地下水非点源污染数值模拟及其不确定性分析  

Numerical Simulation and Uncertainty Analysis of Non-point Source Pollution of Groundwater

作　　者：侯泽宇[1] 卢文喜[1] 陈末[1] 司昌亮[1] 徐海斐 

机构地区：[1]吉林大学环境与资源学院,吉林长春130026

出　　处：《节水灌溉》2014年第9期42-45,49,共5页Water Saving Irrigation

基　　金：国家自然科学基金项目(41372237);吉林科技发展计划基金资助项目(20100215)

摘　　要：利用集总参数地下水模型对虚拟研究区除冰盐的使用所引起的地下水非点源污染问题进行模拟,分别采用一阶估计法和蒙特卡洛方法分析该模型对于各参数的敏感性以及模拟结果不确定性。在蒙特卡洛模拟过程中,模拟多次,每次模拟对模型中不同类型的参数区别对待,这种方式在前人的研究中从未出现过。通过研究得到如下结论:1非点源污染可以使区域地下水水质发生明显变化,应重视并尽可能地控制污染源;2集总参数模型简单易行,可利用有限的数据较为真实地模拟复杂的系统,减少模拟成本的同时为方案的设计与实施提供较为可靠的依据;3地下水模型存在明显的不确定性,不确定性分析可以提供更为全面的参考信息。目前,不确定性分析并未得到广泛的重视,通过研究展示不确定性分析的必要性,并为以后地下水模型的不确定性分析提供参考。In this paper, the lumped parameter groundwater model was chosen to simulate non-point sources pollution of groundwater caused by the use of deicing salt in virtual research area. In addition, the first-order approximation and Monte Carlo method were used to estimate the sensitivity of the model to each parameter and analyze the uncertainty of the simulation model. During the process of Monte Carlo simulation, the simulation was performed for many times and different parameters of the model were treated in different ways. This method has never appeared in previous research. According to the research, it can be found that non-point source pollution could cause obvious change of groundwater water quality in an area, it should be taken seriously and the pollution sources should be controlled as far as possible; lumped parameter could veritably simulate the complex systems with limited data in a simple way to provide a reliable basis for the design and implementation of schemes with low simulate cost; the groundwater model had obvious uncertainty and the uncertainty analysis could provide more comprehensive reference information. At present, uncertainty analysis had not been widely paid attention to, so the authors hope to show the necessity of uncertainty analysis through this article and provide a reference for the future uncertainty analysis of groundwater model.

关 键 词：非点源污染 集总参数模型 一阶估计法 敏感性分析 蒙特卡洛方法 不确定性分析 

分 类 号：P345[天文地球—水文科学]