In the high altitude Hindukush Karakoram Himalaya (HKH) mountains, the complex weather system, inaccessible terrain and sparse measurements make the elevation-distributed precipitation and temperature among the most significant unknowns. The elevation-distributed snow and glacier dynamics in the HKH region are also little known, leading to serious concerns about the current and future water availability and management. The Hunza Basin in the HKH region is a scarcely monitored, and snow- and glacier-dominated part of the Upper Indus Basin (UIB). The current study investigates the elevation-distributed hydrological regime in the Hunza Basin. The Distance Distribution Dynamics (DDD) model, with a degree day and an energy balance approach for simulating glacial melt, is forced with precipitation derived from two global datasets (ERA5-Land and JRA-55). The mean annual precipitation for 1997–2010 is estimated as 947 and 1,322 mm by ERA5-Land and JRA-55, respectively. The elevation-distributed precipitation estimates showed that the basin receives more precipitation at lower elevations. The daily river flow is well simulated, with KGE ranging between 0.84 and 0.88 and NSE between 0.80 and 0.82. The flow regime in the basin is dominated by glacier melt (45%–48%), followed by snowmelt (30%–34%) and rainfall (21%–23%). The simulated snow cover area (SCA) is in good agreement with the MODIS satellite-derived SCA. The elevation-distributed glacier melt simulation suggested that the glacial melt is highest at the lower elevations, with a maximum in the elevation 3,218–3,755 masl (14%–21% of total melt). The findings improve the understanding of the local hydrology by providing helpful information about the elevation-distributed meltwater contributions, water balance and hydro-climatic regimes. The simulation showed that the DDD model reproduces the hydrological processes satisfactorily for such a data-scarce basin.@en

In many high altitude river basins, the hydro-climatic regimes and the spatial and temporal distribution of precipitation are little known, complicating efforts to quantify current and future water availability. Scarce, or non-existent, gauged observations at high altitudes coupled with complex weather systems and orographic effects further prevent a realistic and comprehensive assessment of precipitation. Quantifying the contribution from seasonal snow and glacier melt to the river runoff for a high altitude, melt dependent region is especially difficult. Global scale precipitation products, in combination with precipitation-runoff modelling may provide insights to the hydro-climatic regimes for such data scarce regions. In this study two global precipitation products; the high resolution (0.1° × 0.1°), newly developed ERA5-Land, and a coarser resolution (0.55° × 0.55°) JRA-55, are used to simulate snow/glacier melts and runoff for the Gilgit Basin, a sub-basin of the Indus. A hydrological precipitation-runoff model, the Distance Distribution Dynamics (DDD), requires minimum input data and was developed for snow dominated catchments. The mean of total annual precipitation from 1995 to 2010 data was estimated at 888 mm and 951 mm by ERA5-Land and JRA-55, respectively. The daily runoff simulation obtained a Kling Gupta efficiency (KGE) of 0.78 and 0.72 with ERA5-Land and JRA-55 based simulations, respectively. The simulated snow cover area (SCA) was validated using MODIS SCA and the results are quite promising on daily, monthly and annual scales. Our result showed an overall contribution to the river flow as about 26% from rainfall, 37–38% from snow melt, 31% from glacier melt and 5% from soil moisture. These melt simulations are in good agreement with the overall hydro-climatic regimes and seasonality of the area. The proxy energy balance approach in the DDD model, used to estimate snow melt and evapotranspiration, showed robust behaviour and potential for being employed in data poor basins.

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Floods are brutal, catastrophic natural hazards which affect most human beings in terms of economy and life loss, especially in the large river basins worldwide. The Indus River basin is considered as one of the world’s large river basins, comprising several major tributaries, and has experienced severe floods in its history. There is currently no proper early flood warning system for the Indus River which can help administrative authorities cope with such natural hazards. Hence, it is necessary to develop an early flood warning system by integrating a hydrodynamic model, in situ information, and satellite imagery. This study used Hydrologic Engineering Center–River Analysis System (HEC–RAS) to predict river dynamics under extreme flow events and inundation modeling. The calibration and validation of the HEC–RAS v5 model was performed for 2010 and 2015 flood events, respectively. Manning’s roughness coefficient (n) values were extracted using the land use information of the rivers and floodplains. Multiple combinations of n values were used and optimized in the simulation process for the rivers and floodplains. The Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Moderate Resolution Imaging Spectroradiometer (MODIS) MOD09A1, and MOD09GA products were used in the analysis. The Normalized Difference Water Index (NDWI), Modified NDWI1 (MNDWI1), and MNDWI2, were applied for the delineation of water bodies, and the output of all indices were blended to produce standard flood maps for accurate assessment of the HEC–RAS-based simulated flood extent. The optimized n values for rivers and floodplains were 0.055 and 0.06, respectively, with significant satisfaction of statistical parameters, indicating good agreement between simulated and observed flood extents. The HEC–RAS v5 model integrated with satellite imagery can be further used for early flood warnings in the central part of the Indus River basin.@en

