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The rainfall erosivity (R-factor in USLE) is the long-term average of the sum of the product of rainfall kinetic energy and its maximum 30-min intensity. Therefore, at most 30-min time intervals pluviograph records are required to calculate R-factor. But, such high-resolution data are scarce in many parts of the world and require lengthy processing period. In this study, R-factor was correlated with daily, monthly and annual rainfall, and its spatial variability in Eastern Ghats Highland of east India was mapped. The result showed that power regression models predicted satisfactorily the daily, monthly and annual R-factor, of which annual R-factor model performed best (model efficiency 0.93). Mean monsoon season R-factor was 15.6 and 10.0 times higher than the pre- and post-monsoon season R-factor, and thus remained highly critical with respect to erosion. Annual R-factor values ranged from 3040 to 10,127 MJ mm ha−1 h−1 year−1, with standard deviation of 1981 MJ mm ha−1 h−1 year−1. Rainfall intensity was positively correlated with erosivity density, and numerical value of rainfall intensity was almost double of the erosivity density value. The combination of rainfall and erosivity density was used to identify flood, erosion and landslide-prone areas. The developed iso-erosivity, erosivity density and risk maps can be opted as a tool for policy makers to take suitable measures against natural hazards in Eastern Ghats Highland of east India and elsewhere with similar rainfall characteristics.

Water is the basic requirement for the development of civilization. The primitive civilizations were developed along the surface water bodies to meet the demand of water for the society. With the progress of time, the population-led demand for water was increased in those civilizations and which ultimately led to conflicts. The Indus valley civilization was destroyed mainly because of issues related to water management. In the recent times with the advent of modern tools and gadgets, the issues related to water have increased manifold. The demand from drinking, domestic, agriculture and industry has also increased alarmingly. To meet these demands, use of groundwater has increased tremendously all over the world. With the higher demand, the problems also became higher. In this context, modern tools and techniques like remote sensing, geographical information system, geostatistics and modelling have the potentiality to manage the groundwater-related problems and play a vital role for societal development. In this book we intended to offer novel advances and applications of remote sensing, geographical information system and geostatistical techniques in a precise and clear manner to the research community to achieve in-depth knowledge in the field. The scientific understanding, development and application of geospatial technologies related to water resource management have been advanced. Geostatistics and geospatial techniques for groundwater science assemble the most up-to-date techniques in GIS and geostatistics as they relate to groundwater. Therefore, this book will help the readers to find the recent advancement of the geospatial techniques and its application in the groundwater resources in a single volume.

India is the largest user of groundwater in the world using an estimated 250 km3 of groundwater per annum. In India, groundwater contributes 62% in agriculture sector. In rural India, 85% and in urban India, 45% of water consumption has been met from groundwater. However, this precious water resource is under increasing pressure due to intensification of human activities along with climate change. In India about 36% of groundwater blocks are semi-critical, critical, or overexploited and the situation is deteriorating rapidly. Not only groundwater depletion is unprecedented, its quality is also deteriorating in an alarming rate throughout India. Therefore, groundwater dependent water supply system is expected to hit adversely in the future. In this context, Geographic Information System (GIS) along with geo-statistics play an important role in depicting the spatio-temporal variation of water level and water quality. In this chapter work done by various researchers on GIS and geostatistics in groundwater is highlighted, which will help the policy makers and managers to implement proper regulations for sustainability of this precious resource in India.

The dwindling situation of groundwater resources in the Eastern Ghats Highland region of East India has hampered the livelihood security of the rural peoples living in this area. In this context, the impact of watershed development activities, especially water resource management activities on the livelihood security of the peoples residing in this area, was assessed. Lacchaputraghati watershed of Koraput district of Odisha was chosen as the representative watershed for this study. The study area is dominated by agriculture land use with predominantly monocropping, covering 43% of the watershed area. Forest and scrublands are also dominant and shifting cultivation is rampant. Before the start of the project, the average runoff in the watershed was 24.4%, which was decreased to 14.6% after the successful implementation of the project. Finger millet and upland paddy cultivation are the highly runoff-prone land uses where watershed management treatments reduced the runoff from 29.92% to 15.4%. Even in forested areas, the runoff was decreased from 14.68% to 7.3%. Rainwater harvesting and storing capacity was increased by 93.91 ha-cm within the watershed. The average annual water storage depth in the water bodies was increased from 1.01 to 1.17 m during the project period. A positive change to the tune of 15.04% was observed in terms of water storage capacity within the watershed. The annual average depth to water table from the land surface was decreased from 7.95 to 7.80 m within a span of 5 years because of watershed management activities. The crop yield also responded positively to the watershed management activities and increased by 9.14% with the range of 3–15% for different crops. Therefore, the watershed development activities have shown a positive impact on the conservation of natural resources, especially water resources, and need to be replicated in other areas for sustainable management of natural resources.

