淮河流域四省地下水水砷检测与地理信息系统预测模型结果分析  

Relationship between the actual test results of groundwater arsenic level and the predictions of a geographic information system model in four provinces of Huaihe River Basin

作　　者：刘宇岩[1] 李永芳[1] 王达[1] 杨博逸[1] 范淑君[1] 郅雪原[1] 郑全美[1] 孙贵范[1] 

机构地区：[1]中国医科大学公共卫生学院劳动卫生与环境卫生教研室,沈阳110001

出　　处：《中华地方病学杂志》2014年第1期30-33,共4页Chinese Journal of Endemiology

基　　金：国家自然科学基金（81072243）

摘　　要：目的分析淮河流域山东、河南、安徽、江苏四省地下水水砷分布，探讨地理信息系统（GIS）预测模型结果的准确度。方法以淮河流域四省地下水水砷含量调查结果为分析源数据．按水砷含量进行分层．以水砷〉0．01mg／L为统计标准，计算超标自然村数及各县（区）的超标率。同时，在GIS预测模型地图中标记所有抽样县（区）的位置，以砷污染概率0．3灰度值为标准，将GIS预测模型与该省份地下水水砷实际检测分布情况进行拟合分析，计算GIS预测模型的准确度。结果在淮河流域的四省共抽取61824口井，分布于2781个自然村中，确认高砷污染村（水砷〉0．01rag／L）有474个，平均检出率为17．04％（474／2781）。其中山东、河南、安徽、江苏省高砷村检出率分别为13．19％（79／599）、23．82％（101／424）、74．25％（199／268）和6．38％（95／1490），各省间的检出率比较差异有统计学意义（x2=820．84，P〈0．05）。以县（区）为单位，在四省103个县（区）中j由GIS预测模型所预测的概率〉0．3的高砷县有72个，占总数的69．90％（72／103），其中山东、河南、安徽、江苏省分别为67．86％（19／28）、61．36％（27／44）、85．71％（12／14）和82．35％（14／17）。在103个县（区）中，实际抽样检出超标的县（区）有62个，其中经GIS模型预测地下水高砷概率〉0．3的有42个，灵敏度为67．74％（42／62）；实际抽样检出未超标县（区）有41个，其中经GIS模型预测地下水高砷概率〈0．3的有11个，特异度为26．83％（11／41）。山东、河南、安徽、江苏省GIS模型预测结果灵敏度分别为57．89％（11／19）、59．09％（13／22）、84．62％（11／13）和87．50％（7／8）。结论水砷抽样调查实际结果与GIS模型预测结果拟合度较好，GIS模型对地区地下水高砷污染预测有较高的准确度。Objective To test the accuracy of predicted results by a geographic information system（GIS） model with the actual distribution of groundwater arsenic concentration in four provinces including Shandong, Henan, Anhui and Jiangsu of Huaihe River Basin. Methods The results of groundwater arsenic level of the four provinces in Huaihe River Basin were cited as the data resource; after stratified by arsenic in water, water arsenic 〉 0.01 mg/L as statistical standards, the number of villages and counties（districts） with arsenic level higher than the standards was calculated. Meanwhile, locations of Counties（districts） sampled on the map of GIS predictive model were marked; the gray level of arsenic contaminated probability 0.3 was regarded as ihe criterion and the consistence of both results predicted by GIS model and detected actually in each province was analyzed. Results A total of 61 824 wells distributed in 2 781 villages around the four provinces of Huaihe River Basin were sampledI, and 474 of the 2 781 villages were confirmed as high arsenic villages（arsenic 〉 0.01 rag/L）, with an average detection rate of 17.04% （474/2 781）. The detection rates of high arsenic villages in Shandong, Henan, Anhui and Jiangsu were 13.19% （79/599）, 23.82% （101/424）, 74.25% （199/268） and 6.38% （95/1 490）, respectively, and the differences of detection rates among the provinces were statistically significant （X2= 820.84, P 〈 0.05）. County（district） as a unit, among all the 103 counties （districts）, the number of counties where the probability of high arsenic concentration in groundwater predicted by GIS model that greater than 0.3 was 72, accounting for 69.90% （72/103） of total counties, in whioh Shandong, Henan, Anhui and Jiangsu were 67.86% （19/28）, 61.36% （27/44）, 8S.71%（12/14） and 82.35%（14/17）, respectively. Among all 103 counties（districts）, the number of counties （districts） where the detection rates of high arsenic villages beyond the standards wa

关 键 词：淮河流域 地下水 砷 地理信息系统 预测模型 

分 类 号：R599.1[医药卫生—内科学]