intensive use of chemical fertilizers and deterioration of soil health. To overcome these shortfalls, in the present study, agricultural area diversification plan has been generated from agricultural area and crop rotation maps derived from remote sensing data (IRS P6-AWiFS and RADARSAT ScanSAR) along with few agro-physical parameters in GIS environment. Cropping system indices (area diversity, multiple cropping and cultivated land utilization) were also worked out from remote sensing data .Analysis of remote sensing data (2004–05) revealed that rice and wheat individually remained the dominant crops, occupy 57.8% and 64.9% of total agricultural area (TAA), respectively. Therefore, in the diversified plan, it is suggested that at least 39% of the current 40% TAA under rice–wheat rotation should be replaced by other low water requiring, high value and soil enriching crops, particularly in coarse textured alluvial plain having good quality ground water zones with low annual rainfall(<700 mm). This will reduce water requirement to the tune of 15,660 cm depth while stabilizing the production and profitability by crop area diversification without further degradation of natural resources.     

Irrigation command area inventory and assessment of water requirement using IRS-1B satellite data

Monitoring the crop acreage and irrigation water requirements vis-a-vis irrigation water supplies is important to obtain a realistic view of the “irrigation potential” and “potential utilised”. Satellite data provides information on crop area and thereby net irrigation water requirements of crops. A pilot study was taken up in Mahendragarh distributary canal in Haryana State to estimate net irrigation water requirement of crops under 17 minors for kharif and rabi seasons of 1992–93 period using IRS-1B satellite geocoded FCC images. These water requirements, when analysed with canal and tubewell water supplies for crops, show largescale deficiencies in the irrigation command area.     

In-season time series analysis of Resourcesat-1 AWiFS data for estimating irrigation water requirement

AWiFS sensor on board IRS-P6 (Resourcesat-1), with its unique features—wide swath and 5-day revisit capability provides excellent opportunities to carry out in-season analysis of irrigated agriculture. The study carried out in Hirakud command area, Orissa State indicated that the progression of rice crop acreage could be mapped through analysis of time series AWiFS data set. The spectral emergence pattern of rice crop was found useful to identify the period of rice transplantation and its variability across the command area. This information, integrated with agro-meteorological data, was used to quantify 10-daily canal-wise irrigation water requirement. A comparison with field measured actual irrigation supplies indicated an overall supply adequacy of 88% and showed wide variability at lateral canal level ranging between 18% and 109%. The supply pattern also did not correspond with the chronological variations associated with crop water requirement, supplies were 15% excess during initial part of season (December and January) and were 20.1% deficit during later part of season (February to April). Rescheduling the excess supplies of the initial period could have reduced the deficit to 15% during peak season. The study has demonstrated the usefulness of AWiFS data to generate the irrigation water requirement by mid-season, subsequent to which 38% supplies were yet to be allocated. This would support the irrigation managers to reschedule the irrigation water supplies to achieve better synchronization between requirement and supply leading to improved water use efficiency.     

Application of Multi-Criteria Decision-Making in Land Evaluation of Agricultural Land Use

The present study was carried out to evaluate agricultural capability of a watershed located in Khuzestan; a province in southern Iran. It is aimed to examine the applicability of Multi Criteria Decision-Making (MCDM) methods in site selection process. Accordingly, the ecological resources of the watershed were initially identified. To specify the criteria required for agricultural land evaluation, Delphi method was applied. After selecting the criteria, they were weighted using Analytical Hierarchy Process (AHP) Method. Weighted Overlay (WO) Method was also used to overlay the map layers in the GIS environment. Afterwards, sensitivity analysis was performed using Weights Sensitivity Analysis (WSA) method to show the impressibility rate of the results against a certain changes in the inputs. The results revealed that out of 6591.2 ha of the total watershed area, 50.8 % has unsuitable potentiality while 27.32 % has a poor suitability for irrigated agriculture. It was also determined that only 6.96 % of the whole study area has a suitable potential for this purpose. Besides, the findings indicated that 23.38 % of the total watershed area is unsuitable for rain-fed farming. the results also showed that 31.78 % and 19.12 % of the entire study area has moderate and high potentials for rain-fed agriculture, respectively. In a general overview, this study could present how MCDM is effective in handling land capability studies.     

