[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2768":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"view_count":32,"doi":33,"paper":34,"created_at":59},2768,"Spatial–temporal variability of the Bua River’s physicochemical water quality: a DPSIR-based analysis","https:\u002F\u002Fdoi.org\u002F10.1080\u002F15715124.2026.2722406","Freshwater ecosystems are increasingly threatened by climate variability and catchment degradation, resulting in declining water quality and ecosystem resilience. We assessed spatial and seasonal variability in water quality along the Bua River, Malawi, and applied the Drivers–Pressures–State–Impact–Response (DPSIR) framework to identify degradation pathways and management responses. A stratified sampling design was used across upstream, midstream, and downstream sections during three distinct seasons. Downstream sections consistently exhibited poorer water quality, with turbidity reaching 17.17 ± 0.63 NTU, EC increasing to 183.00 ± 2.80 µS cm−1, ammonium concentrations reaching 120.14 ± 2.00 µg L−1, and chlorophyll-a increasing to 6.70 ± 0.70 µg L−1. Factorial ANOVA revealed significant seasonal effects (F₂,₅₂ = 21.84, p \u003C 0.0001), site (F₂,₅₂ = 6.25, p = 0.0036), and water-quality parameters (F₁₃,₅₂ = 58.80, p \u003C 0.0001). Elevated nutrient concentrations and sediment loads were associated with anthropogenic stressors. Our DPSIR linked these pressures to ecological degradation, declining fisheries productivity and increasing risks to water-dependent livelihoods. Our findings highlight the need for integrated catchment management, riparian restoration, climate-smart agriculture, and strengthened water-quality monitoring to support Malawi’s Nationally Determined Contributions (NDCs), and Sustainable Development Goals (SDGs).","淡水生态系统日益受到气候变率和流域退化的威胁，导致水质下降和生态系统恢复力减弱。我们评估了马拉维布阿河沿线水质的空间和季节变异性，并应用驱动力—压力—状态—影响—响应（DPSIR）框架来识别退化路径和管理响应。采用分层抽样设计，在三个不同季节对上游、中游和下游河段进行采样。下游河段的水质始终较差，浊度达到17.17 ± 0.63 NTU，电导率（EC）升高至183.00 ± 2.80 µS cm⁻¹，铵盐浓度达到120.14 ± 2.00 µg L⁻¹，叶绿素a增加至6.70 ± 0.70 µg L⁻¹。因子方差分析（ANOVA）揭示了显著的季节效应（F₂,₅₂ = 21.84，p \u003C 0.0001）、点位效应（F₂,₅₂ = 6.25，p = 0.0036）和水质参数效应（F₁₃,₅₂ = 58.80，p \u003C 0.0001）。营养物浓度和沉积物负荷升高与人为压力因素相关。我们的DPSIR框架将这些压力与生态退化、渔业生产力下降以及依赖水资源生计的风险增加联系起来。我们的研究结果凸显了综合流域管理、河岸带修复、气候智慧型农业和加强水质监测的必要性，以支持马拉维的国家自主贡献（NDCs）和可持续发展目标（SDGs）。",null,"International Journal of River Basin Management","2026-09-16T00:00:00Z","论文",10,false,66,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,20,16,13,9,1,"以DPSIR框架量化马拉维Bua河水质时空变化，方法规范、数据翔实，但属境外流域案例，对国内三农与农业信息化的直接借鉴价值有限，可作国际参考而非每日精选。",[25],{"name":10,"url":6},[27,28,29,30,31],"气候变化","水资源管理","水质监测","流域治理","面源污染",0,"10.1080\u002F15715124.2026.2722406",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":50,"card":51,"direction":57,"ingested_from":58},"W7213250794",[37,40,42,44,47],{"name":38,"orcid":39},"James N. Nkhoswe","https:\u002F\u002Forcid.org\u002F0000-0002-9044-5913",{"name":41,"orcid":9},"Amon Aine",{"name":43,"orcid":9},"Tamara Tembo",{"name":45,"orcid":46},"Madalitso Chatsika","https:\u002F\u002Forcid.org\u002F0000-0002-3354-4720",{"name":48,"orcid":49},"A. H. N. Mtethiwa","https:\u002F\u002Forcid.org\u002F0000-0003-0793-5186","https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.33845035",{"tldr":52,"method":53,"finding":54,"direction":55,"opportunity":56},"评估马拉维布阿河水质时空变化，并用DPSIR框架分析退化路径与管理对策。","三季上中下游分层采样，测定理化指标，因子方差分析与DPSIR框架。","下游水质最差，浊度、电导率、铵盐和叶绿素a显著升高，季节与点位影响显著。","农业绿色发展与碳","可结合流域农业面源污染监测与气候智慧型农业措施，量化其对水质及碳减排的协同效应。","智慧农业 \u002F 农业物联网","openalex","2026-09-17T23:30:10.468460Z"]