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Hydrol. Earth Syst. Sci., 17, 637-650, 2013
https://doi.org/10.5194/hess-17-637-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
11 Feb 2013
Natural vs. artificial groundwater recharge, quantification through inverse modeling
H. Hashemi1, R. Berndtsson1, M. Kompani-Zare2, and M. Persson3 1Center for Middle Eastern Studies & Department of Water Resources Engineering, Lund University, Lund, Sweden
2Department of Desert Regions Management, College of Agriculture, Shiraz University, Shiraz, Iran
3Department of Water Resources Engineering, Lund University, Lund, Sweden
Abstract. Estimating the change in groundwater recharge from an introduced artificial recharge system is important in order to evaluate future water availability. This paper presents an inverse modeling approach to quantify the recharge contribution from both an ephemeral river channel and an introduced artificial recharge system based on floodwater spreading in arid Iran. The study used the MODFLOW-2000 to estimate recharge for both steady- and unsteady-state conditions. The model was calibrated and verified based on the observed hydraulic head in observation wells and model precision, uncertainty, and model sensitivity were analyzed in all modeling steps. The results showed that in a normal year without extreme events, the floodwater spreading system is the main contributor to recharge with 80% and the ephemeral river channel with 20% of total recharge in the studied area. Uncertainty analysis revealed that the river channel recharge estimation represents relatively more uncertainty in comparison to the artificial recharge zones. The model is also less sensitive to the river channel. The results show that by expanding the artificial recharge system, the recharge volume can be increased even for small flood events, while the recharge through the river channel increases only for major flood events.

Citation: Hashemi, H., Berndtsson, R., Kompani-Zare, M., and Persson, M.: Natural vs. artificial groundwater recharge, quantification through inverse modeling, Hydrol. Earth Syst. Sci., 17, 637-650, https://doi.org/10.5194/hess-17-637-2013, 2013.
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