Droughts exert severe impacts on the environment, economy, and society. The south Asian region is vulnerable to droughts and the Indian sub-continent is one of the most vulnerable in the region to frequent drought disasters. This study assesses the agricultural droughts in the Narmada River Basin (NRB), India, where more than 50% of the area is utilized for agriculture, through freely available local and global remote-sensing-based data focusing on long-term rainfall trends (1989–2018) and recently weakened monsoons in 2017 and 2018. In this study, some of the widely used indices to characterize droughts (viz., Standardized Precipitation Index (SPI), simplified Rainfall Index (RIs), Normalized Difference Vegetation Index (NDVI)), soil moisture content, and reservoir surface areas were used to assess the drought conditions in the Narmada River Basin over the study period. Our analysis shows that the NRB has experienced a decreasing trend in monsoon rainfall over the past three decades. The SPI captured most of the basin’s historical droughts. The weakened monsoons during 2017–2018 show that different parts of the NRB have experienced severe or moderate drought conditions. A clear difference does not show in the NDVI and in the soil moisture contents of the basin over three hydrological years (2015/16, 2016/17, and 2017/18), except for July to September 2017/18. The estimated water area depletion using the Normalized Difference Water Index (NDWI) follows the actual water levels in three selected reservoirs in the basin, of which, two show a decline in the maximum surface area, likely due to the weakened monsoons in 2017 and 2018. This research indicates that the freely available data can be beneficial for local authorities to monitor and understand the drought conditions to support water resources management and planning for agricultural activities.@en

Groundwater is a primary source of freshwater provisions all around the world. Due to its limited availability, water has become a precious entity nowadays. The future accessibility of groundwater is endangered due to its massive exploitation, particularly in the irrigation sector. Therefore, the current study was conducted to assess the declining groundwater levels in Rechna Doab, Punjab, Pakistan, where the aquifer has been reported to be highly stressed. A groundwater flow model was developed using the MODFLOW code of the USGS, and the steady-state model was calibrated for the year 2006, followed by a transient calibration for the years 2006–2010. Finally, the model was validated for 2011–2013, and a new scenario-based approach was used. Multiple future scenarios were developed to simulate the future response of the aquifer under changed recharge and pumping. The hydrodynamics of the groundwater flow was studied for two decades, i.e., up to 2033. The results under the business-as-usual scenario revealed a net gain in water levels in the upper parts of the study area. In contrast, a lowering of water levels was predicted in the central and lower parts. A maximum drop in the water level was anticipated to be 5.17 m, with a maximum gain of 5 m. For Scenario II, which followed the historical trend of pumping, an overall decline in water levels was observed, with a maximum expected drawdown of 15.68 m. However, the proposed water management Scenario III showed a general decrease in the upper study region, with the highest drop being 10.7 m, whereas an overall recovery of 6.87 m in the lower regions was observed. The simulations also suggested that the unconfined aquifer actively responded to the different scenario-based interventions. It was concluded that the region’s aquifer needs immediate action regarding pumping and recharge patterns to avoid a potential increase in pumping costs and to preserve the sustainability of endangered groundwater resources. Moreover, proper groundwater pumping and its policy legislation for its management should be implemented in order to protect this precious resource.@en

