关键词: Extreme climate Harmful algal blooms Nitrogen Non-point source pollution SWAT-Bayesian Network model

Mesh : Lakes Agriculture / methods Bayes Theorem Harmful Algal Bloom Fertilizers / analysis Nitrogen / analysis China Climate Change Phosphorus / analysis Eutrophication Models, Theoretical

来  源:   DOI:10.1016/j.jenvman.2024.121433

Abstract:
Lake eutrophication caused by nitrogen and phosphorus has led to frequent harmful algal blooms (HABs), especially under the unknown challenges of climate change, which have seriously damaged human life and property. In this study, a coupled SWAT-Bayesian Network (SWAT-BN) model framework was constructed to elucidate the mechanisms between non-point source nitrogen pollution in agricultural lake watersheds and algal activities. A typical agricultural shallow lake basin, the Taihu Basin (TB), China, was chosen in this study, aiming to investigate the effectiveness of best management practices (BMPs) in controlling HABs risks in TB. By modeling total nitrogen concentration of Taihu Lake from 2007 to 2022 with four BMPs (filter strips, grassed waterway, fertilizer application reduction and no-till agriculture), the results indicated that fertilizer application reduction proved to be the most effective BMP with 0.130 of Harmful Algal Blooms Probability Reduction (HABs-PR) when reducing 40% of fertilizer, followed by filter strips with 0.01 of HABs-PR when 4815ha of filter strips were conducted, while grassed waterway and no-till agriculture showed no significant effect on preventing HABs. Furthermore, the combined practice between 40% fertilizer application reduction and 4815ha filter strips construction showed synergistic effects with HABs-PR increasing to 0.171. Precipitation and temperature data were distorted to model scenarios of extreme events. As a result, the combined approach outperformed any single BMP in terms of robustness under extreme climates. This research provides a watershed-level perspective on HABs risks mitigation and highlights the strategies to address HABs under the influence of climate change.
摘要:
由氮和磷引起的湖泊富营养化导致了频繁的有害藻华(HAB),特别是在未知的气候变化挑战下,严重损害了人类的生命和财产。在这项研究中,构建了SWAT-贝叶斯网络(SWAT-BN)耦合模型框架,以阐明农业湖泊流域非点源氮污染与藻类活动之间的机制。典型的农业浅水湖盆,太湖流域(TB),中国,在这项研究中被选中,旨在调查最佳管理实践(BMP)在控制结核病HAB风险方面的有效性。通过使用四个BMPs模拟2007年至2022年太湖的总氮浓度(滤纸,草地水道,减少施肥和免耕农业),结果表明,当减少40%的肥料时,减少肥料的施用被证明是最有效的BMP,有害藻华概率减少0.130(HABs-PR),当进行4815ha的过滤条时,使用0.01的HABs-PR的过滤条,而草地水道和免耕农业对预防HAB没有显着影响。此外,减少40%肥料施用和4815ha滤条建设之间的联合实践显示出协同作用,HABs-PR增加到0.171。降水和温度数据被扭曲,以模拟极端事件的情景。因此,在极端气候下的稳健性方面,组合方法优于任何单一BMP。这项研究为缓解HABs风险提供了分水岭层面的观点,并强调了在气候变化影响下解决HABs的策略。
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