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评估流域尺度上基于科学的决策支持潜在最佳管理实践的有效性:以西班牙马尔梅诺尔沿海泻湖为例。

Assessing the effectiveness of potential best management practices for science-informed decision support at the watershed scale: The case of the Mar Menor coastal lagoon, Spain.

作者信息

López-Ballesteros Adrián, Trolle Dennis, Srinivasan Raghavan, Senent-Aparicio Javier

机构信息

Department of Civil Engineering, Catholic University of San Antonio, Campus de Los Jeronimos s/n, 30107 Guadalupe, Murcia, Spain.

Department of Ecoscience, Aarhus University, Vejlsøvej 25, 8600 Silkeborg, Denmark; WaterITech, Krakesvej 53, 8660 Skanderborg, Denmark.

出版信息

Sci Total Environ. 2023 Feb 10;859(Pt 1):160144. doi: 10.1016/j.scitotenv.2022.160144. Epub 2022 Nov 12.

DOI:10.1016/j.scitotenv.2022.160144
PMID:36375550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9760569/
Abstract

Coastal lagoons are ecosystems of high environmental importance but are quite vulnerable to human activities. The continuous inflow of pollutant loads can trigger negative impacts on the ecological status of these water bodies, which is contrary to the European Green Deal. One example is the Mar Menor coastal lagoon in Spain, which has experienced significant environmental degradation in recent years due to excessive external nutrient input, especially from non-point source (NPS) pollution. Mar Menor is one of the largest coastal lagoons of the Mediterranean region and a site of great ecological and socio-economic value. In this study, the highly anthropogenic and complex watershed of Mar Menor, known as Campo de Cartagena (1244 km), was modelled with the Soil and Water Assessment Tool (SWAT) to analyse potential options for recovery of this unique system. The model was used to simulate several best management practices (BMP) proposed by recent Mar Menor regulations, such as vegetative filter strips, shoreline buffers, contour farming, removal of illegal agriculture, crop rotation management, waterway vegetation restoration, fertiliser management and greenhouse rainwater harvesting. Sixteen scenarios of individual and combined BMPs were analysed in this study. We found that, as individual measures, vegetative filter strips and contour farming were most effective in nutrient reduction: approximately 30 % for total nitrogen (TN) and 40 % for total phosphorus (TP). Moreover, waterway vegetation restoration showed the highest sediment (S) reduction at approximately 20 %. However, the combination of BMPs demonstrated clear synergistic effects, reducing S export by 38 %, TN by 67 %, and TP by 75 %. Selecting the most appropriate BMPs to be implemented at a watershed scale requires a holistic approach considering effectiveness in reducing NPS pollution loads and BMP implementation costs. Thus, we have demonstrated a way forward for enabling science-informed decision-making when choosing strategies to control NPS contamination at the watershed scale.

摘要

沿海泻湖是具有高度环境重要性的生态系统,但极易受到人类活动的影响。污染物负荷的持续流入会对这些水体的生态状况产生负面影响,这与欧洲绿色协议相悖。一个例子是西班牙的马尔梅诺尔沿海泻湖,近年来由于外部营养物质输入过多,尤其是来自非点源污染,该泻湖经历了严重的环境退化。马尔梅诺尔是地中海地区最大的沿海泻湖之一,具有巨大的生态和社会经济价值。在本研究中,使用土壤和水资源评估工具(SWAT)对马尔梅诺尔人为活动高度密集且复杂的流域(称为卡塔赫纳地区,面积1244平方公里)进行建模,以分析恢复这个独特系统的潜在方案。该模型用于模拟马尔梅诺尔近期法规提出的几种最佳管理实践(BMP),如植被过滤带、岸线缓冲区、等高耕作、取缔非法农业、作物轮作管理、水道植被恢复、肥料管理和温室雨水收集。本研究分析了16种单个和组合BMP的情景。我们发现,作为单独措施,植被过滤带和等高耕作在减少营养物质方面最有效:总氮(TN)减少约30%,总磷(TP)减少约40%。此外,水道植被恢复在减少沉积物(S)方面效果最为显著,减少约20%。然而,BMP的组合显示出明显的协同效应,S输出减少38%,TN减少67%,TP减少75%。在流域尺度上选择最合适的BMP进行实施需要一种整体方法,要考虑减少非点源污染负荷的有效性和BMP的实施成本。因此,我们展示了一种在选择控制流域尺度非点源污染的策略时实现基于科学的决策的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/b306b5359c56/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/bc20006a245f/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/da13397e8fc1/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/265196b1cb4d/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/550075f59ee6/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/b306b5359c56/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/bc20006a245f/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/da13397e8fc1/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/265196b1cb4d/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/550075f59ee6/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/9760569/b306b5359c56/gr4.jpg

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