THE COMBINED USE OF LONG-TERM MULTI-SENSOR INSAR ANALYSIS AND FINITE ELEMENT SIMULATION TO PREDICT LAND SUBSIDENCE

Land subsidence in Tehran Plain, Iran, for the period of 2003–2017 was measured using an InSAR time series investigation of surface displacements. In the presented study, land subsidence in the southwest of Tehran is characterized using InSAR data and numerical modelling, and the trend is predicted through future years. Over extraction of groundwater is the most common reason for the land subsidence which may cause devastating consequences for structures and infrastructures such as demolition of agricultural lands, damage from a differential settlement, flooding, or ground fractures. The environmental and economic impacts of land subsidence emphasize the importance of modelling and prediction of the trend of it in order to conduct crisis management plans to prevent its deleterious effects. In this study, land subsidence caused by the withdrawal of groundwater is modelled using finite element method software Plaxis 2D. Then, the model was verified using InSAR data. The results were in good agreement with the measurement results. The calibrated model was used to predict the land subsidence in future years. It could predict future subsidence for any assumed rate of water depletion.

Optimization of Integrated Management to use Surface Water and Groundwater Resources by Using Imperialist Competitive Algorithm and Genetic Algorithm (Tehran Plain)

The extensive development of activities in different areas of surface and underground water resources and the lack of sufficient attention to integrated planning and management necessitates research in this regard. Due to the imbalance in the distribution of water resources and the constraints on water resources and the constraints on the use of surface water, it is necessary to combine the use of surface water and underground water resources. In this study, the modelling is done in such a way that maximum use of surface water is achieved and the rate of utilization of groundwater reaches its minimum. In this study, imperialist and genetic competition algorithms are used for optimization. In this study, the extent of utilization of groundwater resources is limited and it has tried to use all of the surface water resources of Tehran Plain. The results of this study showed that the amount of water needed from the beginning of the year begins to decrease and then increases, and this increase is related to the warm seasons of the year. Surface water levels increase in cold seasons. In the cold seasons, the supply of water requirements was complete, but in the warm seasons, some water requirements were not met. The results of this study indicate that if the amount of groundwater resources is kept to an optimum level within 10 years, the problem of groundwater resources in Tehran plain will be solved.