Abstract Understanding snow and ice melt dynamics is vital for flood risk assessment effective water resource management in populated river basins sourced inaccessible high-mountains. This study provides an AI-enabled hybrid approach integrating glacio-hydrological model outputs (GSM-SOCONT), with different machine learning deep techniques framed as alternative ‘computational scenarios, leveraging both physical processes data-driven insights enhanced predictive capabilities. The standalone...

Abstract Several satellite-based and reanalysis products with a high spatial temporal resolution have become available in recent decades, making it worthwhile to study the performance of multiple precipitation forcing data on hydrological modeling. This aims examine veracity five employing semi-distributed model, i.e., Soil Water Assessment Tool (SWAT) simulate streamflow over Chenab River Basin (CRB). The indices such as coefficient determination (R2), Nash–Sutcliffe efficiency (NSE)...

Abstract Hydrological models play a key role in simulating and assessing climate land use/cover (LULC) change impacts on hydrology watershed. In this study, the impact of LULC was investigated using Soil Water Assessment Tool (SWAT) model. The simulated observed streamflow showed good agreement. Both Nash–Sutcliffe Efficiency (NSE) coefficient determination (R2) were found to be greater than 0.7 during calibration (1985–2002) validation (2003–2012) period. water balance components with...

Seasonal snowpacks, characterized by their snow water equivalent (SWE), can play a major role in the hydrological cycle of montane environments with months accretion followed episodes melt controlling flood risk and resource availability downstream. Quantifying temporal spatial patterns snowpack accumulation its subsequent runoff is an internationally significant challenge, particularly within mountainous regions featuring complex terrain limited or absent observational data. Here we report...

Abstract Climate change has implications for water resources by increasing temperature, shifting precipitation patterns and altering the timing of snowfall glacier melt, leading to shifts in seasonality river flows. Here, Soil & Water Assessment Tool was run using downscaled temperature projections from five global climate models (GCMs) their multi-model mean estimate potential impact on balance components sub-basins Upper Indus Basin (UIB) under two emission (RCP4.5 RCP8.5) future...

Climate change plays a key role in changing vegetation productivity dynamics, which ultimately affect the hydrological cycle of watershed through evapotranspiration (ET). Trends and correlation analysis were conducted to investigate responses across whole Upper Jhelum River Basin (UJRB) northeast Pakistan using normalized difference index (NDVI), climate variables, river flow data at inter-annual/monthly scales between 1982 2015. The spatial variability trends calculated with Mann-Kendall...

Soil salinity, being a major land degradation process in arid and semiarid regions, is spreading globally at rate of two million hectares per year. Remote sensing data are widely used for detection mapping saline areas, hence was the objective this study. samples were collected from field analyzed laboratory to check salinity status. Results interpolated map 2011 developed. A satellite image Landsat 5 Thematic Mapper area classified, cover developed containing different classes. Saline areas...

Seasonal snowpacks, characterized by their snow water equivalent (SWE), play a major role in the hydrological cycle, melt contributions to floods and subsequent availability of resources downstream. Accurately estimating SWE understanding its spatial temporal variations presents considerable challenge, particularly within mountainous regions complex terrain limited observational data. Seeking enhance performance widely used Soil Water Assessment Tool (SWAT), we report new approach...

<title>Abstract</title> Understanding snow and ice melt dynamics is vital for flood risk assessment effective water resource management in highly populated river basins rising inaccessible high-mountains. This study evaluated AI-enhanced hydrological modelling using a hybrid approach integrating glacio-hydrological model (GSM-SOCONT), with advanced machine learning deep techniques framed as alternative ‘scenarios’, leveraging both physical processes data-driven insights enhanced predictive...