Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2017WR022220 |
Leveraging Spatial and Temporal Variability to Probabilistically Characterize Nutrient Sources and Export Rates in a Developing Watershed | |
Strickling, H. L.; Obenour, D. R. | |
2018-07-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2018 |
卷号 | 54期号:7页码:5143-5162 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Hybrid watershed models based on nonlinear regression are useful tools for estimating the magnitude of loading rates (i.e., export coefficients) for various pollutant sources within large-scale river basins. Few such models, however, have incorporated temporal variability in either source distributions or climate, despite evidence that precipitation is the primary driver in interannual variability in loading rates. The model developed here includes changes in precipitation, land use, point source discharge, and livestock operations to capture temporal variability in nitrogen loads. Precipitation is incorporated directly in the formulation of export rates using coefficients that vary by source type. Instream and reservoir retention of nitrogen is included to account for nitrogen sinks within the watershed. A Bayesian hierarchical approach is employed to integrate uncertainty in loading estimates, include prior knowledge of parameters, address intrawatershed correlation, and estimate export coefficients probabilistically. We apply this method to three North Carolina river basins that have experienced substantial growth in urban development and livestock operations in the past few decades, and where eutrophication-related water quality problems are common. Accounting for temporal variability constrains uncertainties in nonpoint source export coefficients by nearly 50%, relative to a spatial-only model. Results indicate that livestock operations are a significant contributor of nitrogen throughout much of the study area. Precipitation is shown to have a larger influence on export rates for agricultural than for developed lands, creating a system dominated by agricultural total nitrogen during high precipitation years and by developed (urban) regions during low precipitation years. Plain Language Summary Human activities increase the amount of nutrients (nitrogen and phosphorus) entering streams, lakes, and coastal waters. At high levels, these nutrients can cause harmful algal blooms, fish kills, and other water quality problems. Therefore, it is important to understand where nutrients come from, so that they can be properly managed. In this study, we develop a model to better understand and quantify how different source types (cities, cropland, hogs and chicken livestock operations, and wildland) contribute to overall nitrogen loading. Using the model, our understanding of the importance of each source type is updated based on the amount of nitrogen observed in various streams across our study area. Streams with relatively high nitrogen levels indicate that the nitrogen source types in the stream's upstream watershed are relatively large contributors of nitrogen. When we leverage such data over a large area (eastern North Carolina) and over multiple decades, within the model, we can quantify loading rates from different source types with increased confidence. We can also predict how much of this nitrogen reaches sensitive downstream estuaries. In our study, we find that agricultural sources have become increasingly dominant over time, especially during relatively wet years. |
英文关键词 | hybrid watershed modeling nutrients nitrogen loading Bayesian modeling export coefficients land use change |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000442502100054 |
WOS关键词 | SUBSURFACE DRAINAGE WATER ; SOURCE POLLUTION MODELS ; NEUSE RIVER ESTUARY ; LAND-USE ; NORTH-CAROLINA ; UNITED-STATES ; REFERENCED REGRESSION ; NITROGEN REMOVAL ; SURFACE WATERS ; COASTAL RIVER |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/21606 |
专题 | 资源环境科学 |
作者单位 | North Carolina State Univ, Dept Civil Construct & Environm Engn, Raleigh, NC 27695 USA |
推荐引用方式 GB/T 7714 | Strickling, H. L.,Obenour, D. R.. Leveraging Spatial and Temporal Variability to Probabilistically Characterize Nutrient Sources and Export Rates in a Developing Watershed[J]. WATER RESOURCES RESEARCH,2018,54(7):5143-5162. |
APA | Strickling, H. L.,&Obenour, D. R..(2018).Leveraging Spatial and Temporal Variability to Probabilistically Characterize Nutrient Sources and Export Rates in a Developing Watershed.WATER RESOURCES RESEARCH,54(7),5143-5162. |
MLA | Strickling, H. L.,et al."Leveraging Spatial and Temporal Variability to Probabilistically Characterize Nutrient Sources and Export Rates in a Developing Watershed".WATER RESOURCES RESEARCH 54.7(2018):5143-5162. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论