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DOI | 10.1111/1752-1688.12447 |
BOOSTED REGRESSION TREE MODELS TO EXPLAIN WATERSHED NUTRIENT CONCENTRATIONS AND BIOLOGICAL CONDITION | |
Golden, Heather E.1; Lane, Charles R.1; Prues, Amy G.2; D'; Amico, Ellen2 | |
发表日期 | 2016-10-01 |
ISSN | 1093-474X |
卷号 | 52期号:5页码:1251-1274 |
英文摘要 | Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite-nitrate (No-2-NO3), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors - location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) - emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO2-NO3 concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed-use and heavily impacted watersheds. |
英文关键词 | watersheds;watershed management;environmental impacts;nutrients;biotic integrity;boosted regression trees;machine learning |
语种 | 英语 |
WOS记录号 | WOS:000387170400017 |
来源期刊 | JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
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来源机构 | 美国环保署 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/57084 |
作者单位 | 1.US EPA, Syst Exposure Div, Natl Exposure Res Lab, Off Res & Dev, 26 W Martin Luther King Dr,MS-585, Cincinnati, OH 45268 USA; 2.CSS Dynamac Corp, Cincinnati, OH 45268 USA |
推荐引用方式 GB/T 7714 | Golden, Heather E.,Lane, Charles R.,Prues, Amy G.,et al. BOOSTED REGRESSION TREE MODELS TO EXPLAIN WATERSHED NUTRIENT CONCENTRATIONS AND BIOLOGICAL CONDITION[J]. 美国环保署,2016,52(5):1251-1274. |
APA | Golden, Heather E.,Lane, Charles R.,Prues, Amy G.,D',&Amico, Ellen.(2016).BOOSTED REGRESSION TREE MODELS TO EXPLAIN WATERSHED NUTRIENT CONCENTRATIONS AND BIOLOGICAL CONDITION.JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION,52(5),1251-1274. |
MLA | Golden, Heather E.,et al."BOOSTED REGRESSION TREE MODELS TO EXPLAIN WATERSHED NUTRIENT CONCENTRATIONS AND BIOLOGICAL CONDITION".JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 52.5(2016):1251-1274. |
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