In India, the per capita availability of water is projected to be 1465 m3 and 1235 m3 by the years 2025 and 2050, respectively, and hence, India would be a water-stressed country as per the United Nations’ standard of less than 1700 m3 per capita water availability. India is predominantly an agricultural-dominant country. Rainfed agriculture in the country contributes 40% of food grain production and supports half of the human population and two-thirds of the livestock population. The country has 15 different agro-climatic zones, and each agro-climatic region has its own constraints of water availability and management along with the potential for their optimum utilization. Such situations warrant the formulation of regional-level strategies. Efforts were made to integrate and evaluate the feasibility of water harvesting and its utilization at twelve different sites representing six different agro-climatic conditions spanning pan India. It was found that water harvesting through tanks/ponds is a feasible approach and can increase the crop production as well as diversification. The results reveal that the range of crop diversification index increased from 0.49–0.85 to 0.65–0.98; the crop productivity index increased from 0.28–0.66 to 0.66–0.90; the cultivated land utilization index increased from 0.05–0.69 to 0.34–0.84; and the crop water productivity index increased from 0.20–0.51 to 0.56–0.96, among other production and diversification indices, due to additional water availability through rainwater harvesting intervention. Moreover, the gross return increased from INR 43,768–704,356 to INR 220,840–1,469,108 ha−1, representing a 108 to 400% increase in the returns due to the availability of water. The findings of this study suggest that the water harvesting in small ponds/tanks is economical and feasible, requires less technological intervention, and increases crop diversification in all the studied agro-climatic conditions, and hence, the same needs to be encouraged in the rainfed areas of the country.

Groundwater extraction through electrically operated tubewells offers a resilient source of irrigation supply in arid regions especially during droughts. However, interrupted and low-voltage electric supply with limited availability and frequent trips increases repair and maintenance costs of tubewell irrigation and reduces tubewell discharge resulting in less-efficient and non-uniform water application. This study evaluates performance of an indigenous system of groundwater irrigation that was evolved over the generations in arid region of Gujarat, India to address electricity-triggered issues of irrigated agriculture. In this system, groundwater extracted during electricity availability hours is stored in surface reservoirs for later supplying to irrigate crops under gravity flow irrespective of electricity availability. A comprehensive survey of the indigenous system is conducted in a village of Gujarat to make inventory of all tubewells and storage reservoirs about their depth, size, pump type and horsepower, command area, crops, irrigation timing and frequency, etc. Discharge of tubewells was measured and their locations were recorded. Results revealed that the indigenous system is advantageous over the direct tubewell-irrigation in terms of 37.4% higher water-delivery rate and 50% more average irrigation capacity. These findings prove adequacy of the indigenous system in regulating irrigation supplies to deal with electricity-induced intricacies of irrigated agriculture. Amount of water lost through unit area of earthen (seepage and evaporation-2.77 m) and masonry (evaporation-1.22 m) reservoirs collectively accounts for a negligible proportion (0.9%) of groundwater draft. Furthermore, a methodology is devised to precisely estimate village-level groundwater draft for irrigation, which is validated by 0.9% deviation between observed and predicted values of groundwater draft. Moreover, the indigenous system is simple, cost-effective and easy to implement in other parts of the world especially in arid regions of the developing countries where low-voltage and intermitted electricity supply persists.

A study was conducted to assess the fertility status of Kanwara minor lift canal command area using Nutrient Index values of different soil parameters under study in 2019-20. A systematic set of two hundred and eleven georeferenced soil samples were collected and analysed following the standard sampling and analytical procedure. The analysed values of different parameters were categorized in low, medium and high and further used in determination of the nutrient index. NI value of soil organic carbon was 1.16, 1.00 for available N, 1.47 for available P and 2.55 for available K respectively. Regarding the fertility class based on Nutrient Index values it was deficient in organic carbon, available N and available P while, sufficient in soil available K. This requires immediate attention towards the management of nutrients to restore the soil fertility and sustain crop productivity.

