Evaluation of Satellite Rainfall Estimates in a Rugged Topographical Basin Over South Gojjam Basin, Ethiopia

Under the inaccessibility of optimum networks and lack of well-organized rain gauge data, the provided high-resolution satellite estimates serve as a vital baseline for hydro climate-associated studies. In the rugged topography of South Gojjam Basin, satellite rainfall estimates from the African Rainfall Climatology (ARC2), Climate Hazard Group Infrared Precipitation with Stations Data (CHIRPSv2), African Rainfall Estimations Algorithm (REFv2), and Tropical Applications of Meteorology using Satellite (TAMSATv3) were evaluated and compared with rain gauge rainfall data. Satellite rainfall estimates were evaluated at spatiotemporal scales with observed data using approaches of point observed rainfall data and areal averaged rainfall comparisons for the period of 2001–2018. The basin was divided into two parts, according to geographical region, to identify the effect of topographical variation. Besides, the spatial map of the annual satellite rainfall estimate pattern was illustrated with observed rainfall data for comparison. The result showed that TAMSATv3 and RFEv2 rainfall estimates showed the best performance than ARC2 and CHIRPSv3 products at daily time scales and in both spatial scales (i.e., higher, and lower elevations). On a monthly and wet season timescale, the CHIRPSv2 product was outperformed, even though the four satellite products performed better. CHIRPSv2 and TAMSATv3 products presented overestimated rainfall in the lower elevation region at daily and monthly scales, while ARC2 and RFEv2 products were underestimated at all spatiotemporal scales. Overall, CHIRPSv2 and TAMSATv3 satellite rainfall estimates showed good relation to the rain gauge rainfall data in the rugged topography and a limited number of rain gauges in the South Gojjam basin. Thus, this study decided that CHIRPSv2 and TAMSATv3 satellite rainfall data could be used as an alternative to rain gauge rainfall on a monthly and wet season time scale for hydroclimate studies.