Performance Evaluation of Satellite Rainfall Estimates for Flood Monitoring in Gumera Watershed, Amhara Region, Ethiopia
| dc.contributor.advisor | Asnake Mekuriaw (PhD) | |
| dc.contributor.author | Gebrie Tsegaye | |
| dc.date.accessioned | 2024-01-03T07:55:49Z | |
| dc.date.available | 2024-01-03T07:55:49Z | |
| dc.date.issued | 2022-12-01 | |
| dc.description.abstract | Since the 1980s, several satellites have been providing rainfall data for the tropical parts of the world, including Ethiopia. These data could be used for different applications in various fields of study in areas where ground-based rain gauge stations are unavailable and sparsely distributed. The purpose of this study is to evaluate the performances of satellite rainfall estimates (CHIRPS-V2, TAMSAT-V3.1, and PERSIANN-CDR) for flood monitoring in the most flood-prone area of Amhara Region, Ethiopia. Daily rainfall data from 2004 to 2019 were collected from the National Meteorological Agency. In Addition, satellite rainfall estimates that cover the same periods, and historical flood events in the study area were collected from the internet database and district agriculture office respectively. Continuous statistical indices and categorical statistical indices were employed for data analysis. The performances of the three-satellite rainfall estimates were evaluated on four major temporal scales; annual, seasonal, monthly, and daily temporal scale. In terms of annual and seasonal temporal scales, TAMSAT-V3.1 and CHIRPS-V2 performed well and outperformed PERSIANN-CDR on the major statistical indices. In the Monthly temporal scale, CHIRPS-V2 performed well on the major continuous statistical indices. The application of satellite rainfall products for flood monitoring is also evaluated by using the daily rainfall estimates in two ways; using the overall daily observed rainfall from 2004 to 2019 and using the daily rainfall data during the three most flood events (2006, 2017 and 2019) in the study area. In both cases, all the 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. This research indicated that performance evaluation of satellite rainfall datasets must be conducted before applying for flood monitoring. The study could not address the performance of satellite rainfall estimates in predicting when and where floods will occur in the future. Therefore, future research should be focused on the flood prediction performance of satellite-derived rainfall data | |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/1398 | |
| dc.language.iso | en_US | |
| dc.publisher | Addis Ababa University | |
| dc.subject | Remote Sensing; Flood; Satellite Rainfall Estimate, Evaluation; Dataset | |
| dc.title | Performance Evaluation of Satellite Rainfall Estimates for Flood Monitoring in Gumera Watershed, Amhara Region, Ethiopia | |
| dc.type | Thesis |