Jinan city, the capital of Shandong Province in China, is famous for itsbeautiful springs. With the rapid development of the economy in recent years,water demand in Jinan city has been increasing rapidly. The over-exploitationof groundwater has caused a decline in groundwater level and, notably, driedup springs under extreme climate conditions. To keep the springs gushingperennially and sustainably use groundwater resources, the local governmenthas implemented many measures to restore the water table, such as the SpongeCity Construction Project in Jinan. Focusing on changes in spring flow andits impact factors in Jinan, this paper analyzes the changes in observedspring flow in the most recent 50 years and then discusses the causes ofdecreases in the spring flow with the consideration of climate and humanactivities. Spring flow in the study area was changed from the natural stateto a period of multiwater source management. The artificial neural network(ANN) model was developed to demonstrate the relationship among spring flow,precipitation, and groundwater abstraction to predict the variations ofspring flow under the conditions of climate change and human activities. Thegood agreement between the simulated and observed results indicates that bothprecipitation and exploitation are important influence factors. However theeffective infiltration of precipitation into groundwater is the mostinfluential factor. The results can provide guidance for groundwater resourceprotection in the Jinan spring catchment.
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