生态环境学报 ›› 2021, Vol. 30 ›› Issue (7): 1470-1481.DOI: 10.16258/j.cnki.1674-5906.2021.07.016

• 研究论文 • 上一篇    下一篇

不同空间尺度土地利用结构与景观格局对龙川江流域水质的影响

胡琳1,2(), 李思悦2,3,*()   

  1. 1.重庆交通大学建筑与城市规划学院,重庆 400074
    2.中国科学院重庆绿色智能技术研究院/中国科学院水库水环境重点实验室,重庆 400714
    3.武汉工程大学环境生态与生物工程学院,湖北 武汉 430205
  • 收稿日期:2021-01-25 出版日期:2021-07-18 发布日期:2021-10-09
  • 通讯作者: *李思悦,教授,博士研究生导师,主要研究领域为河-库地球化学过程与环境效应、内陆水体温室气体释放与碳中和,流域水环境与污染源解析。E-mail: syli2006@163.com
  • 作者简介:胡琳(1997年生),男,硕士研究生,主要研究方向为河流水环境与土地利用。E-mail: 634944710@qq.com
  • 基金资助:
    国家自然科学基金项目(31670473);中国科学院高层次人才计划项目

Scale Effects of Land Use Structure and Landscape Pattern on Water Quality in the Longchuan River Basin

HU Lin1,2(), LI Siyue2,3,*()   

  1. 1. College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing 400074, China
    2. Key Laboratory of Reservoir Aquatic Environment/Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
    3. School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China
  • Received:2021-01-25 Online:2021-07-18 Published:2021-10-09

摘要:

为了探究龙川江流域不同尺度土地利用结构与景观格局对水质的影响,于2017年5和9月对龙川江流域的21个样点进行取样,测定水温、pH、溶解氧饱和度、氮、磷等水质指标。结合2017年10 m分辨率的土地利用数据,提取3种空间尺度(河段、河岸带、子流域)的土地利用结构与景观格局指数,运用相关分析、冗余分析(RDA)、“bioenv”分析和逐步回归模型揭示不同尺度土地利用结构与景观格局对水质的影响。结果表明,龙川江水体主要污染物为TN和TP,水质基本指标有月际性差异,N、P浓度在5月高于9月,但差异不显著。不同空间尺度土地利用结构与水质指标的相关关系不同,子流域尺度土地利用组合与总体水质之间的相关性最强,且林地对水质有正面影响,耕地、建设用地对水质有负面影响。不同尺度的景观格局指数组合与水质的相关性存在差异,河岸带景观格局组合与总体水质的相关性最高,RDA分析表明景观格局指数对总体水质的总解释率为河岸带>子流域>河段。整体上,9月土地利用结构与景观格局对水质的影响要大于5月。多元回归模型发现建设用地和耕地对养分的预测能力及预测指标依赖于空间尺度和取样月份。研究以龙川江为例,证实了土地利用结构与景观格局对水质的影响具有尺度效应,水质响应的空间尺度效应应纳入土地利用规划与水资源管理的过程中,提出长江上游更多的个案研究尤为必要,对长江上游河源区水资源保护及土地利用管理具有重要的意义。

关键词: 土地利用, 景观格局, 水质, 尺度效应, 富营养化

Abstract:

To explore the impacts of land use structure and landscape pattern on water quality at different scales, in-situ measurements on water quality were conducted at 21 sampling locations in the Longchuan River network during May and September in 2017. The field measurements included stream water temperature, pH, and dissolved oxygen saturation. In addition, a total of 42 samples were collected from the locations for chemical analysis of total nitrogen (TN) and total phosphorus (TP). These water quality parameters were analyzed in association with land use structure and landscape pattern indices that were derived from land use and land cover (LULC) data in 2017 at a resolution of 10×10 m. Pearson correlation analysis, regression models, “bioenv” analysis and redundancy analysis were used to determine the impacts of land use structure and landscape pattern on stream water quality at the river reach, riparian zone, and sub-basin scales. The results showed that the main pollutants in the Longchuan River were TN and TP. The in-stream water quality parameters had significant monthly variation, while the concentrations of TN and TP showed no clear monthly difference; though they were slightly higher in May than in September. Stream water quality showed the strongest relationship with land use structure along the riparian zone, and forest land showed positive effects on stream water quality. In contrast, cultivated land and residential land showed negative effects on stream water quality. The association of stream water quality with landscape pattern indices varied at different scales, and the explanatory power had the following descending order: riparian zone>sub-basin>river reach. Overall, the association of water quality with land use structure and landscape pattern appeared stronger in September than in May. Based on the findings, we conclude that the impact of land use structure and landscape pattern on stream water quality in a river basin is scale-dependent. A multi-scale approach should be adopted for land use planning and water resource management.

Key words: land use and land cover, landscape pattern, water quality, scale effect, eutrophication

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