Past and future changes toward earlier timing of streamflow over Pakistan from bias-corrected regional climate projections (1962–2099)

Abstract

Streamflow has fluctuated seasonally in Pakistan and surface warming has caused its seasonal change, sometimes resulting in a lack of water resources for agriculture. However, little is known about how the seasonal changes in the hydrologic regimes over Pakistan has been and will be persisted. Using daily streamflow records from four gag stations data and bias-corrected hydrological projections, this study assessed the past and future changes in streamflow timing along four major river basins of Pakistan (Upper Indus, Kabul, Jhelum, and Chenab). First, we simulated the VIC-river routing model to generate past and future daily streamflow data forced by simulated daily surface and base runoff data from six CORDEX-South Asia regional climate models (1962–2099). Second, we corrected minimum and seasonality bias in simulated daily streamflow data against the daily observational records. Third, we calculated half of the annual cumulative streamflows (HCSs) and center-of-volume dates (CVDs) of observed and bias-corrected simulated streamflow data to quantify seasonal changes in the hydrologic regime. Except for the Chenab River basin, observational records revealed a significant decreasing trend in CVD (i.e., an earlier onset of the wet season) over Pakistan basins over 1962–2019. Bias-corrected hydrologic projections revealed a decrease in CVD of 4.2 to 6.3 days across the four study river basins over the overlapped period. The average decrease in CVDs ranged from 5 to 20 days and 11 to 37 days in the near future (the 2050–2059 average) and the far future (the 2090–2099 average), respectively. We found that the hydrologic responses different magnitudes of CVDs) of all four basins are diverse with different magnitudes of CVDs despite a similar magnitude of near-surface temperature across the basins, highlighting the need for basin-specific water resources management and climate change adaptation policies.