Author:
Parizi Esmaeel,Hosseini Seiyed Mossa,Ataie-Ashtiani Behzad,Simmons Craig T.
Abstract
AbstractThe estimation of long-term groundwater recharge rate ($${GW}_{r}$$
GW
r
) is a pre-requisite for efficient management of groundwater resources, especially for arid and semi-arid regions. Precise estimation of $${GW}_{r}$$
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 $${GW}_{r}$$
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 $${GW}_{r}$$
GW
r
estimation. The predicting factors considered include Normalized Difference Vegetation Index (NDVI), mean annual temperature ($$T$$
T
), the ratio of precipitation to potential evapotranspiration ($${P/ET}_{P}$$
P
/
E
T
P
), drainage density ($${D}_{d}$$
D
d
), mean annual specific discharge ($${Q}_{s}$$
Q
s
), Mean Slope ($$S$$
S
), Soil Moisture ($${SM}_{90}$$
SM
90
), and population density ($${Pop}_{d}$$
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 $${GW}_{r}$$
GW
r
and the NDVI has the greatest influence followed by the $$P/{ET}_{P}$$
P
/
ET
P
and $${SM}_{90}$$
SM
90
. In the regression model, NDVI solely explained 71% of the variation in $${GW}_{r}$$
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 $${GW}_{r}$$
GW
r
and vegetation density indicated by the NDVI. The findings of this study can help in better estimation of $${GW}_{r}$$
GW
r
especially for the phreatic aquifers that the hydrogeological ground-data requisite for establishing models are scarce.
Publisher
Springer Science and Business Media LLC
Cited by
29 articles.
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