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

Moiteela Lekula,Maciek W Lubczynski

doi:10.1007/s10040-019-01954-9

Abstract

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.

Highlights

Groundwater is often the only, but vulnerable, source of potable water in arid and semi-arid areas, it must be well evaluated and managed
The main objectives of this study were: (1) to present the use of various remote sensing (RS) products coupled with long-term in-situ monitoring data, as input of a regional-scale distributed numerical integrated hydrological models (IHMs) of the Central Kalahari Basin (CKB); (2) to characterize spatio-temporal water flux dynamics of a semi-arid, multi-layered aquifer system characterized with very thick unsaturated zone; and (3) to provide a long-term quantitative water-balance estimate of such a system, evaluating its groundwater resources
The steep declines of groundwater heads are observed in boreholes W13J, W43J and TP34J located in the wellfield operated by Debswana Diamond Mining

Summary

Introduction

Groundwater is often the only, but vulnerable, source of potable water in arid and semi-arid areas, it must be well evaluated and managed. RS has played an increasingly important role in providing spatio-temporal information for water resources evaluation and management (Coelho et al 2017). Its applications in surface hydrology, including surface-water modelling, are already well known and typically include digital elevation derivatives, land use/cover, and spatio-temporal rainfall and evapotranspiration evaluations (Schmugge et al 2002). Standard published RS applications in groundwater hydrology have involved: assessment of groundwater recharge (e.g., Awan et al 2013; Brunner et al 2004; Coelho et al 2017; Jasrotia et al 2007; Khalaf and Donoghue 2012), surface-water/groundwater interaction (e.g., Bauer et al 2006; Hassan et al 2014; Leblanc et al 2007; Sarma and Xu 2017), and groundwater storage (resources) evaluation and change (e.g., Henry et al 2011; Rodell et al 2007; Rodell and Famiglietti 2002; Taniguchi et al 2011; Yeh et al 2006). With recent advancement of IHMs, the RS contribution to such models is rapidly increasing, mainly because of continuously increasing amounts of downloadable RS-based hydrological products, for example, rainfall or potential evapotranspiration data

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Conclusion