【摘要】：有效識(shí)別地下水污染源信息既是設(shè)計(jì)合理修復(fù)方案的基礎(chǔ),也是依法治污明確責(zé)權(quán)的依據(jù)。本文將污染源反演過(guò)程轉(zhuǎn)化為貝葉斯推斷過(guò)程,并與克里格替代模型相結(jié)合,提出了一種反演地下水污染源釋放歷史的新思路,同時(shí)針對(duì)求解過(guò)程中采用的Metropolis抽樣算法提出改進(jìn)方案。算例結(jié)果表明:(1)該方法能夠有效識(shí)別地下水污染源釋放歷史,反演結(jié)果的平均相對(duì)誤差為3.45%;(2)在500次迭代條件下,改進(jìn)的Metropolis算法將反演結(jié)果的平均相對(duì)誤差從57.41%降低至3.45%,有效提高了反演效率與精度;(3)在污染源釋放速率有較大差異且存在擾動(dòng)的條件下,反演結(jié)果并未出現(xiàn)大幅偏離或波動(dòng)的異常,效果穩(wěn)定。
[Abstract]:The effective identification of groundwater pollution source information is not only the basis of designing reasonable remediation scheme, but also the basis of clear responsibility and right to deal with pollution according to law. In this paper, the source inversion process is transformed into Bayesian inference process, and combined with the Kriging substitution model, a new idea for retrieving the history of groundwater pollution source release is proposed. At the same time, an improved Metropolis sampling algorithm is proposed. The results show that: (1) the method can effectively identify the release history of groundwater pollution sources, and the average relative error of the inversion results is 3.45; (2) under the condition of 500th iteration, the average relative error of the inversion result is reduced from 57.41% to 3.45% by the improved Metropolis algorithm, and the inversion efficiency and precision are improved effectively. (3) under the condition that the release rate of pollution source is different and disturbance exists, the inversion results are not deviated or fluctuated by a large margin, and the effect is stable.
【作者單位】： 吉林大學(xué)地下水資源與環(huán)境教育部重點(diǎn)實(shí)驗(yàn)室;吉林大學(xué)環(huán)境與資源學(xué)院;
【基金】：中國(guó)地調(diào)局項(xiàng)目(1212011140027,12120114027401) 吉林大學(xué)研究生創(chuàng)新基金項(xiàng)目(2015026)
【分類號(hào)】：X523
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本文編號(hào)：2297541