Xu Qiyu, Guo Shufang, Zhai Limei, Wang Chenyang, Yin Yinghua, Liu Hongbin
State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Institute of Ecology and Environment, Inner Mongolia University, Hohhot 010021, Inner Mongolia, China.
Institute of Agricultural Environment and Resources, Yunnan Academy of Agricultural Sciences, Kunming 650201, China.
Sci Total Environ. 2023 Nov 25;901:165869. doi: 10.1016/j.scitotenv.2023.165869. Epub 2023 Jul 30.
Consensus has emerged that landscape pattern evolution significantly impacts the river environment. However, there remains unclear how the landscape pattern evolves possible to achieve a balance between land resource use and water conservation. Thus, simulating future landscape patterns under different scenarios to predict river eutrophication level is critical to propose targeted landscape planning programs and alleviate river water quality degradation. Here, we coupled five water quality parameters (TOC, TN, NO-N, NH-N, TP), collected from October 2020 to September 2021, to construct the river eutrophication index (EI) to assess river water quality. Meanwhile, based on redundancy analysis, patch-generating land use simulation model, and stepwise multiple linear regression model comprehensively analyze the Fengyu River watershed landscape patterns evolution and their impact on river eutrophication. Results indicated that current rivers reach eutrophic levels, and EI reaches 40.7. The landscape patterns explain 88.2 % of river eutrophication variation, while the LPI_Con metric is critical and individually explained 21.5 %. Furthermore, eutrophication in the watershed will increase in 2040 under the natural development (ND) scenario, and the EI will reach 44.4. In contrast, farmland protection (FP) scenarios and environmental protection (EP) scenarios contribute to mitigating eutrophication, the EI values are 38.2 and 38.1, respectively. The results provide a potential mechanistic explanation that river eutrophication is a consequence of unreasonable landscape pattern evolution. Guiding the landscape patterns evolution based on critical driver factors from a planning perspective is conducive to mitigating river water quality degradation.
人们已达成共识,即景观格局演变对河流环境有重大影响。然而,景观格局如何演变才能在土地资源利用和水资源保护之间实现平衡仍不明确。因此,模拟不同情景下的未来景观格局以预测河流富营养化水平,对于提出有针对性的景观规划方案和缓解河流水质恶化至关重要。在此,我们将2020年10月至2021年9月收集的五个水质参数(总有机碳、总氮、硝态氮、氨氮、总磷)相结合,构建河流富营养化指数(EI)来评估河流水质。同时,基于冗余分析、斑块生成土地利用模拟模型和逐步多元线性回归模型,综合分析风雨河流域景观格局演变及其对河流富营养化的影响。结果表明,当前河流达到富营养化水平,EI达到40.7。景观格局解释了河流富营养化变异的88.2%,而景观加权平均形状指数(LPI_Con)指标至关重要,单独解释了21.5%。此外,在自然发展(ND)情景下,2040年流域内的富营养化将加剧,EI将达到44.4。相比之下,农田保护(FP)情景和环境保护(EP)情景有助于减轻富营养化,EI值分别为38.2和38.1。研究结果提供了一种潜在的机理解释,即河流富营养化是不合理景观格局演变的结果。从规划角度基于关键驱动因素引导景观格局演变,有利于缓解河流水质恶化。