Kumar, Amit
(2024)
Investigating the factors influencing the transition from meteorological to hydrological droughts.
PhD thesis, University of Nottingham.
Abstract
Both the hydrological extremes, floods and droughts have serious widespread environmental, societal and economic impacts. The complex nature of droughts makes them one of the most challenging natural disasters to identify, assess, predict and mitigate. As droughts develop in different water resources, their impact can propagate from one sector to another. Traditionally, studies of drought propagation focus only on the temporal linkage of meteorological droughts (MD) and hydrological droughts (HD) using statistical techniques. In addition, analysis to date has emphasised at regional scale. A comprehensive comparison of the evolution of spatiotemporal drought characteristics at a global scale is much needed.
This research study comprehensively examined the effectiveness of climate forcing datasets and hydrological models in evaluating both MD and HD events. It investigated accurate methods for capturing the authentic nature of droughts and their propagation while exploring the multifaceted factors influencing their spread. Keeping in consideration the research questions this thesis aimed at identifying major global drought events with a 3D perspective; and to investigate the factors responsible for influencing the transition of drought from MD to HD. As an outcome this research projects proposes a new technique to identify the propagation of MD events into HD events. In addition, drought events are treated as three-dimensional grid structures spanning space (latitude and longitude) and time.
This study compares the effectiveness of catchment-scale hydrological models (CHMs), global-scale hydrological models (GHMs), and their respective ensemble means (Ens-CHM and Ens-GHM) to simulate observed HD events. HD events were identified from runoff-deficits and the Standardised Runoff Index (SRI). This study found that both sets of models (CHMs and GHMs) show limited ability to simulate detailed characteristics of observed HD events while the ensemble models (Ens-CHM and Ens-GHM) performed better compared to the individual models. In addition, both the ensembles showed least error for duration of extreme SRI drought events.
This study also examined the utility of different climate forcing datasets for MD analysis, to clarify their effect on the estimation of MD conditions. Drought events in this thesis are defined as 3D phenomenon as they occur in nature spanning space-time dimensions. The forcings datasets show a significant increasing trend in annual precipitation, and significant decreasing trend in drought area. However, the outcome may differ based on the composition of forcing datasets. In this study, GSWP3-W5E5 (phase 3 of the Global Soil Wetness Project combined with W5E5 dataset) forcing has shown a lower trend in annual precipitation and higher in TAD (total area under drought) when compared to that for WFD (WATCH Forcing Data methodology applied to ERA-40 reanalysis data) and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim reanalysis data) forcing datasets.
This study also provides the first insights into propagation of drought events with a 3D perspective, on a global scale. This study proposes a new technique linking extreme MD and HD events to establish propagation. The study shows that majority of the MD events did not show propagation, but the tendency of propagation is higher for long-term MD events. This study also shows that 16% of MD events propagated to HD events, with occasional pooling of multiple MD events resulting in one or many branched HD events. However, in comparison to the propagation among drought events, pooling or branching of drought events is even rarer. This study also shows that there is a higher affinity towards branching if MD events also exhibit pooling.
Actions (Archive Staff Only)
 |
Edit View |
Tools
Tools
![[thumbnail of Thesis_Final_Draft_pdf_UH.pdf]](https://eprints.nottingham.ac.uk/style/images/fileicons/application_pdf.png "Thesis_Final_Draft_pdf_UH.pdf")