Evaluation of simulated IRS-1C WiFS data for concurrent monitoring of command areas at disaggregated level

Data of Wide Field Sensor (WiFS) to go onboard Indian Remote Sensing Satellite, IRS-1C, in December 1995, is simulated mainly from IRS IB LISS I data of Bhadra command area, Karnataka (India) during 1993–94 summer season, to evaluate its capability in concurrent monitoring of irrigated crops at disaggregated level Crop area, crop-growth profiles of homogeneous crops like paddy, as obtained from both simulated WiFS data and LISS I data are very close for almost all the distributary commands of Bhadra project Though non-paddy-crop groups could also be classified satisfactorily, the Workability with small-extent-individual crops like groundnut, garden and sugarcane is found to be less due to coarse resolution of WiFS data and hence the individual crops could not be separated out. This study proves the potential of WiFS in concurrent monitoring of fairly-large-extent irrigated crops at distributary level. The basic feasibility of WiFS had been established in an earlier work at broad level and this study demonstrates the feasibility of information extraction at distributary command level from WiFS data.     

Study of irrigation and crop water requirements and growth of two <Emphasis Type="Italic">Rabi</Emphasis> crops grown in a semi arid region using agrometeorology and remote sensing

Irrigation water requirements of wheat and mustard crops grown in Western Yamuna Canal Command area were estimated using FAO model CROPWAT with the help of agrometeorological and remote sensing data (1986–1998 and 2008). The variations in irrigation water requirements of these two crops were judged by calculating coefficient of Variations (CVs) of yearly data. Crop coefficient values were obtained through FAO (1993) method. Supervised Maximum Likelihood Classification (MXL) of IRS 1B image was done to estimate area under wheat and mustard in the canal command. Water need was calculated from amount of supply and water requirement for the whole area. Results showed that ET_crop values of both wheat and mustard varied very little over different years (CVs 4.7% and 5.6% respectively). Irrigation water requirements of both these crops were having relatively large variations (CVs 14.1% and 22.6% respectively) which were mainly because of high variations of their effective rainfall (CVs 61.1% and 69.2% respectively). In general, increase in amount of irrigation enhanced the growth performance of the wheat crop. Increase in distribution equity within soil associations slightly improved the growth performance of the wheat crop. Agro-climatic data merged with satellite image approximated the deficiency of applied irrigation amount (549.5 ha-m for wheat and 692.7 ha-m for mustard) as compared to requirement.     

National Inventory of Rabi Pulses in India Using Remotely Sensed Data

A scheme called National Food Security Mission was launched by Government of India in 2007 for wheat, rice and pulses crops. At the request of Ministry of Agriculture for monitoring intensification of pulses a project called Pulses Intensification was taken up in Rabi season 2012–2013. Reliable statistics using advanced methods is very important for variety of pulse crops. Remotely sensed data can help in pre-harvest area estimation of pulse crops. Pulses in India are grown as partly scattered and partly contiguous crop. Growth in scattered areas and poor vegetation canopy of some of the pulse crops poses a challenge in its identification and discrimination using remotely sensed data. National Inventory of Rabi pulse crops in major growing regions of northern and southern parts of India was attempted. Multi-date AWiFS data and multi-date NDVI products of AWiFS of Rabi season 2014–2015 were used to study spectral-temporal behavior of pulse crops. Pulse crops accuracies of more than 95 % was observed in contiguous areas and 50–80.77 % in scattered regions. All India area estimate of Rabi pulses for the year 2014–2015 was 8963.327 ‘000 ha.     

