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The Gravity Recovery and Climate Experiment (GRACE) satellite provides valuable data to monitor groundwater variation. This study investigates groundwater dynamics in India during deficit and excess monsoon years. It finds possible interactions by exploring how groundwater levels respond to meteorological and hydrological conditions. Groundwater anomalies (GWA) are estimated using Terrestrial Water Storage Anomalies (TWSA) from GRACE and hydrological parameters from the Global Land Data Assimilation System (GLDAS). The statistical analysis reveals that the standard deviation is higher for hydrological parameters in summer (June to September), whereas it is higher in fall (October to November) for GWA in many parts of India. The modulation in hydrological parameters subsequently impacts GWA during the following seasons. The study reports increased groundwater across many parts of India during fall. However, groundwater decline is closely linked to unsaturated soil moisture from fall to winter (December to February). Groundwater storage is at its lowest levels during the following spring (March to May) over India. Four deficit and three excess summer monsoons occurred from 2002 to 2022. Composite analysis of GWA reveals that there is replenishment (depletion) of groundwater during the following fall and winter in excess (deficit). The analysis based on extreme deficit monsoon years (2002, 2009) and excess monsoon year (2019) reveals that during the deficit years, groundwater recharge is less, and excess monsoon year it is more; and is vice versa for GWA. The study reports decline in GWA during the summer 2019, which is attributed to the hydrological conditions of the preceding year and modulation of the hydrological processes. As climate variability and water scarcity become increasingly pressing issues, understanding the relationships between hydrological factors and groundwater dynamics is essential for ensuring sustainable water use and resilience to extremely varying climate conditions. [ABSTRACT FROM AUTHOR]

Temporal gaps in the Gravity Recovery and Climate Experiment (GRACE) and GRACE–FO missions pose difficulties in analyzing spatiotemporal variations of terrestrial water storage (TWS) anomalies over Indian river basins. In this study, we developed a deep learning-based CNN–LSTM model to address these temporal gaps by integrating GRACE–TWS with other meteorological variables. The model achieved a strong Pearson's correlation coefficient (median of 0.96 in training, 0.92 in testing), high Nash–Sutcliffe efficiency (0.91 in training, 0.85 in testing) and low normalized root-mean-squared error (0.064 in training, 0.098 in testing) when compared to the original GRACE–TWS. Moreover, a comparison with two publicly available global datasets suggests the superior performance of CNN–LSTM in predicting TWSA (terrestrial water storage anomalies). The study also highlighted potential biases up to 2 cm/yr in long-term TWSA trends due to temporal gaps in GRACE/GRACE–FO. Additionally, the estimated TWSA matched well with in situ wells across majority of the Indian river basins. The findings revealed significant groundwater depletion in the northern and northwestern river basins but positive trends in the central and southern basins in India. Overall, the estimated TWSA product developed in this study provides continuous data records and valuable insights into long-term trends in groundwater storage, making it useful for groundwater monitoring. [ABSTRACT FROM AUTHOR]

Extreme flood events have been recorded recently in the Mahanadi River basin in India with a high destructive potential that causes large social and economic damages. Because fewer hydrometeorological stations can record the flood magnitude in the basin, exploring new datasets like Gravity Recovery and Climate Experiment (GRACE) becomes important to overcome the barriers of assessing the hydrological extremes. The study estimates the flood potential using the GRACE-based terrestrial water storage (TWS) and analytical hierarchy process (AHP)-based topographic flood susceptibility to model the non-stationary flood frequency. During extreme flood events, the magnitude of the combined flood potential index (CFPI) is high (CFPI > 0.6), which correlates with higher river discharge. The CFPI value for the 2012 flood event with a discharge of 11,000 m3/sec (corresponds to a 35-year return period) is recorded at 0.67. Likewise, the CFPI for the flood event in 2011, which corresponds to a return period of 17 years, also stands at 0.63. The overall correlation between the discharge values of various flood events and CFPI values is above 0.8 for all locations, indicating GRACE-based CFPI's applicability for identifying the flood risk for larger basins like Mahanadi. Furthermore, on integrating CFPI as a covariate in non-stationary flood frequency modeling, the study found its superior performance when compared to both stationary models and non-stationary models with time or other climate indices as covariates, thus, helping in accurate estimation of flood return levels that are very useful in the hydrological design of water resources projects. [ABSTRACT FROM AUTHOR]

Climate change is a key threat to biodiversity and ecosystems. The impacts of climate change on vegetation must be evaluated to control the sustainability of the ecosystem. Precipitation and temperature are the most important climatic parameters affecting vegetation growth. It is important to analyze the spatial and temporal variations of vegetation under changing climatic parameters to envisage the response to the regional ecosystem. In this study, variation of the Normalized Difference Vegetation Index over five different agro-climatic zones in the Upper Bhima Sub-basin from 2003 to 2013 was analyzed to find the effect of climatic and hydrological variables on vegetation dynamics. The correlation analysis has been performed by using the Pearson correlation method and Geographical Detector Model. Taylor diagrams are generated to highlight the variation in the correlation values of NDVI with other variables. Results show that precipitation and temperature are key parameters for the growth of the vegetation, but Western Ghat Zone shows contradictory results. To identify the reasons behind contradictory results in the Western Ghat Zone, hydrological parameters such as soil moisture, terrestrial water storage and groundwater levels are analyzed. NDVI shows a positive correlation with precipitation in Water Scarcity Zone, and Assured Rainfall Zone with correlation values 0.37, and 0.462 respectively, but, in the Western Ghat Zone, NDVI has a negative correlation (− 0.38) though more than average precipitation occurs in that region. The result of the Geographical Detector Model reveals that the terrestrial water storage and precipitation are dominant factors affecting vegetation in WGZ and WSZ, respectively. [ABSTRACT FROM AUTHOR]

Droughts frequently occurring in India have significant societal, economic, and environmental effects. The lack of direct measurements of groundwater in location and time hinders quantitative methods to analyse the intricate nature of groundwater drought. This work used the datasets derived from the Gravity and Climate Experiment (GRACE and GRACE-FO) and Global Land Data Assimilation System (GLDAS) to extensively analyse Groundwater Storage changes in the Lower Gangetic Basin (LGB) using unique hydrological parameters between the years 2003 and 2022. The analysis highlights that the GRACE-derived terrestrial water storage anomaly in the LGB decreased significantly (-12.12 mm/yr), and the amount of Groundwater Storage Anomaly (GWSA) decreased similarly (-10.80 mm/yr), while in the GRACE-FO period, a positive trend has been noticed in TWSA (33.96 mm/yr) and GWSA (64.8 mm/yr) respectively. A drought indicator called the GRACE-derived groundwater drought index (GGDI) has been computed for the entire LGB region. A traditional drought study viz. Standardised Precipitation Index (SPI) was performed over LGB to justify the results of the GGDI. The results from GGDI study effectively matched the periods of significant drought occurrences with the 12-month SPI time series. From the GGDI, this study examined groundwater drought's spatial distribution, temporal evolution, and trend (Modified Mann Kendall trend) aspects. According to research findings, the LGB experienced three major drought periods between 2009–2010, 2019 (moderate), and 2015–2016 (severe). The study offers reliable quantitative data on the evolution of GRACE-derived groundwater drought, which may add a new perspective to additional drought research in the densely populated study area, which depends majorly on agriculture, livestock and less skilled water-intensive industries such as leather and textile industries in a sub-tropical climate. This paradigm incorporates changes in groundwater resources caused by human activities and climate change, paving the way for measuring progress towards sustainable use and water security. [ABSTRACT FROM AUTHOR]

