Spatial and Temporal Evaluation of the Latest High-Resolution Precipitation Products over the Upper Blue Nile River Basin, Ethiopia

Abstract

Quality and representative precipitation data play an essential role in hydro-meteorological analyses. However, the required reliability and coverage is often unavailable from conventional gauge observations. As a result, globally available precipitation datasets are being used as an alternative or supplementary to gauge observations. In this study, the accuracy of three recently released, high-resolution precipitation datasets with a spatial resolution of 0.1° and a daily temporal resolution is evaluated over the Upper Blue Nile River Basin (UBNRB) for the period of 2007 to 2016. The datasets are Integrated Multi-satellitE Retrievals for GPM version 6 (IMERG6), Multi-Source Weighted-Ensemble Precipitation version 2.2 (MSWEP2.2) and soil moisture to rain using Advanced SCATterometer version 1.1 (SM2RAIN-ASCAT1.1). The comparison was made between rain gauge observations and two other high-resolution precipitation datasets named Enhancing National Climate Services (ENACTS) and Climate Hazards Group Infrared Precipitation with Stations version 2 (CHIRPS2). The modified Kling-Gupta efficiency (KGE’) and four categorical indices named probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and frequency bias (fBIAS) was used to measure the skills of each dataset. Results revealed that, except SM2RAIN-ASCAT1.1, all other datasets show a better ability on a monthly time scale for areas with an elevation below 1500 m above sea level (m.a.s.l). The overall performance was better in the wetter months of March to August than the drier months of September to February. Besides, all products including SM2RAIN-ASCAT1.1 could detect no rain events (rain < 1 mm) correctly, but their skill deteriorates on identifying higher intensity events. By comparison, ENACTS (calibrated with most quality gauges of Ethiopia) and CHIRPS2 exhibited the best performance due to their high-resolution nature and inclusion of physiographic information in their data generation procedures. IMERG6 and MSWEP2.2 showed the next best performance according to both the continuous and categorical indices used. SM2RAIN-ASCAT1.1 demonstrates the least skill everywhere due to problems that could be associated with misinterpretations of soil moisture signals by the SM2RAIN algorithm. Considering the scarcity of gauged datasets over UBNRB, IMERG6 and MSWEP2.2 could be regarded as valuable datasets for hydro-climatic analysis, mainly where gauge density is low. SM2RAIN-ASCAT1.1, on the other hand, needs significant bias correction to treat its apparent wet biases before any application.

Evaluation of Soil Moisture-Based Satellite Precipitation Products over Semi-Arid Climatic Region

“…However, all other products were inappropriate with respect to spatial and temporal variation of precipitation over the study area, with similar outcomes found in the previous findings of certain studies [37][38][39]. The temporal estimations of SM2Rain were in better agreement with gauge estimation, which is consistent with the findings of a particular study [10,24]. On a monthly scale, All SPPs estimations were in better agreement with gauge estimations as compared to the daily scale, which is comparable with previously documented studies [22,40,41].…”

“…The uncertainty analysis of selected SPPs showed that their accuracy completely depends upon the in-situ topographical and environmental conditions. Previously, numerous researchers assessed the accuracies of many SPPs (SM2Rain, GPM-SM2Rain, CCI, ASCAT, and IMERG) over different parts of the earth [10,17,18]. The results of previous studies also indicated that the performance of SPPs was strongly influenced by the topography and climatic conditions of the study area [32][33][34].…”

“…The SM2RAIN-CCI [19,32] collects data by comparing the two precipitation satellite products, such as Tropical Measurement Mission Multi-Satellite precipitation analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH). Among the other products, the SM2RAIN-CCI is only product that does not use rain gauge observations [10].…”

“…Therefore, validating SPPs accuracy is necessary before using them effectively in a variety of hydro-climatological analyses [9]. On the other hand, SPPs can deliver constant information on precise spatial and temporal scales [10]. It is very difficult to get accurate precipitation data on a fine spatiotemporal scale in the developing world because of uneven distribution of rain gauge networks [11].…”

Estimating the Water Budget of the Upper Blue Nile River Basin With Water and Energy Processes (WEP) Model

“…The average annual precipitation increases from the eastern to southern direction. This pattern of increasing precipitation from eastern and northeastern portions of the basin to southern and southwestern portions is reported in Abtew et al (2009), Abebe et al (2020) and Abera et al (2017).…”