Evaluation of daily based satellite rainfall estimates for flood monitoring in Gumera Watershed, Amhara region, Ethiopia
In developing countries, including Ethiopia, ground-based rain gauge stations are limited and unevenly distributed. This makes it difficult to find accurate spatial data on the amount of rainfall. However, since the 1980s, several satellites have been used as alternative rainfall data sources. The d...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Cogent Social Sciences |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23311886.2024.2433690 |
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| Summary: | In developing countries, including Ethiopia, ground-based rain gauge stations are limited and unevenly distributed. This makes it difficult to find accurate spatial data on the amount of rainfall. However, since the 1980s, several satellites have been used as alternative rainfall data sources. The data could be used for different hydrological analyses including flood monitoring. This study aims to evaluate the performances of daily-based satellite rainfall estimates for flood monitoring in the Gumera Watershed of Amhara region, Ethiopia. Three daily satellite rainfall estimates (Tropical Application of Meteorology using Satellite and ground-based observations (TA MSAT -V3.1), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS-V2) and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks Climate Data Record (PERSIANN-CDR)) are evaluated against independent gauge data (2004–2019). Observed rainfall, estimated rainfall, and flood events were the data used for the study. Continuous and categorical statistical indices were used for data analysis. The result shows that all three satellite datasets underestimate the highest amount of observed rainfall and overestimate the lowest amount of daily rainfall conditions. Relatively, CHIRPS-V2 had the best skill in estimating the highest daily rainfall observed in the study area. Future research shall be focused on the flood prediction performance of satellite-derived rainfall data. |
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| ISSN: | 2331-1886 |