<div class="csl-bib-body">
<div class="csl-entry">Hepp, G., Zoboli, O., Strenge, E., & Zessner, M. (2022). Particulate PhozzyLogic Index for policy makers — an index for a more accurate and transparent identification of critical source areas. <i>Journal of Environmental Management</i>, <i>307</i>, 1–11. https://doi.org/10.1016/j.jenvman.2022.114514</div>
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dc.identifier.issn
0301-4797
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/19390
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dc.description
The source code of the enhanced PhosFate model used in this study is available on GitHub in the form of an R package called RPhosFate (https://github.com/gisler/RPhosFate).
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dc.description.abstract
The identification of critical source areas (CSAs) is a key element in a cost-effective mitigation of diffuse emissions of phosphorus from agricultural soils into surface waters. One of the challenges related to CSAs is how to couple complex, data-intensive fate and transport models with easy-to-use information on field level for management purposes at the scale of large watersheds. To fill such a gap and create a bridge between the two tasks, this study puts forward the new Particulate PhozzyLogic Index (PPLI) based on the innovative combination of the results of a complex watershed model (in this case the PhosFate model) with fuzzy logic. Its main feature is the ability to transform the results of diverse scenarios or even models into a final map showing a catchment-wide ranking of the possibility of high PP emissions reaching surface waters for all agricultural fields. Further, this study enhances the PhosFate model with a new algorithm for the allocation of particulate phosphorus (PP) loads entering surface waters to their sources of origin. This is a basic requirement for the identification of critical PP source areas and in consequence for a cost-effective implementation of mitigation measures. By means of a sensitivity analysis, this study investigates the impacts of storm drains, discharge frequencies and flow directions on the designation of CSAs with the help of present-day scenarios for a case study catchment with an area of several hundred square kilometres. The upfront model calibration exhibits a Nash-Sutcliffe efficiency (NSE) of about 0.95 and a modified Nash-Sutcliffe efficiency (mNSE) of around 0.83. A core result of the sensitivity analysis is that the scenarios at least partially disagree on the identified CSAs and suggest that especially open furrows at field borders have the potential to lead to deviating outcomes. All scenario results nevertheless support the 80:20 rule, which states that about 80% of the phosphorus inputs into the surface waters of a catchment originate from only about 20% of its area.
en
dc.language.iso
en
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dc.publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
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dc.relation.ispartof
Journal of Environmental Management
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Water pollution
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dc.subject
Spatial modeling
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dc.subject
PhosFate model
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dc.subject
Sediment transport
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dc.subject
Watershed management
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dc.subject
Fuzzy logic
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dc.title
Particulate PhozzyLogic Index for policy makers — an index for a more accurate and transparent identification of critical source areas