摘要
定量探讨不同景观格局与水质关系对于指导城市景观规划、保护周边水环境具有重要意义.以南京市九乡河流域为研究区域,基于2009年的Quick Bird影像和2009年10月~2010年9月的水质实时监测数据,利用GIS空间分析技术以及统计分析的方法,从景观水平和类型水平2个方面分析了流域景观格局空间分异对河流总氮(TN)、总磷(TP)、高锰酸盐指数和氨氮(NH4+-N)的影响.结果表明,流域的大部分景观类型与河流TN、TP、高锰酸盐指数和NH4+-N浓度存在显著的相关关系:建设用地和未利用地的面积比例与TN、TP、高锰酸盐指数和NH4+-N浓度显著正相关,林地的面积比例与这些指标呈显著负相关,而耕地的面积比例与TN、TP、高锰酸盐指数和NH4+-N浓度相关性不显著;从景观水平上看,流域景观以少数类型大斑块为主或同一类型的斑块高度连接时,河流中TN、TP、高锰酸盐指数和NH4+-N浓度较低,水质较好;但针对具体的景观类型有所不同,建设用地、未利用地以及耕地的集中连片分布会引起TN、TP、高锰酸盐指数和NH4+-N浓度的上升,而林地的大面积分布则对这些指标具有相反的效应.
Exploring the quantitative relationship between landscape characteristics and surface water quality indicators can provide important information to urban landscape planning and water environment protection.Jiuxiang River watershed in Nanjing city,being as a typical case study area,its landscape classification maps was conducted in 2009 by remote sensing digital images interpretation.Based on the remote sensing images and real-time monitoring data from October 2009 to September 2010,geospatial analysis and statistical analysis were integrated to explore the relationship between landscape composition,landscape pattern(landscape-level and class-level) and river water quality at the subwatershed scale.Results showed that most of landscape compositions influenced river water quality.Percentage of built-up land and unused land was positively related to total nitrogen(TN),total phosphorus(TP),ammonia nitrogen(NH+4-N) and permanganate index,while percentage of forestland showed a negative relationship.At the landscape level,the water quality was good when the size of patch was big.But at class-level,the aggregated distribution of the built-up land,unused land and arable land might cause TN,TP,permanganate index and NH+4-N concentration increased.But the aggregated distribution of the forestland had the opposite effect on water quality indicators.
出处
《环境科学》
EI
CAS
CSCD
北大核心
2012年第3期794-801,共8页
Environmental Science
基金
国家自然科学基金项目(40871084
41071119)
江苏省"青蓝工程"项目(184080H10240)
江苏省高校优势学科建设工程项目
关键词
景观格局
河流水质
空间分异
相关
九乡河流域
landscape pattern
river water quality
spatial difference
correlation
Jiuxiang River watershed