Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia
Drought is a major natural hazard in Ethiopia, posing significant challenges and severe consequences. This research aimed to assess the occurrence and distribution of drought in the Bilate River Watershed (BRW) using the Vegetation Health Index (VHI), Vegetation Condition Index (VCI), and Temperatur...
| Autores principales: | , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Informa UK Limited
2024
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/151514 |
| _version_ | 1855520584167849984 |
|---|---|
| author | Burka, A. Biazin, B. Bewket, W. |
| author_browse | Bewket, W. Biazin, B. Burka, A. |
| author_facet | Burka, A. Biazin, B. Bewket, W. |
| author_sort | Burka, A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Drought is a major natural hazard in Ethiopia, posing significant challenges and severe consequences. This research aimed to assess the occurrence and distribution of drought in the Bilate River Watershed (BRW) using the Vegetation Health Index (VHI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI), along with the Google Earth Engine platform. Vegetation products (MOD13Q1) and LST products (MOD11A2) were selected from May to October each year, covering the period from 2000 to 2022. The VCI, TCI, and VHI maps were generated, identifying extreme and severe drought events with extensive spatial coverage in 2002, 2009, 2015, and 2022, which were the major drought years. According to the VHI, the watershed experienced extreme, severe, and moderate drought classes in May and October, affecting 62% and 70% of the area, respectively. The years 2009 and 2015 were particularly devastating in terms of drought. . The spatial autocorrelation analysis demonstrated significant positive autocorrelation of drought, as indicated by the values of Moran’s I and z scores, which ranged from 0.23 to 0.79 and 8.66 to 24.64, respectively. The correlation analysis findings showed strong positive relationships among the vegetation indices and rainfall, while showing negative associations with temperature and land surface temperature. The frequency analysis also revealed a significant occurrence of drought in the southern portion of the watershed. Therefore, these results hold practical significance for decision-makers and practitioners involved in drought management planning within the BRW. |
| format | Journal Article |
| id | CGSpace151514 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Informa UK Limited |
| publisherStr | Informa UK Limited |
| record_format | dspace |
| spelling | CGSpace1515142025-10-26T13:01:55Z Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia Burka, A. Biazin, B. Bewket, W. drought normalized difference vegetation index remote sensing climate change land degradation Drought is a major natural hazard in Ethiopia, posing significant challenges and severe consequences. This research aimed to assess the occurrence and distribution of drought in the Bilate River Watershed (BRW) using the Vegetation Health Index (VHI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI), along with the Google Earth Engine platform. Vegetation products (MOD13Q1) and LST products (MOD11A2) were selected from May to October each year, covering the period from 2000 to 2022. The VCI, TCI, and VHI maps were generated, identifying extreme and severe drought events with extensive spatial coverage in 2002, 2009, 2015, and 2022, which were the major drought years. According to the VHI, the watershed experienced extreme, severe, and moderate drought classes in May and October, affecting 62% and 70% of the area, respectively. The years 2009 and 2015 were particularly devastating in terms of drought. . The spatial autocorrelation analysis demonstrated significant positive autocorrelation of drought, as indicated by the values of Moran’s I and z scores, which ranged from 0.23 to 0.79 and 8.66 to 24.64, respectively. The correlation analysis findings showed strong positive relationships among the vegetation indices and rainfall, while showing negative associations with temperature and land surface temperature. The frequency analysis also revealed a significant occurrence of drought in the southern portion of the watershed. Therefore, these results hold practical significance for decision-makers and practitioners involved in drought management planning within the BRW. 2024-12-31 2024-08-02T14:12:06Z 2024-08-02T14:12:06Z Journal Article https://hdl.handle.net/10568/151514 en Open Access Informa UK Limited Burka, A.; Biazin, B.; Bewket, W. 2024. Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia. Geomatics Natural Hazards and Risk. ISSN 1947-5713. 15(1). https://doi.org/10.1080/19475705.2024.2377672 |
| spellingShingle | drought normalized difference vegetation index remote sensing climate change land degradation Burka, A. Biazin, B. Bewket, W. Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia |
| title | Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia |
| title_full | Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia |
| title_fullStr | Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia |
| title_full_unstemmed | Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia |
| title_short | Spatial drought occurrences and distribution using VCI, TCI, VHI, and Google Earth Engine in Bilate River Watershed, Rift Valley of Ethiopia |
| title_sort | spatial drought occurrences and distribution using vci tci vhi and google earth engine in bilate river watershed rift valley of ethiopia |
| topic | drought normalized difference vegetation index remote sensing climate change land degradation |
| url | https://hdl.handle.net/10568/151514 |
| work_keys_str_mv | AT burkaa spatialdroughtoccurrencesanddistributionusingvcitcivhiandgoogleearthengineinbilateriverwatershedriftvalleyofethiopia AT biazinb spatialdroughtoccurrencesanddistributionusingvcitcivhiandgoogleearthengineinbilateriverwatershedriftvalleyofethiopia AT bewketw spatialdroughtoccurrencesanddistributionusingvcitcivhiandgoogleearthengineinbilateriverwatershedriftvalleyofethiopia |