A drainage basin morphometric analysis has been carried out for the trans-boundary Duduya watershed located in the marginal parts of the Eastern Himalaya and its foreland of Bhutan and India. The linear, areal and relief morphometric parameters have been estimated based on topographical maps and SRTM DEM data. It is found that the Duduya is a 6th order drainage basin with asymmetric drainage arrangements with a total stream length of 1208.19 km. Almost all of the eleven sub-watersheds of the Duduya are elongated in nature and are characterized by medium drainage related parameters, e.g., density, frequency and texture signifying moderate flood susceptibilities while the presence of permeable soils, good vegetation cover facilitated considerable infiltration and water storage implying good groundwater potentials. The skewed distribution of relief parameters specially total relief, relief ratio and slope are indicators of erosion potential, however, this erosion potential is balanced by the elongated shape of the individual sub-watersheds and medium drainage related parameters. The region receives very high annual rainfall, besides majority of the watershed area is featured with very gentle slopes and flat terrains and therefore has prolonged runoff disposal meaning increased chances of floods in the downstream reaches. Several of the computed morphometric parameters were observed to have varied statistical associations and some of them are impacting each other significantly. A hierarchical cluster analysis suggested two different clusters of sub-watersheds, where SW1 and SW3 of the Eastern Himalayas need proper management for environmental issues like flash flood, channel avulsion and erosion due to high reliefs and moderate slopes, the rest of the sub-watersheds that are draining the lower parts of piedmont and the low-lying southern plain provide ideal conditions for cultivation due to flat terrains, meager slopes, greater infiltration and water storage capacities. [ABSTRACT FROM AUTHOR]

The immense dependence of the growing population on groundwater has resulted in depletion at a fast pace can be seen nowadays. Identifying a groundwater potential zone can be proved as an aid to provide insight to the decision-makers and local authorities for planning purposes. This study evaluated the delineation of groundwater potential zones using integrated remote sensing and GIS approach. Various thematic layers such as geology, geomorphology, lineament, slope, drainage, soil, land use/land cover, and rainfall were considered in this study as these have influence on the occurrence of groundwater and its cycle, and maps have been prepared in GIS domain. Afterward, appropriate weights were assigned to these layers based on multi-criteria decision analysis, i.e., Analytical Hierarchy Process (AHP). Groundwater potentiality has been delineated in different zones (low, moderate, high, and very high) in the study region based on weighted overlay analysis. The study reveals zones with different groundwater prospects viz. low (1.27%), moderate (15.65%), high (75.54%), and very high (7.29%). The ground survey data provided by CGWB (Central Ground Water Board) of nearly 100 wells/dug wells/borewells/piezometers have been used for validation purposes, showing comparable results with the groundwater prospects zones. It also confirms that the majority of these wells fall under very high or high groundwater potential zones. They were also found to be thereby indicating that there is the existence of a permeable reservoir with considerable water storage in the subsurface. One of the most important issues for users and governments is groundwater depletion. Planning for the available groundwater resource is made easier by identifying the potential for groundwater (low to high). [ABSTRACT FROM AUTHOR]

Water storage structures raised on the rivers are subjected to sedimentation. The sedimentation is caused by deposition of eroded sediment particles carried by the streams just behind a dam in a reservoir. In this study, we carried out loss in live storage capacity of Samrat Ashok Sagar Reservoir, Vidisha, Madhya Pradesh, India due to sedimentation using satellite imageries with various combinations of color bands (green, red, blue, near infrared, etc.) and on the basis of degree of reflectance and absorption of particular wavelengths of light. Normalized difference water index (NDWI) derived through the combination of green and NIR bands images have been used to calculate the water spread at various elevations by creating false color composites (FCC). Seven dates of IRS-(R2/P6) L-3 satellite images covering live storage of reservoir in elevation as per the field records collected from the reservoir site have been analyzed using ArcGIS. The resulted sedimentation in the live storage of the reservoir is approximately 46.48 Mm3 for the span of 20 years (1997–2017). The rate of sedimentation in Samrat Ashok Sagar Reservoir is 2.324 Mm3/ year or 0.9% per year. Reservoir silting rate has also been compared with empirical formulas of Khosla's and Joglekar's. [ABSTRACT FROM AUTHOR]

In addition to supplying cooled water, clay pots can also be used to store fruits, vegetables, and even medicines that need to be kept at a moderate temperature. The authors recommended storing perishable things submerged inside the clay pot filled with water in locally accessible polythene bags. In the present paper, a mathematical model to determine the preservation temperature has been developed and validated for the climate of Raipur, Chhattisgarh, India. The convective coefficient between the pot and the surrounding air has been determined. Experiments were performed by loading a pot with apples/tomatoes. It is seen that with a load up to 10 W, the preservation temperature is between 20 and 25°C during summer for the climate of Raipur. The cost of cooling water and storing product is Rs 0.11/kWh (US$0.00146/kWh). The load test reveals that apples can be stored inside for about 8–9 days, whereas tomatoes can be stored up to 7 days inside the pot. [ABSTRACT FROM AUTHOR]

As a natural hazard, drought is a complex multivariate phenomenon that does not depend on only one hydrometeorological variable, as well as, considering a particular kind of drought may not be effective for drought management. Considering this, many multivariate drought indices have been developed based on linearity assumptions or conventional copulas assuming symmetric relationships among univariate drought indices. In this study, D‐vine copula was applied to construct a four‐dimensional index, named as Integrated Drought Index (IDI), by combining four univariate drought indices (Standardized Precipitation Index [SPI], Reconnaissance Drought Index [RDI], Standardized Soil moisture Index [SSI] and Standardized stream flow Drought Index [SDI]) to better reflect many hydrometeorological variables (precipitation, evapotranspiration, soil moisture and stream flow) and different kinds of drought (meteorological, agricultural and hydrological) simultaneously. Vine copula was used to solve nonlinear and asymmetric relationships among drought indices due to its flexibility over the free selection of copula(s) in each step of hierarchical structure in high dimensional modelling. The IDI was constructed for 1‐ and 4‐month timescales for the upper Tapti basin of the central region in India. The performance of IDI was tested with dependence measures (Pearson's correlation coefficient, Mutual Information) and evaluated against the Terrestrial Water Storage Anomaly data derived from the Gravity Recovery and Climate Experiment (GRACE) mission. Spatial analysis of drought was carried out by fuzzy c‐means (FCM) clustering algorithm with IDI. IDI based on vine copula solved the nonlinear and asymmetric relationships among different variables associated with the occurrence of droughts effectively with a reduction of uncertainty as compared to the single drought indices for different kinds of droughts. Analysis revealed spatially different drought risks in the upper and lower river basins. In general, the vine copula addresses nonlinear and asymmetric relationships that exist between the variables associated with natural hazards like drought. [ABSTRACT FROM AUTHOR]

In semi‐arid regions as in India, where agriculture relies on groundwater abstraction, increase of water resources availability through managed aquifer recharge (MAR) or rainwater harvesting (RWH) is often perceived as a major solution. Studies on these structures' efficiency exists but despite the interest, limited information is available on the temporal variation of their replenishment. In a monsoon driven climate, the inter‐annual variations are crucial to assess the potential of water storage and multi‐year management especially for these structures. Here, we aim at developing a methodology to reconstruct water storage of RWH tanks to further improve our understanding on long term efficiency and multi‐years drought management. To tackle this issue, long‐term monitoring of a RWH tank located in Telangana in Southern India is achieved by a combination of field monitoring over 2 years (tanks surface and water levels) and a daily water balance compared to LANDSAT measurements of the tank area. The procedure allows reconstructing the tank filling dynamic over a 14‐years period at a daily time step and show the extreme variability of the tank filling level. During this period, the yearly maximum tank volume ranges from 8650 to ~200 000 m3. On the 14‐years period, the tank reach its maximum capacity only once and, for 1/3 of the time, yearly maximum replenishment is below 15% of its capacity. The surface water availability remains limited in time since the tank dries‐up annually, except for 2 years. However, water percolation to the aquifer is slightly enhanced for some years. During this monitoring period, very few extreme raining events (6) contribute for more than 50% of the collected volume. This observation highlights (1) the dependency of the structure to extreme storm events, (2) the limited capacity for a multi‐year's management and (3) the farmers vulnerability to successive droughts. [ABSTRACT FROM AUTHOR]

