Response of river water quality to background characteristics of landscapes in Taihu Lake basin

Wen, 周文 Zhou; Maosong, 刘茂松 Liu; Xu, 徐驰; Ge, 何舸 He; Lei, 王磊 Wang; Xuejiao, 杨雪姣 Yang

doi:10.5846/stxb201110311624

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“…There was a significant negative correlation between forest land, grassland, and water quality indicators, while arable land and construction land showed a strong positive correlation (Zhang, Cheng & Xiang, 2011; Yang et al, 2017). However, due to the multi-scale and distribution pattern of land use (Tu, 2011; Zhou et al, 2012), there is a significant scale correlation between LULC changes and water quality indicators, which leads to uncertainty about the relationship between land use patterns and river water quality. From the saliency of spatial influence, the sub-basin scale is significantly higher than the riparian buffer scale (Sliva & Williams, 2001; Jarvie, Oguchi & Neal, 2002; Woli et al, 2004; Li, Xu & Li, 2012), and some studies have reached the opposite conclusion (Sahu & Gu, 2009; Li et al, 2009; Huang et al, 2011; Ou, Wang & Geng, 2012).…”

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confidence: 99%

Multi-scale relationship between land use/land cover types and water quality in different pollution source areas in Fuxian Lake Basin

Li¹,

Peng

Jin

et al. 2019

PeerJ

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The spatial-temporal evolution of land use and land cover (LULC) and its multi-scale impact on the water environment is becoming highly significant in the LULC research field. The current research results show that the more significant scale impact on LULC and water quality in the whole basin and the riparian buffer scale is unclear. A consensus has not been reached about the optimal spatial scale problem in the relationship between the LULC and water quality. The typical lake basin of the Fuxian Lake watershed was used as the research area and the scale relationship between the LULC and water quality was taken as the research object. High resolution remote sensing images, archival resources of surveying, mapping and geographic information, and the monitoring data of water quality were utilized as the main data sources. Remote sensing and Geometric Information Technology were applied. A multi-scale object random forest algorithm (MSORF) was used to raise the classification accuracy of the high resolution remote sensing images from 2005 to 2017 in the basin and the multi-scale relationship between the two was discussed using the Pearson correlation analysis method. From 2005 to 2017, the water quality indicators (Chemical Oxygen Demand (COD), Total Phosphorous (TP), Total Nitrogen (TN)) of nine rivers in the lake’s basin and the Fuxian Lake center were used as response variables and the LULC type in the basin was interpreted as the explanation variable. The stepwise selection method was used to establish a relationship model for the water quality of the water entering the lake and the significance of the LULC type was established at p < 0.05.The results show that in the seven spatial scales, including the whole watershed, sub-basin, and the riparian buffer zone (100 m, 300 m, 500 m, 700 m, and 1,000 m): (1) whether it is in the whole basin or buffer zone of different pollution source areas, impervious surface area (ISA), or other land and is positively correlated with the water quality and promotes it; (2) forestry and grass cover is another important factor and is negatively correlated with water quality; (3) cropping land is not a major factor explaining the decline in water quality; (4) the 300 m buffer zone of the river is the strongest spatial scale for the LULC type to affect the Chemical Oxygen Demand (COD). Reasonable planning for the proportion of land types in the riparian zone and control over the development of urban land in the river basin is necessary for the improvement of the urban river water quality. Some studies have found that the relationship between LULC and water quality in the 100 m buffer zone is more significant than the whole basin scale. While our study is consistent with the results of research conducted by relevant scholars in Aibi Lake in Xinjiang, and Erhai and Fuxian Lakes in Yunnan. Thus, it may be inferred that for the plateau lake basin, the 300 m riparian buffer is the strongest spatial scale for the LULC type to affect COD.

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