Use of remote sensing and long-term in-situ time-series data in an integrated hydrological model of the Central Kalahari Basin, Southern Africa

Distributed numerical models, considered as optimal tools for groundwater resources management, have always been constrained by availability of spatio-temporal input data. This problem is particularly distinct in arid and semi-arid developing countries, characterized by large spatio-temporal variability of water fluxes but scarce ground-based monitoring networks. That problem can be mitigated by remote sensing (RS) methods, which nowadays are applicable for modelling not only surface-water but also groundwater resources, through rapidly increasing applications of integrated hydrological models (IHMs). This study shows implementation of various RS products in the IHM of the Central Kalahari Basin (~200 Mm2) multi-layered aquifer system, characterized by semi-arid climate and thick unsaturated zone, both enhancing evapotranspiration. The MODFLOW-NWT model with UZF1 package, accounting for variably saturated flow, was set up and calibrated in transient conditions throughout 13.5 years using borehole hydraulic heads as state variables and RS-based daily rainfall and potential evapotranspiration as driving forces. Other RS input data included: digital-elevation-model, land-use/land-cover and soils datasets. The model characterized spatio-temporal water flux dynamics, providing 13-year (2002–2014) daily and annual water balances, thereby evaluating groundwater-resource dynamics and replenishment. The balances showed the dominant role of evapotranspiration in restricting gross recharge to only a few mm yr−1 and typically negative net recharge (median, −1.5 mm yr−1), varying from −3.6 (2013) to +3.0 (2006) mm yr−1 (rainfall of 287 and 664 mm yr−1 respectively) and implying systematic water-table decline. The rainfall, surface morphology, unsaturated zone thickness and vegetation type/density were primary determinants of the spatio-temporal net recharge distribution.