Because of changing climatic conditions, uneven distribution of rainfall occurs throughout India. As a result, dependence on groundwater for irrigation has increased tremendously for industrial and domestic purposes. In India approximately 89% of agricultural demands are met through groundwater. Due to increases in population, demand for groundwater and lack of effective utilization have resulted in rapid depletion of groundwater in most parts of the country. Therefore, quantifying groundwater resources is a serious concern in populated states of India, because it is now difficult to supply enough water to every citizen, and will remain so in the future. Because of difficulties in accessing observation data, researchers have begun to depend on satellite-based remote sensing information to deal with groundwater variations. The present study deals with filling the data gap between Gravity Recovery And Climate Experiment (GRACE) and GRACE Follow On (GRACE FO) missions using multilayer perceptron's (MLPs) during 2017–2018 to obtain a continuous terrestrial water storage anomaly (TWSA) series from 2003 to 2020 for Telangana state, India. The MLP model performed well in predicting the TWSA, with a correlation coefficient of r = 0.96 between modeled TWSA and GRACE TWSA during the test period. Telangana state observed negative TWSAs (annual) in the years 2003, 2004, 2005, 2009, 2012, 2015, and 2016–19. This TWSA series (2003–2020) was then used to evaluate regional groundwater storage anomalies (GWSAs) in Telangana state, which is considered to be one of the water stress regions in India. The TWSAs were converted to GWSAs using Global Land Data Assimilation System (GLDAS) parameters. The Telangana state experienced decreasing GWSA in the years 2005, 2009, and 2012, and from 2015 to 2019, leading to severe droughts. Groundwater well measurements were obtained from the Central Groundwater Board (CGWB) and converted to GWSA at a seasonal scale. The GWSAs obtained from GRACE (GWSAGRACE) were converted to seasonal values and compared with GWSAs obtained from observation well data (GWSAobs). The performance metrics of r = 0.74, RMSE = 5.3, and NSE = 0.62 were obtained between (GWSAGRACE) and (GWSAobs), representing a good correlation among them. Over the past decade, Telangana state has significantly relied on groundwater resources for irrigation, domestic, and industrial purposes. As a result, evaluating groundwater storage variations at a regional scale may help policy makers and water resource researchers in the sustainable utilization and management of groundwater resources. [ABSTRACT FROM AUTHOR]

We analyze the periodic and stochastic/random dynamics in the water storage changes at Visakhapatnam, Andhra Pradesh, India. We used time-variable gravity data in terms of Equivalent Water Thickness (EWT) measured from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On satellite missions for the period 2002 to 2021 along with average rainfall data to assess the natural and anthropogenic impacts on water storage changes. We employ Wavelet Spectrum and Singular Spectrum Analysis (SSA) methods to analyze the non-stationary variation of spectral power and principal components. The water storage in the study area shows a significant positive trend with a peak correlation of 0.52 with the rainfall data at a lag of 3 months. The first, second, third, fourth, and fifth principal components depicting the monotonic trend and oscillations together contribute 69.48% to the total water storage changes. The wavelet spectrum of the SSA reconstructed signal from the first four principal components revealed non-stationary annual and 1.3 to 8 years periodicities associated with natural solar and El-Nino Southern Oscillations (ENSO) respectively. The phase plot of the residual signal of ~ 30% variance suggests the random dynamics. Thus the study suggests: (i) an increasing groundwater trend in the study area, (ii) nearly 70% of the water storage changes are linked with natural solar and ENSO variations, and (iii) 30% of water storage changes are with random dynamics possibly linked with anthropogenic activities and catastrophic climatic episodes of shorter duration at Visakhapatnam, Andhra Pradesh, India. [ABSTRACT FROM AUTHOR]

The present study intended to assess groundwater storage dynamics (GWS) and identify potential zones using the Multi-Criteria Decision Making (MCDM) method and geospatial technology in the Murshidabad district of West Bengal, India. The study district is located in the Ganga–Padma–Bhagirathi rivers' floodplain and covers approximately a 5324 km2 area, comprising 26 blocks in five sub-divisions. The study portrayed a quantitative investigation of the pre-monsoon and post-monsoon season's variability of GWS from 2000 to 2020, taking Landsat TM/Landsat 8 OLI/SRTM satellite data. The geo-spatio-temporal analysis of groundwater storage variability for 20 years was carried out by such remotely sensed data with the geospatial method to portray the dynamics and uncover the potential zones of GWS using various cartographic and statistical techniques. We determined nine parameters for the study, and the analytical hierarchy process (AHP) method was employed for the computation. The present estimation and assessment include the MCDM method, covering assorted parameters and the variations and aspects of GWS in the pre- and post-monsoon seasons from 2000 to 2020. The outcome illustrates that a decline in water storage has taken place in most of the blocks of Murshidabad district on average during the study period, which indicates a water stress provison in the near future. However, the micro (block)-level scenario of the spatiotemporal dynamics of GWS and the potential zonation in the Murshidabad District were investigated to form a location-specific micro-level arrangement for the sustainable management of water. [ABSTRACT FROM AUTHOR]

Climate change remains one of the main problems of the century which causes abrupt change in metrological phenomena. Hydrological drought assessment is very critical for ungauged catchments and important for the water storage and management of the reservoir. The research analyses the temporal variation of the drought events in Kolar River basin located in Madhya Pradesh state, India. Also, critical watershed is also identified which suffers most of the drought events. To accomplish this, four drought indices, namely, Standardized Precipitation Index, Reconnaissance Drought Index, and Rainfall Decile, sand Modified China Z-Index, are used for the analysis. Rainfall from three rain gauge stations, namely, Birpur, Brijesh Nagar, and Ichhawar, from the sites were collected from the site ranging from 1988 to 2018 for thirty years. The contemporary research can be treasured source of scientific basis of policy formation and decision of stakeholders involved. Also, the analysis indicates the changing trends in rainfall patterns of the basin which affects the storage and preventive measures to be incorporated in the basin for the future availability of water for agricultural purposes and ever-growing domestic use water demand. It shows based on analysis that middle region of Kolar river basin is more vulnerable to drought in recent years. [ABSTRACT FROM AUTHOR]

Groundwater is the second largest store of freshwater in the world. The sustainability of the ecosystem is largely dependent on groundwater availability, and groundwater has already been under tremendous pressure to fulfill human needs owing to anthropogenic activities around various parts of the world. The footprints of human activities can be witnessed in terms of looming climate change, water pollution, and changes in available water resources. This paper provides a comprehensive view of the linkage between groundwater, climate system, and anthropogenic activities, with a focus on the Indian region. The significant prior works addressing the groundwater-induced response on the climatic system and the impacts of climate on groundwater through natural and human-instigated processes are reviewed. The condition of groundwater quality in India with respect to various physicochemical, heavy metal and biological contamination is discussed. The utility of remote sensing and GIS in groundwater-related studies is discussed, focusing on Gravity Recovery and Climate Experiment (GRACE) applications over the Indian region. GRACE-based estimates of terrestrial water storage have been instrumental in numerous groundwater studies in recent times. Based on the literature review, the sustainable practices adopted for optimum utilization of groundwater for different purposes and the possible groundwater-based adaptation strategies for climate change are also enunciated. [ABSTRACT FROM AUTHOR]

Heterogeneity in lithological and structural characteristics results in variation of specific yield (Sy) value in spatial domain. It also depends upon degree of saturation of aquifer. This imparts temporal variation in Sy value in an aquifer. Bonasuria micro-watershed of Damodar river-basin in India is selected to undertake the study of estimation of temporal variation in Sy based upon monthly ground water budgeting for three non-monsoon months. Sy value gradually changes with progression of summer months. Average specific yield value has been estimated as 0.002593 in March and 0.001446 in April. Determined specific yield values indicate low water storage capacity of the shallow aquifer system. This highlights the need of efficient water management for sustainable development of the area. Present study indicates that this can be achieved through storing the effluent seepage going out of the micro- water shed system as base flow. By constructing appropriate water storage structure at the mouth of the water shed and diverting the same back to the aquifer through suitable means is expected to rejuvenate the aquifer system. Holistically this intervention will lead towards development of sustainable dry-season agricultural practices in the study area. [ABSTRACT FROM AUTHOR]

