吉林市城区土地利用对地下水污染空间分布的影响

利用吉林市城区91眼监测井2013年的地下水水质监测数据,采用改进内梅罗污染指数法求取地下水污染指数,同时考虑第二松花江两岸地下水污染的非连续性,采用Kriging方法进行分区插值,然后叠加融合得出城区地下水污染指数空间分布图.结合吉林市城区土地利用类型,采用CM模型和SLM模型提取监测井不同半径范围内的土地利用类型,利用多元回归分析方法确定监测井最可能受污染的范围,最后利用Kendall秩次相关检验法和回归分析方法分析城区土地利用类型对地下水污染空间分布的影响.研究结果表明,吉林市城区地下水污染呈现出明显的空间分布特征;城区地下水受到不同程度的污染,其中江北片区和中心片区较为严重;在考虑地下水流动的情况下,监测井最可能受污染的范围为沿地下水流向方向500m;吉林市城区土地利用类型对地下水污染空间分布有较大影响,其中传统工业用地、居民和商业用地、城市交通设施用地为主要因素,其Kendall秩次相关检验τ值分别为0.248、0.174、0.143;在各研究片区,该3种土地利用类型和地下水污染空间分布也存在较好的相关性.

Effect of urban land use on the spatial distribution of groundwater pollution in the Jilin City.

Improved Nemerow Pollution Exponential method was adopted to calculate groundwater pollution index using 91monitoring wells groundwater quality data in 2013 of Jilin City. The distribution maps of groundwater pollution indexes were established by using the Kriging interpolation method and considering the non-continuity of groundwater pollution between the both sides of Songhua River. The land use types were extracted using the CM model and SLM model within the increment radius of the monitoring wells. And the most possible contaminated area of monitoring wells was calculated by multivariate regression analysis. In addition, the effect of urban land use on the spatial distribution of groundwater pollution was analyzed by Kendall method and multivariate regression analysis combined the urban land use of Jilin City. The results showed that the groundwater contamination of Jilin City had an obvious spatial distribution. Groundwater was contaminated in all districts with different severities, especially in JiangBei district and ZhongXin district. The most possible contaminated area was 500m along the flow direction under considering groundwater flow. The urban land uses have a great impact on the spatial distribution of groundwater pollution, especially conventional industrial areas, residential and commercial areas, transportation facilities areas, with the Kendall τ values were 0.248, 0.174, and 0.143. The three land uses types also have a good correlation with the spatial distribution of groundwater contamination in the study districts.