Forest ecosystem is vital for the existence of human beings. Since ages we are depending on forest for food, fiber, fodder, fuel wood, and shelter. Apart from humans, it is home to various other animals, birds, and microbes. It covers nearly one-third of the global land area. However, this natural ecosystem is under threat since ages. The Koraput district, Odisha, India popularly known as the land of aboriginals is one of the biodiversity rich regions. Over time the district has seen large scale deforestation. In this study an attempt has been made to know the changes in forest cover in Koraput district, Odisha, India during last eight decades using remote sensing and Geographical Information System. The classification accuracy to identify forest lands for the years 1973, 1990, 2004, and 2013 was 72%, 85%, 91%, and 93%, respectively. The analysis of the Survey of India (SoI) topographic sheet reveals that there was decease in reserve forest cover by 0.6%, while 22.51% in mixed forest cover during the period 1932–2008. Similarly the analysis of satellite images showed decrease in dense forest cover by 11.6%, 17.7%, and 19.3% during the years 1990, 2004, and 2013, respectively, in comparison to reference year 1973. The agricultural expansion due to the creation of irrigation facilities through construction of reservoirs, shifting cultivation, and poor employment opportunities are some of the reasons behind the deforestation in the study area. Creation of diversified land-based and other livelihood activities with proper marketing linkage, awareness among the local people about the impact of deforestation on the ecosystem, and the convergence of both government and nongovernment schemes can help with restoration of forest resources in the study area.

India stands first in the world in terms of groundwater use followed by China and the USA. However day by day, the groundwater level is depleting in an alarming rate all over the country. The Rayalaseema region of Andhra Pradesh is one of such regions, where groundwater depletion is a major problem and attributed to both natural and anthropogenic causes. In this study the spatial variation of groundwater was mapped for the year 2018 in Anantapur district, Andhra Pradesh, India, which is located in the Rayalaseema region. The groundwater level varied from 2.0 to 69.96 m with a mean value of 18.52 m during pre-monsoon, and during post-monsoon the depth of groundwater ranged between 1.15 m and 68.37 m with a mean value of 17.63 m. With respect to groundwater development, one-third of the mandals has reached the critical or overexploited stage. The overall stage of groundwater development was observed to be more than 80% in the study area, indicating heavy withdrawal of water from the aquifer. Mandals like Agali, Peddapappur, Rolla, Tadimarri, and Yellanur showed the level of groundwater development even more than 150%. In the study area, the mandals in which groundwater is at critical stage are Madakasira, Parigi, Penukonda, Raptadu, and Roddam. Therefore water conservation and groundwater recharge techniques may be executed, and awareness about judicious use of water may be created to avoid further depletion of aquifer in the district.

Western Delhi is a peri-urban area and mainly produces cash crops like vegetables. For round the year vegetable production, the farmers in this area depend on groundwater for irrigation. Thus, widespread groundwater withdrawal for intensive vegetable cultivation is the primary cause of depletion of groundwater quantity in this part of Delhi. To understand sub-surface geologic condition and to assess groundwater availability, geophysical imaging of the sub-surface was carried out. Groundwater potential zones were found at 18–30 m below ground level, and the quality of groundwater seems to be of moderate to poor because of low resistivity values in the water potential zones. Geospatial mapping of the resistivity values of different sub-surface layers identified the geological formations like coarse fragments, clay, calcite and other formations. Longitudinal Unit Conductance (S value) and Transverse Unit Resistance (T value) and their combinations are found effective to identify groundwater potentiality. Geospatial maps prepared by ordinary kriging interpolation method indicated that 20.2% of the area has potential to get good quality groundwater. But these areas are scatteredly distributed at the east, west, and north side of west Delhi. The aquifer of the southern part of the study area showed low resistivity formation, which indicates groundwater pollution. The infiltrations of highly polluted Najafgarh drain water and fertilizer laden surface water and their subsequent movements to the aquifer are mainly responsible for this. The study will help to identify the hotspots for periodic monitoring of groundwater quality. The study also suggests the directions of future research works for scientific development and management of groundwater resources in west Delhi.

