A new workflow for estimating groundwater recharge in data-scarce environments

This study proposes a novel workflow for estimating groundwater recharge in data-scarce environments, using the Densu Basin in Ghana as a case study. The method combines the water table fluctuation method (WTFM) and the soil water balance (SWB) approach, with a bias correction step applied to reconcile systematic differences between the two methods. Recharge estimates from both approaches revealed significant spatial and seasonal variability, with higher rates in the northern sectors characterized by favorable soil types (sandy clay loam and sandy clay) and extensive forest cover. The WTFM, applied from 2004 to 2009, yielded an average monthly recharge of 43.9 mm, while the SWB approach, covering 1960–2015, estimated a lower average of 33.7 mm. The June–July–August season (June–August) exhibited the highest recharge contribution. Bias correction of the SWB series using WTFM as reference substantially reduced systematic error, with linear scaling achieving the smallest mean bias and providing corrected recharge estimates ranging from 27 to 39 mm/month, increasing from the southern to the northern parts of the basin. The soil conservation service method estimated an annual runoff of 439 mm (26% of annual rainfall). The results highlight the influence of soil properties, land cover, and rainfall patterns on recharge dynamics and emphasize the need for adaptive, localized water management strategies to ensure long-term sustainability of groundwater resources in the Densu Basin.