Characterization of Interannual and Seasonal Variability of Hydro-Climatic Trends in the Upper Indus Basin

Abstract

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.

Spatio-temporal evolution of wet–dry event features and their transition across the Upper Jhelum Basin (UJB) in South Asia

“…The data are developed by using an advanced 4D-Var assimilation scheme and provide various atmospheric variables at 139 pressure levels for the period 1979-present. The suitability of ERA5 to the UJB and surrounding region was also reported by Liaqat et al (2021) and Baudouin et 2020). The DM method adjusts the cumulative distribution function (CDF) of modelled precipitation to match with the observed precipitation CDF using a transfer function (Sennikovs and Bethers, 2009), and it is commonly used to correct the systematic distributional biases (Cannon et al, 2015).…”

Climate change projections of wet and dry extreme events in the Upper Jhelum Basin using a multivariate drought index: Evaluation of bias correction

“…The use of W5E5 (WFDE5 data over land and ERA5 over ocean) for the present study is motivated by the 40 numerous previous studies. For instance, the suitability of ERA5 and its slightly overestimation of precipitation over the study region (UJB), especially over the mountainous part of the basin, have been evaluated and acknowledged by several researchers (Ansari et al, 2022;(Baudouin et al, 2020;Arshad et al, 2021;Liaqat et al, 2022). These studies recommend performing the bias correction of ERA5 with localized data before its application in impact studies.…”