Land degradation has been a major global issue due to its adverse effect on food security, environment and ecology. Among different degraded lands, gullied and ravine lands are very important and remained a highly researchable topic. Gullies are continuous depression on the sloping land surface as a result of soil displacement caused by overland water flow and aided by gravity force, whereas ravines are most extreme form of erosion with intricate network of various forms of gullies, having high drainage density and multidirectional slopes. In India, ravines are mostly found in four states such as Uttar Pradesh, Madhya Pradesh, Gujarat and Rajasthan. During 1976, total ravine land in India was 3.67 million ha, which has been reduced to about 60% at present, and the treatable area including peripheral land is likely to be as high as 1.5 times the actual ravine.

Spatial heterogeneity of a river basin increases the predicting uncertainty of streamflow using hydrological models, and for such river basins calibration and prediction become a challenge....

Accurate assessment of deep percolation (potential groundwater recharge) under different field crops is essential for sustainable management of scarce water resources and proper planning of crop rotation in irrigated, semi-arid regions of the world. The potential recharge from commonly grown field crops in semi-arid Indo-Gangetic Plain (IGP) of India was estimated using HYDRUS-1D model, where, irrigation, evapotranspiration, and soil moisture dynamics were simulated. Simultaneously, net groundwater use by different cropping patterns was also calculated. Among the hydraulic parameters, n was found most sensitive for water percolation. During rainy season, 293.8 and 159.1 mm water was percolated below the root zone of cotton and soybean, respectively, which accounted for 39.4 and 32.9% of the water input. During winter season, 66.8 and 30.3 mm water was percolated below the root zone of winter maize and mustard, respectively, accounting for 20.5 and 10.6% of added water. It was observed that net groundwater use was positive for cotton, soybean, and summer maize with the values of 168.8, 159.1, and 18.0 mm year−1, respectively, and negative for rice, wheat, winter maize, and mustard. For the eight most important cropping patterns of semi-arid IGP, the net groundwater use was negative and varied between − 4.4 mm year−1 for cotton-maize and −423 mm year−1 for rice-wheat. With these cropping patterns, the overall rate of decline of groundwater was 231 mm year−1. It was found that maize-wheat and soybean-wheat cropping patterns consume much less water than rice-wheat cropping pattern and therefore are suitable to arrest the declining trend of groundwater in semi-arid IGP of India.

Continual, historical, and accurate information about the land use/land cover (LULC) changes of the earth’s surface is extremely important for sustainable management of natural resources. In this study, historical topographic sheets, IRS P6 LISS-III, and LANDSAT TM images were used to provide recent and historical LULC conditions of the Eastern Ghats Highlands of east India. The supervised classification results were further improved by employing image enhancement and visual interpretation. Ratio Vegetation Index with fuzzy-based possibilistic c-means classification approach has improved the classification accuracy of the shifting cultivated area. Post-classification comparisons of the classified images indicated that the major change consisted of barren land and forestland changing into agricultural land and scrubland. Between 1931 and 2008, forest cover was decreased from 52.7% to 29.6% of total area. There was an increase in the scrub area from 874 (10.4%) to 1269 km2 (15.2%), and agricultural land from 978 (11.7%) to 2864 km2 (34.2%) during the same period. The rate of deforestation was found to be 0.65 km2 per year for reserve forest and 24.50 km2 per year for mixed forest. The shifting cultivated area in the district was 308.7 km2 during 2004, and that has been reduced since then and now is stabilized to 186.4 km2 area. Among this 186.4 km2 area, nearly half is covered by abandoned shifting cultivation. The decadal rate of decrease of shifting cultivated area is 0.15% per year. The shifting cultivated areas were mainly distributed at elevations 580–810 and 810–907 m and slopes 20–30 and 30–40%. Southeast and south facing slopes were preferred for shifting cultivation. Based on the identified causes of the change in shifting cultivation, policy recommendations for their better management were made.

