Bias-corrected climate change projections over the Upper Indus Basin using a multi-model ensemble

Environ Sci Pollut Res Int. 2023 May;30(23):64517-64535. doi: 10.1007/s11356-023-26898-2. Epub 2023 Apr 18.

Abstract

The study projects climate over the Upper Indus Basin (UIB), covering geographic areas in India, Pakistan, Afghanistan, and China, under the two Representative Concentration Pathways (RCPs), viz., RCP4.5 and RCP8.5 by the late twenty-first century using the best-fit climate model validated against the climate observations from eight meteorological stations. GFDL CM3 performed better than the other five evaluated climate models in simulating the climate of the UIB. The model bias was significantly reduced by the Aerts and Droogers statistical downscaling method, and the projections overall revealed a significant increase in temperature and a slight increase in precipitation across the UIB comprising of Jhelum, Chenab, and Indus sub-basins. According to RCP4.5 and RCP8.5, the temperature and precipitation in the Jhelum are projected to increase by 3 °C and 5.2 °C and 0.8% and 3.4% respectively by the late twenty-first century. The temperature and precipitation in the Chenab are projected to increase by 3.5 °C and 4.8 °C and 8% and 8.2% respectively by the late twenty-first century under the two scenarios. The temperature and precipitation in the Indus are projected to increase by 4.8 °C and 6.5 °C and 2.6% and 8.7% respectively by the late twenty-first century under RCP4.5 and RCP8.5 scenarios. The late twenty-first century projected climate would have significant impacts on various ecosystem services and products, irrigation and socio-hydrological regimes, and various dependent livelihoods. It is therefore hoped that the high-resolution climate projections would be useful for impact assessment studies to inform policymaking for climate action in the UIB.

Keywords: Climate model; Climate projections; Downscaling; Model ensemble; Upper Indus.

MeSH terms

  • China
  • Climate Change*
  • Ecosystem*
  • Forecasting
  • Temperature