Tropical reservoir ecosystems cover more than 3.51 million ha in India which are the major sources of fish production from inland open waters and supports rich diversity of fish. The present study quantifies fisheries enhancement and evaluates the impact of stocking of Indian major carp fingerlings in six large reservoir ecosystems of India. Analysis of time series data revealed a significant increase (p < 0.05) in fish yield from 12.3 kg ha−1 year−1 in 2004–2005 to 52.4 kg ha−1 year−1 in 2016–2017 due to stocking. The average fish yield of these six reservoirs was estimated to be higher than the national average of 33 kg ha−1 year−1 recorded for large Indian reservoirs. Fingerling stocking had a significant positive impact on fish yield (r = 0.238, p = 0.035). The reservoir water storage level was positively correlated (r = 0.621, p < 0.05) to fish production. The study also shows that the reservoir habitat support 99 finfish species in the central Indian reservoirs of which two species belong to endangered category warranting conservation efforts. This study is the first of its kind on assessing the impact of stocking in large number of tropical reservoirs including the largest reservoir in the country revealing positive effect on fish yield. The fish yield of 85.8 kg ha−1 year−1 obtained in Gandhisagar reservoir (72,300 ha), India revealed that fisheries enhancement is effective and remunerative. The study also highlights the global status of stocking impact in large reservoirs and deliberates issues and suggests management strategies for sustainable fisheries enhancement in large tropical reservoirs. [ABSTRACT FROM AUTHOR]

Background: Western Rajasthan in India has a typical desert climate. Until the introduction of the canal water irrigation system, malaria was an unstable and seasonal occurrence. Due to the scarcity of water, the community practised having one large underground tank (locally known as the tanka) in their house to collect rainwater for long-term household use. Anopheles stephensi, one of the major malaria vectors, breeds in improperly covered "tankas" if not properly covered and harbours a vector population throughout the year. Methods: Two villages, Ajasar (intervention) and Tota (control), with similar ecological features, were selected for the study. A pre-intervention survey was carried out in both villages to assess the presence and quality of lids of tankas, and mosquito breeding and adult mosquito density. Awareness of the community about malaria and mosquitoes was also assessed during the pre-intervention period. In the intervention village, damaged or improper lids were replaced with improved mosquito proof polyvinyl chloride plastic (PVC) lids and lasted longer than the conventional lids. The fitness of the lids was assessed one year after the pre-intervention survey. The entomological assessment was carried out in both intervention and non-intervention villages. The level of community awareness about malaria, mosquitoes, their breeding places, and the role of tankas in malaria transmission was assessed both during pre- and post-intervention. Results: During the pre-intervention survey,Anopheles breeding was found in 22.1% (58/262) of tankas in the intervention village and 27.1% (19/70) in tankas in the control village. Mosquito breeding was observed in the tankas with iron lids in the intervention village (48.3%) and the control village (42.1%). In the intervention village, out of 262 tankas in the village, 200 lids were replaced, resulting in the complete absence of mosquito breeding. In the pre-intervention survey conducted in May 2018, Anopheles stephensi consisted of 46% of adult mosquitoes in the intervention village and 55% in the control village. Its density was significantly reduced to 0.55 per man-hour (94.95%) and 0.22 per man-hour (97.8%) in the post-intervention survey in June 2018 and a follow-up survey in May 2019, respectively, in the intervention village. Discussion: The density of Anopheles stephensi adults was reduced significantly (97.8%) in the intervention village due to complete prevention of breeding in the underground tankas in the intervention village as compared to the control with no density reduction. The awareness level of the community was also improved due to their involvement in the study. Conclusion: Provision of proper metal lids or replacement of damaged lids on underground water storage tanks as an environmental management approach prevented the breeding of the malaria vector, Anopheles stephensi, in a desert village in western Rajasthan. [ABSTRACT FROM AUTHOR]

The Earth's gravity field measurements and their applications for resource exploration and geodynamic studies form an important part of geophysical studies initiated at the CSIR-National Geophysical Research Institute (CSIR-NGRI) since its inception. Finite Element analysis for regional-residual separation, scaling attributes of the source distribution, together with the mathematical formulation to density distribution in sedimentary basins have transformed the interpretation of gravity data. Collection, collation, and standardization of terrestrial gravity data have led to the compilation of the Gravity Map Series of India. Analyses of these data with contemporary computational technologies help in deciphering better-resolved density models under different parts of the Indian plate. These studies have provided well-constrained models of active and ancient continental collision zones, magmatic underplating beneath large igneous provinces, an integrated lithospheric density structure of Dharwar and Singhbhum cratons, the evolution of passive continental margins of India, and estimation of the effective strength of the Indian lithosphere. The studies on temporal gravity changes from terrestrial and satellite observations are also carried out to infer the redistribution of mass in the earthquake-prone regions and water storage variabilities over India. Recently, moving-platform gravity gradiometry has been introduced by the Institute in India. The gravity studies have continued to be a vital component of an integrated geophysical approach adopted by CSIR-NGRI for shallow and deep earth explorations. [ABSTRACT FROM AUTHOR]

Long-term droughts significantly impact surface and groundwater resources in India, however, observed changes in major river basins have not been well explored. Here we use Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) at three different time scales (24, 48, and 60 months) to identify long-term droughts in India for the observed record of 1951–2015. Drought characteristics (extent, events, frequency, and intensity) are analyzed for different river basins in India. Increasing trend in the areal extent of droughts is observed in two methods with three time scales in the maximum area (63.66%) in India. We use the data from the Gravity Recovery and Climate Experiment (GRACE) to estimate the changes in the terrestrial water storage (TWS) during the period 2002–2015. We identify that major long-term droughts in India occurred from 1966 to 1969, 1972, 1986–1987, and 2002–2004. The all-India average TWS shows a negative trend from 2002 to 2015 with prominent decline in north Indian river basins and positive trend in south Indian river basins. SPI and SPEI at longer time scales are positively associated with TWS indicating the adverse impacts of droughts on surface and groundwater resources in such a populated region. [ABSTRACT FROM AUTHOR]

Six rivers flow from Indian Occupied Kashmir (IOK) to Pakistan, a water source for millions of people in Pakistan and northwestern India. The distribution of rivers water emerged as a bone of conflict between India and Pakistan shortly after the partition of the Sub-continent. Since then, multiple agreements have been signed between two nuclear power countries to solve the water sharing issue. Finally, with the cooperation of the World Bank, on October 19, 1960, Indus Water Treaty (IWT) was signed between Indian and Pakistan in Karachi, and the problem stood resolved. However, time and again, India has been violating the Treaty. The crisis became serious when India managed to deprive Pakistan of its share. India built up the Bhakara dam and barrage to control the water flow to West Pakistan. Pakistan protested vehemently against it and brought the matter to the notice of the world. After the international community's involvement, both countries were brought to the table to negotiate the issue, but in vain. The study aims to develop an understanding of hydro challenges and Indian violation of IWT by constructing multiple dams on the rivers in the share of Pakistan. The Indian prime minister's recent statement that blood and water cannot flow altogether and bluntly threat of abrogation of IWT has created a new escalation of hydro clash in the region. To strategize its policy options, it is the need of the hour to engage academic discourse. Pakistan requires to enhance water storage capacity abruptly. [ABSTRACT FROM AUTHOR]

• Anthropogenic water regulation (AWR) has incorporated into the CIESM model. • The worldwide TWS simulation results improve with AWR incorporation. • The impact of AWR on regional hydroclimate change is significant. This study examines the impact of anthropogenic water regulation (AWR) on hydroclimatic systems by incorporating an AWR module into the Community Integrated Earth System Model (CIESM), validated against GRACE satellite data. This approach assesses the influence of human activities, including irrigation and groundwater extraction, on global and regional hydrology and climate. Key findings include: Implementation of the AWR module significantly improves terrestrial water storage (TWS) simulation accuracy in CIESM. The correlation coefficient for global-scale TWS improved from 0.33 in the control (CTRL) to 0.89 in the experiment (EXP). Notably, the model's performance enhanced in Northern India and the North China Plain, while the Central United States showed limited improvement. AWR markedly alters the global water cycle, evidenced by substantial increases in soil moisture (about 0.04 to 0.02 m3/m3) and evapotranspiration. These changes have led to increased latent heat flux (around 5 W/m2) and a decrease in temperature by 0.1 °C to 1 °C in heavily irrigated regions. The study highlights the role of AWR in modifying the energy balance, particularly in agricultural areas where irrigation exerts a significant cooling effect. Despite its potential, the study identifies considerable uncertainties in coupling AWR within the CIESM model, related to inherent model limitations, incomplete water intake data, variable groundwater levels, and simplifications in water transfer parameters. Future research should aim to refine these aspects, focusing on enhancing the physical mechanisms and performance of AWR modules in hydroclimatic simulations. In conclusion, this research underscores the substantial modifications in hydrological and climatic conditions due to human activities. The improved AWR scheme within CIESM provides valuable insights for understanding and predicting climate change impacts on water resources, demonstrating its utility in simulating complex hydroclimatic changes at both global and regional scales. [ABSTRACT FROM AUTHOR]

