State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi' an, 710048, Shaanxi, China.
State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi' an, 710048, Shaanxi, China.
Environ Pollut. 2023 Sep 15;333:122097. doi: 10.1016/j.envpol.2023.122097. Epub 2023 Jun 21.
Comprehensive landscape patterns influence water quality with multiple factors, complex processes, and scale dependence. However, studies identifying landscape thresholds causing abrupt water quality changes and characterizing the contribution of topography to water quality are still limited. Exploring the impact mechanisms of natural geographical and landscape characteristics on spatial and seasonal water quality variations is conducive to watershed water resource protection and ecosystem restoration. Based on water quality monitoring data of Minjiahe River in the typical headwater area of the upstream Dan River in China from 2019 to 2021, we employed redundancy analysis, partial redundancy analysis, and nonparametric change-point analysis to analyze the relationship between stream water quality and multi-spatial scale comprehensive landscape patterns, to obtain the interactive and independent contributions of different landscape categories at multi-spatial scales on water quality, and to find the key landscape threshold leading to abrupt changes in water quality. Results showed that landscape configuration, landscape composition, and topographic factors collectively explain over 89.1% of water quality variation. Most seasonal variations in water quality were primarily caused by landscape configuration. The landscape composition was mainly responsible for the differences in water quality variations among spatial scales. The topographic factors made the least independent contribution and had a potential impact on overall water quality variation. In order to protect the water quality of streams, it is more reasonable to regulate the landscape at different scales. At the sub-catchment scale, interspersion and juxtaposition index (IJI) and landscape shape index (LSI) should be controlled below 82% and 22. At the 100 m riparian scale, farmland, urban land, IJI, and LSI should be controlled below 29%, 6.5%, 92%, and 26, respectively. Our results provide important guidance for optimizing landscape patterns and water conservation in the watershed.
综合景观格局通过多种因素、复杂的过程和尺度依赖性影响水质。然而，确定导致水质急剧变化的景观阈值并描述地形对水质贡献的研究仍然有限。探讨自然地理和景观特征对空间和季节水质变化的影响机制，有利于流域水资源保护和生态系统恢复。基于 2019 年至 2021 年中国丹江上游典型河源米家河河流的水质监测数据，采用冗余分析、偏冗余分析和非参数变点分析方法，分析了流域水质与多空间尺度综合景观格局的关系，获得了不同景观类型在多空间尺度上对水质的交互和独立贡献，并找到了导致水质急剧变化的关键景观阈值。结果表明，景观配置、景观组成和地形因素共同解释了超过 89.1%的水质变化。水质的季节性变化主要是由景观配置引起的。景观组成主要负责解释不同空间尺度上水质变化的差异。地形因素的独立贡献最小，对整体水质变化有潜在影响。为了保护溪流的水质，在不同尺度上调节景观更为合理。在子流域尺度上，分散度和并置指数（IJI）和景观形状指数（LSI）应控制在 82%和 22 以下。在 100m 河岸带尺度上，应将农田、城市土地、IJI 和 LSI 分别控制在 29%、6.5%、92%和 26 以下。我们的研究结果为优化流域景观格局和水资源保护提供了重要指导。
