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引用本文:张志敏,杜景龙,陈德超,张飞.典型网状河网区域土地利用和景观格局对地表季节水质的影响——以江苏省溧阳市为例.湖泊科学,2022,34(5):1524-1539. DOI:10.18307/2022.0509
Zhang Zhimin,Du Jinglong,Chen Dechao,Zhang Fei.Effects of land use and landscape pattern characteristics on seasonal surface water quality in a typical reticulated river network area—a case study of Liyang City, Jiangsu Province. J. Lake Sci.2022,34(5):1524-1539. DOI:10.18307/2022.0509
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典型网状河网区域土地利用和景观格局对地表季节水质的影响——以江苏省溧阳市为例
张志敏1, 杜景龙1, 陈德超1, 张飞2
1.苏州科技大学地理科学与测绘工程学院,苏州 215009;2.新疆大学资源与环境科学学院,乌鲁木齐 830046
摘要:
地表水质受区域景观组成及其空间配置的影响较大,了解景观特征与水质之间的关系可以极大地提高潜在污染的可预测性和污染物输出的评估能力. 以典型网状河网区域(江苏省溧阳市)为例,研究了土地利用和景观格局特征对地表季节水质的影响. 本研究基于2017年每单月从12个监测断面收集的21个水质指标,首先分析了多尺度缓冲区(500、1000、1500、2000、2500和3000 m)内土地利用和景观格局特征,然后通过主成分分析选取12个指标作为主要水质因子,采用冗余分析确定景观因子对水质指标的最佳影响尺度,最后采用偏最小二乘回归(PLSR)探究了最佳影响尺度下景观因子对季节水质的影响. 结果表明,2500 m缓冲区是该区域景观因子对水质指标的最佳影响尺度,旱季大多数水质指标PLSR模型的显著性和预测能力比雨季强. 雨季大多数水质指标都受园地、林草地、散布与并列指数(IJI)和香农均匀度指数(SHEI)的重要影响,并且这些景观因子与除pH和溶解氧浓度之外的其他水质指标均呈负相关. 在旱季,溶解氧、石油类、化学需氧量、总氮和总磷浓度受土地利用的影响最大; 另外,IJI是电导率、硫酸盐和亚硝酸盐氮浓度的最重要影响因子,而SHEI对硫化物和总悬浮物浓度的影响最大. 此外,景观指数对雨季水质的影响更大. 本研究结果揭示了网状河网区域土地利用/景观格局与季节性水质的关系,为区域水环境管理和景观格局优化提供了科学依据.
关键词:  土地利用  景观指数  水质  偏最小二乘回归(PLSR)  网状河网区域
DOI:10.18307/2022.0509
分类号:
基金项目:国家自然科学基金项目(41701477)和江苏省建设系统科技项目(2017ZD031)联合资助
Effects of land use and landscape pattern characteristics on seasonal surface water quality in a typical reticulated river network area—a case study of Liyang City, Jiangsu Province
Zhang Zhimin1, Du Jinglong1, Chen Dechao1, Zhang Fei2
1.College of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, P. R. China;2.College of Resources and Environment Science, Xinjiang University, Urumqi 830046, P. R. China
Abstract:
Surface water quality is greatly affected by regional landscape composition and its spatial configuration. Understanding their relationship can greatly improve the predictability of potential pollution and the evaluation capability of pollutant output. Taking a typical reticulated river network area (Liyang City, Jiangsu Province) as an example, the effects of land use and landscape pattern characteristics on seasonal surface water quality were examined. In this study, 21 water quality indicators were collected from 12 monitoring sections every single month in 2017. Firstly, the characteristics of land use and landscape pattern in multi-scale buffer zones (500, 1000, 1500, 2000, 2500 and 3000 m) were analyzed. Then 12 water quality indexes were identified as the main water quality factors through principal component analysis, and the best impact scale of regional landscape factors on water quality indicators was revealed by redundancy analysis. Finally, partial least squares regression (PLSR) was used to explore the landscape impact on seasonal water quality in the best impact scale. The results showed that 2500 m buffer zone was the best impact scale on water quality indicators. The significance and prediction ability of PLSR models of most water quality indicators were stronger in dry season than that in rainy season. Most water quality indicators in rainy season were significantly affected by orchard land, forest-grass land, dispersion and juxtaposition index (IJI) and Shannon evenness index (SHEI), and these landscape factors were negatively correlated with other water quality parameters except pH and dissolved oxygen (DO). In the dry season, DO, petroleum, chemical oxygen demand, total nitrogen and total phosphorus were most affected by land use. In addition, IJI was the most important impact factor of electrical conductivity, sulfate and nitrite nitrogen, while SHEI had the greatest impact on sulfide and total suspended solids. In addition, landscape metrics had greater impacts on water quality in rainy season. This study revealed the relationship between land use/landscape pattern and seasonal water quality in the reticulated river network area, and provided scientific basis for regional water environment management and landscape pattern optimization.
Key words:  Land use  landscape metrics  water quality  partial least squares regression (PLSR)  reticulated river network area
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