Estimates of the soil and nutrient losses are essential for design and planning of soil conservation measures in Indian arid region. This study aims at estimating rainfall-runoff, soil and nutrient losses from different cover crops, and to identify the best cover for checking soil loss. The study is conducted for 2013-2015 in research farm of the Central Arid Zone Research Institute, Regional Station, Bhuj, Gujarat, India. Ten treatments comprising four sole-crop, that is, sorghum (Sorghum bicolor), pearl millet (Pennisetum glaucum), green gram (Vigna radiata), and cluster bean (Cyamopsis tetragonoloba) and four cereal-legume intercropping with two controls (cultivated and unplowed fallows) are undertaken in randomized block design with three replications. Multi-slot divisors are fabricated and installed. Analysis of variance (ANOVA) is performed, and their interrelationships are explored. The highest soil loss is recorded from cultivated fallow (108.03 +/- 49.95 kg.ha(-1).yr(-1)) and unplowed fallow (78.95 +/- 28.42 kg.ha(-1). yr(-1)). Green gram is found effective in controlling soil loss as sole-crop (event-wise soil loss similar to 0.54-33.94 kg.ha(-1)) as well as intercropping with sorghum (event-wise soil loss similar to 0.60-23.37 kg.ha(-1)) and pearl millet (eventwise soil loss similar to 2.45-31.11 kg.ha(-1)). ANOVA revealed significance (p < .05) of runoff-generating rainfall, crop cover, and their sole- and intercropping practices. Values of coefficient of determination (R-2) indicated highly corre- lated (R-2 >= 0.75) relationships of rainfall-runoff for all treatments, rainfall-soil loss for sole cereals and cultivated fallow, and runoff-soil loss for pearl millet and intercropping with green gram. This study concludes that cereal-legume intercropping diminishes the adverse impact of raindrops on soil erosion and crop production.

This study developed a novel framework for integrating time series modeling with geographic information system (GIS). For the first time, procedures of four statistical tests, i.e., t-test of stationarity, cumulative deviation test of homogeneity, autocorrelation technique of persistence, and variance-corrected Mann–Kendall test of trend, are implemented in GIS platform to enable use of raster dataset. Application of developed framework is demonstrated by exploring time series characteristics of pre- and post-monsoon groundwater levels in an Indian arid region. Raster dataset of 22-year (1996–2017) groundwater levels are generated using four best-fit geostatistical models, according to mean absolute error, root mean square error, correlation coefficient and modified index of agreement. Increasing groundwater level trends in central and southern parts are attributed to abrupt change-points in annual rainfall that enhanced groundwater recharge. The developed framework can be adopted in other parts of the world to explore groundwater-level dynamics in spatially-distributed manner.

This study delineates groundwater potential zones by following an “equifinality” approach and adopting a standard methodology using remote sensing, geospatial modeling, geographic information system (GIS) and multicriteria decision analysis (MCDA) techniques. A total of 11 thematic layers (ie, rainfall, topographic elevation, slope, slope length, slope steepness, soil, geomorphology, geology, drainage density, and pre‐ and post‐monsoon groundwater levels) which have an influence on the occurrence of the groundwater are developed. The suitable weights to themes and their features are assigned and then normalized by using an analytic hierarchy process (AHP)—MCDA technique. All themes are integrated in GIS for generating a groundwater potential index (GPI) map, which classifies the study area into three zones of “good” (588.5 km2, 34.1%), “moderate” (933.4 km2, 54.1%), and “poor” (203.3 km2, 11.8%) groundwater potential. Furthermore, the accuracy of the developed GPI map is verified from the coherent estimates of rainfall‐recharge. Unlike earlier studies, this study further evaluates relative sensitivity of the themes, and develops a novel “parsimonious” groundwater potential index (PGPI). The PGPI is a cost‐effective and time‐efficient method that excludes redundant parameters from the analysis and employs only the most sensitive themes in assessing groundwater potential. The results of both GPI and PGPI are found in good harmony over 86.7% area, which confirms the efficacy of the developed PGPI. The results of this study may be of interest to planners and policymakers as a guideline for locating appropriate groundwater development sites and managing sustainable water supplies, especially under data scarcity conditions and/or in developing countries.

This study used hierarchical cluster analysis (HCA) to delineate the spatial patterns of monthly, seasonal and annual rainfall by clustering 62 stations in the western arid region of India based on a 55 year (1957–2011) data set. The statistical properties of clusters were computed and box–whisker plots plotted. Furthermore, the relative influence of three geographical factors (longitude, latitude and altitude) and five statistical parameters (the mean, standard deviation (SD), co‐efficient of variation (CV), and maximum and minimum rainfall) on mean rainfall was investigated using principal component analysis (PCA). The use of HCA resulted in four rainfall clusters geographically located at a distinct position. Cluster I, characterized by the lowest mean rainfall and highest CV, was located in the western portion, whereas mean rainfall was the highest for cluster IV situated in the eastern portion. Box–whisker plots revealed a slight skewness, although the monsoon and annual rainfall followed a normal distribution. The PCA results indicted two to three significant principal components (PCs) with eigenvalues > 1. In four clusters, two PCs explained the major variance, ranging from 69.41% (June) to 91.83% (August) in monthly rainfall, from 63.62% (monsoon) to 93.30% (post‐monsoon) in seasonal rainfall, and from 71.48% to 90.73% in annual rainfall. In monthly and seasonal rainfall, first PC 1 is termed the “mean rainfall component”, which has strong to moderate associations with longitude, and is equally opposed by the CV. These findings are vital for planners and decision‐makers to formulate strategies to manage unusual rainwater quantities.

