Michael Schramm, Duncan Kikoyo, Janelle Wright, Shubham Jain
{"title":"A meta-analysis of the impacts of best management practices on nonpoint source pollutant concentration","authors":"Michael Schramm, Duncan Kikoyo, Janelle Wright, Shubham Jain","doi":"10.3389/frwa.2024.1397615","DOIUrl":null,"url":null,"abstract":"Best management practices (BMPs) are important tools for mitigating the impact of non-point source pollutants on water quality. Drivers of the high variance observed in BMP performance field tests are not well documented and present challenges for planning BMP construction and forecasting water quality improvements.We conducted a systematic review of published nonpoint source water quality BMP studies conducted in the United States and used a meta-analysis approach to describe variance in pollutant removal performance. We used meta-regression to explore how much BMP pollutant removal process, influent pollutant concentration, and aridity effected BMP performance.Despite high variance, we found the BMPs on average were effective at reducing fecal indicator bacteria (FIB), total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) concentrations. We found that influent concentration and interaction effect between the BMP pollutant removal process and aridity explained a substantial amount of variance in BMP performance in FIB removal. Influent concentration explained a small amount of variability in BMP removal of TP and orthophosphate (PO4). We did not find evidence that any of our chosen variables moderated BMP performance in nitrogen or TSS removal. Through our systematic review, we found inadequate spatial representation of BMP studies to capture the underlying variability in climate, soil, and other conditions that could impact BMP performance.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Water","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frwa.2024.1397615","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0
Abstract
Best management practices (BMPs) are important tools for mitigating the impact of non-point source pollutants on water quality. Drivers of the high variance observed in BMP performance field tests are not well documented and present challenges for planning BMP construction and forecasting water quality improvements.We conducted a systematic review of published nonpoint source water quality BMP studies conducted in the United States and used a meta-analysis approach to describe variance in pollutant removal performance. We used meta-regression to explore how much BMP pollutant removal process, influent pollutant concentration, and aridity effected BMP performance.Despite high variance, we found the BMPs on average were effective at reducing fecal indicator bacteria (FIB), total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) concentrations. We found that influent concentration and interaction effect between the BMP pollutant removal process and aridity explained a substantial amount of variance in BMP performance in FIB removal. Influent concentration explained a small amount of variability in BMP removal of TP and orthophosphate (PO4). We did not find evidence that any of our chosen variables moderated BMP performance in nitrogen or TSS removal. Through our systematic review, we found inadequate spatial representation of BMP studies to capture the underlying variability in climate, soil, and other conditions that could impact BMP performance.