The advent of Gravity Recovery and Climate Experiment (GRACE) has opened the doors for remote monitoring of gravitational changes and its derivatives across the globe, but received less attention due to poor spatial and temporal representation. Statistical models of varying complexity are commonly employed to downscale the GRACE datasets for use with local to regional applications. This study presents the application of two commonly employed machine learning models, multi-linear regression (MLR) and random forest (RF), in spatially downscaling (from 1° to 0.25°) the GRACE-derived terrestrial water storage anomalies (TWSA) by establishing a correlation with various land surface and hydroclimatic variables. The downscaled TWSA was further converted into groundwater storage anomalies. Applicability of the proposed methods was tested on four contrasting hydrogeological basins of India. For each basin, the significant predictor variables were considered to establish the relations. Seasonal groundwater levels observed in 236 wells during 2006–2015 were used for method validation and accuracy assessment. We observed a close match between GRACE-derived groundwater levels and the measurements for three of the four basins (r = 0.40–0.92, Root mean square error (RMSE) = 3.6–10.5 cm). Our results indicate that the predictor variables to downscale TWSA should be considered cautiously based on the hydrogeological, topographical, and meteorological characteristics of the basin. [ABSTRACT FROM AUTHOR]

In this study, advanced scatterometer (ASCAT) soil moisture data is employed to compute the basin water index (BWI) over six river basins of India for 10 years (2007–2016). The BWI time series is assessed for the development of its relationship with observed streamflow. Further, a popular ensemble learning technique, random forest, is employed to compute the 10-d streamflow using the BWI time series. Moreover, the results are compared with the classical rainfall–runoff model forced with satellite-based precipitation and evapotranspiration, BWI–rainfall–runoff model, and Global Flood Awareness System (GloFAS). The performance of the model is evaluated in terms of multiple efficiency measures, viz. Nash-Sutcliffe efficiency (NSE), correlation coefficient (R) and root mean square error (RMSE). The results reveal the BWI–rainfall–runoff model is the most accurate model for prediction of discharge. The performance of the BWI–rainfall–runoff model is very good over four of six catchments and good to satisfactory over the remaining two catchments. [ABSTRACT FROM AUTHOR]

The study interprets the effect of seasonal (pre-, co- and post-monsoon) hydrological loading due to the Ganga river basin over the seismicity and geodetic deformation in the Garhwal Himalayan region. Geodetic data from six cGPS sites are used, three sites out of six are established in the Himalayan region, one is located in the Ganga basin and two sites are located in the Indian shield. First, we estimated the average seasonal variation in GRACE-derived TWS of entire India for the period of 2002–2016. It is observed the seasonal effect over TWS (Terrestrial Water Storage) due to hydrological fluctuations in the Indo-Gangetic Plain (IGP). It has also been noticed that the geodetic velocities for both the North and East components are more in pre-monsoon than post-monsoonal season. Whereas the vertical component in cGPS sites of Himalaya (DEHR and MAND) agrees to the hypothesis of upliftment during post-monsoon and subsidence in pre-monsoon. TWS mass change is detected high during the co-monsoon (2.32 × 104 km3) and it is observed low −2.22 × 104 km3 (in pre-) and −8.13 × 103 km3 (in post-) monsoon seasons respectively. GPS measured horizontal displacement agrees with seasonal loading but it contains some anomalous behaviour, which may be the result of surface hydrological mass movement or the effect of the Gorkha earthquake, 2015, however an inverse relation between vertical geodetic displacement and loading have been observed. The average strain rate values over cGPS sites during 2016–2018, are more negative in post-monsoon than in pre-monsoon which means that plate movement is highly compressional. We have also inferred a significant role of loading over the seismicity and linear strain rate, which increases with decreasing hydrological loading in the Ganga river basin and vice versa. [ABSTRACT FROM AUTHOR]

Groundwater is rapidly depleting in India primarily because of pumping for irrigation. However, the crucial role of crop growth at annual and seasonal time scales in groundwater storage variability remains mostly unexplored. Using the data from the Gravity Recovery Climate Experiment (GRACE) satellites and well observations, we show that crop growth is negatively correlated with groundwater storage at annual and seasonal time scales in north India. Precipitation is positively associated with groundwater storage variability at the yearly time scale in north-central India (NCI) and south India (SI). In contrast, precipitation is negatively correlated with groundwater storage from the GRACE satellites in northwest India (NWI). The negative correlation between precipitation and groundwater from the GRACE in NWI is primarily due to groundwater depletion due to anthropogenic pumping from deep aquifers. Precipitation and groundwater storage from the well observations are positively correlated in all the three regions, indicating the influence of precipitation on shallow aquifers. Analysis of the two main crop growing seasons (Rabi and Kharif) showed that crop growth is negatively related to groundwater storage in both Kharif (June–September) and Rabi seasons in north India (NWI and NCI). Groundwater contributes more than precipitation in NCI during the Kharif season and in NWI and SI during the Rabi season. Granger's causality test showed that groundwater is a significant contributor to crop growth in NWI and NCI in both Kharif and Rabi seasons. Our results highlight the need for agricultural water management in both the crop growing seasons in north India for reducing the rapid groundwater depletion. [ABSTRACT FROM AUTHOR]

Rapid groundwater depletion due to anthropogenic pumping for irrigation poses enormous challenges on socio‐economic, agricultural, and financial spheres of India. However, the role of groundwater depletion on flood potential in India remains unexplored. We examine the role of changes in terrestrial water and groundwater storage on flood potential using in situ and Gravity Recovery and Climate Experiment (GRACE) satellites observations and the simulations from the Variable Infiltration Capacity (VIC) model. Terrestrial Water Storage (TWS) has declined significantly (p value <0.05) with a rate of −0.63 cm yr−1 during 2002–2016 in the Indian subcontinent. Ganga, Brahmaputra, Indus, Brahmani, and Subernarekha river basins experienced a significant decline while Godavari, Mahi, Tapi, and Narmada basins witnessed a substantial increase in TWS during 2002–2016. The relative contribution of TWS on flood potential is higher than precipitation for the majority of the subcontinental river basins. The significant increase/decline in TWS in the subcontinental river basins is driven by the changes in groundwater storage either due to groundwater pumping or natural variability in climate. A significant decrease (increase) in the flood potential in Ganga, Brahmaputra, and Indus (Godavari, Narmada, and Tapi) is linked to the changes in groundwater storage, which shows the influence of groundwater storage variability beyond water and food security in the region. Key Points: Terrestrial Water Storage (TWS) has declined significantly (p value < 0.05) with a rate of −0.63 cm yr−1 during 2002–2016 in the Indian subcontinentThe relative contribution of TWS on flood potential is higher than precipitation for the majority of the subcontinental river basinsA significant decrease in the flood potential in Ganga, Brahmaputra, and Indus is linked to groundwater depletion [ABSTRACT FROM AUTHOR]

Six rivers are flowing from Indian occupied Kashmir (IOK) to Pakistan, a water source for millions of people in Pakistan and northwestern India. Distribution of rivers water emerged as a bone of conflict between India and Pakistan shortly after the Sub-continent partition. Since then, multiple agreements have been signed between two nuclear power countries to solve the water sharing issue. Finally, with the World Bank's cooperation, on October 19, 1960, Indus Water Treaty (IWT) was signed between Indian and Pakistan in Karachi, and the problem stood resolved. However, time and again, India has been violating the Treaty. The study aims to understand hydro challenges and Indian violation of IWT by constructing multiple dams on the rivers in Pakistan's share. The Indian prime minister's statement that blood and water cannot flow altogether and bluntly threaten abrogation of IWT has created a new escalation of hydro clash in the region. To strategise its policy options, it is the need of the hour to engage academia discourse. Pakistan requires to enhance water storage capacity abruptly. [ABSTRACT FROM AUTHOR]

