Probabilistic simulation of phosphorus loss using the Vermont P-index: a bottom-up field to watershed approach Article Swipe
B. K. Dube
,
Jon D. Erickson
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1017/s1742170523000327
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1017/s1742170523000327
Anthropogenic nutrient loading from land use, especially agriculture, is a major threat to waterbodies worldwide. Efforts to govern nutrient pollution are increasingly based on simulation modeling for research, evaluation, and regulation. This study develops a novel approach to simulate nutrient losses from agriculture applied to the Lake Champlain basin in the US state of Vermont. The Vermont Phosphorus-Index—a farm-based empirical model regularly used for site evaluation—is scaled up to the basin level with high-resolution geographic data and probabilistic estimation of unknown parameters and management practices. Results are comparable with analyses using more data and computationally intensive tools. Important insights into basin-wide management include: (1) nutrient-management planning can significantly reduce P losses in a livestock-agriculture-dominated watershed by re-distributing manure applications from areas of high loss to low loss; (2) hotspot identification from geographic data alone may be deeply complicated by high underlying heterogeneity of soil phosphorus; and (3) probabilistic modeling using simple, field-scale models is a potentially useful complement to complex watershed process models. Findings suggest that currently available best-management practices will likely be insufficient to reach reduction targets in the most impaired sub-watersheds. Reductions of agricultural land use and herd size, particularly in intensive dairy operations, may be necessary.
Related Topics
Concepts
Watershed
Environmental science
Surface runoff
Land use
Agriculture
Manure
Nutrient management
Manure management
Agricultural land
Hydrology (agriculture)
Land management
Water resource management
Environmental resource management
Agricultural engineering
Computer science
Geography
Ecology
Engineering
Civil engineering
Machine learning
Archaeology
Geotechnical engineering
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1017/s1742170523000327
- https://www.cambridge.org/core/services/aop-cambridge-core/content/view/04BA0010B40AC503F289F8349502FB37/S1742170523000327a.pdf/div-class-title-probabilistic-simulation-of-phosphorus-loss-using-the-vermont-p-index-a-bottom-up-field-to-watershed-approach-div.pdf
- OA Status
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- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386687698
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4386687698Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1017/s1742170523000327Digital Object Identifier
- Title
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Probabilistic simulation of phosphorus loss using the Vermont P-index: a bottom-up field to watershed approachWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
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B. K. Dube, Jon D. EricksonList of authors in order
- Landing page
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https://doi.org/10.1017/s1742170523000327Publisher landing page
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/04BA0010B40AC503F289F8349502FB37/S1742170523000327a.pdf/div-class-title-probabilistic-simulation-of-phosphorus-loss-using-the-vermont-p-index-a-bottom-up-field-to-watershed-approach-div.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/04BA0010B40AC503F289F8349502FB37/S1742170523000327a.pdf/div-class-title-probabilistic-simulation-of-phosphorus-loss-using-the-vermont-p-index-a-bottom-up-field-to-watershed-approach-div.pdfDirect OA link when available
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Watershed, Environmental science, Surface runoff, Land use, Agriculture, Manure, Nutrient management, Manure management, Agricultural land, Hydrology (agriculture), Land management, Water resource management, Environmental resource management, Agricultural engineering, Computer science, Geography, Ecology, Engineering, Civil engineering, Machine learning, Archaeology, Geotechnical engineering, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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45Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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