In irrigated semi-arid regions, knowledge of groundwater recharge and nitrate leaching is essential for sustainable management of water resources. In this study, the potential recharge and nitrate leaching below the root zone of rice crop were estimated using a root zone modelling approach through simulation with HYDRUS-1D model. The field data collected for a single season were used for calibrating the model and validated for the next season. The simulated results, when compared with the measured soil water and nitrate contents at different soil depths showed good agreement between the HYDRUS-1D simulation and field data. The validated results indicated that 55.5 % of the applied water percolated below the root zone. Nitrogen balance within 120 cm deep soil profile indicated that volatilization, denitrification, plant uptake and leaching losses were 24.0, 18.9, 109.0 and 28.5 kg N ha−1, respectively. The magnitude of nitrate leaching was 23.7 % of added fertilizer. Different nitrate leaching scenarios were generated using different fertilizer application rates exceeding the optimal dose. These scenarios showed an increasing trend with increase of fertilizer rates, fitted with a second-order polynomial equation (R 2 = 0.99). The equation can be used for estimation of nitrate leaching below root zone under different fertilizer input scenarios of rice grown in similar hydro-agro-climatic regions.

Sustainable and safe use of groundwater requires periodical monitoring of its quality. Because of the presence of multiple contaminants, spatial variation of overall groundwater quality is difficult to describe. The present study describes the overall groundwater quality for irrigation using a multi-criteria quality assessment system and sustainability of water use by incorporating the aspect of temporal variation of groundwater quality. The GIS-based multi-criteria system effectively amalgamated different quality parameters into an easily understandable format and assessed the spatial variation of groundwater quality for irrigation in west Delhi, India. The rate of spatial increment of poor quality groundwater within the study period was 3.7 km2 per year. It has been observed that there is deterioration of groundwater quality from southwest to east, along the general groundwater flow direction, and improvement of groundwater quality from west to northeast, due to less urbanization and availability of groundwater recharge zones with good quality water. Temporal variation of groundwater quality is high (V > 20 %) at northern part, moderate (V = 10–20 %) at middle and southern parts, and less (V

Indiscriminate use of agro-chemicals for intensive agriculture is mainly responsible for deterioration of groundwater quality in west Delhi of India. Geophysical and hydrochemical investigations were carried out to decipher subsurface geologic formation and assess groundwater salinity. Electrical resistivity tomography surveys revealed the presence of potential groundwater zones at 20–30 m below ground level. The groundwater quality was moderate to poor as evidenced from the low resistivity value of the potential aquifer. Only 20.2 % of the study area showed good quality groundwater potentiality, situated at few pockets in eastern, western, and northern parts of the study area. Low resistivity formation at southern part of the study area was due to infiltration of highly polluted drain water along with fertilizer rich surface water to the aquifer. Hydrochemical investigation also confirmed the result. The average electrical conductivity of groundwater was around 5,950 μS cm−1. Longitudinal unit conductance and transverse unit resistance values were calculated and used for delineation of saline groundwater zones. A direct relationship between longitudinal unit conductance and groundwater salinity made it possible to develop empirical equations by which salinity can be predicted from computed longitudinal unit conductance value. It helps for periodic monitoring of the pollution level by spending less labour and money and benefits immensely the policy makers. The article suggests further study and research work that can lead to sustainable exploitation/use and management of groundwater resources in west Delhi.

The groundwater resources of semi-arid region in Indo-Gangetic Plain is declining rapidly and necessitates accurate quantification of potential recharge from different agricultural land uses. The potential recharge on a daily basis for three different land uses, such as fallow, rice and non-rice cropped areas for three cropping seasons, was estimated using soil water balance approach. Beside this, the net groundwater use for eight different crops was also calculated. The potential recharge from fallow land was 126 mm year−1, which was 14.9 % of total rainfall. The mean potential recharge from kharif (rainy) and rabi (winter) seasons was 527.3 and 81.7 mm season−1, respectively. Among the rabi crops, least recharge was observed for winter maize and mustard with 29.3 mm season−1, followed by wheat with 108.4 mm season−1. Among the kharif crops, least recharge was observed for green gram with 59.7 mm season−1, followed by soybean with 113.9 mm season−1. Rice had the highest recharge potential of 929.1 mm season−1, followed by maize with 149.1 mm season−1 and cotton with 132.7 mm season−1. It was observed that the annual average groundwater use was highest for wheat with 190 mm year−1, followed by winter maize with 188 mm year−1, mustard with 169 mm year−1, paddy with 151 mm year−1, kharif maize with 94 mm year−1, green gram with 15 mm year−1. Cotton and soybean crops exhibited an additional potential recharge of 8 and 114 mm year−1 into the groundwater. It was revealed that the maize–wheat cropping system consumed less groundwater than rice–wheat and, therefore, can be considered as a better option for sustainable use of groundwater.

