Abstract

Abstract Investigating the effects of climate and land-use changes on surface runoff is critical for water resources management. The majority of studies focused on projected climate change effects on surface runoff, while neglecting future land-use change. Therefore, the main aim of this article is to discriminate the impacts of projected climate and land-use changes on surface runoff using the Soil and Water Assessment Tool (SWAT) through the lens of the Upper Indus Basin, Pakistan. Future scenarios of the land-use and climate changes are predicted using cellular automata artificial neural network and four bias-corrected general circulation models, respectively. The historical record (2000–2013) was divided into the calibration period (2000–2008) and the validation period (2009–2013). The simulated results demonstrated that the SWAT model performed well. The results obtained from 2000 to 2013 show that climate change (61.61%) has a higher influence on river runoff than land-use change (38.39%). Both climate and land-use changes are predicted to increase future runoff depth in this basin. The influence of climate change (12.76–25.92%) is greater than land-use change (0.37–1.1%). Global weather data has good applicability for simulating hydrological responses in the region where conventional gauges are unavailable. The study discusses that both climate and land-use changes impact runoff depth and concludes with some suggestions for water resources managers to bring water environment sustainability.

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