Satellite rainfall performance evaluation and application to monitor meteorological drought: a case of Omo-Gibe basin, Ethiopia
Article
Dejene, IN, Wedajo, GK, Bayissa, YA et al. (2023). Satellite rainfall performance evaluation and application to monitor meteorological drought: a case of Omo-Gibe basin, Ethiopia
. NATURAL HAZARDS, 119(1), 167-201. 10.1007/s11069-023-06127-2
Dejene, IN, Wedajo, GK, Bayissa, YA et al. (2023). Satellite rainfall performance evaluation and application to monitor meteorological drought: a case of Omo-Gibe basin, Ethiopia
. NATURAL HAZARDS, 119(1), 167-201. 10.1007/s11069-023-06127-2
Drought assessment is important to minimize its negative consequences and design appropriate management strategies. However, in situ rainfall measurement networks are scarce and unevenly distributed in the majority of watersheds in Ethiopia to assess drought. Performance-evaluated satellite rainfall estimates (SREs) could be an alternative data source in this regard. This study assessed the performance of SREs, namely Climate Hazards Group InfraRed Precipitation with Stations version 2 (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR) and Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) in Omo-Gibe basin. Point-to-pixel pairwise comparison using statistical indices such as Pearson correlation coefficient (r), mean error (ME), root mean square error (RMSE), and bias was used to evaluate the SREs for the 2000 to 2019 study periods. The best SRE was identified and Standardized Precipitation Index (SPI) was used to assess meteorological drought. The CHIRPS-based SPI was compared with station-based SPI and further compared with MODIS-derived vegetation drought indices. The results showed ‘better’ performance of CHIRPS with higher r and lower ME, and bias, and acceptable RMSE values at monthly, seasonally and annual timescales, and its meteorological drought detection capability. Consequently, the CHIRPS rainfall product was used as input data to assess the spatiotemporal meteorological drought for 3- and 12-month periods. The results showed that 2000, 2002, 2009, and 2015 were identified as drought years where the central and southern parts of the basin experienced severe to extreme drought. The 3-month SPI drought index was correlated with drought severity index (DSI) and Vegetation Condition Index (VCI) with R2 value of 0.4 and 0.5, respectively. In the next 100 years, 3-month drought occurrences will be expected in the basin with varying intensities. Henceforth, the CHIRPS rainfall product can be used as an alternative rainfall data source in developing grid-based drought monitoring tools for data-scarce basins, which could assist in creating early warning systems.
