本文關鍵詞：SCEUA算法在地下水污染溯源中的應用研究　出處：《濟南大學》2015年碩士論文　論文類型：學位論文

  更多相關文章： 優(yōu)化算法 溯源模型 地下水污染源

【摘要】：隨著經濟的快速發(fā)展,全國各地的地下水都受到了不同程度的污染。但我國地下水污染預防、監(jiān)測和修復系統(tǒng)還不完善,因此導致人類賴以生存的地下水環(huán)境遭受到了嚴重的威脅。近年來,人們越來越關注地下水的污染問題。由于地下水污染具有隱蔽性,因此對地下水污染預防和治理的關鍵是及時有效地確定污染源。然而,目前我國對地下水污染源的確定方法還不夠成熟,存在較多不足。本文針對這一問題探索了地下水污染溯源的方法。優(yōu)化算法是進行地下水污染溯源研究的一種有效的方法。由于優(yōu)化算法在不斷地更新發(fā)展,不同優(yōu)化算法有其各自優(yōu)點,將其應用到許多領域后體現(xiàn)了很好的優(yōu)越性,解決了一些原本傳統(tǒng)方法不能解決的問題。本文將SCE-UA優(yōu)化算法與地下水溶質運移程序(MT3DMS)相結合的基礎上,建立地下水污染溯源智能搜索模型(SCEUA-MT3DMS)。首先通過優(yōu)化算法模型來生成污染種群樣本點,然后再利用種群樣本點,通過地下水污染物運移數(shù)值模型來模擬污染物在含水介質中的滲流與遷移過程,同時將模擬預測的結果進一步作為優(yōu)化算法模型選擇的依據(jù)。優(yōu)化算法模型經過種群變異、反射和進化等過程,從眾多潛在污染源位置中自動選擇出可能性最大的污染源位置及污染物的排放強度。建成地下水污染溯源智能搜索模型后,通過對單污染源和雙污染源、已知位置和未知位置及穩(wěn)定流和非穩(wěn)定流等不同情況下模擬實驗,一般在進化代數(shù)T=40,復型個數(shù)p=40的情況下,均能夠準確定位污染源真實位置,所反演的污染濃度與真實值間的相對偏差D2均小于2%,可以滿足精度的需要,驗證了該方法的可行性,反映了智能搜索模型能夠高效地收斂到全局最優(yōu)解,對污染源位置和濃度的反演定位準確,能夠進一步應用于水文地質條件更為復雜的實例污染源反演問題。寧陽工業(yè)園區(qū)地下水污染相對集中且污染比較嚴重,水文地質資料等相對全面,將該模型應用到寧陽工業(yè)園區(qū)進行區(qū)域大模型的實際案例,考慮到區(qū)域大模型存在的問題,采用了網格嵌套數(shù)值模擬方法,子模型實現(xiàn)了對研究區(qū)的局部細化,減少了不同化工企業(yè)之間的相互影響,提高智能搜索模型地下水污染溯源反演效率和反演精度,有效的縮短了模型的運行時間。經分析選定位置合適的某化工廠、監(jiān)測井及兩種特征污染物多氯聯(lián)苯(PCB)和硝酸根離子,運用該模型進行有關污染源位置和污染物排放濃度的反演定位。反演結果基本可以滿足精度需要,也比較符合污染源的實際位置及濃度情況,通過實例體現(xiàn)了該地下水污染溯源智能搜索模型較好的準確性和可靠性。研究表明,通過將SCE-UA算法與地下水溶質運移程序(MT3DMS)耦合來進行地下水污染反演是一種有效的方法,可以快速準確的定位污染源,達到了溯源的目的,體現(xiàn)了方法的正確性和可行性。
[Abstract]:With the rapid development of economy, groundwater in various parts of the country has been polluted to varying degrees. However, the system of prevention, monitoring and restoration of groundwater pollution in China is not perfect. In recent years, people pay more and more attention to the problem of groundwater pollution, because of the hidden nature of groundwater pollution. Therefore, the key to the prevention and control of groundwater pollution is to determine the source of pollution in time and effectively. However, at present, the method of determining the source of groundwater pollution in China is not mature enough. There are many shortcomings. This paper explores the method of groundwater pollution traceability. Optimization algorithm is an effective method for groundwater pollution traceability research. Because the optimization algorithm is constantly updated and developed. Different optimization algorithms have their own advantages, and their application in many fields shows a good advantage. Some problems that could not be solved by the traditional method were solved. In this paper, the SCE-UA optimization algorithm is combined with the groundwater solute transport program MT3DMS. An intelligent searching model for traceability of groundwater pollution was established. Firstly, the pollution population sample points were generated by optimizing the algorithm model, and then the population sample points were used. The seepage and migration process of pollutants in aqueous medium is simulated by means of a numerical model of groundwater pollutant transport. At the same time, the results of simulation prediction are further used as the basis for the selection of the optimization algorithm model, which goes through the process of population mutation, reflection and evolution. The most likely pollution source location and pollutant emission intensity are automatically selected from many potential pollution sources. After the establishment of the intelligent searching model of groundwater pollution traceability, the single and double sources of pollution are analyzed. Under different conditions, such as known and unknown position, stable flow and unstable flow, the simulation experiments can accurately locate the true location of the source of pollution in the case of evolutionary algebra T _ (40) and the number of complex types (p _ (40)). The inverse relative deviation between the pollution concentration and the real value is less than 2, which can meet the need of accuracy. The feasibility of this method is verified, which reflects that the intelligent search model can converge to the global optimal solution efficiently. The exact location of the location and concentration of pollution sources can be further applied to the source inversion of more complicated hydrogeological conditions. The pollution of groundwater in Ningyang Industrial Park is relatively concentrated and serious. The hydrogeological data are relatively comprehensive. This model is applied to the practical case of the regional large-scale model in Ningyang Industrial Park. Considering the problems of the regional large-scale model, the numerical simulation method of grid nesting is adopted. The sub-model realizes the local refinement of the study area, reduces the interaction between different chemical enterprises, and improves the retrieval efficiency and accuracy of the intelligent search model for groundwater pollution traceability. The operation time of the model was effectively shortened. A chemical plant with suitable location was selected, monitoring well and two characteristic pollutants, PCB) and nitrate ion. The model is used to locate the pollution source location and pollutant emission concentration. The inversion results can meet the need of accuracy, and also accord with the actual location and concentration of the pollution source. The example shows that the intelligent searching model of groundwater pollution traceability is accurate and reliable. It is an effective method to retrieve groundwater pollution by coupling SCE-UA algorithm with MT3DMS. it can locate pollution sources quickly and accurately. The purpose of traceability is achieved, and the correctness and feasibility of the method are demonstrated.
【學位授予單位】：濟南大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：X523

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相關期刊論文 前1條

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本文編號：1426074