Assessing El Niño-induced drought in Zambia and its effects using earth observation data
Southern Africa faces significant impacts of El Niño primarily in the form of droughts. Zambia is not an exception. Standardized Precipitation Index (SPI), rainfall anomaly and Vegetation Condition Index (VCI) are robust indicators for drought studies due to their distinct and complementary roles. O...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
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Springer
2025
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| Acceso en línea: | https://hdl.handle.net/10568/158362 |
| _version_ | 1855543344081403904 |
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| author | Ghosh, Surajit Kour, Sneha Taron, Avinandan Kaywala, Karyn Rajakaruna, Punsisi |
| author_browse | Ghosh, Surajit Kaywala, Karyn Kour, Sneha Rajakaruna, Punsisi Taron, Avinandan |
| author_facet | Ghosh, Surajit Kour, Sneha Taron, Avinandan Kaywala, Karyn Rajakaruna, Punsisi |
| author_sort | Ghosh, Surajit |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Southern Africa faces significant impacts of El Niño primarily in the form of droughts. Zambia is not an exception. Standardized Precipitation Index (SPI), rainfall anomaly and Vegetation Condition Index (VCI) are robust indicators for drought studies due to their distinct and complementary roles. Our results reveal severe meteorological drought conditions in Zambia using SPI and rainfall anomaly. VCI values have declined in the cropping season due to vegetation stress induced by water deficit conditions. Low rainfall leads to widespread deterioration of crop production, with approximately 40.46% of the country experiencing drought conditions in 2023–2024. The Central, Eastern, Southern, Lusaka, and Copperbelt provinces showed lower VCI values in March and April 2024, indicating poor crop health and drought-like conditions. On the other hand, low rainfall has substantially influenced hydropower reservoirs. Significant surface water loss is observed in the hydropower reservoirs such as Itezhi Tezhi Dam (117.40 sq. km), Mita Hills Dam (25.72 sq. km) and in parts of Lake Kariba (58.72 sq. km) between December 2023 and April 2024. This loss has disrupted industries relying on water resources and hindered hydropower generation, leaving substantial portions of the population without electricity for extended periods. The present study aims to explore the power of open access Earth Observation data and cloud analytics to evaluate the extent and multi-sectoral impact of the recent drought in Zambia. Results highlight the upcoming challenges the country might face in food and nutrition and the critical need for stakeholder involvement and policy design to mitigate future crises and strengthen vulnerable communities. |
| format | Journal Article |
| id | CGSpace158362 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1583622025-10-26T12:55:15Z Assessing El Niño-induced drought in Zambia and its effects using earth observation data Ghosh, Surajit Kour, Sneha Taron, Avinandan Kaywala, Karyn Rajakaruna, Punsisi El Niño drought assessment hydropower satellite observation rainfall precipitation dry spells vegetation index vulnerability stakeholders policies Southern Africa faces significant impacts of El Niño primarily in the form of droughts. Zambia is not an exception. Standardized Precipitation Index (SPI), rainfall anomaly and Vegetation Condition Index (VCI) are robust indicators for drought studies due to their distinct and complementary roles. Our results reveal severe meteorological drought conditions in Zambia using SPI and rainfall anomaly. VCI values have declined in the cropping season due to vegetation stress induced by water deficit conditions. Low rainfall leads to widespread deterioration of crop production, with approximately 40.46% of the country experiencing drought conditions in 2023–2024. The Central, Eastern, Southern, Lusaka, and Copperbelt provinces showed lower VCI values in March and April 2024, indicating poor crop health and drought-like conditions. On the other hand, low rainfall has substantially influenced hydropower reservoirs. Significant surface water loss is observed in the hydropower reservoirs such as Itezhi Tezhi Dam (117.40 sq. km), Mita Hills Dam (25.72 sq. km) and in parts of Lake Kariba (58.72 sq. km) between December 2023 and April 2024. This loss has disrupted industries relying on water resources and hindered hydropower generation, leaving substantial portions of the population without electricity for extended periods. The present study aims to explore the power of open access Earth Observation data and cloud analytics to evaluate the extent and multi-sectoral impact of the recent drought in Zambia. Results highlight the upcoming challenges the country might face in food and nutrition and the critical need for stakeholder involvement and policy design to mitigate future crises and strengthen vulnerable communities. 2025-03 2024-10-31T21:04:22Z 2024-10-31T21:04:22Z Journal Article https://hdl.handle.net/10568/158362 en Limited Access Springer Ghosh, Surajit; Kour, Sneha; Taron, Avinandan; Kaywala, Karyn; Rajakaruna, Punsisi. 2025. Assessing El Niño-induced drought in Zambia and its effects using earth observation data. Natural Hazards, 121(4):4505-4530. [doi: https://doi.org/10.1007/s11069-024-06976-5] |
| spellingShingle | El Niño drought assessment hydropower satellite observation rainfall precipitation dry spells vegetation index vulnerability stakeholders policies Ghosh, Surajit Kour, Sneha Taron, Avinandan Kaywala, Karyn Rajakaruna, Punsisi Assessing El Niño-induced drought in Zambia and its effects using earth observation data |
| title | Assessing El Niño-induced drought in Zambia and its effects using earth observation data |
| title_full | Assessing El Niño-induced drought in Zambia and its effects using earth observation data |
| title_fullStr | Assessing El Niño-induced drought in Zambia and its effects using earth observation data |
| title_full_unstemmed | Assessing El Niño-induced drought in Zambia and its effects using earth observation data |
| title_short | Assessing El Niño-induced drought in Zambia and its effects using earth observation data |
| title_sort | assessing el nino induced drought in zambia and its effects using earth observation data |
| topic | El Niño drought assessment hydropower satellite observation rainfall precipitation dry spells vegetation index vulnerability stakeholders policies |
| url | https://hdl.handle.net/10568/158362 |
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