Spatiotemporal variability and trends in rainfall and temperature in Alwero watershed, western Ethiopia

Arragaw Alemayehu,Mohammed Assen,Molla Maru,Woldeamlak Bewket

doi:10.1186/s40068-020-00184-3

Arragaw Alemayehu, Mohammed Assen + Show 2 more

Open Access

https://doi.org/10.1186/s40068-020-00184-3

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Abstract

Climate analysis at relevant time scales is important for water resources management, agricultural planning, flood risk assessment, ecological modeling and climate change adaptation. This study analyses spatiotemporal variability and trends in rainfall and temperature in Alwero watershed, western Ethiopia. Our analysis is focused on describing spatial and temporal variability of rainfall in the study area including detection of trends, with no attempt at providing meteorological explanations to any of the patterns or trends. The study is based on gridded monthly rainfall and maximum and minimum temperature data series at a resolution of 4 × 4 km which were obtained from the National Meteorological Agency of Ethiopia for the period 1983–2016. The study area is represented by 558 points (each point representing 4 × 4 km area). Mean annual rainfall of the watershed is > 1600 mm. Annual, June–September (Kiremt), March–May (Belg) rainfall totals exhibit low inter-annual variability. Annual and October-February (Bega) rainfalls show statistically significant increasing trends at p = 0.01 level. May and November rainfall show statistically significant increasing trends at p = 0.01 level. March shows statistically significant decreasing trend at p = 0.1 level. The mean annual temperature of the watershed is 25 °C with standard deviation of 0.31 °C and coefficient of variation of 0.01 °C. Mean annual minimum and maximum temperatures show statistically non-significant decreasing trends. Bega season experienced statistically significant deceasing trend in the maximum temperature at p = 0.01 level. The year-to-year variability in the mean annual minimum and maximum temperatures showed that the 2000s is cooler than the preceding decades. Unlike our expectations, annual and seasonal rainfall totals showed increasing trends while maximum and minimum temperatures showed decreasing trends. Our results suggest that local level investigations such as this one are important in developing context-specific climate change adaptation and agricultural planning, instead of coarse-scale national level analysis guiding local level decisions.

Highlights

Climate change is increasing the occurrence and magnitude of rainfall extremes that cause increased drought and flood risks (Chen et al 2014)
The focus of this study is to investigate the spatiotemporal variability and trends in rainfall and temperature in Alwero watershed in the western part of Ethiopia using a dense network of 4 × 4 km gridded data (558 points) reconstructed from weather stations and meteorological satellite records which spatially covers the watershed
Rainfall variability and trends in Alwero watershed Annual and seasonal rainfall patterns Mean annual rainfall of Alwero watershed is 1665.5 mm (Table 1), and its inter-annual variability is low with a Coefficient of variation (CV) of 8.7%

Summary

Introduction

Climate change is increasing the occurrence and magnitude of rainfall extremes that cause increased drought and flood risks (Chen et al 2014). The influence of current climate variability on crop production is large in developing countries like Ethiopia where agriculture is primarily dependent on rainfall Robust information on the seasonality of rainfall in the country is important to tackle its adverse economic and social consequences including on agriculture (Korecha 2013) and for local level climate change adaptation planning (Alemayehu and Bewket 2017a). The rainfall pattern in Ethiopia is strongly seasonal (World Bank 2006). The high and low rainfall phenomena can give rise respectively to flood and drought conditions with adverse economic and humanitarian crises (World Bank 2006). In Ethiopia, the performance of the agricultural sector and the rainfall pattern show strong correlations (Admassu 2004; Lemi 2005; World Bank 2006; Bewket 2009; Conway and Schipper 2011; Alemayehu and Bewket 2016a). Rainfall shortage often leads to famines (Alemayehu and Bewket 2017b)

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