Environmental Science and Pollution Research

, Volume 25, Issue 21, pp 21070–21085 | Cite as

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

  • Jingjun Su
  • Xinzhong Du
  • Xuyong Li
Research Article


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.


Non-point source P indicator Uncertainty analysis GLUE Likelihood formulation Acceptability threshold 


Funding information

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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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijingChina
  2. 2.Athabasca River Basin Research Institute (ARBRI)Athabasca UniversityEdmontonCanada

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