Urbanization Factors of Groundwater Vulnerability Assessment in Karst Area: A Case Study of Shuicheng Basin
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摘要: 岩溶地下水是贵州省六盘水市的重要供水水源，但针对该地区的岩溶地下水脆弱性评价，尤其是城镇化区域的岩溶地下水脆弱性评价尚未见报道.运用改进的径流-覆盖层-降雨（COP）模型，利用RS及GIS技术对水城盆地的土壤类型、土地利用/覆盖类型、降水量数据进行处理，研究了岩溶地下水脆弱性评价的城镇化因子.结果显示，2004~2016年间，研究区地下水固有脆弱性整体呈现出由中脆弱性向低脆弱性转变的趋势，脆弱性降低的区域与城镇化过程中增加的不透水地面区域相一致；表明不透水地面有效地阻碍了地表污染物进入地下，降低了地下水固有脆弱性.本结果为水城盆地岩溶水资源管理提供了重要依据.Abstract: Karst groundwater is an important water supply source for Liupanshui City of Guizhou Province. However, vulnerability assessment of karst groundwater in this region, especially in the urbanized areas has not been reported. To characterize urbanization factors of groundwater vulnerability assessment in karst area, we chose Shuicheng Basin as the study area, used and improved the Concentration of Flow-Overlying Layers-Precipitation (COP) model, and processed data of soil types, land use/land cover, and precipitation by RS and GIS technologies. Results show that the inherent vulnerability of groundwater for the study area decreased from medium to low during 2004 to 2016, and the area with decreased vulnerability is consistent with the increased impervious area caused by urbanization. It suggests that impervious grounds hinder inputs of surface pollutants, reducing inherent vulnerability of groundwater. Our results are important for karst water resource management in the study area.
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Key words:
- urbanization /
- inherent vulnerability assessment /
- COP model /
- karst area /
- hydrogeology
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表 1 研究区土壤类型、质地及厚度统计
Table 1. Type, texture and thickness of soil in the study area
土壤类型 土壤质地 厚度（cm） 山地灌丛草甸土 重壤土 20~50 山地黄棕壤 中-轻壤土 50~100 黄壤 中壤土 70~120 石灰土 中壤土-重粘土 14~85 紫色土 中/重壤土 20~30 潮土 砂壤土 30 沼泽土 中-重壤土 80 水稻土 壤土 60 注：据贵州省农业厅和中国科学院南京土壤研究所（1980），六盘水市地方志编纂委员会（1980）. 
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表 2 六盘水-安顺-毕节地区1981~2010年降雨统计
Table 2. Annual rainfall of the Liupanshui-Anshun-Bijie region during 1981-2010
区站号 站名 经度 纬度 海拔(m) 累年年平均降水量(mm) 累年年降水天数 降水强度(mm/d) 56598 赫章 104°26' 27°05' 1 535.1 832.9 167.9 5.0 56691 威宁 104°10' 26°31' 2 237.5 859.4 177.8 4.8 56793 盘县 104°17' 25°26' 1 800.0 1 383.4 186.9 7.4 57800 纳雍 105°13' 26°28' 1 457.1 1 203.0 211.0 5.7 57805 织金 105°28' 26°25' 1 319.3 1 355.4 204.2 6.6 57807 六枝 105°17' 26°07' 1 361.9 1 480.0 192.1 7.7 57808 普定 105°27' 26°11' 1 274.5 1 340.6 174.7 7.7 57809 镇宁 105°27' 26°02' 1 251.0 1 347.0 175.6 7.7 57903 关岭 105°22' 25°34' 1 142.0 1 327.7 174.7 7.6 注：数据来自中国气象数据网，http://data.cma.cn/.
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表 3 2004~2010年脆弱性面积转移矩阵（km2）
Table 3. Vulnerability area transfer matrix during 2004-2010 (km2)
极高脆弱性 高脆弱性 中脆弱性 低脆弱性 极低脆弱性 2010年合计 极高脆弱性 3.04 0.05 0.00 0.04 0.01 3.13 高脆弱性 0.08 3.96 1.18 0.13 1.93 7.28 中脆弱性 0.00 0.23 66.53 20.73 6.54 94.04 低脆弱性 0.00 0.10 4.63 54.10 3.58 62.41 极低脆弱性 0.00 0.41 9.01 7.80 15.83 33.04 2004年合计 3.12 4.75 81.36 82.79 27.88
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表 4 2010~2016年脆弱性面积转移矩阵（km2）
Table 4. Vulnerability area transfer matrix during 2010- 2016 (km2)
极高脆弱性 高脆弱性 中脆弱性 低脆弱性 极低脆弱性 2016年合计 极高脆弱性 2.98 0.07 0.00 0.01 0.01 3.06 高脆弱性 0.10 3.57 0.90 0.07 0.48 5.11 中脆弱性 0.00 0.65 65.91 11.54 6.67 84.78 低脆弱性 0.04 0.23 7.06 37.05 4.13 48.51 极低脆弱性 0.01 2.76 20.14 13.73 21.79 58.44 2010年合计 3.13 7.28 94.01 62.40 33.08
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表 5 2004、2010、2016年研究区脆弱性分布面积（%）
Table 5. Fractions (%) of vulnerability levels in 2004、2010、2016 for the study area
脆弱性 面积占比（%） 2004年 2010年 2016年 高脆弱性及以上 3.94 5.21 4.09 中脆弱性 40.70 47.03 42.35 低脆弱性及以下 55.36 47.76 53.56
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