{"title":"揭示耕地分流域的季节性硝酸盐污染动态:比拉特农业流域的地貌分析","authors":"","doi":"10.1016/j.envadv.2024.100572","DOIUrl":null,"url":null,"abstract":"<div><p>Cropland sub-watershed surface and groundwater contamination are pressing issues for water management. This study examines the impact of sediment transport indices (STI) on nitrate concentration in downstream water bodies. The research highlights rainfall's significant role in predicting seasonal nitrate levels. Employing GIS-SWPT tools and hydro-geomorphologic analysis, cropland sub-watersheds, particularly sub-watersheds one and three, are prioritized for their high contribution to downstream surface and groundwater nitrate contamination, with prioritization values of 105.58 and 180.63, respectively. Statistical analysis, conducted using Python's scikit-learn library, validated the findings of the study, with the model's F-statistic of 79.63 and a corresponding p-value of 0.0147 underscoring its overall significance. However, while STI alone showed a prioritization parametric correlation coefficient of 0.5077, suggesting other external factors also contribute to nitrate loading, a strong relationship between STI and nitrate concentration was revealed (R² of 0.993). This integrated approach enhances understanding of how geomorphologic parameters of cropland sub-watersheds influence water quality downstream. By clarifying the complex interactions between sediment transport and nitrate concentration, evidence-based strategies can be developed to mitigate surface and groundwater nitrate pollution. This research provides valuable insights into cropland sub-watershed pollution dynamics and informs targeted management interventions.</p></div>","PeriodicalId":34473,"journal":{"name":"Environmental Advances","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666765724000905/pdfft?md5=427f241329a3313892c5479d11dcb78b&pid=1-s2.0-S2666765724000905-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Unveiling seasonal nitrate contamination dynamics in cropland sub-watersheds: A geo-morphological analysis of the bilate agricultural watershed\",\"authors\":\"\",\"doi\":\"10.1016/j.envadv.2024.100572\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Cropland sub-watershed surface and groundwater contamination are pressing issues for water management. This study examines the impact of sediment transport indices (STI) on nitrate concentration in downstream water bodies. The research highlights rainfall's significant role in predicting seasonal nitrate levels. Employing GIS-SWPT tools and hydro-geomorphologic analysis, cropland sub-watersheds, particularly sub-watersheds one and three, are prioritized for their high contribution to downstream surface and groundwater nitrate contamination, with prioritization values of 105.58 and 180.63, respectively. Statistical analysis, conducted using Python's scikit-learn library, validated the findings of the study, with the model's F-statistic of 79.63 and a corresponding p-value of 0.0147 underscoring its overall significance. However, while STI alone showed a prioritization parametric correlation coefficient of 0.5077, suggesting other external factors also contribute to nitrate loading, a strong relationship between STI and nitrate concentration was revealed (R² of 0.993). This integrated approach enhances understanding of how geomorphologic parameters of cropland sub-watersheds influence water quality downstream. By clarifying the complex interactions between sediment transport and nitrate concentration, evidence-based strategies can be developed to mitigate surface and groundwater nitrate pollution. This research provides valuable insights into cropland sub-watershed pollution dynamics and informs targeted management interventions.</p></div>\",\"PeriodicalId\":34473,\"journal\":{\"name\":\"Environmental Advances\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666765724000905/pdfft?md5=427f241329a3313892c5479d11dcb78b&pid=1-s2.0-S2666765724000905-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666765724000905\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Advances","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666765724000905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 0
摘要
耕地分流域地表水和地下水污染是水资源管理的紧迫问题。本研究探讨了沉积物迁移指数(STI)对下游水体硝酸盐浓度的影响。研究强调了降雨在预测季节性硝酸盐含量方面的重要作用。利用 GIS-SWPT 工具和水文地质分析,确定了耕地子流域,尤其是一号和三号子流域的优先级,因为它们对下游地表水和地下水硝酸盐污染的影响较大,优先级值分别为 105.58 和 180.63。使用 Python 的 scikit-learn 库进行的统计分析验证了研究结果,模型的 F 统计量为 79.63,相应的 p 值为 0.0147,强调了其整体意义。不过,虽然科技创新本身显示出的优先参数相关系数为 0.5077,表明其他外部因素也会造成硝酸盐负荷,但科技创新与硝酸盐浓度之间的关系却很密切(R²为 0.993)。这种综合方法加深了人们对耕地子流域地貌参数如何影响下游水质的理解。通过阐明沉积物迁移与硝酸盐浓度之间复杂的相互作用,可以制定出以证据为基础的策略,减轻地表水和地下水硝酸盐污染。这项研究为了解耕地次级流域的污染动态提供了宝贵的见解,并为有针对性的管理干预措施提供了信息。
Unveiling seasonal nitrate contamination dynamics in cropland sub-watersheds: A geo-morphological analysis of the bilate agricultural watershed
Cropland sub-watershed surface and groundwater contamination are pressing issues for water management. This study examines the impact of sediment transport indices (STI) on nitrate concentration in downstream water bodies. The research highlights rainfall's significant role in predicting seasonal nitrate levels. Employing GIS-SWPT tools and hydro-geomorphologic analysis, cropland sub-watersheds, particularly sub-watersheds one and three, are prioritized for their high contribution to downstream surface and groundwater nitrate contamination, with prioritization values of 105.58 and 180.63, respectively. Statistical analysis, conducted using Python's scikit-learn library, validated the findings of the study, with the model's F-statistic of 79.63 and a corresponding p-value of 0.0147 underscoring its overall significance. However, while STI alone showed a prioritization parametric correlation coefficient of 0.5077, suggesting other external factors also contribute to nitrate loading, a strong relationship between STI and nitrate concentration was revealed (R² of 0.993). This integrated approach enhances understanding of how geomorphologic parameters of cropland sub-watersheds influence water quality downstream. By clarifying the complex interactions between sediment transport and nitrate concentration, evidence-based strategies can be developed to mitigate surface and groundwater nitrate pollution. This research provides valuable insights into cropland sub-watershed pollution dynamics and informs targeted management interventions.