Deducing Rice Crop Dynamics and Cultural Types of Bangladesh Using Geospatial Techniques

Rice crop occupies an important aspect of food security and also contributes to global warming via GHGs emission. Characterizing rice crop using spatial technologies holds the key for addressing issues of global warming and food security as different rice ecosystems respond differently to the changed climatic conditions. Remote sensing has become an important tool for assessing seasonal vegetation dynamics at regional and global scale. Bangladesh is one of the major rice growing countries in South Asia. In present study we have used remote sensing data along with GIS and ancillary map inputs in combination to derive seasonal rice maps, rice phenology and rice cultural types of Bangladesh. The SPOT VGT S10 NDVI data spanning Aus, Aman and Boro crop season (1^st May 2008 to 30^th April 2009) were used, first for generating the non-agriculture mask through ISODATA clustering and then to generate seasonal rice maps during second classification. The spectral rice profiles were modelled and phenological parameters were derived. NDVI growth profiles were modelled and crop calendar was derived. To segregate the rice cultural types of Bangladesh into IPCC rice categories, we used elevation, irrigated area, interpolated rainfall maps and flood map through logical modelling in GIS. The results indicated that the remote sensing derived rice area was 9.99 million ha as against the reported area of 11.28 million ha. The wet and dry seasons accounted for 64% and 36 % of the rice area, respectively. The flood prone, drought prone and deep water categories account for 7.5%, 5.56% and 2.03%, respectively. The novelty of current findings lies in the spatial outcome in form of seasonal and rice cultural type maps of Bangladesh which are helpful for variety of applications.     

Regional-scale monitoring of cropland intensity and productivity with multi-source satellite image time series

In the context of growing populations and limited resources, the sustainable intensification of agricultural production is of great importance to achieve food security. As the need to support management at a range of spatial scales grows, decision-support tools appear increasingly important to enable the timely and regular assessment of agricultural production over large areas and identify priorities for improving crop production in low-productivity regions. Understanding productivity patterns requires the timely provision of gapless, spatial information about agricultural productivity. In this study, dense 30-m time series covering the 2004–2014 period were generated from Landsat and MODerate-resolution Imaging Spectroradiometer (MODIS) satellite images over the irrigated cropped area of the Fergana Valley, Central Asia. A light-use efficiency model was combined with machine learning classifiers to assess the crop yield at the field level. The classification accuracy of land cover maps reached 91% on average. Crop yield and acreage estimates were in good agreement (R² = 0.812 and 0.871, respectively) with reported yields and acreages at the district level. Several indicators of cropland intensity and productivity were derived on a per-field basis and used to highlight homogeneous regions in terms of productivity by means of clustering. Results underlined that regions with lower water-use efficiency were not only located further away from irrigation canals and intake points, but also had limited access to markets and roads. The results underline that yield could be increased by roughly 1.0 and 1.4 t/ha for cotton and wheat, respectively, if the access to water would be optimized in some of the regions. The minimum calibration requirement of the method and the fusion of multi-sensor data are keys to cope with the constraints of operational crop monitoring and guarantee a sustained and timely delivery of the agricultural indicators to the user community. The results of this study can form the baseline to support regional land- and water-resource management.     

Delineation and characterization of waterlogging and salt affected areas in a canal irrigated semiarid region of north west India

Indian Remote Sensing (IRS) Linear Imaging Self Scanning (LISS II) data are interpreted, followed by ground verification facilitated identification of waterlogged areas (ponded water), salt affected soils (salt efflorescence) and high water table zones (potential waterlogging zones) in the Indira Gandhi Nahar Pariyojona (IGNP) command area (India). The false colour composites (bands 4, 3, 2) for February 1996, November 1996 and June 1998 on 1:50 000 scale revealed occurrence and seasonal dynamics of permanent waterlogging in low-lying flats and depressions. The extent of waterlogging was higher in February 1996 due to less evaporation and more agricultural operation during the period. Salt accumulation was higher in November 1996 due to freshly precipitated seasonal salts. Seepage and accumulation of excess irrigation water through coarse sandy mass was primarily responsible for the development of waterlogging in the irrigated zone. The capillary rise of soluble salts with a rising water table and high evaporative demand caused secondary soil salinization. A ground truth study found areas with a high water table (<1.5 m) with patchy crop stands and a potentially sensitive zone with a fluctuating (1.5–6.0 m) water table with poor vegetative growth. The soil characteristics showed moderate to high soil salinity in the control section of soil profiles. These were characterized by medium to coarse texture, weak to moderately strong structure, weak consistency, low organic matter content and the presence of abundant CaCO₃ nodules. The composition of saturated soil paste showed a preponderance of chlorides and sulphates of sodium, calcium and magnesium. The presence of fine texture and calcium carbonate layers at a depth below the surface caused the development of a perched water table indicating unsuitability for traditional irrigated agriculture. The quality of pond water was extremely poor and unfit for reuse. The ground water was saline in some areas but normally lies within the prescribed limit. The quality of drainage water was poor in saline depressions and unsuitable for reuse but moderate in other areas suggesting its safe reuse when mixed with good quality water. Suitable soil and water management practices were necessary for sustainable crop production in the command area.     