Underground surge pool cavern for the storage and lifting of water is being constructed in the part of Telangana State of India. For better rock mass characterization and support design, 3D engineering geological mapping was carried for the heading portion of the surge pool. 3D geologic mapping of heading portion is very important for large underground cavern to know about the cavern behavior during benching down. The direction of the longest axis of the cavern was finalized based on the in-situ hydrofracturing testing inside the deep borehole. The assessment of tunnel quality index 'Q' for the exposed granitic rock mass was done based on the information available of the rock joints and their nature, 3D geological mapping and in-situ stress measurement. Roof support and wall support pressure was estimatedbased on Q-values, and in this case applicable for the non-squeezing ground condition. For structural stability of crown and walls, rock support arrangement was recommended based on NMT technology and geological conditions of site, which includes steel fibre reinforced shotcrete, grouting, rock bolt and drainage hole provisions. The capacity of support system is determined to evaluate the efficacy of the proposed support system. [ABSTRACT FROM AUTHOR]

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Estuaries being the connecting link between terrestrial and marine environment, experience spatial variations in the hydrographic variables as well as concentrations of pollutants. The present study reports a contrasting difference in the metal tolerance and enzyme activity of particle-associated bacteria (PAB) isolated from the upstream and downstream reaches of a tropical estuary [Cochin Estuary (CE) in the southwest coast of India], exposed to different levels of heavy metal contamination. The upstream of the estuary has been overloaded with heavy metals in the last few decades, while the downstream is less polluted. There were only 25% of culturable PAB phylogenetically common in both upstream and downstream. The PAB isolated from the upstream were dominated by γ-proteobacteria (48.1%) followed by α-proteobacteria (25.0%), while it was in the reverse order of α-proteobacteria (45.9%) and γ-proteobacteria (36.1%) in the downstream. More number of PAB from the upstream showed tolerance to higher concentrations of Zn and Cd. The Acinetobacter sp. MMRF1051 isolated from the upstream showed tolerance up to 250 mM Zn, 100 mM Cd, and 250 mM Ni. The enzyme expression profile of PAB from downstream was in the order of lipase > phosphatase > β-glucosidase > aminopeptidase, while it was in the order of β-glucosidase > lipase > aminopeptidase > phosphatase in the upstream of the estuary. The present study shows the selective pressure exerted by heavy metal pollution on the diversity of culturable bacteria associated with particulate matter in a tropical estuary. Also, the variation in their enzyme activities may impinge the remineralization of particulate organic matter (POM) in the system and may impart adverse impacts on ecosystem functioning. [ABSTRACT FROM AUTHOR]

The Gravity Recovery and Climate Experiment (GRACE) twin satellite provides an efficient method of assessing groundwater anomalies by measuring variations in terrestrial water storage (TWS) and its anomalies (TWSA). The TWS is the sum of all forms of water such as groundwater, soil moisture, surface water and snow water equivalent. We used CSR RL05 Mascon solutions (http://www.csr.utexas.edu/grace) to estimate the seasonal level regional scale groundwater depletion rates across India between 2002 and 2016. The groundwater storage showed substantial spatial variations at the seasonal scale. At the regional scale, our analysis revealed the steepest decline in the northwest and northeast regions of India. This has been caused by a significant increase of land under well and tube‐well irrigation. Furthermore, the rapid rates of urbanization associated with a lower recharge of the groundwater table due to increased runoff also contributed to depleted groundwaters across India. [ABSTRACT FROM AUTHOR]

The present study is undertaken in the eastern coast of India, along the coastal tract of Bay of Bengal (BoB), to delineate the submarine groundwater discharge (SGD)-borne nutrient flux at temporal scale and their impact to coastal ecology and biogeochemical processes. Solutes chemistry, seepage meter study, stable-isotopic signature, and geophysical techniques were used to identify the surface water–groundwater interaction zone, SGD rate and nutrient flux. The estimated rate of major annual discharge of nutrient fluxes were 240 and 224 mM m−2 day−1 for NO3− and Fetot. The variation of solute and nutrient fluxes was depending on the load of terrestrial water masses, which is triggered by the local monsoonal meteoric recharge. The ecohydrological response to this solute flux results in spatio-temporal patterns of N and P-sensitive algal blooms in the intertidal zones. Most algae were identified as dinoflagellates and some haptophytes, with greenish and brownish hue that provides a distinct look to the coastal landscape. The algal blooms were found to be substantially influenced by the seasonal-nutrients flux and discharge location. Our study is expected to increase the understanding of a rarely reported eco-hydrological response to terrestrial–marine water interactions and their implications in the tropical ocean adjoining the Indian Subcontinent. [ABSTRACT FROM AUTHOR]

In present study, a detailed analysis on the rate of sedimentation of Katery lake (Tamil Nadu, India) was performed by using Differential Global Positioning System-based single-beam dual-frequency echo sounder bathymetry technique to find out the amount of sediment deposited over the years and reasons behind the water scarcity to local population. The collected bathymetry data during survey were processed with MATLAB and Surfer software for lake bed surface profile generation to find out the depth of water and deposited sediments, while the volume estimation was carried out by Extended Simpson 3/8 method. Sedimentation analysis was performed over the time interval of 10 years during 2003 and 2013. Herein, it was observed that rate of sedimentation was 3224.8 m3/year and the estimated quantity of deposited silt was 156,327 m3 which are 69% of total water storage capacity of the lake. Therefore, in order to curtail the after-effects of fast sedimentation, the rejuvenation program was executed in the years 2014–2015, to maintain long-term sustainability and performance of the lake. Sediment estimation was validated using numerical analysis and practical dredged volume, which helped in regaining 239% water storage capacity of lake. Thus, the lake rejuvenation program was successfully executed using bathymetry survey analysis for all three phases. [ABSTRACT FROM AUTHOR]

Gravity Recovery and Climate Experiment (GRACE) satellite mission is ground‐breaking information hotspot for the evaluation of groundwater storage. The present study aims at validating the sensitivity of GRACE data to groundwater storage variation within a basaltic aquifer system after its statistical downscaling on a regional scale. The basaltic aquifer system which covers 82.06% area of Maharashtra state in India, is selected as the study area. Five types of basaltic aquifer systems with varying groundwater storage capacities, based on hydrologic characteristics, have been identified within the study area. The spatial and seasonal trend analysis of observed in situ groundwater storage anomalies (ΔGWSano) computed from groundwater level data of 983 wells from the year 2002 to 2016, has been performed to analyze the variation in groundwater storages in the different basaltic aquifer system. The groundwater storage anomalies (ΔGWSDano) have been derived from GRACE Release 05 (RL05) after removing the soil moisture anomaly (ΔSMano) and canopy water storage anomaly (ΔCNOano) obtained from Global Land Data Assimilation System (GLDAS) land surface models (NOAH, MOSAIC, CLM and VIC). The artificial neural network technique has been used to downscale the GRACE and GLDAS data at a finer spatial resolution of 0.125°. The study shows that downscaled GRACE and GLDAS data at a finer spatial resolution is sensitive to seasonal groundwater storage variability in different basaltic aquifer systems and the regression coefficient R has been found satisfactory in the range of 0.696 to 0.818. Article impact statement: Validation of sensitivity of GRACE‐GLDAS data to groundwater storage variations within a basaltic aquifer system by statistical downscaling technique using artificial neural network (ANN). [ABSTRACT FROM AUTHOR]

