Dissertation
Dissertation > Astronomy,Earth Sciences > Geology > Hydrogeology and Engineering Geology > Hydrogeology (groundwater hydrology ) > Groundwater resource management

Study on the Karstic Groundwater Allowable Withdrawal of the East Hot Spring Basin,Chongqing

Author ChenAiHua
Tutor ZhaoQiHua; FanZeYing
School Chengdu University of Technology
Course Geological Engineering
Keywords Banan chongqing city the east hot spring groundwater allowable withdrawal Spring discharge ANN
CLC P641.8
Type Master's thesis
Year 2011
Downloads 44
Quotes 0
Download Dissertation

Karst area is widelv distributed in China. The total volume of Karst water resource in china is about2039.67×109m3/year which accouts for about50%of groundwater resource in China. Karst water resource in south China makes up50%of Karst water resource.Thus Karst water is not only the local drinking water resource, but also an important role in national economic construction. The hot spring is an especial resource of karst spring, which is a renewable resource with thermal energy and water resource.Karst area is a heterogeneous aquifer medium、special water circulation and runoff processes.Therefore, Karst groundwater system is a complex dynamic system with high heterogeneity. The normal hydrology model by groundwater hydrodynamic theory based on homogeneous medium can not interpret and calculate water movement in karst region. This character lead to many problems to evaluate groundwater allowable withdrawal.At recent,the hot spring tourism become a new tourism industry.Because of the increasing requirement of hot spring resource, the natural groundwater resource has been consumed with many environment geological disaster occurring.Banan basin is the tenth "hot spring village" in China and the first "hot spring village" in west China. It is significant to study on groundwater allowable withdrawal in Banan basin for reasonable utilization of hot spring resource and environmental conservation.This paper has taken the east hot spring of Chongqin as the object of this study. As system theory a guiding ideology, Collectting springs in different periods of the domain karst ground and volume material, with more discipline knowledge and theory for support,with reading lots of literature, on the basis of the existing groundwater resource evaluation method are deeply analyzed.It introduced a brief overview of the geographical, geological and hydrogeological conditions of the east hot spring. Based on the time series data of the east hot spring, the factors which affect the dynamic variation of the spring discharge had been discussed. And on this basis the Artificial neural network (Artificial neural wants abbreviations ANN) is selected for domain model of east spring groundwater studies model. A prediction model of spring discharge dynamic had been built based on artifical neural networks (ANN) of the east hot spring basin, Chongqing.After testing and rectification of the ANN model, in order to study the hot spring groundwater simulation, Forecasting meteorological and hydrological and mining conditions of different under the dynamic change of springs flowing, gotten the inversion of different rainfall assurance springs domain is available groundwater, and on the east spring in the karst area can be exploited to study and evaluate groundwater. For the research results:1、According to the domain springs of the east spring for many years and hydrological and meteorological datathis model is capable to predict the spring discharge of the east spring basin in Chongqin. The precipitation and the groundwater withdraws are the main factors. There is a time-lag between the precipitation and the spring discharge. According to correlation analysis, the residence time in the east spring is about2years. Groundwater withdraw is the main factor which lead to the recession of the east spring. Due to the long-term and exploitation of groundwater in the east spring karst basin, one of the nature discharge point(S2) dried up in2008.2、Using of MATLAB software based on the artificial neural network man-machine interactive graphical user interface GUI establish east spring dynamic prediction of BP artificial neural network model. this model is capable to predict the spring discharge of the east spring basin in Chongqin.3、Based on this ANN model, the spring discharge can be predicted by this model under different precipitation conditions. When the spring discharge declined to0, the corresponding groundwater withdraws is the groundwater allowable withdrawal under this corresponding precipitation conditions. The results showed the influential factors of the hot spring discharge are precipitation, groundwater withdraws. Groundwater withdraws plays an important part in spring discharge recession. The groundwater allowable withdrawals under different precipitation conditions are9697m3/d in normal year,10471m3/d in wet year and7849m3/d in dry year, respectively.

Related Dissertations
More Dissertations