| 不同时空尺度下土地利用结构与空间格局对苏州河水质的影响 |
| 摘要点击 1351 全文点击 302 投稿时间：2023-03-03 修订日期：2023-05-04 |
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| 中文关键词 水质 土地利用 景观格局 空间尺度 苏州河 |
| 英文关键词 water quality land use landscape pattern spatial scale Suzhou Creek |
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| 中文摘要 |
| 土地利用与河湖水质的关系存在时空异质性.以上海苏州河为研究对象，基于2001、2005、2010、2015和2020年水质监测和土地利用数据，提取5种空间尺度（200、500、1 000、2 000和5 000 m河段缓冲区）的景观格局指数，采用相关分析和冗余分析，研究了多时空尺度下苏州河水质与缓冲带土地利用构成和空间格局特征的响应关系.结果表明：①苏州河水质近20年呈逐步改善趋势，TN是当前水体主要污染物.②不同尺度缓冲带土地利用均以建设用地为主，绿地林地占比呈小幅增长趋势.③缓冲带土地利用景观特征与水质存在关联性，并表现出时间和空间尺度效应.时间尺度上，建设用地、农业用地、景观优势度、聚集度和多样性指数与各项水质参数呈现出显著的相关性.就NH4+-N、TP和TN而言，2010年呈现出与其他年份相反的相关关系.2001年土地利用景观特征对水质的总解释率最高，为93.65%.近10年来，绿地林地对水质的调控作用凸显.④空间尺度上，绿地林地、斑块数量、景观形状和多样性指数与大部分水质指标呈现出显著的相关性.绿地林地对NH4+-N、TP和TN的正调控效应均以2 000 m尺度最强.斑块数量和景观形状指数在较大空间尺度上对水质的调控作用相对较强，而香农多样性指数则在小尺度上对水质起到较好的正调控作用.2 000 m尺度下土地利用景观特征对水质总解释率最高，为68.47%.研究表明，增加2 000 m缓冲区内绿地林地的面积并优化其景观配置将对苏州河水质保护具有积极作用. |
| 英文摘要 |
| 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 2001， 2005， 2010， 2015， and 2020， five spatial scales （200， 500， 1 000， 2 000， and 5 000 m reach buffer） 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 that： ① the water quality of Suzhou Creek has gradually improved in the past 20 years； other indicators were between Class II to Class IV in 2020 except TN， and TN was the main pollutant. ② The main land use type of the buffer zone was construction land， and the proportion of greenland and woodland showed a small growth trend. ③ The water quality was closely related to landscape pattern， showing temporal and spatial scale effects. On the time scale， indicators such as construction land， agricultural land， landscape dominance， aggregation， and diversity had significant correlations with various water quality parameters， and there was an inverse correlation in 2010 compared with that in other years for NH4+-N， TP， and TN. The landscape pattern in 2001 had the greatest explanation for water quality， 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. ④ On the spatial scale， there were significant correlations between greenland and woodland， patch number， landscape shape index， diversity index， and water quality. There was a strong positive regulatory effect of greenland and woodland on NH4+-N， TP， 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 scale， 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 factors， 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. |
