Normalized difference vegetation index as the dominant predicting factor of groundwater recharge in phreatic aquifers: case studies across Iran

The estimation of long-term groundwater recharge rate (GW_r) is a pre-requisite for efficient management of groundwater resources, especially for arid and semi-arid regions. Precise estimation of GW_r is probably the most difficult factor of all measurements in the evaluation of GW resources, particularly in semi-arid regions in which the recharge rate is typically small and/or regions with scarce hydrogeological data. The main objective of this study is to find and assess the predicting factors of GW_r at an aquifer scale. For this purpose, 325 Iran’s phreatic aquifers (61% of Iran’s aquifers) were selected based on the data availability and the effect of eight predicting factors were assessed on GW_r estimation. The predicting factors considered include Normalized Difference Vegetation Index (NDVI), mean annual temperature (T), the ratio of precipitation to potential evapotranspiration (P/ ET_P), drainage density (D_d), mean annual specific discharge (Q_s), Mean Slope (S), Soil Moisture (SM₉₀), and population density (Pop_d). The local and global Moran’s I index, geographically weighted regression (GWR), and two-step cluster analysis served to support the spatial analysis of the results. The eight predicting factors considered are positively correlated to GW_r and the NDVI has the greatest influence followed by the P/ ET_P and SM₉₀. In the regression model, NDVI solely explained 71% of the variation in GW_r, while other drivers have only a minor modification (3.6%). The results of this study provide new insight into the complex interrelationship between GW_r and vegetation density indicated by the NDVI. The findings of this study can help in better estimation of GW_r especially for the phreatic aquifers that the hydrogeological ground-data requisite for establishing models are scarce.