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.

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.

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.