A high resolution seasonal and annual precipitation climatology of the Upper Indus Basin was developed, based on 1995-2017 precipitation normals obtained from four different gridded datasets (Aphrodite, CHIRPS, PERSIANN-CDR and ERA5) and quality-controlled high and mid elevation ground observations. Monthly precipitation values were estimated through the anomaly method at the catchment scale and compared with runoff data (1975-2017) for verification and detection of changes in the hydrological cycle. The gridded dataset is then analysed using running trends and spectral analysis and the Mann–Kendall test was employed to detect significant trends. The nonparametric Pettitt test was also used to identify the change point in precipitation and runoff time series.
The results indicated that bias corrected CHIRPS precipitation dataset, followed by ERA5, performed better in terms of RMSE, MAE, MAPE and BIAS in simulating rain gauge-observed precipitation. The running trend analysis of annual precipitation exhibited a very slight increase whereas a more significant increase was found in the winter season (DJF). A runoff coefficient value greater than one, especially in glacierized catchments (Shigar, Shyok and Gilgit) indicate that precipitation was likely underestimated and glacial melt in a warming climate provides excess runoff volumes.
As far as the streamflow is concerned, variabilities are more pronounced at the seasonal rather than at the annual scale. At the annual scale, trend analysis of discharge shows slightly significant increasing trend for the Indus River at the downstream Kachura, Shyok and Gilgit stations. Seasonal flow analysis reveals more complex regimes and its comparison with the variability of precipitation favours a deeper understanding of precipitation, snow- and ice-melt runoff dynamics, addressing the hydroclimatic behaviour of the Karakoram region.