期刊
WATER RESEARCH
卷 191, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2021.116811
关键词
Stream water quality; Landscape metrics; Spatial scales effects; Seasonal sensitivity analysis; Partial redundancy analysis; Nonparametric change-point analysis
资金
- Key Research and Development Project of the Ministry of Science and Technology [2016YFD0801103]
- National Natural Science Foundation of China [41977006]
The physiography and land use patterns influence stream water quality by affecting non-point source pollution process. Quantitative analysis of landscape metrics scale effect and determination of abrupt change-point in the relationship between stream water quality and metrics is essential for landscape planning of water quality protection. Results showed that landscape configuration metrics had the greatest impact on stream water quality, with physiographic metrics having the most significant spatial scale effect.
Physiography and land use patterns influence streams water quality by affecting non-point source (NPS) pollution process. However, each landscape factor may affect the NPS pollution process differently with the variations of the spatial scale and season. Thus, quantitative analysis of each landscape metrics scale effect and determination of the abrupt change-point in the relationship between stream water quality and the metrics is very helpful for landscape planning of water quality protection. Based on water quality monitoring data for four years in 12 sub-watersheds of a typical headwater watershed in Eastern China, we adopted regular and partial redundancy methods to quantify the spatial scale effects and seasonal dependence of various landscape metrics impact on stream water quality, and then to identify the abrupt change-point of the water quality along the gradient of landscape metrics. Results revealed that the pure effects of different categories of landscape metrics on stream water quality were in the following order: landscape configuration metrics (20.5-31.6%) > physiographic metrics (4.0-15.9%) >landscape composition metrics (3.2-7.5%). The spatial scale effect of physiography impact on stream water quality was the most significant, while the impact of landscape configuration on water quality had the highest seasonal sensitivity. The overall water quality variation was better explained by buffer zone scale than by catchment scale landscape characteristics, and this phenomenon was more obvious during the wet season than during the dry season. In the studied watershed, we identified the largest patch index of farmland (LPI far) and the landscape shape index of forest (LSI for) as the key landscape metrics at sub-watershed scale and buffer zone scale, respectively. The LPIfar > 7.0% at the sub-watershed scale and LSI for < 5.5 at the buffer zone scale were suggested as the preferred landscape planning parameters to protect the stream water quality efficiently. Results indicated that, to protect water quality, landscape regulation should follow the scale-adaptability measures and consider the landscape thresholds, which cause abrupt changes in water quality. (C) 2021 Elsevier Ltd. Allrightsreserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据