Water Balance Components Estimation using WetSpass Model: A Case study of Mekelle Area, Tigray, Ethiopia

Kahsay Hailekiros *

Mekelle Industrial Park, Industrial Park Development Corporation (IPDC), Mekelle, Tigray, Ethiopia.

Tesfamichael Gebreyohannes

Department of Geology, School of Earth Science, Mekelle University, P.O.Box 3066, Mekelle, Tigray, Ethiopia.

Abdelwassie Hussein

Department of Geology, School of Earth Science, Mekelle University, P.O.Box 3066, Mekelle, Tigray, Ethiopia.

Hagos Brhane

Tigray Agricultural Research Institute, Mekelle Soil Research Center, Ethiopia.

*Author to whom correspondence should be addressed.


Abstract

This research was aimed at estimating the spatially distributed Water balance components of the catchments in Mekelle area by using WetSpass hydrological model and verifying the model outputs with ground truth. Long term mean metrological data and physical characteristics of the catchments were used as an input to the model. The input data were manipulated using Arc- GIS tools. Results of this model depicted that about 73.13% and 19.96% of the precipitation in the study area was lost through evapotranspiration and surface runoff respectively. However, 7% of it replenished the groundwater. The annual runoff and groundwater recharge estimated in WetSpass model accumulated using Arc-GIS were verified using the annual runoff gauged records and base flow measurements. Accordingly the accumulated runoff and base flow derived from the WetSpass model using Arc-GIS software results were quite close to the observed runoff and base flow values measured in the gauging points. Therefore, WetSpass model is appropriate model in estimating water balance components in the study area.

Keywords: Groundwater, recharge, runoff, evapotranspiration, WetSpass, Mekelle


How to Cite

Hailekiros , K., Gebreyohannes , T., Hussein , A., & Brhane , H. (2023). Water Balance Components Estimation using WetSpass Model: A Case study of Mekelle Area, Tigray, Ethiopia. Physical Science International Journal, 27(3), 27–37. https://doi.org/10.9734/psij/2023/v27i3793

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