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The distribution and availability of water resources have been greatly impacted by global climate change and unsustainable human activities. This has resulted in increased pressure on surface water supplies, human consumption and socioeconomic growth. Although water management requires monitoring, a substantial amount of water consumption globally, including both groundwater and surface water, remains unmeasured. Madhya Pradesh (MP) has a very varied semi-arid geographical region in Central India. Recent studies have found that 36 out of 51 districts in the state of MP have been facing severe hydrological drought conditions. Despite the challenges in the MP region, there is little understanding of the permanent and seasonal changes in surface water and the overall availability of surface water resources in each district. Field-based monitoring of surface water bodies in large regions such as MP poses considerable difficulties. However, gaining knowledge about changes in the distribution of water on the Earth's surface across time and space can be enhanced by analysing data obtained via remote sensing. To understand the long-term changes in surface water in different districts of Madhya Pradesh, India, over the past 38 years, we analysed a publicly accessible global surface water dataset provided by the Joint Research Centre (JRC) European Commission. This dataset is based on Landsat imagery and covers the period from 1984 to 2021. This research study examines the associations between variations in the permanent surface water level and the extent of land being irrigated, the intensity of agricultural activities and the seasonal oscillations in surface water for several districts in Madhya Pradesh. The findings from this research will be beneficial for assessing several significant MP districts in terms of their water footprint and sustainable management. [ABSTRACT FROM AUTHOR]

Dams are an integral component of water resources systems and management in the Upper Ganga basin. However, the impact of dam operations on the characteristics of hydrological extremes and their regional spatial pattern is less explored. Based on observational datasets, we studied the changes in the flood and drought characteristics at local and regional scales by comparing them during pre- and post-dam periods. It was observed that the annual frequency of streamflow is missing from the spectral representation of daily streamflow at the Tehri catchment during the post-dam period. The dam operation has reduced the flood peaks but increased their duration and volume, and the dam has influenced the variability in drought duration, intensity, and deficit. The operation of dams has changed the timing and strength of seasonality of these extremes. Ultimately, the dam has increased the risk of regional occurrences of droughts and minimized the risk of floods. [ABSTRACT FROM AUTHOR]

This study examines the proportional contribution of snow/ice melt, rainfall, and groundwater to Sutlej River discharge at various locations. Sutlej River is a major tributary of the Indus River system and an important water supply source for irrigation through the canal network in northwest India. Here, we used hydrograph separation and associated uncertainty and applied the snowmelt runoff model (SNOWMOD) to estimate the contribution from different water sources to the Sutlej River. We used δ18O and electrical conductivity values of different waters for the hydrograph-separation approach. The first-order Gaussian error propagation and Monte-Carlo simulation are used to assess the accuracy. The estimated contribution at Rampur is ~ 62.7% (snow/ice melt), 18.7% (rainfall), and ~ 18.4% (groundwater); for Ropar is 59 ± 2% (snow/ice melt), 23 ± 2% (rainfall), and 18 ± 2% (groundwater); and for Yusufpur, 25 ± 3% (snow/ice melt), 39 ± 3% (rainfall), and 36 ± 2% (groundwater) during July–December 2013. The findings from the hydrograph-separation and SNOWMOD analysis established a fundamental understanding of the hydrological processes in the Sutlej River system, providing valuable baseline data essential for developing sustainable water resource management strategies. [ABSTRACT FROM AUTHOR]

The west‐central Himalayan River basins face significant damage caused by extreme floods annually. We selected the upper Ganga basin (UGB), the west‐central Himalayan basin, to demonstrate how maximum cumulative storm and total rainfall received during monsoon control the extreme flow variability. In addition, the downscaled CMIP6 data sets were used for projections of extremes. The results suggest that historically Alaknanda basin receives a relatively higher magnitude of monsoon and storm rainfall than the other regions in the UGB, which manifested into significant extreme flow variability at the Alaknanda outlet. The extreme flows at the UGB outlet are projected to be more frequent under warming scenarios. The nonstationary flood frequency magnitudes are higher than those obtained from the stationary frequency method, implying a need for a review of return periods used in the designs of flood control structures in the region. Plain Language Summary: Floods are frequent natural disasters in India that affect millions of people and disrupt socioeconomic conditions. Climate change and human interventions further exaggerate flood hazards in many regions of the country. The west and west‐central Indian Himalayas are the worst flood‐affected regions in recent decades. A detailed scientific analysis is, therefore, crucial for sustainable flood management. Here, we analyze the historical behavior and future projections of annual maximum flows in the upper Ganga basin (UGB; located in the west‐central Himalayan region). Our results indicate that the eastern Alaknanda basin has historically been a highly flood‐prone region in the UGB. The warming climate might further amplify the extreme flood hazards. The nonstationary flood magnitudes are also expected to intensify, posing a severe threat to the operation of hydraulic structures. These inferences would be helpful in formulating sustainable flood mitigation strategies for the west‐central Himalayan region. Key Points: Eastern Alaknanda basin is one of the worst flood‐affected regions in the upper Ganga basinWarming climates are observed to amplify the extreme flood magnitudes in the upper Ganga basinNonstationary flood frequency magnitudes are higher than those obtained from the stationary frequency method [ABSTRACT FROM AUTHOR]