Water scarcity problems in arid regions have been successfully tackled by water harvesting from the times immemorial. This study focuses on an indigenous rainwater harvesting system, locally known as virda that was evolved centuries ago in Banni grassland of Kachchh, Gujarat, India. Animal husbandry is the major occupation of local people called as maldharies, and agriculture is not possible due to low rainfall and inherent salinity present in soil and water. The indigenous water harvesting system based on traditional knowledge is found to be highly effective in sustaining livelihoods of people and life of animals. Success of virda is evident from the fact that the method, developed centuries back, is still found in existence and operational. This indigenous technology developed by the maldharies learnt over the generations based on their wisdom and experience, is not only a traditional method rather it has also been embedded into their culture. Quality of virda water is found suitable for drinking purpose. Thus, virda is a unique water culture for the maldharies community of Banni. Moreover, suitable scientific interventions are suggested to integrate with traditional knowledge-based indigenous technology for further improvement.

Small reservoirs have proved as successful rainwater harvesting systems in semi-arid regions; however, their dependability in arid regions is not tested. This study aimed at evaluating cost-effectiveness of small reservoir used for supplying irrigation water to wheat and mustard crops in an arid region of India by employing three performance indicators, i.e., benefit-cost (B-C) ratio, net present value (NPV) and internal rate of return (IRR). In addition, sensitivity analysis of the variables influencing the economics of the reservoirs is also carried out. The actual water requirements for wheat and mustard crops over their entire life span of 110 and 95 days, respectively, are computed as 319 and 227 mm, respectively, in comparison to existing practice of excessively irrigating the crops. Fixed cost, i.e., cost of construction of the reservoir is estimated as Rs. 1,033,349, for a total storage capacity of 29,184.5 m3, whereas, the running cost, i.e., cost of cultivation for wheat and mustard, is worked out to be Rs. 41,800 and 31,100 per ha, respectively. The net benefit of Rs. 28,901 and 38,835 per ha, respectively for wheat and mustard crops clearly indicated that mustard is 34% economical over the wheat. The optimistic, pessimistic, and average unit costs of harvested rainwater over a 30-year period is calculated as Rs. 1.51, 3.03, and 2.27 m−3, respectively, which suggests that a small reservoir is a viable option for rainwater management in the arid regions. This finding is further supported from the optimum values of B-C ratio (1.01), NPV (Rs. 10,093), and IRR (10.12%). This study considered a scenario of demand-based efficient irrigation supplies with improved values of the B-C ratio (2.18), NPV (Rs. 1,330,558), and IRR (24%). Furthermore, sensitivity analysis revealed that the grain yield is the most significant variable affecting the cost-effectiveness of the reservoir system, which needs to be carefully monitored and enhanced in order to further increase reservoir dependability in arid regions. Finally, the findings of this study are very useful for planners and decision-makers to formulate appropriate strategies for managing scarce rainwater in the study area as well as in other arid climate regions of the world.

This study examined trends and change points in 100-year annual and seasonal rainfall over hot and cold arid regions of India. Using k-means clustering, 32 stations were classified into two clusters: the coefficient of variation for annual and seasonal rainfall was relatively high for Cluster-II compared to Cluster-I. Short-term and long-term persistence was more dominant in Cluster-II (entirely arid) and Cluster-I (partly arid), respectively. Trend tests revealed prominent increasing trends in annual and wet season rainfall of Cluster-II. Dry season rainfall increased by 1.09 mm year(-1) in the cold arid region. The significant change points in annual and wet season rainfall mostly occurred in the period 1941-1955 (hot and cold), and in the dry season in the period 1973-1975 (hot arid) and in 1949 (cold arid). The findings are useful for managing a surplus or deficiency of rainwater in the Indian arid region.

