Underground Dam Locating for Sustainable Groundwater Management Using Numerical Simulation

Carrying capacities and water resources ecological footprints since 2010 has been considered as an important problem. Comparing the evaluation indicators of the water resources indicated the variation levels of the stability. Machine Learning - Support Vector Regression (ML-SVR) was implemented to formulate the ecological footprints. The obtained status of water resources have always been characterized by ecological deficit. Experiments should be indicated outperforms classical model on both fitted values and the validation value. The results show that ecological footprints from 2010 to 2020 in Iran keep steady with higher levels, while from 2014 to 2016 witness a significant decline compared with previous years. The predicted ecological footprint for a ten recent years continue to decrease in semi-arid regions. The predicted results via SVR showed that ecological footprints from 2017 to 2020 will present a rising trend meaning the situation of water crisis will be increasingly serious in east parts of the central deserts.