Utilizing the HBV-Light semi-distributed conceptual hydrological model to estimate groundwater recharge in the upstream part of the Awash River basin, Ethiopia

Study region

Upstream part of the Awash River basin, located central part of Ethiopia

Study focus

In this paper, we estimated the groundwater recharge using a semi-distributed, conceptual hydrological HBV-Light model. We used metrological and flow data from the Ethiopia Metrological Agency and the Ministry of Water and Energy, respectively. To simulate groundwater recharge over the reference period from 1988 to 2015 we merged these data with the conceptual HBV-Light rainfall-runoff model for calibration and validation. The average yearly precipitation from 1986 to 2015 was 1117 mm. Two calibration situations are examined to determine the level of uncertainty using a Monte Carlo approach with randomly generated parameter values.

New hydrological insights for the region

For a 20-year calibration period, several parameter values were observed and modeled flow equally well. Except for most parameters, good simulations were discovered with values that varied across vast ranges. A few parameters were well-defined (i.e., the optimum parameter values were within limited ranges). We also employed the regional sensitivity analysis (RSA) method to assess the sensitivity of model parameters and model. HBV-light and the generalized likelihood uncertainty estimation method were used for selecting its parameters. The results indicate that the calculated evapotranspiration is 79.5–80 % of the precipitation. Awash Melkakuntiro and Hombele’s calculated recharge rates are 220.8 mm/yr and 212.01 mm/yr, respectively. Thus, the average annual recharge for the study area is 216 (19.6 %) of the yearly precipitation. The study found that groundwater resource availability is strongly linked to current recharge rates. To improve the accuracy of groundwater recharge estimation, the HBV-Light model was employed. The study recommends enhancing data consistency and quality by expanding the hydrometeorological database and integrating real-time data for daily recharge calculations.