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Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia
Recently, floods and drought have become common natural hydroclimatic hazards in several countries. Consequently, the identification of an appropriate drought index is now a challenging task for researchers. It is obvious that there is not a single best drought index; rather a comparison of indices...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720029/ https://www.ncbi.nlm.nih.gov/pubmed/36478851 http://dx.doi.org/10.1016/j.heliyon.2022.e12000 |
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author | Tareke, Kassa Abera Awoke, Admasu Gebeyehu |
author_facet | Tareke, Kassa Abera Awoke, Admasu Gebeyehu |
author_sort | Tareke, Kassa Abera |
collection | PubMed |
description | Recently, floods and drought have become common natural hydroclimatic hazards in several countries. Consequently, the identification of an appropriate drought index is now a challenging task for researchers. It is obvious that there is not a single best drought index; rather a comparison of indices will give a relative option. The objective of this study was to compare two hydrological drought indices; the modified surface water supply index (M1SWSI) and streamflow drought index (SDI) over eight river basins, in Ethiopia. The M1SWSI and SDI value was computed from 1973 to 2014 using 34 streamflow stations, 42 rainfall gauge stations, and 3 lake-level data. The two indices results showed that the 1980s were the most severe drought years for all river basins. But for the case of Genale Dawa and Wabishebele basins, the drought severity increased from 2000 to 2014. Hydrological drought analysis using SDI has more drought occurrence frequency than M1SWSI. In all river basins from 1973 to 2014, there were a total of 18 severe drought events when using M1SWSI, but there were a total of 39 severe and 12 extreme drought events when using SDI. This implied that M1SWSI reduced the occurrence probability of severe drought by 53.85% and extreme drought by 100%. It is known that Ethiopia is stricken by extreme droughts in the last few decades. But M1SWSI doesn't detect those invidious drought events. In this study, SDI is found to be a better hydrological drought index. Therefore, policy and strategic planners, master plan developers, and decision-makers can use SDI to analyze historical and future hydrological drought trends to develop effective drought mitigation measures. |
format | Online Article Text |
id | pubmed-9720029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97200292022-12-06 Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia Tareke, Kassa Abera Awoke, Admasu Gebeyehu Heliyon Research Article Recently, floods and drought have become common natural hydroclimatic hazards in several countries. Consequently, the identification of an appropriate drought index is now a challenging task for researchers. It is obvious that there is not a single best drought index; rather a comparison of indices will give a relative option. The objective of this study was to compare two hydrological drought indices; the modified surface water supply index (M1SWSI) and streamflow drought index (SDI) over eight river basins, in Ethiopia. The M1SWSI and SDI value was computed from 1973 to 2014 using 34 streamflow stations, 42 rainfall gauge stations, and 3 lake-level data. The two indices results showed that the 1980s were the most severe drought years for all river basins. But for the case of Genale Dawa and Wabishebele basins, the drought severity increased from 2000 to 2014. Hydrological drought analysis using SDI has more drought occurrence frequency than M1SWSI. In all river basins from 1973 to 2014, there were a total of 18 severe drought events when using M1SWSI, but there were a total of 39 severe and 12 extreme drought events when using SDI. This implied that M1SWSI reduced the occurrence probability of severe drought by 53.85% and extreme drought by 100%. It is known that Ethiopia is stricken by extreme droughts in the last few decades. But M1SWSI doesn't detect those invidious drought events. In this study, SDI is found to be a better hydrological drought index. Therefore, policy and strategic planners, master plan developers, and decision-makers can use SDI to analyze historical and future hydrological drought trends to develop effective drought mitigation measures. Elsevier 2022-11-30 /pmc/articles/PMC9720029/ /pubmed/36478851 http://dx.doi.org/10.1016/j.heliyon.2022.e12000 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Tareke, Kassa Abera Awoke, Admasu Gebeyehu Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia |
title | Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia |
title_full | Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia |
title_fullStr | Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia |
title_full_unstemmed | Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia |
title_short | Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia |
title_sort | comparing surface water supply index and streamflow drought index for hydrological drought analysis in ethiopia |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720029/ https://www.ncbi.nlm.nih.gov/pubmed/36478851 http://dx.doi.org/10.1016/j.heliyon.2022.e12000 |
work_keys_str_mv | AT tarekekassaabera comparingsurfacewatersupplyindexandstreamflowdroughtindexforhydrologicaldroughtanalysisinethiopia AT awokeadmasugebeyehu comparingsurfacewatersupplyindexandstreamflowdroughtindexforhydrologicaldroughtanalysisinethiopia |