Abstract
Abstract Understanding rainfall distribution in space and time is crucial for sustainable water resource management and agricultural productivity. This study investigated the spatial distribution and temporal trends of rainfall in Amhara region using time series rainfall data of Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) for the period 1981–2017. Coefficient of variation, standardized anomaly index (SAI), precipitation concentration index (PCI) and seasonality index (SI) were used to evaluate rainfall variability and seasonality. Mann–Kendall's test was also employed for rainfall trend analysis. Results showed that the region has been experiencing variable rainfall events that cause droughts and floods over different years. SAI also witnessed the presence of inter-annual variability of rainfall with negative and positive anomalies in 59.46% and 40.54% of the analyzed years, respectively. PCI and SI results implied that the area had irregular and strong irregular rainfall distribution. Trend analysis results showed an overall increase in the annual and seasonal rainfall (except winter) during the study period. The information obtained from this study could serve as a proxy for rainfall variability and trend in the study area which might be used as input for decision-makers to take appropriate adaptive measures in various agricultural and water resources sectors.
Highlights
Climate change and variability are perceived as being the greatest threats to agricultural production and food security in sub-Saharan African countries, for regions that depend on rain-fed agriculture (Kisaka et al )
Good agreement between the station observations and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall data was observed with correlation coefficients R 1⁄4 0.91 and R 1⁄4 0.86 for monthly and annual scales, respectively
Values of mean error (ME) and percent bias (PB) in both temporal scales indicated that the CHIRPS data tended to slightly underestimate the observed rainfall data
Summary
Climate change and variability are perceived as being the greatest threats to agricultural production and food security in sub-Saharan African countries, for regions that depend on rain-fed agriculture (Kisaka et al ). Analysis of the spatial distribution and the temporal trends of rainfall is crucial for water resource management, agricultural productivity and climate change mitigation (Ayalew et al ). Analyzing both inter-annual and intra-annual trends in rainfall offers intuitive information on the dynamics of soil moisture in rain-fed systems (Zhao et al ). Such spatial and temporal trend analyses of rainfall require long-term rainfall time series data at high temporal and spatial resolutions. Meteorological stations have been used as the main source
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