Trend Analysis of Hydro-meteorological Data and their Implication in Water Resource Development (Case Study in Arjo-didessa Sub-basin)
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Date
2021-04
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Addis Ababa University
Abstract
The issue of hydro-climatic variability and trend has been taken into the attention of the scientific community over the world. As such, the variability and the length of the period during which the change would occur have considerably different implication for water resources planning and management. This study aimed to investigate and characterize the trend of hydro-meteorological variables in the Arjo-didessa sub-basin in Ethiopia.
A non-parametric test, Mann-Kendall, modified Mann-Kendall, Sen’s slope estimator, and Innovative Trend tests were used to detect trends exhibited by rainfall, temperature, and stream flow on monthly, seasonal, and annual time scale. To represent the variability and trend condition in the sub-basin, monthly rainfall data from eleven stations, monthly mean temperature from three stations, and daily stream flow from three gauging stations were collected and analyzed for trends detection. Four open-source library of R packages; modifiedmk, trend, hydroTSM, and trend change were used in R language to perform trend analysis, and homogeneity tests.
The monthly rainfall trend result shows non-uniform in rainfall intensity. Different stations and variables show different results while applying the methods. Accordingly, mean monthly maximum temperature shows an increasing trend in Bedele and Nekemte. Monthly streamflow, Didessa Nr. Arjo shows an increasing trend. Only Arjo and Kone station shows a significant increasing trend in annual rainfall. A significant increasing trend in annual mean Tmax was observed for Nekemte station and significant decreasing annual mean Tmin was observed for Alibo stations.
Generally, an increasing or decreasing level of rainfall, temperature, and streamflow in each selected station for the study area indicates the change in trend. The coefficient of variation used to analyze spatial variability of annual rainfall for each station varies from 9.83% to 24.54% which indicates from less to moderate variability in rainfall data. High variability of coefficient of variation for rainfall stations was observed in the study area for seasonal time scale. The findings from this study can help experts, researchers, and policy makers to get awareness about the variability and temporal trends of precipitation, temperature, and streamflow alteration in the Arjo-didessa sub-basin which will definitely affect the water resources development.
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hydro-climatic data, trend detection, Mann-Kendall test, Sen’s slope estimator, Innovative trend analysis (ITA)