Developing earth observation-based combined drought indicator to monitor agricultural drought in Ethiopia
Study area: Ethiopia and in particular the crop growing areas. Study focus: Drought is one of the most devastating natural disasters in the world, so better monitoring and assessment are essential. It is essential for facilitating decision-making for establishing an agricultural drought monitoring i...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581825003817 |
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| Summary: | Study area: Ethiopia and in particular the crop growing areas. Study focus: Drought is one of the most devastating natural disasters in the world, so better monitoring and assessment are essential. It is essential for facilitating decision-making for establishing an agricultural drought monitoring index by integrating several input factors into a single index. The objective of this study is to develop a combined agricultural drought index (CADI) for Ethiopia. From 2001–2021, remote sensing-based input parameters such as land surface temperature (LST), precipitation, normalized difference vegetation index (NDVI), soil moisture, and evapotranspiration were used to develop a combined agricultural drought index (CADI) on a monthly scale. New hydrological insights for the region: CADI maps across 2001–2021 depict moderate-to-extreme drought cases in Ethiopia, with 2002, 2009, and 2015 shown as severe examples. The results show that the combined agricultural drought index performed well in terms of capturing and characterizing agricultural drought events in the main crop-growing areas during the Kiremt seasons. The combined agricultural drought index and crop yield had the highest correlation (r = 0.87) in Eastern Tigray, demonstrating the indicator's applicability for agricultural drought monitoring. Overall, the combined agricultural drought index captured the spatial and temporal patterns of the historic drought effectively, and thus the model can be utilized to construct agricultural drought monitoring and an early warning system in Ethiopia to avert the adverse impacts of drought. |
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| ISSN: | 2214-5818 |