Groundwater levels in hard-rock areas in India have shown very large declines in the recent past. The situation is becoming more critical due to a paucity of rainfall, limited surface water resources and an increasing pattern of groundwater extraction in these areas. Consequently, the Ground Water Department with the aid of World Bank has implemented the water structuring programme to mitigate groundwater scarcity and to develop a viable solution for sustainable development in the region. The present study has been undertaken to assess the impact of artificial groundwater recharge structures in the hard-rock area of Rajasthan, India. In this study groundwater level data (pre-monsoon and post-monsoon) of 85 dug-wells are used, spread over an area of 413.59 km2. The weathered and fractured gneissic basement rocks act as major aquifer in the area. Spatial maps for pre- and post-monsoon groundwater levels were prepared using the kriging interpolation technique with best fitted semi-variogram models (Spherical, Exponential and Gaussian). The groundwater recharge is calculated spatially using the water level fluctuation method. The entire study period (2004–2011) is divided into pre- (2004–2008) and post-intervention (2009–2011) periods. Based on the identical nature of total monsoon rainfall, two combinations of average (2007 and 2009) and more than average (2006 and 2010) rainfall years are selected from the pre- and post-intervention periods for further comparisons. All of the water harvesting structures are grouped into the following categories: as anicuts (masonry overflow structure); percolation tanks; subsurface barriers; and renovation of earthen ponds/nadis. A buffer of 100 m around the intervention site is taken for assessing the influence of these structures on groundwater recharge. The relationship between the monsoon rainfall and groundwater recharge is fitted by power and exponential functions for the periods of 2004–2008 and 2008–2011 with R 2 values of 0.95 and 0.98, respectively. The average groundwater recharge is found to be 18% of total monsoon rainfall prior to intervention and it became 28% during the post-intervention period. About 70.9% (293.43 km2) of the area during average rainfall and more than 95% (396.26 km2) of the area during above-average rainfalls show an increase in groundwater recharge after construction of water harvesting structures. The groundwater recharge pattern indicates a positive impact within the vicinity of intervention sites during both average and above-average rainfall. The anicuts are found to be the most effective recharge structures during periods of above-average rainfall, while subsurface barriers are responded well during average rainfall periods. In the hard-rock terrain, water harvesting structures produce significant increases in groundwater recharge. The geo-spatial techniques that are used are effective for evaluating the response of different artificial groundwater recharge techniques.

This study developed a standard methodology for identifying spatial trends using satellite-based raster datasets. It involves the novelty of exploring the capabilities of a geographic information system in implementing the procedures of three trend tests, the Spearman rank order correlation (SROC) test, the Kendall rank correlation (KRC) test and the Mann-Kendall (MK) test, on raster datasets of the Tropical Rainfall Measuring Mission at 0.25 degrees x 0.25 degrees resolution. Comparative evaluation of the three tests revealed fair agreement of a major part of the test results for pre-, post- and non-monsoon and one-day maximum rainfall. Also, similar results from KRC and MK tests were obtained over a considerable area for annual, monsoon and monthly maximum rainfall. These findings suggest the importance of selecting the appropriate test depending on rainfall magnitudes at the chosen time scale and emphasize the robustness of the KRC and MK tests.

ABSTRACTThis study aimed at identification of abrupt change points (CPs) and detection of gradual trends in 34‐year (1980–2013) annual rainfall at nine stations of an Indian arid region. The CPs were determined by five tests and their significance was examined by two tests. Furthermore, trends were tested by three tests and their magnitudes were quantified by two tests. Novelty of the study lies in investigating significance of trends sequentially over years by applying Mann–Kendall (M–K) test. The identified CPs were similar for standard normal homogeneity test and cumulative deviations test at most stations. In contrast, Pettitt and Bayesian tests detected CP in years 2002 and 2005 at six and three stations, respectively, and their significance was verified. Results of sequential M–K test did not match with other tests' results. The mean annual rainfall after CP (350–627 mm) increased by 14–80% of the amount before CP (306–444 mm) with 7–42% reduction in coefficient of variation. The box–whisker plots supported these findings. Results of trend tests indicated statistically significant trends at Anjar, Bhachau, Mandvi and Rapar. Trend magnitudes by linear regression prior to CP (−6.2 to 7.1 mm year−1) showed an overall increase after CP (4.7–40.8 mm year−1) with negative trend at one station. Sen's slope test, showing good harmony with linear regression, revealed that trend magnitudes after CP were 2–10 times higher than that for 34‐year period at six stations. Results of M–K test applied for sequential periods emphasized that rainfall trends are becoming stronger over time. This finding suggests that significance level of increasing rainfall trends may further increase in future. Finally, findings of this study are useful for planners and decision makers for developing policies to meet the challenges of the heightened rainfall in study area. Also, the approach used here may be adopted in other parts of the globe.

