MODELLING GROUNDWATER RECHARGE ESTIMATION USING MODIFIED SOIL MOISTURE BALANCE APPROACH IN OTUKPO BASIN
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ABSTRACT
In this study, groundwater recharge in Otukpo basin has been estimated using a modified daily soil moisture balance based on a single soil water store for a climate classified as tropical with distinct dry and wet seasons in the Middle Belt part of Nigeria. Soil properties like field capacity, permanent wilting point, readily available water, actual and potential evapotranspiration, soil moisture deficit were all estimated and deployed in the model which algorithm was developed using Python programming language, hence the name modified soil moisture balance model. Runoff is estimated using runoff matrix and runoff coefficients which depend on rainfall intensity and soil moisture deficits. A new component, near surface storage, is used to represent continuing evapotranspiration on days following heavy rainfall even though the soil moisture deficit is high. Groundwater recharge is estimated for cassava and yam which are commonly cultivated vegetable crops in the study area. Meteorological data for the periods of 2008 to 2018 were used in the model analysis. The model recorded annual groundwater recharge which varied from 333.35 mm in 2009 water year (just 20.01% of annual rainfall for the year) to 38.119 mm in 2017 water year which is 3.6% of annual rainfall for the year). The highest annual rainfall depth was also observed in the year 2009 as 1665.4 mm, with the lowest annual rainfall depth, 1062.4 mm also observed in the year 2017. The annual runoff ranged from 322.04 mm in the year 2015, a 32.16 % of annual rainfall for the year to 935.56 mm in the year 2008 a 58.17 % of annual rainfall for the year. The lowest actual evapotranspiration AE was also observed in 2017 as against the highest in 2012. The AE ranged from 583.84 mm in 2017 to 721.39 mm in 2012. The model gave a simplified method of groundwater recharge estimation as well as runoff depth coupled with rainfall-runoff relationship.
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