Parsimonious Model of Groundwater Recharge Potential as Seen Related with Two Topographic Indices and the Leaf Area Index - Rodríguez-Moreno Victor Manuel; Kretzschmar Thomas Gunter (Hydrology)
A concise model, utilizing the threshold values of closed depressions, the convergence index, and the leaf area index (LAI) that play a significant role in modeling vegetation–atmosphere interactions and understanding the impact of vegetation on the hydrological cycle, was employed to pinpoint potential aquifer recharge centroids. The LAI index served as a geographic mask, linking centroid locations to soil vegetation cover. Analyzing a paired subsample of 500 centroids for each strata (true and false), we observed that maximum values of true centroids, indicating potential groundwater recharge, correlated with the presence of abundant vegetation (0.074 < LAI < 0.639). Conversely, lower LAI values were associated with sparse vegetation in false centroids (0.01 < LAI < 0.590). The study’s findings hold promising implications for aquifer management, biodiversity conservation, hydric planning, and land use protection, making a substantial contribution to the field. The recharge hypothesis is theoretically sound and empirically supported to propose that areas of high topographic convergence and closed depressions are potential water recharge zones, and these locations may exhibit permanent or denser vegetation, reflected as higher LAI values. This happens because water accumulates or lingers in these zones, soil moisture is maintained more consistently, and plant roots access water for longer periods, even during dry seasons. Vegetation becomes more resilient and persistent (possibly even forming phreatophytes—plants accessing groundwater). Additionally, there is potential for expanding the research by incorporating field observations, including tracking the routes of surface and subsurface runoff and determining arrival times to the aquifer. Such studies are increasingly vital for addressing contemporary environmental and water resource challenges.