Quantification of hydrological processes is necessary for management of small reservoirs especially in arid regions characterized by hot climate, scanty rainfall magnitudes and large rainfall variability. This study focuses on estimating inflow and outflow components of a small reservoir situated in arid Kachchh region of Gujarat, India, by developing a water balance model. Daily reservoir water levels were monitored for years 2012 and 2013. All water balance components, i.e. rainwater directly falling into reservoir, surface runoff, irrigation extractions, and evaporation and percolation, were either measured or estimated. Results indicated that rainfall has a fair control on amount of harvested runoff water. In year 2012, meagre rainfall (79 mm) could store 925 m3 of water with 66 cm depth. In contrast, reservoir water levels were at 2.85 m depth in year 2013 with full capacity of 24,879 m3 when rainfall totalled to 291 mm. The mean percolation rate (0.14 cm h−1), determined from 24-h long-term infiltration tests, revealed that full storage will get depleted within 85 days. A major portion (51%) of storage was lost through evaporation and percolation, and only 21% stored water could be utilized for supplemental irrigation. This finding suggested that suitable measures need to be adopted to check evaporation and seepage losses from the reservoirs in arid regions for improved agricultural productivity. Moreover, results of this study may be useful for water resources managers and decision-makers to develop appropriate operational strategies for the reservoirs in the study area as well as in other arid regions of the world.

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling techniques and sustainability approach. Five characteristics, i.e., normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980–2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and non-parametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability (R y), resilience (R e), and vulnerability (V y) approach. Box–whisker plots, normal probability plots, and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively skewed and non-normal compared with that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro–Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t tests and the non-parametric Mann–Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag), and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations (R y = 0.50 and 0.44; R e = 0.47 and 0.47; V y = 0.49 and 0.46, respectively) are the most sustainable and dependable compared with that of other stations. The highest values of sustainability index at Mundra (0.120) and Naliya (0.112) stations confirmed the earlier findings of R y–R e–V y approach. In general, annual rainfall of the study area is less reliable, less resilient, and moderately vulnerable, which emphasizes the need of developing suitable strategies for managing water resources of the area on sustainable basis. Finally, it is recommended that multiple statistical tests (at least two) should be used in time-series modeling for making reliable decisions. Moreover, methodology and findings of the sustainability concept in rainfall time series can easily be adopted in other arid regions of the world.

The study aimed at sedimentation assessment in a reservoir, for the first time, in an arid region watershed located in Kukma village of Kachchh, Gujarat by performing aerial topographical survey. The topographical database was subjected to SURFER software to generate grid, contour map and three-dimensional digital model of the reservoir by interpolating reduced levels spatially using kriging technique. Storage volumes were computed for entire depth of the reservoir at 10 mm intervals using trapezoidal formula. The storage volume data were utilized to develop depth-capacity curve, which was fitted with logarithmic, power, and exponential empirical regression models; and the best-fit model was selected by applying correlation coefficient (R), coefficient of determination (R2 ), root mean square (RMSE), modified Nash-Sutcliffe efficiency (MNSE) and modified index of agreement (MIA) goodness-offit criterion. Contour map of the reservoir revealed the maximum depth of 2.85 m corresponding to full storage capacity of 24879 m3 . The three-dimensional view closely matched with the real outlook, which confirmed accuracy of the survey and data analysis. The depth-capacity curve was utilized to determine rainwater storage during years 2012 and 2013 as 925 and 24879 m3 , respectively, in response to 79.1 and 291.9 mm of rainfall, respectively. This finding suggested that reduction in monsoon rainfall caused significant reduction in the rainwater storage. The power regression model was considered as the best-fit in this study due to the lowest RMSE (293 m3 ), and highest R (0.98) and R2 (0.93) values. The values of MNSE (0.60) and MIA (0.83) further supported the selection of the best-fit model. It was revealed that capacity of the reservoir reduced by 4305.5 m3 (14.75%) over a period of 12 years due to sedimentation at average annual rate of 358.8 m3 . Finally, it is emphasized that there is need for planning and implementation of appropriate soil conservation measures within the reservoir catchment.