Abstract:
Understanding the hydrological environment and groundwater resource availability leads to
effectively planning, developing, and managing the available water resources. There are dif ferent physical and empirical models to understand the water balance components of a given
watershed. One of the spatially distributed physical models is the Wetspass model that’s re spond the impact of lulc on water balance components and climate Hargeisa watershed. The
Wetspass-M model has simulated the annual, monthly water balance components of the Har geisa watershed successfully, based on the model, the monthly water balance components in
the Hargeisa watershed is summed up by seasonality; the highest season recharge occurs in
summer were 0 to 74.9mm, sprin were 0 to 68mm, and Autumn moderate, while winter is dry.
The recharge rates performed by Wetspass model were consequently compared with those
achieved by empirical relations namely; Chaturvedi Formula (CF), Sehgal Formula (SF),
Krishna Rao Formula (KRF), and Bhattacharya Formula (BF). It was exhibited that average
rate of yearly groundwater recharge for calibration periods during 2014–2017 was
193.02mm/yr with RMSE and R², of 46.76mm, 0.7, respectively. The model also resulted in
monthly annual runoff in the watershed, which were seasonal 69.37mm, 59.38mm, and
40.4mm in the spring, summer, and autumn, respectively. Likewise, the AET seasonal water shed is 138mm, 159mm, 207mm, and autumn 158mm in the winter, spring, summer, and au tumn, respectively. The sensitivity analysis of the different input variables was conducted and
most of the variables are highly sensitive in the Hargeisa watershed. The analysis results
show that rainfall, soil, and slope are the most important hydrologic processes in the study
area in terms of affecting the amount and rate of the different water balance components. The
parametric coefficient of alfa coefficients, interception coefficients, and Lp coefficient are
also relatively sensitive. The calibration was made between the simulated and observed em pirical recharge through the coefficient determination R^2 0.87, which indicates a good cor relation between both. the future climate projected using Regional climate model based
CMIP5 namely single model ROC-ESM-CHEM under RCP4.5, and 8.5 scenarios, in the pro jected temperatures to rise incessantly, although the monthly annual rainfall increased, the
seasonal rainfall increased in winter, and autumn for both scenarios, but summer decreased
RCP4.5 13.47 and 9% 2020s, 2050s, and RCP8.5 2.47% 2050s. Spring decreased for both
scenarios in all periods. The Wetspass-M model has successfully simulated the annual
monthly water balance components.
The high variable distribution of the climatic inputs (parameters) with the variation in lulc,
soil texture, topography, and slope are responsible for variations of water balance elements
within the watershed. Likewise, the future climate projected result shows the increase in tem perature max/min annually and season, while the rainfall increases annually, but decreases
seasonally specifically rain season in the study