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The temporal compounding of two contrasting extremes of the hydrological spectrum (droughts and floods) reflects a volatile hydrological cycle and makes water resources management more challenging. To this end, the present study examines extreme wet-dry events and their temporal compounding over the Upper Jhelum Basin (UJB) in the future climate context based on simulations of climate models from three modeling initiatives (CMIP6, CORDEX - WAS-44 domain and CORDEX-CORE - WAS-22 domain) under low, medium and high emission scenarios for two-time segments i.e., near future (2040-2059) and far future (2080-2099). Wet and dry events are characterized by using a multivariate drought index (namely the Standardized Precipitation Evapotranspiration Index, SPEI), which is derived from daily precipitation and maximum and minimum temperatures. The temporally compound event (hereafter referred as compound event-CE), which is defined as a successive transition from one powerful state to another, includes dry to wet (D-to-W) events and wet to dry (W-to-D) events in the adjacent month. Therefore, the minimum duration of a compound event is 2 months. A D-to-W compound event is defined as a dry spell (SPEIi ≤−1) abruptly changing into a wet spell (SPEIi+1 ≥1) in the next month. Conversely, a W-to-D compound event is defined as a wet spell (SPEIi ≥1) abruptly changing into a dry spell (SPEIi+1 ≤−1) in the next month. The statistical interdependency of temporally compound wet and dry events (CEs) and their statistical significance are investigated using event coincidence analysis (ECA). The significance test is performed based on the assumption of a Poisson process with the null hypothesis that the successive occurrence of wet and dry event is randomly distributed. Results show that the probability of D-to-W CEs is much higher than the W-to-D CEs under both retrospective (i.e., past) or prospective (i.e., future) climate contexts. Specifically, the probability of D-to-W events is high in the southwest of the basin (up to 80 %, statistically significant at 5% level) both in the historical and projections. In contrast, the W-to-D CEs are found to be statistically non-significant for a 95% confidence level (up to 40 %) with no clear pattern of occurrence. There are some differences depending on the climate model ensembles used. CORDEX models (WAS44 and WAS22) show decreasing probability of D-to-W CEs in the southwest part of the basin by the end of the century whereas the CMIP6 ensemble shows a negligible increase from near to far future especially under the highest emission scenario. Overall, the CMIP6 ensemble presents higher probability of CEs under all scenarios and time segments. Climate projections of this kind of extreme events, spanning different scenarios and all sources of uncertainty are essential to fully characterize their impacts on water-related sectors and to plan possible adaptation strategies, such as developing more efficient reservoir operation rules or agricultural planning.

The compound occurrence of two extremes of the hydrological spectrum (droughts and floods) either in space and/or time, could aggravate the associated socio-economic impacts with respect to those caused by the individual extreme event. Both extreme events share the potentially linked driving mechanisms and interconnected characteristics, therefore the better understanding of the dependence structures of the contributing variables is essential to avoid the underestimation of the possible risks of compound hazards. To this end, the present study focusses on spatio-temporally compound extreme events under a changing climate and identify/locate the most vulnerable hotspots in the Upper Jhelum Basin (South Asia), paving the way for adaptation and mitigation measures. Climate models are the main tools to assess climate projections and, particularly, to provide relevant information for sectoral applications. They often present systematic biases, thus some sort of bias adjustment is performed in impact assessments. The framework of the present study is two-fold: (i) evaluation of bias correction (BC) of climate model historical simulations and (ii) projection of extreme compound events in the near future (2040-2059) and far future (2080-2099) for three different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Droughts and floods are characterized by using a multivariate drought index (namely the Standardized Precipitation Evapotranspiration Index, SPEI), which is derived from daily precipitation (P) and maximum (Tmax) and minimum temperatures (Tmin). In the first step, the intercomparison of different state-of-the-art BC methods (uni- and multi-variate) and BC approaches (direct and component-wise) for climate model simulations stemming from different experiments (CMIP6, CORDEX -WAS-44- and CORDEX CORE -WAS-22) is performed following a multivariate framework. The added value/performance of BC and climate model simulations is examined in terms of inter-variable physical coherence of involved key essential variables (P, Tmax and Tmin) and characteristics of extreme events (duration, severity, intensity, and frequency of floods and droughts) during the historical period. In the second step, projected changes in the extreme events characteristics and their compounding in space and time are analyzed for the near and far future under all available scenarios. Climate projections of this kind of extreme events, spanning different scenarios and other sources of uncertainty is essential to better implement adaptation and mitigation solutions that can help reduce the negative impacts of climate change.

The increasing rate of extreme events (Droughts and floods) and their rapid transition magnifies the associated socio-economic impacts than the individual event. Understanding of spatio-temporal evolution of wet-dry events collectively, their characteristics and transition (wet to dry and dry to wet) is therefore significant to identify and locate most vulnerable hotspots, providing the basis for the adaptation and mitigation measures. The Upper Jhelum Basin (UJB)-South Asia was selected as a case study, where the relevance of wet-dry events and their transition have not been assessed yet, despite of clear evidence of climate change in the region. The Standardized Precipitation Evapotranspiration Index (SPEI) at the monthly time scale was applied to detect and characterize wet and dry events for the period 1981–2014. The results of temporal variations of SPEI showed a strong change in basin climatic features associated with El Niño Southern Oscillation (ENSO) at the end of 1997, with the prevalence of wet and dry events before and after 1997 respectively. The results of spatial analysis show a higher susceptibility of the monsoon-dominated region towards wet events, with more intense events occurring in the eastern part, whereas a higher severity and duration is featuring in the southwestern part of the basin. In contrast, westerlies-dominated region was found to be the hotspot of dry events with higher duration, severity, and intensity. Moreover, the surrounding region of the Himalaya divide line and the monsoon-dominated part of the basin were found to be the hotspots of rapid wet-dry transition events.

Global warming and anthropogenic activities have significantly altered the hydrological cycle and amplified the extreme events (floods and droughts) in many regions of the world, with associated environmental, economic, and social losses. For effective hydro extremes hazards management, it is significant to understand how climate change influences the occurrence, duration, and severity of the regional dryness/wetness conditions (droughts/floods). The present study was carried out over Upper Jhelum Basin (UJB) in Pakistan which lies in the western Himalaya, a most effected mountainous range by Climate Change. Firstly, a suitable gridded precipitation dataset was selected/chosen among various datasets (APHRODITE, CHIRPS, ERA5, PGMFD, MSWEP) through spatio-temporal comparison against in situ data at monthly, seasonal, and annual scale. Secondly, selected gridded data was adjusted for biases using linear (Linear scaling-LS, Local intensity scaling-LOCI) and nonlinear (Power transformation-PT and Distribution mapping-DM) statistical methods. Finally, standardized precipitation index (SPI) at multiple time scale was used to analyses dryness/wetness conditions in the Upper Jhelum Basin over a 35-year period (1981–2015). Results show the higher capability of ERA5 data to represent the UJB precipitation patterns with correlation coefficient (r=0.79) and normalized standard deviation (nSD=1.1), despite of overestimation especially during peak months. Regarding precipitation bias adjustment, all methods were able to correct the mean values while LOCI and DM take advantage over other two methods to correct wet-day probability and precipitation intensity. The SPI analysis at different time scales showed that wet periods occurred more in the first half of the study period, but at later years, drying periods ranging from moderate to severe continue to be seen with increasing frequency. A strong change in dry/wet conditions was observed around years 1997/1998. This change may be the result of the strongest El Nino event (1997-98) occurred in the history. However, further studies are still needed to check whether there is only a large multi-decadal variation or dry conditions will prevail in future. Overall, these findings would assist to better understand the changing pattern of extreme events with climate variability and help water resources managers to develop basin wide appropriate mitigation and adaptation measures to combat climate change and its consequences.