Estimation of terrestrial water budget at global and regional scales are essential for efficient agricultural water management, flood predictions, and, hydrological modeling. In hydrological modeling, it is a challenging task to quantify the major hydrological components like runoff, evapotranspiration (ET), and total water storage (TWS) due to improper and limited availability of detailed meteorological datasets. Furthermore, there has been no consensus to answer a-decade-long critical question that a less data-intensive models can be an alternate to robust data-intensive models in data scarce conditions. This study aims at multi-model approach over the single models usage for representing the hydrological behaviour in the Kangsabati River Basin (KRB), India. It is done by applying the standard model selection criteria over various hydrological models. Two hydrological models are selected, a semi- distributed model, Variable Infiltration Capacity (VIC-3 L), and a conceptually lumped model, Identification of unit Hydrograph and Component flows from Rainfall, Evapotranspiration and Streamflow (IHACRES). Both models were calibrated against the observed daily discharge at the KRB outlet for the period of 2001–2006 and validated for 2008–2010. The results show that both VIC-3 L and IHACRES produce reasonable runoff estimates at daily and monthly time scale in the KRB. The ET estimates show that VIC-3 L and IHACRES captured the seasonal variations with the percent change of 0.4% and 6.6% respectively. As IHACRES is simpler, parsimonious, fewer parameters, and better performances, it can be useful for hydrological modeling in data-scarce regions. [ABSTRACT FROM AUTHOR]

• An Indian Land Data Assimilation System (ILDAS) is established and ran at 0.1° spatial resolution for a period of 40 years. • The model is able to capture water balance components at monthly and daily scale. • IMD outperformed global precipitation datasets in reproducing streamflow anomalies. Effective management of water resources requires reliable estimates of land surface states and fluxes, including water balance components. But most land surface models run in uncoupled mode and do not produce river discharge at catchment scales to be useful for water resources management applications. Such integrated systems are also rare over India where hydrometeorological extremes have wreaked havoc on the economy and people. So, an Indian Land Data Assimilation System (ILDAS) with a coupled land surface and a hydrodynamic model has been developed and driven by multiple meteorological forcings (0.1°, daily) to estimate land surface states, channel discharge, and floodplain inundation. ILDAS benefits from an integrated framework as well as the largest suite of observation records collected over India and has been used to produce a reanalysis product for 1981–2021 using four forcing datasets, namely, Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), ECMWF's ERA-5, and Indian Meteorological Department (IMD) gridded precipitation. We assessed the uncertainty and bias in these precipitation datasets and validated all major components of the terrestrial water balance, i.e., surface runoff, soil moisture, terrestrial water storage anomalies, evapotranspiration, and streamflow, against a combination of satellite and in situ observation datasets. Our assessment shows that ILDAS can represent the hydrological processes reasonably well over the Indian landmass with IMD precipitation showing the best relative performance. Evaluation against ESA-CCI soil moisture shows that MERRA-2 based estimates outperform the others, whereas ERA-5 performs best in simulating evapotranspiration when evaluated against MODIS ET. Evaluations against observed records show that CHIRPS-based estimates have the highest performance in reconstructing surface runoff and streamflow. Once operational, this system will be useful for supporting transboundary water management decision making in the region. [ABSTRACT FROM AUTHOR]

• Large-scale TWS assimilation improves model performance. • Data assimilation captures negative trends in TWS, soil moisture, and ET. • Anthropogenic contribution to TWS trend marginally increases with assimilation. Terrestrial water storage (TWS) encompasses various components such as snow water, surface water, canopy water, soil water, and groundwater. Therefore, TWS is strongly affected by several factors including climate change, floods, drought, and anthropogenic activities. Predicting and quantifying TWS is critical in understanding terrestrial water cycles, as well as for managing water resources at the regional and global scale. TWS can be monitored with the Gravity Recovery and Climate Experiment (GRACE) satellites and estimated using land surface models (LSMs) on various spatial scales. The present study demonstrated how large-scale TWS data assimilation affects model performance by assessing the variations in TWS and related hydrological variables. Moreover, unlike traditional physical-based models, the assimilation of TWS data into an LSM enabled the assessment of anthropogenic impacts. TWS data from GRACE was assimilated into the Community Land Model version 5 (CLM5) with the CLM5-BGC biogeochemistry module covering the East Asia region. The model was forced using 40-ensemble meteorological forcing data from 2003 to 2010 and GRACE TWS data were assimilated using the ensemble adjustment Kalman filter (EAKF). Data assimilation markedly improved the performance of the model, as demonstrated by a decrease in the root mean square error from 0.71 mm/month in the free run (FR) without data assimilation to 0.48 mm/month in the data assimilation (DA) run, in addition to an increase in the correlation coefficient from 0.55 in FR to 0.69 in DA. Additionally, unlike the FR model, the DA model effectively captured the observed negative trends of the TWS, soil moisture, and evapotranspiration in Northern India and the Northern China Plain. Finally, our findings also demonstrated that the anthropogenic contribution to the negative trend of the TWS over Northern India and Northern China Plain was marginally increased in the DA model compared to the FR model. Collectively, our findings demonstrated that TWS data assimilation enables a more realistic evaluation of the long-term and large-scale changes in hydrologic variables. [ABSTRACT FROM AUTHOR]

Among the As Cryptosporidium is a parasite please modify bacterial to non-viral agents, Vibrio cholerae, Cryptosporidium spp., Shigella spp., non-typhoidal Salmonella spp. and diarrhoeagenic Escherichia coli have been documented[[1]],[[9]]. Six of the 46 specimens showed yellow-coloured colonies on TCBS agar plates and were confirmed as V. cholerae O1 Ogawa by slide agglutination test using type-specific antiserum. Cholera is an acute diarrhoeal disease caused by ingestion of toxigenic strains of V. cholerae serogroups O1 and O139 in contaminated water or food. By definition, cholera is endemic when the causative organisms reside in the local environment and the occurrence of the disease in humans is not dependent on the importation of cholera from outside[[9]]. [Extracted from the article]

It has been found that the less care is shown while constructing the water retention structures as compared to the amount of care shown in designing for it. This is more often in earthen embankments, where soil properties need to be controlled within the designed limits. The life and stability of embankments are entirely based on the extent to which the design assumptions are achieved in the field. History shows many failures were due to the lack of quality control during construction. In India every year many water storage structures fail, but very few were reported. Till date, only 37 dam failures in India are reported but not appropriately analyzed. This paper is focused on compiling the Indian dam failure list with relevant data which can be used for developing breach parameters equation. The data are collected from Government reports, articles news reports and magazines. This paper is also focused on developing new empirical equations for breach parameters and peak outflow from the dam failure which suits Indian condition. In developing the regression equation for breach depth, average breach width, peak discharge and failure time, different combinations of control variables is highlighted such as the dam height, reservoir capacity, average dam width, dam type, failure mode and dam erodibility. In this study, we incorporate the dam average thickness as another control variable for finding out the breach parameters and found suitable for breach depth calculation. New equations are proposed to compute the peak outflow rate. Further, these equations are compared with other developed regression equations for breach parameters and peak outflows. [ABSTRACT FROM AUTHOR]

Background: Sanitation is the basic & fundamental requirement to maintain good health. Poor sanitation and hygiene are linked to various diseases like, communicable diseases, diarrheal disease, worm infestation, etc., which are preventable. A remarkable reduction in the nations mortality & morbidity rates are possible by adopting sanitation and hygiene practices by the people. Various interventions have been formulated in India to establish proper sanitation and measures to monitor level of awareness among the people and their active participation is very essential. Objectives: To know the Knowledge, Attitude and Practices regarding sanitation and hygiene and their determinants, to know the proportion of population with and without sanitary latrines and to find out the extent of Open-Air Defecation practices and its determinants in the study area. Methodology: A household based cross-sectional study was conducted in the Rural field practice area of a Medical College, Vikarabad from February to July 2018. Out of 488 households in Gottimukla village, 97 houses were earmarked for the study by systematic Random sampling method and information was collected from any resident available at the household at the time of visit. A pretested semi-structured questionnaire was used for data collection. Results: Majority (61.9%) of the participants had knowledge about Swatch Bharat Abhiyan. About 64.9% had better knowledge regarding Sanitation and Hygiene. Nearly 74.2% felt that maintaining good hygiene is important to stay healthy and to be free form sickness. A greater proportion of the study participants (91.8%) were disposing the solid waste in open drains though they had good knowledge and willingness it was not reflected in their practice. Conclusion and Recommendations: The villagers had ample knowledge and positive attitude regarding sanitation and Hygiene, but failed to apply the same in their practice. It can be overcome with repeated Awareness programmes to the target population. [ABSTRACT FROM AUTHOR]

