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The Protection Theory And Recovery Technology Of Groundwater

Posted on:2011-08-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y H DongFull Text:PDF
GTID:1100360308460377Subject:Hydrology and water resources
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Groundwater overexploitation leaded to series of environmental and geological problems, such as aquifer draining, land subsidence, and inducing ground fissure. The problems are very serious in Xi'an after at least 10 years groundwater overexploitation. The research of groundwater protection and recovery is urgent for the sustainable use of water resources and groundwater environmental protection in Xi'an. As the groundwater vulnerability assessment was the base of groundwater protection theories and selecting the recovery region, furthermore the research of water quantity recovery was few. The groundwater protection and recovery were studied entirely in this paper.The existing research of groundwater vulnerability was more about assessing the unconfined water quality vulnerability; the vulnerability for confined water and quantity of water were few. The evaluation criterions were non-uniform and the methods needed to be perfect. Reducing the groundwater exploitation in high vulnerability region and groundwater depression cone was useful to the groundwater level recover, but the effect was not obvious. Artificial groundwater recharge was needed to raise the speed of recovery. The study of groundwater level prediction for short time data should be enhanced also. The well reinjection was another recovery technology and was suitable for groundwater level recovery for the regions with little bare area. The research of well reinjection to confined aquifer was also short. The recovery effect of well reinjection and the groundwater hydrodynamic field needed to be further studied. The mature standard and theory were scarce. For resolving the above problems, combining with the subject of groundwater protection and utilization and artificial groundwater recharge, the concept, criterion and method of groundwater vulnerability assessment was studied, the effect of reducing groundwater exploitation and carrying out well reinjection in high vulnerability regions and groundwater depression cone were researched. After theory research and well reinjection test verification, the results are as follows:1. The exiting concepts of groundwater vulnerability were analyzed. A more comprehensive concept was put forward, including the vulnerability of unconfined water, confined water, water quantity and quality. The character and assessment principle of groundwater vulnerability were presented. The rationality of Weber-Fechner expand law was test by an example for groundwater quality classify. The law was used at defined the groundwater vulnerability evaluation criterion.2. A new groundwater vulnerability assessment method was put forward, which was called Probabilistic Neural Network with W-F expand law method, the method combined Weber-Fechner expand law and Probabilistic Neural Network. The new method was used in Xi'an for groundwater vulnerability assessment. The assessment results were compared with the actual exploitation, water quality and the former assessment results. The new method results were more according with the actual situation. The PNN & W-F method avoided the subjectivity of present method, the determination of evaluation criterions was not restricted by the region, and the evaluation range was wider, the vulnerability of unconfined water, confined water, water quantity and quality could be evaluated. The new method could reflect the nonlinear relationship of groundwater, and the sensitive degree and recovery ability of groundwater under the same load of future exploitation and pollutant discharge.3. The dynamic groundwater level and its influence of 4 groundwater source region in Xi'an were deeply analyzed. The rainfall, evaporation, runoff and artificial exploitation were defined as the input of predict model, groundwater level was the output. The forecast results were compared among Back-Propagation Network, Radial Basis Function Neural Network and Gray model. The precision of Radial Basis Function Neural Network(RBF) was the highest. On the base of prediction for rainfall, evaporation and runoff, and determining the reducing exploitation value, the groundwater level was predicted by the optimal model RBF model. The result shows that the recovery effect of reducing exploitation was not obvious for short time. Artificial recharge should be done to improve the recovery speed, using the redundant surface water of wet season. The RBF model needs fewer data than other methods, the simulation precision was high, the computing speed was fast, the parameters needed to be adjusted were fewer, the predict result was reliable, the model was more steady, would not get into part minimum, and was very suitable to forecast the samples which had short-time data.4. Based on the water quantity balance principle, the needed quantity for artificial groundwater recharge was calculated. There were 3.25×108m3 water should be recharged to confined water for the groundwater level recovering to the level of 1984. The result supplies reference to carry out the project of artificial recharge, sealing well and stop overexploitation in Xi'an.5. The single well reinjection with pressure test was done. The formula for calculating the rise of water level was deduced and was called revised Theis formula. The water in tap-water supply was recharged to the medium sand, fine sand confined water for the cover depth of 100-300m at the south suburbs of Xi'an, where was the high water quantity vulnerability and serious overexploitation region. The result shows that the rise of water level of the reinjection well and observation well are linear with the lnt. The well reinjection could be regarded as the opposite process of water pumping. The rise of water level could be calculated by the revised Theis formula. This formula can inflect the relationship among the rise of water level, the quantity of water recharge and time. The suitable quantity of water recharge per unit time and influence radial could be calculated using the formula. The hydraulic conductivity for artificial groundwater recharge attenuated with time power function and the coefficient was smaller than the hydraulic conductivity for water pumping. When the quantity of water recharge per unit time was smaller, the attenuation of hydraulic conductivity was slower. The effect of small quantity of water recharge per unit time was better than the large. The results supplied theoretical and technological foundation for carrying out artificial groundwater recharge in Xi'an city, and also supplied technological reference for the similar region.
Keywords/Search Tags:groundwater vulnerability, Weber-Fechner expand law, Probabilistic Neural Network, forecast of groundwater level, Radial Basis Function Neural Network, well reinjection test, hydraulic conductivity, Xi'an
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