Feasible conversion degree of dryland to paddy field in Jinxian County,Jiangxi province,China

The purpose of this paper was to evaluate the feasibility of conversion from dryland to paddy field in Jinxian County under the water resources constraint and dryland suitability condition. We constructed a water resources balance model to evaluate irrigation needs and a dryland suitability model that coupled various spatial data layers. Our research showed that under the water resources constraint, the amount of conversion from dryland to paddy field was 26,971.69 ha and the feasible conversion degree of dryland to paddy field was 0.84, while under the dryland suitability condition, it was 23,262.74 ha and 0.72, respectively. According to the principle of maximum constraint, we conclude that the feasible conversion degree of dryland to paddy field was 0.72. This research can provide an objective and scientific basis for carrying out a programme of farmland conversion in counties of China as well as similar areas worldwide.     

Assessing gaps in irrigated agricultural productivity through satellite earth observations—A case study of the Fergana Valley,Central Asia

Improving crop area and/or crop yields in agricultural regions is one of the foremost scientific challenges for the next decades. This is especially true in irrigated areas because sustainable intensification of irrigated crop production is virtually the sole means to enhance food supply and contribute to meeting food demands of a growing population. Yet, irrigated crop production worldwide is suffering from soil degradation and salinity, reduced soil fertility, and water scarcity rendering the performance of irrigation schemes often below potential. On the other hand, the scope for improving irrigated agricultural productivity remains obscure also due to the lack of spatial data on agricultural production (e.g. crop acreage and yield). To fill this gap, satellite earth observations and a replicable methodology were used to estimate crop yields at the field level for the period 2010/2014 in the Fergana Valley, Central Asia, to understand the response of agricultural productivity to factors related to the irrigation and drainage infrastructure and environment. The results showed that cropping pattern, i.e. the presence or absence of multi-annual crop rotations, and spatial diversity of crops had the most persistent effects on crop yields across observation years suggesting the need for introducing sustainable cropping systems. On the other hand, areas with a lower crop diversity or abundance of crop rotation tended to have lower crop yields, with differences of partly more than one t/ha yield. It is argued that factors related to the infrastructure, for example, the distance of farms to the next settlement or the density of roads, had a persistent effect on crop yield dynamics over time. The improvement potential of cotton and wheat yields were estimated at 5%, compared to crop yields of farms in the direct vicinity of settlements or roads. In this study it is highlighted how remotely sensed estimates of crop production in combination with geospatial technologies provide a unique perspective that, when combined with field surveys, can support planners to identify management priorities for improving regional production and/or reducing environmental impacts.     

Global rain-fed,irrigated, and paddy croplands: A new high resolution map derived from remote sensing,crop inventories and climate data

Irrigation accounts for 70% of global water use by humans and 33–40% of global food production comes from irrigated croplands. Accurate and timely information related to global irrigation is therefore needed to manage increasingly scarce water resources and to improve food security in the face of yield gaps, climate change and extreme events such as droughts, floods, and heat waves. Unfortunately, this information is not available for many regions of the world. This study aims to improve characterization of global rain-fed, irrigated and paddy croplands by integrating information from national and sub-national surveys, remote sensing, and gridded climate data sets. To achieve this goal, we used supervised classification of remote sensing, climate, and agricultural inventory data to generate a global map of irrigated, rain-fed, and paddy croplands. We estimate that 314 million hectares (Mha) worldwide were irrigated circa 2005. This includes 66 Mha of irrigated paddy cropland and 249 Mha of irrigated non-paddy cropland. Additionally, we estimate that 1047 Mha of cropland are managed under rain-fed conditions, including 63 Mha of rain-fed paddy cropland and 985 Mha of rain-fed non-paddy cropland. More generally, our results show that global mapping of irrigated, rain-fed, and paddy croplands is possible by combining information from multiple data sources. However, regions with rapidly changing irrigation or complex mixtures of irrigated and non-irrigated crops present significant challenges and require more and better data to support high quality mapping of irrigation.     

