GROUNDWATER LEVEL PREDICTION THROUGH GMS SOFTWARE – CASE STUDY OF KARVAN AREA, IRAN

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Mandana Bayat
Saeid Eslamian
Gholamreza Shams
Alborz Hajiannia

Abstract

Iran, being located in arid and semi-arid regions, faces an increase in human demand for water, and the global climate change has led to the excessive use of groundwater. China, India and Iran were ranked from first to third, respectively, in excessive groundwater consumption in 2005. The effects of effective parameters on groundwater recharge such as precipitation, surface recharge and well water harvesting in the Karvan aquifer are assessed. Groundwater flow models have typically been and are being adopted since the beginning of this millennium to better manage groundwater resources. The decrease in groundwater level and the potential environmental hazards thereof have made the researchers here to apply the Groundwater Modelling System (GMS software) in 3D in the subject area. This modelling is calibrated and validated for 86 months at steady and unsteady states. In this study, six scenarios are defined as both an increase and a decrease of 30% in precipitation, both an increase and a decrease of 30% in surface recharge, an increase of 10% in well water harvesting and a decrease of 30% in well water harvesting. The best scenario is selected for the subject area water management.

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Bayat, M., Eslamian, S., Shams, G., & Hajiannia, A. (2020). GROUNDWATER LEVEL PREDICTION THROUGH GMS SOFTWARE – CASE STUDY OF KARVAN AREA, IRAN. Quaestiones Geographicae, 39(3), 139–145. https://doi.org/10.2478/quageo-2020-0028
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