Spatial and temporal rainfall variability analysis at a basin scale is essential to understand water availability for sustainable water resource management. This study investigated the spatial distribution and temporal rainfall trend in the Tekeze river basin using daily rainfall data collected from 43 meteorological stations with records from 1960 to 2019. Coefficient of variation, seasonality index (SI) and trend index were used to evaluate monthly, seasonal and annual rainfall variability in the basin. The non‐parametric Mann‐Kendall's test was used to understand any rainfall trends. Results showed that there is moderate annual rainfall variability in the basin. Rainfall variability is higher in the Tsedey, Bega and Belg than kiremt season. SI results showed that majority of the Tekeze river basin is categorized as seasonal, most of the rain occurring in less than 3 months. Overall, Mann‐Kendall's test result revealed that there is no significant annual rainfall trend in the basin except for four stations. The seasonal rainfall characteristics and short duration of rain in the basin indicate that there is a need to implement water harvesting measures during the wet season for use in the dry periods.
This research assesses the streamflow response of Werie River to climate change. Baseline (1980–2009) climate data of precipitation, maximum and minimum temperature were analyzed using delta based statistical downscaling approach in R software packages to predict future 90 years (2010–2099) periods under two emission scenarios of Representative Concentration Pathways (RCP) 4.5 and RCP 8.5, indicating medium and extremely high emission scenarios respectively. Generated future climate variables indicate Werie will experience a significant increase in precipitation, and maximum and minimum air temperature for both RCPs. Further, Water and Energy Transfer between Soil, Plants, and Atmosphere (WetSpa) was applied to assess the water balance of Werie River. The WetSpa model reproduced the streamflow well with performance statistics values of R2 = 0.84 and 0.85, Nash–Sutcliffe efficiency = 0.72 and 0.72, and model bias = –0.14 and –0.15 for the calibration data set of 1999–2010 and validation data of 2011–2014 respectively. Finally, by taking the downscaled future climate variables as input, WetSpa future prediction shows that there will an increase in the Werie catchment mean annual streamflow up to 29.6% for RCP 4.5 and 35.6% for RCP 8.5 compared to the baseline period.
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