The Ganga River is one of the largest river systems in the world that has built extensive alluvial plains in northern India. The stretch of the Lower Ganga River is vulnerable to siltation because of: (a) the naturally low slope in the alluvial stretch; (b) the confluence of several highly sediment‐charged rivers such as the Ghaghra, Gandak, and Kosi; and (c) the reduction in non‐monsoon flows because of upstream abstractions of both surface and groundwater. Additionally, the Farakka barrage has impacted the morphology of the Ganga River significantly, both upstream and downstream of the barrage. Large‐scale siltation in several reaches has reduced the channel capacity, leading to catastrophic floods in this region even at low discharges. This work has utilized historical remote sensing data and UAV surveys to reconstruct channel morphodynamics and compute sediment volumes accumulated in the channel belt along the Lower Ganga River between Buxar and Farakka. The work was carried out by dividing the total length of the river into four continuous stretches: (a) Buxar–Gandhighat (GW1, 160 km); (b) Gandhighat–Hathidah (GW2, 106 km); (c) Hathidah–Azmabad (GW3, 182 km); and (d) Azmabad–Farakka (GW4, 132 km). We document that major 'hotspots' of siltation have developed in several reaches of the Lower Ganga during the last four to five decades. Sediment budgeting using planform maps provides estimates of 'extractable' volumes of sediment in GW1, GW2, GW3, and GW4 as 656 ± 48, 706 ± 52, 876 ± 71, and 200 ± 85 Mm3, respectively. These estimates are considerably lower than those computed from the hydrological approach using observed suspended sediment load data, which assumes uniform sedimentation between two stations. Further, our approach provides reach‐scale hotspots of aggradation and estimates of extractable sediment volumes, and this can be very useful for river managers to develop a strategic sediment management plan for the given stretch of the Ganga River. [ABSTRACT FROM AUTHOR]

The Betwa River basin, a semi-arid catchment that has been classified as a major hotspot of groundwater depletion in Central India. The rainfall and streamflow intermittency have affected agricultural practices due to the variability of groundwater availability for irrigation. This study evaluates the spatial and temporal variations of groundwater level (GWL) in the last 25 years (1993–2018) in the catchment. We applied a nonparametric Seasonal Trend decomposition based on the Loess (STL) method to decompose the GWL time series into the seasonal, trend, and remainder components. We observed that the GWL in the northeastern regions of the basin has depleted about 3–5 mbgl in the last two decades. During the same period, the basin has experienced a reduction in the rainfall magnitude (2.07 mm/yr). We observed that the overexploitation of groundwater for irrigation and rainfall variability have greatly impacted the GWL condition in the study area. Further, if the groundwater extraction continues at present rates, the Betwa River basin may experience severe depletion in the future. [ABSTRACT FROM AUTHOR]

The Indian Summer Monsoon (ISM) characterizes the hydrometeorological variability across the north Indian region and contributes more than 75% of the annual rainfall during the monsoon (June–September) season. In the present study, we analysed the long-term monsoon rainfall for the Ganga River basin to investigate its spatio-temporal variability. A statistically increasing (10 to 17 mm/year; p < 0.05) trend has been observed in ISM rainfall for the mountainous region since 1980, accompanied by increased temperature. We further note that high, very high and extreme rainfall events are also increasing, enhancing the flash flood risk in the mountainous region. In contrast, the ISM rainfall in the alluvial region is observed to be statistically decreasing (−5 to −20 mm/year; p < 0.05) with the combined influence of reduced vegetation. These findings provide valuable insights into the variations in regional hydrology of the Ganga River basin caused by natural and anthropogenic factors. [ABSTRACT FROM AUTHOR]

High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE) and the sediment delivery ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23±4.7 t ha-1 yr-1) with higher values in the upper mountainous region (92±15.2 t ha-1 yr-1) compared to the lower alluvial plains (19.3±4 t ha-1 yr-1). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin - Nanak Sagar Dam (NSD) for the period 1962-2008 and Husepur gauging station (HGS) for 1987-2002. The SY at NSD and HGS are estimated to be 6.9±1.2×105 t yr-1 and 6.7±1.4×106 t yr-1, respectively, and the estimated 90% interval contains the observed values of 6.4×105 t yr-1 and 7.2×106 t yr-1, respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins. [ABSTRACT FROM AUTHOR]

High soil erosion and excessive sediment load are serious problems in several Himalayan River basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties of SE over two distinct morpho-climatic regimes of the Garra River basin, namely, upper mountainous region & lower alluvial plains. The results suggest that average SE in the basin falls in very high category (20.4 ± 4.1 t/ha/y) with higher values in the upper mountainous region (84.4 ± 13.9 t/ha/y) than in the lower alluvial plains (17.7 ± 3.6 t/ha/y). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin – Nanak Sagar dam (NSD) for the period 1962–2008 and Husepur gauging station (HGS) for 1987–2002. The SY at NSD and HGS are estimated to be 8.0 ± 1.4 × 105 t/y and 7.9 ± 1.7 ×106 t/y, respectively, and the estimated 90 % confidence interval contains the observed values 6.4 × 105 t/y and 7.2 × 106 t/y. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins. [ABSTRACT FROM AUTHOR]