Geospatial Approach in Assessing Agro-Climatic Suitability of Soybean in Rainfed Agro-Ecosystem

The present study demonstrated the methodology to assess agro-climatic suitability of the soybean crop through integration of crop suitability based on FAO framework of land evaluation and biophysical (water limited) yield potential in the rainfed agro-ecosystem. A long term climatic database (1980–2003) was prepared to compute decadal rainfall and temperature variations of 13 IMD stations in part of Madhya Pradesh state. The climatic database was used in soil water balance software–BUDGET to compute crop specific length of growing period (LGP) and biophysical production potential such as water limited crop yield potential of each soil types for soybean crop. Water limited crop yield potential of soils were found to be varied from 33 to 100 and LGP ranged from 65 to 180 days in the area. FAO based land suitability was analyzed in association with the water limited yield potential for better appraisal of land potential and assess their suitability in rainfed area. FAO based land suitability indicated 2.45 % area as highly suitable and 57.49 % area as moderately suitable. However, integration of water limited crop yield potential with FAO based land suitability lead to agro-climatic suitability analysis indicated 17.60 % and 40.03 % area, respectively as highly suitable and moderately suitable. FAO based land evaluation showed 88.13 % of plains as moderately suitable whereas agro-climatic suitability indicated only 47.79 %. Agro-climatic suitability analysis revealed undulating plateau and undulating plains as most suitable for soybean crop.     

Geostatistical and visualization analysis of crop suitability for diversification in sub-mountain area of Punjab,North-West India

This study presents a Geographic Information System (GIS)-based geostatistical and visualization analysis of crop suitability in two blocks of sub-mountain area of Punjab under diversification programme. It combines the limitation approach of land capability classification, productivity potential evaluation procedure and crop suitability evaluation framework of FAO. Two blocks from the sub mountain Siwalik region of Punjab viz., Mahalpur and Garhshankar were selected. This study evaluates the capabilities of the study area for traditional crops like wheat, paddy and maize, and recently introduced crops like sugarcane, sunflower, pea, rapeseed-mustard, potatoes and kinnow for agricultural diversification. The suitability of the crops has been worked out at the village level. About 35–40 per cent of total area mostly in Siwallik hills is not fit for growing any type of crop. Sandy texture, uneven topography, moderately steep slopes and excessive drainage are responsible for unsuitability of this area. The GIS based suitability analysis for traditional crops as well as for new crops, under diversification of agriculture has been undertaken. The geostatistical analysis points towards suitability of relatively large areas for new crops like sunflower, potato, pea (green) and sugarcane. Forty three and 14 per cent of total area has been found highly suitable and suitable respectively for growing green pea - a cash crop. Thirty three per cent of total area is suitable for growing kinnow fruit. The success of diversification programme is subject to logical government policy in terms of providing cold storage, food processing facility and marketing infrastructure.     

A simple assessment approach for winter wheat loss risk impacted by water stress

In this study, an empirical assessment approach for the risk of crop loss due to water stress was developed and used to evaluate the risk of winter wheat loss in China, the United States, Germany, France and the United Kingdom. We combined statistical and remote sensing data on crop yields with climate data and cropland distribution to model the effect of water stress from 1982 to 2011. The average value of winter wheat loss due to water stress for the three European countries was about ?931 kg/ha, which was higher than that in China (?570 kg/ha) and the United States (?367 kg/ha). Our study has important implications for the operational assessment of crop loss risk at a country or regional scale. Future studies should focus on using higher spatial resolution remote sensing data, combining actual evapotranspiration to estimate water stress, improving the method for downscaling of statistical crop yield data and establishing more sophisticated zoning methods.