Variation and Prediction of Landscape Pattern and Habitat Conservation Based on Ca-Markov and Invest Model in Haihe Source Region, China

WANG, J.; Wu, Tingting; LI, Q.; WANG, S.

doi:10.15666/aeer/1906_45834597

Cited by 3 publications

(1 citation statement)

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“…Multivariate statistical analysis is the primary method to quantify the contribution of land use variables to water quality [11][12][13]. In previous studies, researchers often conducted a correlation analysis on the impact of land use on water quality at larger spatial scales.…”

Section: Introductionmentioning

confidence: 99%

Effects of Hydrological Season on the Relationship between Land Use and Surface Water Quality

Wei

Huang

Ding

et al. 2023

Water

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In recent decades, land use patterns have changed significantly in highly urbanized areas, which is usually linked with the spatial variation of surface water quality at the catchment scale, but little attention has been paid to how hydrological seasons affect this relationship. Taking Pudong New Area of Shanghai, China, as an example, this paper evaluated the influence of hydrological seasons on the relationship between land use and water quality under different hydrological buffers. It was shown that the contribution of land use to the spatial variation of water quality is approximately 30%. In addition, the explanatory ability was greatest in the average season while it was smaller in the dry and wet seasons. Land uses showed scale effects; at a smaller scale, urban areas, agricultural land and water areas were the most important land uses affected by water quality. As the buffers changed from 500 to 1500 m, the impact of urban areas decreased significantly, while that of agricultural land and water areas increased rapidly; however, when the buffer was greater than 1000 m, the explanatory ability of water areas did not increase further but remained stable. Green space is only significant at the 200 m and 500 m scales, which showed the effect of improving river quality. This study is expected to provide references for future decision making of urban construction, environmental planning and management.

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Section: Introductionmentioning

confidence: 99%