RESUMO
Relationships between land use and water quality of rivers and lakes vary spatially and temporally. These variations were analyzed using spatial analysis and mathematical statistical methods for the Suzhou Creek in Shanghai. Based on the data of water quality and land use in 2001ï¼ 2005ï¼ 2010ï¼ 2015ï¼ and 2020ï¼ five spatial scales ï¼200ï¼ 500ï¼ 1 000ï¼ 2 000ï¼ and 5 000 m reach bufferï¼ of the landscape pattern were extracted using correlation and redundancy analysis to explore the impact of land use composition and spatial pattern on water quality at different spatial and temporal scales. The results showed thatï¼ â the water quality of Suzhou Creek has gradually improved in the past 20 yearsï¼ other indicators were between Class II to Class IV in 2020 except TNï¼ and TN was the main pollutant. â¡ The main land use type of the buffer zone was construction landï¼ and the proportion of greenland and woodland showed a small growth trend. ⢠The water quality was closely related to landscape patternï¼ showing temporal and spatial scale effects. On the time scaleï¼ indicators such as construction landï¼ agricultural landï¼ landscape dominanceï¼ aggregationï¼ and diversity had significant correlations with various water quality parametersï¼ and there was an inverse correlation in 2010 compared with that in other years for NH4+-Nï¼ TPï¼ and TN. The landscape pattern in 2001 had the greatest explanation for water qualityï¼ with an explanation rate of 93.65%. The impact of greenland and woodland on water quality has begun to emerge in the past 10 years. ⣠On the spatial scaleï¼ there were significant correlations between greenland and woodlandï¼ patch numberï¼ landscape shape indexï¼ diversity indexï¼ and water quality. There was a strong positive regulatory effect of greenland and woodland on NH4+-Nï¼ TPï¼ and TN at the scale of 2 000 m. The patch number and landscape shape index had relatively strong regulatory effects on water quality on a larger spatial scaleï¼ whereas the Shannon diversity index had a better positive regulatory effect on water quality on a small scale. The landscape pattern within a buffer of 2 000 m had the highest interpretation degree for all factorsï¼ with an explanation rate of 68.47%. The study showed that rationally planning the proportion of greenland and woodland within the 2 000 m buffer zone and optimizing its landscape configuration is an important measure to purify the surface water quality of Suzhou Creek.