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Title: Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient

Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (Kd) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). Here, we formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling Kd from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. Furthermore, the correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. Our study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport.
Authors:
; ; ; ; ;
Publication Date:
Report Number(s):
PNNL-SA-124748
Journal ID: ISSN 0048-9697; PII: S0048969717304928
Grant/Contract Number:
AC0576Rl01830; 51139003; 11372161
Type:
Accepted Manuscript
Journal Name:
Science of the Total Environment
Additional Journal Information:
Journal Volume: 592; Journal Issue: C; Journal ID: ISSN 0048-9697
Publisher:
Elsevier
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Phosphorus transport; Stochastic model; Partition coefficient; Uncertainty; Three Gorges Reservoir
OSTI Identifier:
1349083

Huang, Lei, Fang, Hongwei, Xu, Xingya, He, Guojian, Zhang, Xuesong, and Reible, Danny. Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient. United States: N. p., Web. doi:10.1016/j.scitotenv.2017.02.227.
Huang, Lei, Fang, Hongwei, Xu, Xingya, He, Guojian, Zhang, Xuesong, & Reible, Danny. Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient. United States. doi:10.1016/j.scitotenv.2017.02.227.
Huang, Lei, Fang, Hongwei, Xu, Xingya, He, Guojian, Zhang, Xuesong, and Reible, Danny. 2017. "Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient". United States. doi:10.1016/j.scitotenv.2017.02.227. https://www.osti.gov/servlets/purl/1349083.
@article{osti_1349083,
title = {Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient},
author = {Huang, Lei and Fang, Hongwei and Xu, Xingya and He, Guojian and Zhang, Xuesong and Reible, Danny},
abstractNote = {Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (Kd) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). Here, we formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling Kd from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. Furthermore, the correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. Our study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport.},
doi = {10.1016/j.scitotenv.2017.02.227},
journal = {Science of the Total Environment},
number = C,
volume = 592,
place = {United States},
year = {2017},
month = {8}
}