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Assessment of erosion status of a watershed is an essential prerequisite of integrated watershed management. This not only assists in chalking out suitable soil and water conservation measures to arrest erosion and conserve water but also helps in devising best management practices to enhance biomass production in watersheds. The geologic stages of development and erosion proneness of the watersheds are quantified by hypsometric integral. The estimation of hypsometric integral is carried out from the graphical plot of the measured contour elevation and encompassed area and by using empirical formulae. In this study, efforts were made to estimate the hypsometric integral values of the Sainj and Tirthan watersheds and their sub watersheds in the Lesser Himalayas using four different techniques, and to compare the procedural techniques of its estimation and relevance on erosion status. It was revealed that the hypsometric integral calculated by elevation-relief ratio method was accurate, less cumbersome and easy to calculate within GIS environment. Also comparison of these hypsometric integral values revealed that the Sainj watershed (0.51) was more prone to erosion than the Tirthan watershed (0.41). Further, the validation of these results with the recorded sediment yield data of 24 years corroborated that the average annual sediment yield during this period for Sainj watershed (0.53 Mt) was more than that of the Tirthan watershed (0.3 Mt). Thus, the hypsometric integral value can be used as an estimator of erosion status of watersheds leading to watershed prioritization for taking up soil and water conservation measures in watershed systems.

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The groundwater quantity and quality scenario is of much concern in the National Capital Territory of Delhi, India, which necessitates an investigation to envisage the extent of spatial variability of groundwater depth and pollutant concentration levels in this region. Therefore, in this study, an effort was made to generate the spatial variability map of groundwater depth and quality parameters (viz. chloride, electrical conductivity, fluoride, magnesium, and nitrate). Ordinary kriging was used to analyze the spatial variability of groundwater depth and quality parameters, whereas indicator kriging was used to analyze groundwater quality parameters equal to or greater than the pollution threshold values. It was observed that the semivariogram parameters fitted well in the exponential model for water depth and in the spherical model for water quality parameters. The generated spatial variability maps indicated that in 43% of the study area, groundwater depth was within 20 m. The salinity level was higher than 2.5 dS m(-1) in 69% of the study area and the nitrate concentration exceeded 45 mg l(-1) in 36% of the area. The probability maps showed that about 24% of the area had the highest probability (0.8-1.0) of exceedence of the threshold electrical conductivity value and an area of 2% exhibited the highest probability of exceedence of the threshold value of nitrate concentration in the groundwater. The generated spatial variability and probability maps will assist water resource managers and policymakers in development of guidelines in judicious management of groundwater resources for agricultural and drinking purposes in the study area.

Crop models assist in generating crop productivity trends under future climate and different irrigation water supply scenarios. In this study, the AquaCrop model with a salinity module to simulate the grain yield and water productivity of four wheat varieties, including three salt-tolerant (i. ) for grain yield, were 0.85, 0.96, 0.94 and for biomass 0.7, 0.95, 0.95, respectively, for all varieties and salinity levels. It was observed that the AquaCrop model was better at predicting the grain yield compared to biomass and water productivity for all varieties and salinity levels.