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Remote sensing and Geographical Information System (GIS) techniques were used to estimate actual crop evapotranspiration of wheat crop grown in Tarafeni South Main Canal (TSMC) irrigation command of West Bengal State in India. The area under wheat crop was clipped from landuse/land cover map generated from Indian Remote Sensing Satellite P6 (IRS P6) image of January, 2004 for winter season 2003-04. The IRS P6 image and four wide field sensor (WiFS) images for different months of winter season were used to determine the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) for area under wheat crop. The relationship between vegetation indices and crop coefficients (K c ) of wheat for corresponding months were developed. Based on these developed regression equations crop coefficient maps were generated for each month of wheat crop season. Monthly reference crop evapotranspiration (ETo) was estimated based on FAO-56, Penman-Monteith method. ETo was combined with spatially distributed K c maps of different months of wheat crop season to generate crop evapotranspiration (ET c ) maps of each month. The crop water demand of wheat estimated using spatially distributed ET c maps for months of

Crop yield estimation has an important role on economy development and its accuracy and speed influence yield price and helps in deciding the excess or deficit production conditions. The water productivity evaluates the irrigation command through water use efficiency (WUE). Remote sensing (RS) and geographical information system (GIS) techniques were used for crop yield and water productivity estimation of wheat crop (Triticum aestivum) grown in Tarafeni South Main Canal (TSMC) irrigation command of West Bengal State in India. One IRS P6 image and four wide field sensor (WiFS) images for different months of winter season were used to determine the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) for area under wheat crop. The temporally and spatially distributed spectral growth profile and AREASUM of NDVI (A NDVI ) and SAVI (A SAVI ) with time after sowing of wheat crop were developed and correlated with actual crop yield of wheat (Y act ). The developed relationships between A SAVI and Y act resulted high correlation in comparison to that of A NDVI . Using the developed model the RS based wheat yield (Y RS ) predicted from A SAVI varied on entire TSMC irrigation command from 22.67 to 33.13 q ha −1 respectively, which gave an average yield of 26.50 q ha −1 . The RS generated yield based water use efficiency (WUE YRS ) for water supplied from canal of TSMC irrigation command was found to be 6.69 kgha −1 mm −1 .

It is possible to plan suitable measures to mitigate the ill effects of droughts if the severity, recurrence interval, and frequency of droughts can be estimated efficiently. The present study was conducted to assess the drought proneness of various districts of the Saurashtra region of Gujarat state (India) by developing the drought severity–duration–frequency (DSDF) curves using the Standardized precipitation evapotranspiration index (SPEI) using rainfall and temperature data of 40 years (1980–2019) of 36 stations. The drought severities for various return periods ranging from 2 to 100 years were estimated using the best-fit probability distributions to derive district-wise DSDF curves for various districts for durations of 1–4 months. The results revealed that severe droughts are expected to occur once in 29–44 years for various districts of Saurashtra. The districts were ranked based on criteria such as proneness to higher severities for longer drought durations, high severities with short drought duration, and low severities with long drought duration. The finding of the study and DSDF curves can serve as a convenient tool for risk assessment, planning various crop cultivation and irrigation interventions, preparedness, and mitigation against droughts.

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