Key points are not available for this paper at this time.
The use of hydro-climatological time series to identify patterns is essential for comprehending climate change and extreme events such as drought. Hence, in this study, hydrological drought variability based on the standard drought index (SDI) using DrinC was investigated at ten (10) hydrological stations in the Upper Indus River Basin (UIRB) of Pakistan on a monthly timescale for a period of 1961–2018. Moreover, the applicability of the improved innovative trend analysis by Sen Slope method (referred hereafter as the IITA) method was evaluated in comparison with innovative trend analysis (ITA) and Mann–Kendall (MK). The findings demonstrated a significant decreasing trend in the hydrological drought from October to March; on the other hand, from April through September, a significant increasing trend was observed. In addition to that, the consistency of the outcomes across the three trend analysis methods was also observed in most of the cases, with some discrepancies in trend direction, such as at Kharmong station. Conclusively, consistency of results in all three trend analysis methods showed that the IITA method is reliable and effective due to its capability to investigate the trends in low, median, and high values of hydrometeorological timeseries with graphical representation. A degree-day or energy-based model can be used to extend the temporal range and link the effects of hydrological droughts to temperature, precipitation, and snow cover on a sub-basin scale.
Ashraf et al. (Sat,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: