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

Abstract

Abstract. The increasing rate of occurrence of extreme events (droughts and floods) and their rapid transition magnify the associated socio-economic impacts with respect to those caused by the individual event. Understanding of spatio-temporal evolution of wet–dry events collectively, their characteristics, and the 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) in South Asia was selected as a case study, where the relevance of wet–dry events and their transition has not been assessed yet, despite clear evidence of climate change in the region. The standardized precipitation evapotranspiration index (SPEI) at the monthly timescale was applied to detect and characterize wet and dry events for the period 1981–2014. The results of temporal variations in 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 are featured in the southwestern part of the basin. In contrast, the 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.

Evaluation of bias correction methods for a multivariate drought index: case study of the Upper Jhelum Basin

“…Results show that the northeast part of the region, located at the foothills of the Western Himalayas, is found to be more affected by wet and dry events with higher sever-ity and duration (see the upper left panel in each figure). The higher susceptibility of the region towards more extreme events could be explained with the increasing rates of global warming over mountainous region, i.e., Western Himalayas, also reported by many researchers (Pachauri et al, 2014;Zaz et al, 2019;Rashid et al, 2020;Shafiq et al, 2020;Ansari and Grossi, 2022). Studies by Negi et al (2018) and Dimri and Dash (2012) also confirm that most of the Western Himalayan region recorded a significant warming trend especially from 1975 onwards.…”

“…It can be interpreted as the number of standard deviations by which the observed anomaly deviates from the long-term mean. Various researchers highlighted its suitability to detect the onset and spatiotemporal evolution of drought at the regional to global scales Ansari and Grossi, 2022) and recommended it for operational drought monitoring (Vicente-Serrano et al, 2010).…”

“…The SPEI calculation involves two further steps: aggregation of daily climatic water balance time series at different timescales (30 d in the present study) and then its normalization into a loglogistic probability distribution to obtain the SPEI series. The log-logistic distribution for the SPEI calculation is used and recommended by many researchers (Vicente-Serrano et al, 2010;Wang et al, 2015;Himayoun and Roshni, 2019;Ansari and Grossi, 2022). A more detailed description of the SPEI calculation procedure can be found in Vicente-Serrano et al (2010) and Wang et al (2015).…”

“…Several studies employ such indices and impact models for the assessment of the sectorial impacts of climate change: for instance, drought indices (standardized precipitation index -SPI -and standardized precipitation evapotranspiration index -SPEI) with implications in water-related sectors, especially agriculture, hydrology, and water management (Maru et al, 2022;Ansari and Grossi, 2022); snow indices (snow days and mean winter snow depth) in the context of water management, ecology, tourism, or road maintenance (Schmucki et al, 2017); and river flow indices (100year return level of daily high streamflow and 10-year return level of 7 d average low streamflow) for reservoir operation, energy production, flood and drought management (Naz et al, 2018), etc. To assess the climate change impacts through such indices or any impact models, there is the need to have good-quality observations and an adequate number of climate model simulations to characterize uncertainties at sufficiently high resolution to provide tailored regional to local climate information for impact assessments.…”

Identification, physical mechanisms and impacts of drought–flood abrupt alternation: a review

“…In order to protect human society from DFAA and to set up emergency plans for DFAA, current studies have tried to explore the generation, pattern and impact of DFAA (Wu et al, 2006;Shan et al, 2015;Chen et al, 2020;Bi et al, 2021;Ford et al, 2021;Yu et al, 2021;Ansari & Grossi, 2022). To study the generation of DFAA events, the physical mechanism needs to be analyzed on the basis of the precise definition and extraction of a DFAA event.…”