• Computation of a novel Combined Climatologic Deviation Index (CCDI) for drought monitoring. • Comprehensive monitoring and assessment of droughts in India using CCDI. • Spatial and temporal distribution of droughts. • Comparative analysis of CCDI and other commonly used drought indices. Drought is a recurring natural hazard that significantly affects the economy and environment of large areas worldwide. It is therefore imperative to develop techniques that enable comprehensive monitoring and assessment of drought. Here we propose a novel drought index (Combined Climatologic Deviation Index (CCDI)) that encompasses all the aspects of meteorologic, agricultural, hydrologic and human-induced drought occurrences. Critical to the proposed framework is the concept of combining deviations in precipitation and terrestrial water storage, observed by Gravity Recovery and Climate Experiment (GRACE) satellites, from climatologic (normal) conditions as a measure of drought. In order to evaluate the applicability of this new index, it is analyzed over four major river basins in India (i.e. Ganga, Krishna, Godavari and Mahanadi). The propounded drought index (CCDI) has demonstrated its ability to identify drought events and render rational quantification of its severity. Results also depict an improved understanding of holistic drought conditions compared to other available drought indices. Comparison of CCDI with commonly used drought indices highlighted some of the fundamental differences while demonstrating good correspondence with PDSI (r = 0.79) and GRACE DSI (r = 0.94). Further, it is evident that in almost all the river basins there have been at least two drought periods with intensities ranging from D1 (moderate drought) to D4 (exceptional drought). The longest drought period, extending for 36 months, from July 2002 to June 2005, is observed in the Krishna Basin. Results from this study show appreciable reliance on the potential for quantifying droughts using CCDI, which will only improve with better quantification and extended availability of terrestrial water storage observations from the recently launched GRACE-Follow On mission. [ABSTRACT FROM AUTHOR]

Smart water management in a large-scale campus is a good instance of cyber physical system (CPS). For realising this instantiation calls, a systematic framework together with the actual implementation of the associated modules needs to be devised. In this paper, the key issues of monitoring/sensing, networking, and computation parts put forward toward a deployable solution are proposed. Monitoring and Networking involving appropriate sensing and data transmission to monitor the water flow in the storage tanks at National Institute of Technology, Surathkal, Karnataka, India, are worked out to a mature stage. This paper captures essential details of these technical contributions, including necessary customisation and enhancement of the existing technologies. In the direction of addressing the data analytics of the computing part, the issue of imputing the missing values has been considered. An extensive set of results and comparisons obtained by applying different algorithms to the collected data are also presented. The technical contributions of this paper form a strong base toward the CPS realisation in the Campus, resulting in efficient water management when augmented with further analytics and modeling to address scalability. [ABSTRACT FROM AUTHOR]

Highlights • Estimation of total usable groundwater storage (UGWS) in India. • Groundwater storage depletion/replenishment fraction against total availability. • Temporal downscaling of groundwater availability using satellite-based measurements. • Estimates of groundwater availability and change across Indian states. • Agricultural water use intensified in rapid groundwater depleting regions. Abstract Groundwater use in India has been in the limelight in recent years due to its intensive and apparent unsustainable use that poses threats to water security, drinking water supply and food production. Here, we present estimates of usable groundwater storage, for the first time, at the state-level across all of India using both in situ and satellite-based measurements. Groundwater-level data are used from 3907 in situ monitoring wells across India and the total usable groundwater storage (UGWS) is estimated between 2005 and 2013. The UGWS estimates indicates high rates of depletion (>5 km3/yr) of groundwater storage (GWS) in north-east India (i.e. Assam), even though increase in precipitation has been observed in that state. Satellite-based (Gravity Recovery and Climate Experiment, GRACE) estimates indicate that the development of recent GWS-depletion zones is concentrated in unconsolidated sediments or lithotype across the Indus, Ganges and Brahmaputra basins, in the states of Punjab, Haryana, Uttar Pradesh, Bihar, and West Bengal. In contrast, southern and central Indian states (such as Andhra Pradesh, Maharashtra, Gujarat, Tamil Nadu, and Chattisgarh), show replenishing GWS trends. We also find that the states with highest groundwater depletion rates are subjected to water-intensive cropping practices during the study period. We temporally downscale the UGWS with support from GRACE satellite-based measurements. We conclude that the approach we developed here can be applied in other parts of the world to devise management options for sustainable groundwater use. [ABSTRACT FROM AUTHOR]

Since 2002, Gravity Recovery and Climate Experiment (GRACE) satellite has provided monthly estimates of land water storage variations by monitoring time-variable components of earth's gravity field. We present GRACE satellite RL05 gravity data at 1° × 1° resolution to estimate terrestrial water storage change (surface water + groundwater) over India during Indian Summer Monsoon (ISM) and Northeast (NE) monsoon periods for the year 2015. As the NE monsoon was above normal in 2015, groundwater storage has increased significantly. By using GLDAS2.1 (1° × 1° resolution data) land surface state variables, we deduced as to how Terrestrial Water Storage (TWS) is partitioned into canopy water and soil moisture components. By computing storage changes in GRACE TWS, Global Land Data Assimilation System (GLDAS) land surface state variables and by using a terrestrial-based water balance approach, we calculated changes in the groundwater storage. The GRACE data indicate the variation of 15 cm in the TWS during the ISM period over India and a gain of 2.35 cm NE season over Peninsular India. After the ISM season, the groundwater storage was increased by 13 cm over India and 6.45 cm during the NE monsoon over Peninsular India. We also observed a high run-off (sub-surface + surface) rate in both the monsoon periods. The accumulated rainfall over India was estimated as 76.58 cm out of which 33.8 cm was computed as run-off (ISM season). Similarly, the mean rainfall in Peninsu lar India was calculated as 8 cm out of which 3.86 cm was approximated as run-off (NE monsoon season). [ABSTRACT FROM AUTHOR]

To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (−0.07 °C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 °C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R2 = 0.92), although a negative relationship is apparent between LST and vegetation (R2 = −0.83). Additionally, increased LST in the low-elevation parts of the study area impacted PET (R2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana. [Display omitted] • Vegetation change during 2000–2022 is strongly elevation-dependent. • Rainfall increased in higher elevation regions but decreased in the lower altitude plains. • LST increased in the plains but declined in the mountains. • Spatio-temporal variations in driving factors are reflected in vegetation change (EVI). • The relative importance of climate and human activities varies markedly with altitude. [ABSTRACT FROM AUTHOR]

One of the important objectives of water resources planning is to tap the maximum possible water available in the river basin that can be utilized particularly during the period of drought. This can be materialized by creating water storage structures. For this purpose initially, the first task could be the identification of suitable site for creating water storage sites. With the advent of Remote Sensing (RS) and Geographic Information System (GIS) techniques, it becomes easier for water resources planner to identify the suitable location of water storage structure within the basin. Present study demonstrates the identification of suitable location in the upper basin of Sheonath river in Chhattisgarh State, India. Based on the various physical characteristics of the basin, GIS based multi-criteria evaluation technique is being applied to determine the most suitable water storage sites. The suitable sites are assessed by considering the spatially varying parameters. These parameters include potential runoff, hydrologic soil group, land use, lineament, slope, stream order and settlement and basin area. Potential runoff is calculated from Soil Conservation Service Curve Number (SCS-CN) equation. Since, there is more than one parameter; it is significant to determine the importance of one layer over another layer. Analytic Hierarchy Process (AHP) is one of the multi-criteria decision making method resulting in the percentage relative importance. The AHP model consists of three levels objective i.e. suitable site for water storage, the parameter used and the alternatives. In the overlay process of GIS the relative importance determined by AHP is applied to produce suitable locations. Suitability is divided into three categories "suitability level 1", "suitability level 2" and "suitability level 3" representing storage tank, stop dam and check dam respectively. This mapping helps in selecting potential site for water storage structures in the basin. [ABSTRACT FROM AUTHOR]