将生态系统服务供需动态整合到流域管理：量化水净化服务的新框架

IF 12.4 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research Pub Date : 2025-09-22 DOI:10.1016/j.watres.2025.124657

Lei Tan , Guishan Yang , Qing Zhu , Rongrong Wan , Jun Li , Hengpeng Li , Bing Li

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引用次数: 0

摘要

了解水净化服务（WPS）供需不匹配的时空动态对于制定有效的流域管理策略以保障湖泊和水库下游水质至关重要。然而，开发一个可推广的框架来量化这些复杂的供需动态，提出了方法学上的挑战，目前限制了有效的水质管理。在这项研究中，我们开发了一个新的框架来量化动态WPS供需关系。通过将长期水质监测数据与水文建模和随机森林算法相结合，该框架量化了上游各子流域的WPS供应能力以及湖泊和水库的WPS需求。我们将这一新框架应用于中国东部一个重要的饮用水源流域。结果表明：(1)上游生态系统为下游水库截留了大量的总氮（TN）和总磷（TP），平均每年截留6.80 × 10⁶kg TN和2.57 × 10⁶kg TP，且供水量因年份、季节和子流域而异。(2)需求侧要求下游水库总氮和总磷负荷分别减少14.7%和32.4%。(3)供需间存在时间错配，总氮错配65%集中在3 - 5月，总磷错配71%集中在7、3、6月。我们建议采取具有空间针对性的保护措施和具有时间适应性的管理策略来优化WPS供需平衡。该框架通过解决WPS供需的时空差异，为有针对性的流域管理提供了有效的信息方法。

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Integrating ecosystem service supply-demand dynamics into watershed management: A novel framework for quantifying water purification services

Understanding the spatiotemporal dynamics of water purification service (WPS) supply-demand mismatches is critical for developing effective watershed management strategies to safeguard downstream water quality in lakes and reservoirs. However, developing a generalizable framework to quantify these complex supply-demand dynamics presents methodological challenges that currently constrain effective water quality management. In the study, we developed a novel framework that quantifies the dynamic WPS supply-demand relationship. By coupling long-term water quality monitoring data with hydrological modeling and random forest algorithms, the framework quantifies the WPS supply capacities of each upstream subbasin and the WPS demand of lakes and reservoirs. We applied this new framework to a critical drinking water source watershed in eastern China. Results showed that (1) Upstream ecosystems retained substantial total nitrogen (TN) and total phosphorus (TP) for the downstream reservoir, intercepting an average of 6.80 × 10⁶ kg TN and 2.57 × 10⁶ kg TP annually, and the supply varied among years, seasons, and subbasins. (2) On the demand side, 14.7 % and 32.4 % reductions in TN and TP loads of the downstream reservoir were required. (3) Temporal mismatches between supply and demand were revealed, with 65 % of TN mismatches concentrated in March-May, and 71 % of TP mismatches occurring in July, March, and June. We recommend spatially targeted conservation measures and temporally adaptive management strategies for optimizing WPS supply-demand balance. Our framework provides an effective method for giving information to targeted watershed management by resolving spatiotemporal disparities of WPS supply and demand.

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来源期刊

Water Research 环境科学-工程：环境

CiteScore

20.80

自引率

9.40%

发文量

1307

审稿时长

38 days

期刊介绍： Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.