Long-Term Evolution of Cones of Depression in Shallow Aquifers in the North China Plain
نویسندگان
چکیده
The North China Plain (NCP) is one of the places where the groundwater is most over-exploited in the world. Currently, our understanding on the spatiotemporal variability of the cones of depression in this region is fragmentary. This study intends to simulate the cones of depression in the shallow aquifer across the entire NCP during the whole period from 1960 to 2011. During the simulation, the dominant role of anthropogenic activities is emphasized and carefully taken into account using a Neural Network Algorithm. The results show that cones of depression in the NCP were formed in 1970s and continuously expanded. Their centers were getting deeper with an increasing degree of groundwater exploitation. This simulation provides valuable insights for developing more sustainable groundwater management options after the implementation of the South-to-North Water Diversion Project (SNWDP), which is a very important surface water project in China in the near future. The numerical model in this paper is built by MODFLOW, with pumpage data completed by neural network algorithm and hydrogeological parameters calibrated by simulated annealing algorithm. Based on our long-term numerical model for regional groundwater flow in the NCP, one exploitation limitation strategy after the implementation of SNWDP is studied in this paper. The results indicate that the SNWDP is beneficial for groundwater recovery in the NCP. A number of immense groundwater cones will gradually shrink. However, the recovery of the groundwater environment in the NCP will require a long time.
منابع مشابه
A study of the relationship between the exploitation and subsidence of Salmas
Salmas plain is located at the west of Uremia lake and at the 75 km of north of Uremia city. The main river of the plain, called Zulachai, is drained into Uremia Lake. Salmas aquifer is one of the coastal aquifers of Uremia Lake and has hydraulic connection with the lake. The recent draught occurrences and increased water consumption in agriculture and drinking sections water have not only caus...
متن کاملWater use patterns of forage cultivars in the North China Plain
Water shortage is the primary limiting factor for crop production and long-term agricultural sustainability of the North China Plain. Forage cultivation emerged recently in this region. A fiver-year field experiment studies were conducted at Yucheng Integrated Experiment Station to quantify the water requirement and water use efficiency of seven forage varieties under climate variability, that ...
متن کاملThree-dimensional Magnetotelluric Modeling of data from Northeast of Gorgan Plain
Magnetotelluric measurements have been conducted in the period range of 0.005-128 s along five parallel east-west directed profiles including 85 sites totally in the north-eastern part of Gorgan Plain, Golestan Province, North of Iran; with the aim of exploring iodine. Distortion and dimensionality analysis of data imply the existence of a north-south elongated two-dimensional model with some l...
متن کاملVertical Displacements Driven by Groundwater Storage Changes in the North China Plain Detected by GPS Observations
The North China Plain (NCP) has been experiencing the most severe groundwater depletion in China, leading to a broad region of vertical motions of the Earth’s surface. This paper explores the seasonal and linear trend variations of surface vertical displacements caused by the groundwater changes in NCP from 2009 to 2013 using Global Positioning System (GPS) and Gravity Recovery and Climate Expe...
متن کاملImpact of spatial-temporal variations of climatic variables on summer maize yield in North China Plain
Summer maize (Zea mays L.) is one of the dominant crops in the North China Plain (NCP). Its growth is greatly influenced by the spatial-temporal variation of climatic variables, especially solar radiation, temperature and rainfall. The WOFOST (version 7.1) model was applied to evaluate the impact of climatic variability on summer maize yields using historical meteorological data from 1961 to 20...
متن کامل