长期水质动态及趋势评估揭示生态补偿的有效性:中国首个跨省补偿流域的启示

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2024-11-16 DOI:10.1016/j.ecolind.2024.112853
Haitao Chen , Chengcheng Wang , Qiuru Ren , Xia Liu , Jiaxue Ren , Gelin Kang , Yuqiu Wang
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引用次数: 0

摘要

尽管全球都在采用流域生态系统服务补偿(PES)来改善水质,但对其改善效果的评估仍然不足。本研究采用时间、排放量和季节加权回归(WRTDS)模型,评估了中国首个跨省生态补偿(EC)流域从 2000 年到 2020 年的水质变化,并确定了人为干预和气候变化的影响。结果表明,WRTDS 模型准确预测了 TN、NH4+、CODMn 和 TP 的浓度和负荷,而包括污水处理厂建设和生态补偿措施在内的人为干预措施在不同程度上改善了水质。具体而言,NH4+浓度在2000年至2008年期间急剧上升,但在EC期间有所下降,这表明废水处理取得了成效。然而,TN 浓度持续上升,TP 含量也没有显著下降,这可能是由于土壤和地下水中遗留的氮和磷的积累。此外,从 2000 年到 2020 年,CODMn 的浓度呈稳步上升趋势。这些趋势共同表明,点源污染控制是有效的,而非点源污染,尤其是遗留污染源,仍然是一个相当大的挑战。此外,不同气候条件下的水质变化揭示了潜在污染源的多样性,而极端降水事件可能会增加 TN、CODMn 和 TP 的浓度。总体而言,WRTDS 模型有效地评估了流域 EC 方案,确定了长期水质趋势和潜在污染源,并为优化污染控制策略提供了宝贵的见解。
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Long-term water quality dynamics and trend assessment reveal the effectiveness of ecological compensation: Insights from China’s first cross-provincial compensation watershed
Despite the global adoption of watershed Payments for Ecosystem Services (PES) to enhance water quality, their effectiveness in achieving improvements remains inadequately assessed. This study employed the Weighted Regressions on Time, Discharge, and Season (WRTDS) model to evaluate water quality changes in China’s first cross-provincial Ecological Compensation (EC) watershed from 2000 to 2020, and to determine the impact of human interventions and climate change. Results showed that the WRTDS model accurately predicted concentrations and loads of TN, NH4+, CODMn, and TP, while human interventions, including WWTPs construction and EC measures, have improved water quality to varying extents. Specifically, NH4+ concentrations rose sharply from 2000 to 2008 but decreased during the EC period, indicating effective wastewater treatment. However, TN concentrations continued to rise, and TP levels did not significantly decrease, probably due to the accumulation legacy N and P in soil and groundwater. Moreover, CODMn concentrations exhibited a steady increased from 2000 to 2020. These trends collectively suggest that point source pollution controls are effective, while non-point source pollution, particularly legacy sources, remains a considerable challenge. In addition, water quality variations under different climate conditions reveal the diversity of potential pollution sources, while extreme precipitation events potentially increasing TN, CODMn, and TP concentrations. Overall, the WRTDS model effectively evaluates the watershed EC programmes, identifies long-term water quality trends and potential sources, and offers valuable insights for optimizing pollution control strategies.
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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