Intensive agriculture by indiscriminate use of agrochemicals, sewage water, and polluted drain water has posed a serious threat to groundwater quality in some peri-urban areas of Delhi like Najafgarh block. The objective of the study was to determine the groundwater quality and to map their spatial variation in terms of suitability for irrigation and drinking purpose. Ordinary kriging method was used for preparation of thematic maps of groundwater quality parameters such as electrical conductivity, sodium adsorption ratio, bicarbonate, magnesium/calcium ratio, total dissolved solids, chloride, nitrate and hardness. Exponential semivariogram model was best fitted for all quality parameters except chloride and hardness, where spherical model fitted best. Pollution level was highest at south and south-eastern part of the study area. Better quality groundwater may be expected at the northern and western part. High salinity was due to high chloride concentration in the groundwater. Nitrate pollution level was found to be very alarming and need immediate interventions. High dissolved solids and hardness made the groundwater unsuitable for drinking. There were negligible sodium and bicarbonate hazard in the study area. The groundwater quality index was devised to analyse the combined impact of different quality parameters on irrigation and drinking purposes. The irrigation water quality index and drinking water quality index distribution maps delineated an area of 47.29 and 6.54 km2 suitable for irrigation and drinking, respectively. These safe zones were found as a small strip along the northern boundary and a very small pocket at the western side of the study area.

Two non-parametric kriging methods such as indicator kriging and probability kriging were compared and used to estimate the probability of concentrations of Cu, Fe, and Mn higher than a threshold value in groundwater. In indicator kriging, experimental semivariogram values were fitted well in spherical model for Fe and Mn. Exponential model was found to be best for all the metals in probability kriging and for Cu in indicator kriging. The probability maps of all the metals exhibited an increasing risk of pollution over the entire study area. Probability kriging estimator incorporates the information about order relations which the indicator kriging does not, has improved the accuracy of estimating the probability of metal concentrations in groundwater being higher than a threshold value. Evaluation of these two spatial interpolation methods through mean error (ME), mean square error (MSE), kriged reduced mean error (KRME), and kriged reduced mean square error (KRMSE) showed 3.52% better performance of probability kriging over indicator kriging. The combined result of these two kriging method indicated that on an average 26.34%, 65.36%, and 99.55% area for Cu, Fe, and Mn, respectively, are coming under the risk zone with probability of exceedance from a cutoff value is 0.6 or more. The groundwater quality map pictorially represents groundwater zones as "desirable" or "undesirable" for drinking. Thus the geostatistical approach is very much helpful for the planners and decision makers to devise policy guidelines for efficient management of the groundwater resources so as to enhance groundwater recharge and minimize the pollution level.

The cost and time involved in frequent field observations pertaining to quantification of nitrate leaching below the crop root zone leads to the use of simulation models, which is a more plausible approach. Nitrate leaching below the root zone of a maize–wheat cropping system under surface irrigation was assessed. The model’s predicted results pertaining to water percolation and nitrate leaching were in line with the observed data, with root mean square error (RMSE) values close to zero, and index of agreement values close to 1. The seasonal percolation of water below 120 cm soil depth in maize and wheat were 36.5 and 27.5% of applied water, respectively. Similarly, nitrate leaching below 120 cm soil depth was 18.1 and 14.3% of the applied nitrogenous fertilizer in maize and wheat, respectively. Under similar conditions, the nitrate leaching under a maize–wheat cropping system was 6.8 kg NO3 ha−1 less than in a rice–wheat cropping system. Furthermore, nitrate leaching below the crop root zone und...

Accurate and reliable interpolation of groundwater depth over a region is a pre-requisite for efficient planning and management of water resources. The performance of two deterministic, such as inverse distance weighting (IDW) and radial basis function (RBF) and two stochastic, i.e., ordinary kriging (OK) and universal kriging (UK) interpolation methods was compared to predict spatio-temporal variation of groundwater depth. Pre- and post-monsoon groundwater level data for the year 2006 from 110 different locations over Delhi were used. Analyses revealed that OK and UK methods outperformed the IDW method, and UK performed better than OK. RBF also performed better than IDW and OK. IDW and RBF methods slightly underestimated and both the kriging methods slightly overestimated the prediction of water table depth. OK, RBF and UK yielded 27.52, 27.66 and 51.11 % lower RMSE, 27.49, 35.34 and 51.28 % lower MRE, and 14.21, 16.12 and 21.36 % higher R 2 over IDW. The isodepth-area curves indicated the possibility of exploitation of groundwater up to a depth of 20 m.