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 / E T P ), drainage density ( D d ), mean annual specific discharge ( Q s ), Mean Slope ( S ), Soil Moisture ( SM 90 ), 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 SM 90 . 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.