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Developing a non-point source P loss indicator in R and its parameter uncertainty assessment using GLUE: a case study in northern China

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Abstract

Uncertainty analysis is an important prerequisite for model application. However, the existing phosphorus (P) loss indexes or indicators were rarely evaluated. This study applied generalized likelihood uncertainty estimation (GLUE) method to assess the uncertainty of parameters and modeling outputs of a non-point source (NPS) P indicator constructed in R language. And the influences of subjective choices of likelihood formulation and acceptability threshold of GLUE on model outputs were also detected. The results indicated the following. (1) Parameters RegR2, RegSDR2, PlossDPfer, PlossDPman, DPDR, and DPR were highly sensitive to overall TP simulation and their value ranges could be reduced by GLUE. (2) Nash efficiency likelihood (L1) seemed to present better ability in accentuating high likelihood value simulations than the exponential function (L2) did. (3) The combined likelihood integrating the criteria of multiple outputs acted better than single likelihood in model uncertainty assessment in terms of reducing the uncertainty band widths and assuring the fitting goodness of whole model outputs. (4) A value of 0.55 appeared to be a modest choice of threshold value to balance the interests between high modeling efficiency and high bracketing efficiency. Results of this study could provide (1) an option to conduct NPS modeling under one single computer platform, (2) important references to the parameter setting for NPS model development in similar regions, (3) useful suggestions for the application of GLUE method in studies with different emphases according to research interests, and (4) important insights into the watershed P management in similar regions.

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Funding

This study was supported by the National Natural Science Funding (Grant number: 41401590), Project of State Key Laboratory of Urban and Regional Ecology in China (SKLURE2017-1-5), Major Science and Technology Program for Water Pollution Control and Treatment (Grant number: 2015ZX07203-005-01).

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Authors and Affiliations

  1. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Room 302, No. 18 Shuangqing Road, Haidian District, Beijing, 100085, China

    Jingjun Su & Xuyong Li

  2. Athabasca River Basin Research Institute (ARBRI), Athabasca University, 10011 109 St. NW, Edmonton, AB, T5J 3S8, Canada

    Xinzhong Du

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  1. Jingjun Su
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Correspondence to Xuyong Li.

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Su, J., Du, X. & Li, X. Developing a non-point source P loss indicator in R and its parameter uncertainty assessment using GLUE: a case study in northern China. Environ Sci Pollut Res 25, 21070–21085 (2018). https://doi.org/10.1007/s11356-018-2113-0

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