The covered karst water resource evaluation and mining plan prediction in Daxing overlapping uplift area

The Daxing overlapping uplift area is located in the middle and lower reaches of the alluvial-proluvial plain of the Yongding and Chaobai rivers in the south of Beijing. The karst water under the quaternary aquifer has good quality and large storage. With the development of the urban area, the demand for groundwater has increased. Leadings to increased use of the karst water. With the continuous decline of the karst water level, it is essential to assess the groundwater resource and analyze the exploitation plan. A numerical model was set up by means of GMS, simulating the karst groundwater flow system and predicting variations in the groundwater level. The model was conceptualized with five layers, the 1st and 2nd layers are quaternary aquifers, the 3rd to 5th layers are karst aquifers. The model was calibrated using historical data spanning 12 years and 9 months. According to the model’s water budget, the recharge of the groundwater system is 14,425.74×104 m3/a, the total allowable exploitation of the groundwater system is 14,310.52×104 m3/a, of which the karst aquifer is 2,309.36×104 m3/a. Analysis of the groundwater budget indicates, that the main recharge of the karst water aquifer is the leakage from the upper quaternary aquifer. Considering the local hydrogeological condition and the groundwater supply conditions, four exploitation plans have been proposed,(1)Maintain current exploitation;(2)Exploit according to the allowable exploitation level;(3)Maintain current exploitation until 2020, exploit by according to allowable exploitation level after 2020;(4)Maintain current exploitation until 2020, then stop the Niantan water source exploitation after 2020, and exploit according to the allowable exploitation level after 2025. By analyzing the stage hydrograph of typical observed well and the water balance, The 4th plan is the best exploitation plan.In conclusion, the model is fit to describe the local hydrogeological features and has been successfully applied to predict changes in groundwater level.