Abstract
Groundwater recharge rates emerge from complex interactions within the soil-vegetation-atmosphere system. While it is widely recognized that numerical models are able to properly simulate soil water dynamics depending on boundary forcing data, in-depth information on episodic recharge generation needs to be gained. In this study, the water balance of a heterogeneous 300 cm-deep soil profile beneath a rainfed maize agro-ecosystem in eastern Nebraska was numerically simulated in HYDRUS-1D for 12 years (2001–2012) on daily time steps. We estimated potential groundwater recharge as the downward flux simulated below maximum maize root depth (150 cm). This model was calibrated in a previous study by using direct field measurements. Simulated results indicated that annual rainfall scarcely controls the amount of annual recharge. The impact of individual storm event on recharge episodicity was assessed through iterative scenario modeling. We investigated the importance of rainfall events classified according to convective-stratiform scoring, spanning from 0 and 1, designating extremely stratiform and convective, respectively. The inequality of frequency distribution of rainfall and recharge was assessed by using the Gini coefficient. We detected relatively few significant recharge responses clustering near the 1:1 rainfall/recharge line in late winter (38% of events) and spring (only 13% of events). Generally, the recharge events are triggered by stratiform (28% of total sum) and convective (44% of total sum) precipitation events. Nonetheless, the most efficient recharge events are generated by stratiform rainfall when soil saturation increases without runoff generation. The intense convective storm events often cause saturation excess with runoff generation and mostly occur when evapotranspiration demand is high. For these two main reasons, convective storms lead to inefficient recharge rates characterized by extreme episodicity.
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