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引用本文:郭羽羽,李思悦,刘睿,张静.黄河流域多时空尺度土地利用与水质的关系.湖泊科学,2021,33(3):737-748. DOI:10.18307/2021.0310
Guo Yuyu,Li Siyue,Liu Rui,Zhang Jing.Relationship between landscape pattern and water quality of the multi-scale effects in the Yellow River Basin. J. Lake Sci.2021,33(3):737-748. DOI:10.18307/2021.0310
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黄河流域多时空尺度土地利用与水质的关系
郭羽羽1, 李思悦2, 刘睿1, 张静1
1.重庆师范大学地理与旅游学院, 重庆 401331;2.中国科学院重庆绿色智能技术研究院生态水文研究中心, 重庆 400714
摘要:
为探究不同时空尺度土地利用与水质的相互关系,以黄河流域为研究对象,基于2018年河流水质与土地利用数据,提取3种空间尺度(1000 m河段缓冲区、500 m河岸带缓冲区、子流域)的景观格局指数,结合4个季节河流水质指标,采用冗余分析方法定量探讨土地利用对河流水质的多时空尺度影响,获得水质资源管理最有效的时空尺度.结果表明:(1)在3种空间尺度下,耕地和草地占比最大.斑块密度(PD)在1000 m河段缓冲区尺度下更大,香农多样性指数(SHDI)在3种空间尺度下变化不大;(2)水质指标季节性和空间性存在显著差异,夏季水质优于冬季;(3)土地利用在夏季和1000 m河段缓冲区尺度下对水质影响最显著;(4)不同景观格局指数对河流水质产生的影响不同,耕地面积占比和林地面积占比、未利用地面积占比和SHDI对水质影响最为显著,除了耕地面积占比和PD值的增加会导致水质下降外,其余土地利用指数在大多数时空尺度下均可改善水质.该研究基于不同的时空尺度对土地利用与水质的关系进行定量研究,为合理规划土地资源提供参考,从而保护流域水质安全.
关键词:  土地利用  多尺度效应  冗余分析  水质  黄河流域
DOI:10.18307/2021.0310
分类号:
基金项目:国家自然科学基金项目(41801063)、重庆市教委科学技术研究计划项目(KJQN201900548)、重庆市自然科学基金项目(cstc2020jcyj-msxmX0549)和重庆师范大学基金项目(20XLB022)联合资助.
Relationship between landscape pattern and water quality of the multi-scale effects in the Yellow River Basin
Guo Yuyu1, Li Siyue2, Liu Rui1, Zhang Jing1
1.School of Geography and Tourism, Chongqing Normal University, Chongqing 401331, P. R. China;2.Research Center for Eco-hydrology, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, P. R. China
Abstract:
To explore the relationship between landscape patterns and water quality at different spatial and temporal scales, we choose the Yellow River Basin as the research object. Based on the data of river water quality and land use in 2018, the three spatial scales (1000 m reach buffer, 500 m riparian corridor buffer, and catchment) of the landscape pattern were extract, combined with four seasons of water quality, using redundancy analysis to quantitatively explore the impact of landscape pattern on water quality at multiple spatial and temporal scales, to obtain the most effective scales for water quality management. The results showed that: (1) Under the three spatial scales, the proportion of farmland and grassland was the largest. The value of patch density (PD) was larger in reach scale, while the Shannon diversity index (SHDI) varied little at the three scales, and the spatial distribution was relatively balanced. (2) There were significant differences in seasons and spatial scales of water quality indicators, and water quality in the summer was better than that in the winter. (3) The landscape pattern had the most significant impact on water quality in the summer and the reach scale. (4) Different landscapes had different impact on water quality. That is, farmland, forest, unused land and PD were the most significant influence on water quality. Except for the increase in farmland and PD value, which will lead to a decline in water quality, other land use indices can improve water quality at most temporal and spatial scales. The relationship between landscape pattern and water quality was quantitatively studied based on different scales, which provides references for optimizing landscape pattern and rational planning of land use, to protect water quality safety in the river basin.
Key words:  Landscape pattern  multi-scale effects  redundancy analysis  water quality  Yellow River Basin
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