Abstract

Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. The Upper Ganges (UG) river basin in northern India experiences monsoon flooding almost every year. Studies have shown evidence of strong coupling between the land surface (soil moisture) and atmosphere (precipitation) in northern India, which means that regional climate variations and changes in land use/cover could influence the temporal dynamics of land-atmosphere interactions. <br><br> This work aims to quantify how future projections of land-use and climate change are affecting the hydrological response of the UG river basin. Two different sets of modelling experiments were run using the JULES Land Surface Model and covering the period 2000–2035: In the first set, climate change is taken into account, as JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two Representative Concentration Pathways (RCP4.5 & RCP8.5), whilst land use was kept constant at year 2010. In the second set, both climate change and land-use change were taken into consideration, as apart from the CMIP5 model outputs, JULES was also forced with a time-series of 15 future land-use scenarios, based on Landsat satellite imagery and Markov chain simulation. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. <br><br> Significant changes in the near-future (years 2030–2035) hydrologic fluxes arise under future land cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow [Q<sub>5</sub>] is projected to increase by 63 % under the combined land-use and climate change high emissions scenario [RCP8.5]. The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. <br><br> Results are further presented in a water resources context, aiming to address potential implications of climate change from a water-demand perspective, highlighting that that demand thresholds in the UG region are projected to be exceeded in the future winter months (Dec–Feb).

Highlights

  • Over recent decades, the Indian subcontinent has undergone some of the largest environmental changes in human history

  • The impact of land-use change and climate change on the future hydrology of the Upper Ganges basin was assessed by calculating annual variations in hydrological components

  • Three sets of modelling experiments were run in the Joint UK Land Environment Simulator (JULES) land-surface model, covering the period 2000–2035: (a) the model was forced with future climate projections from the CMIP5 multi-model database, whilst land use was held fixed at year 2010; (b) the model was forced with 15 future land-use pathways, based on Landsat satellite images and the Markov chain simulation, whilst the meteorology was held fixed; and (c) the model was forced with future climate projections from the CMIP5 multi-model database, in conjunction with the 15 future land-use pathways

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Summary

Introduction

The Indian subcontinent has undergone some of the largest environmental changes in human history. India’s green revolution of widespread implementation of irrigation, application of fertiliser and other modern farming practices, in addition to the ubiquitous benefits, have resulted in large-scale changes in land cover and a significant increase in the exploitation of water resources, including the vast groundwater aquifers of the Gangetic plains. These changes have put severe pressure on water resources – a pressure that is exacerbated further since the increasing demand for a better diet led farmers to mainly plant high-waterintensity crops such as wheat, rice and sugarcane (Kaushal and Kansal, 2011). Population density in Uttar Pradesh (which covers a large part of our study area) has increased by more than 100 % from 1971 to 2001, leading to a sharp increase in water demand (Kaushal and Kansal, 2011).

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