In the high elevation Hindukush Karakoram Himalaya (HKH) mountain region, the complex weather system and sparse measurements make the elevation-distributed precipitation among the most significant unknowns and limit the realistic and comprehensive assessment of precipitation. In addition, due to local orographic effects, precipitation can vary highly over short horizontal distances. Accurate quantification of precipitation, however, is critical for understanding hydro-climatic dynamics. Moreover, snow and glacier dynamics, and their contribution to river flow in the HKH region, are also mostly unknown, leading to serious concerns about current and future water availability. The recent acceleration in climate change (CC) heightens concerns about future water availability from high elevation mountain regions. The HKH region heavily depends on its upstream frozen water resources, and an accelerated melt may severely affect future water availability. In line with rapid population growth in the Indo-Gangetic plain, there will be increased water, food and energy demands in the future. Therefore, increasing knowledge of the hydro-climatic regime and glacier and snowmelt contributions to the river flow under current and future climate change scenarios is essential. The Indus basin, with a downstream population of around 250 million, is among three highly populated river basins originating from the HKH mountains, followed by Ganges and Brahmaputra. This PhD research was designed to quantitatively and comprehensively assess precipitation and its distribution for the Gilgit and Hunza sub-basins of the Upper Indus Basin (UIB). In addition, the hydrological regime and snow and glacier dynamics were investigated, and the future hydro-climatic regime and water availability from the highly glaciated Hunza basin were analysed. For the present-day investigations, the elevation-distributed precipitation was derived from better performing global precipitation datasets which include the high resolution (0.1°x0.1°) and newly developed ERA5-Land, and a coarser resolution (0.55°x0.55°) JRA-55. These estimates were forced to a data parsimonious precipitation-runoff model, Distance Distribution Dynamics (DDD), with its energy balance and temperature index approaches for snow/glacier melt simulation. The model was calibrated from 1997–2005 and validated from 2006–2010. For future scenarios, the ERA5-Land corrected precipitation against the observed flow was employed to bias correct the precipitation from two global circulation models (GCM) using the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections. The DDD model was set up again using these bias corrected GCM projections for baseline (1991–2010), mid-century (2041–2060) and end-century (2081–2100) projections under Shared Socioeconomics Pathways (SSP) SSP1, SSP2 and SSP5 emission scenarios. @en

The Upper Indus Basin (UIB) heavily depends on its frozen water resources, and an accelerated melt due to the projected climate change may significantly alter future water availability. The future hydro-climatic regime and water availability of the Hunza basin (a sub-basin of UIB) were analysed using the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections. A data and parameter parsimonious precipitation-runoff model, the Distance Distribution Dynamics (DDD) model, was used with energy balance-based subroutines for snowmelt, glacier melt and evapotranspiration. The DDD model was set up for baseline (1991–2010), mid-century (2041–2060) and end-century (2081–2100) climates projections from two global circulation models (GCM), namely EC-Earth3 and MPI-ESM. The projections indicate a substantial increase in temperature (1.1–8.6 °C) and precipitation (12–32%) throughout the twenty-first century. The simulations show the future flow increase between 23–126% and the future glacier melt increase between 30–265%, depending on the scenarios and GCMs used. Moreover, the simulations suggest an increasing glacier melt contribution from all elevations with a significant increase from the higher elevations. The findings provide a basis for planning and modifying reservoir operation strategies with respect to hydropower generation, irrigation withdrawals, flood control, and drought management.

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Near real-time estimation of soil loss from river catchments is crucial for minimizing environmental degradation of complex river basins. The Chenab river is one of the most complex river basins of the world and is facing severe soil loss due to extreme hydrometeorological conditions, unpredictable hydrologic response, and complex orography. Resultantly, huge soil erosion and sediment yield (SY) not only cause irreversible environmental degradation in the Chenab river catchment but also deteriorate the downstream water resources. In this study, potential soil erosion (PSE) is estimated from the transboundary Chenab river catchment using the Revised Universal Soil Loss Equation (RUSLE), coupled with remote sensing (RS) and geographic information system (GIS). Land Use of the European Space Agency (ESA), Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data, and world soil map of Food and Agriculture Organization (FAO)/The United Nations Educational, Scientific and Cultural Organization were incorporated into the study. The SY was estimated on monthly, quarterly, seasonal, and annual time-scales using sediment delivery ratio (SDR) estimated through the area, slope, and curve number (CN)-based approaches. The 30-year average PSE from the Chenab river catchment was estimated as 177.8, 61.5, 310.3, 39.5, 26.9, 47.1, and 99.1 tons/ha for annual, rabi, kharif, fall, winter, spring, and summer time scales, respectively. The 30-year average annual SY from the Chenab river catchment was estimated as 4.086, 6.163, and 7.502 million tons based on area, slope, and CN approaches. The time series trends analysis of SY indicated an increase of 0.0895, 0.1387, and 0.1698 million tons per year for area, slope, and CN-based approaches, respectively. It is recommended that the areas, except for slight erosion intensity, should be focused on framing strategies for control and mitigation of soil erosion in the Chenab river catchment.@en