Uncertainty and equifinality driven by rainfall in the APEX model

Andres F. Prada, Maria Librada Chu, Jorge Alberto Guzman Jaimes, Daniel Moriasi, Kevin W. King, David Bosch, David Bjorneberg, Stephen Teet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Uncertainty is an inherent part of complex environmental models. Uncertainty in model inputs, model parameterization, and model structure can propagate non-linearly to the model outputs. Evaluating, quantifying, and reporting uncertainty is crucial when model results are used as basis for managerial decisions and policies. Results should be presented with the full disclosure of the risks associated with uncertainty of the outputs. In this study, we evaluated the uncertainty and equifinality of the Agricultural Policy/Environmental extender (APEX) model for a sub-watershed in the Upper Big Walnut Creek in Ohio. Three APEX models were developed using three different rainfall datasets: (I) estimated from 38 NOAA stations surrounding the watershed; (2) measured in the watershed; and (3) generated from PRISM models. A two-step probabilistic approach to calibrate the model was implemented using global uncertainty and sensitivity analysis. A preliminary analysis was conducted using 22 uncertain global parameters. Each parameter was assigned a uniform distribution with ranges derived from measurements, literature, and model range validity. Sampling of the probability distribution functions was performed using the Sobol method. Acceptable models were evaluated using the Nash-Sutcliffe Efficiency Coefficient. Preliminary results indicated that rainfall datasets rather than parameter ranges were driving model uncertainty and equifinality. Model results using the NOAA dataset have the highest model efficiency but also the highest uncertainty and equifinality. Quantifying uncertainty and equifinality can improve model result understanding, increase model robustness, and help practitioners identify the validity of model outcome ranges.

Original languageEnglish (US)
Title of host publicationAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2015
PublisherAmerican Society of Agricultural and Biological Engineers
Pages2384-2393
Number of pages10
ISBN (Electronic)9781510810501
StatePublished - Jan 1 2015
EventAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2015 - New Orleans, United States
Duration: Jul 26 2015Jul 29 2015

Publication series

NameAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2015
Volume3

Other

OtherAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2015
CountryUnited States
CityNew Orleans
Period7/26/157/29/15

Fingerprint

agricultural policy
Rain
uncertainty
rain
Watersheds
model uncertainty
Uncertainty
environmental models
walnuts
probability distribution
Uncertainty analysis
Model structures
Parameterization

Keywords

  • APEX model
  • Equifinality
  • Nash-Sutcliffe Efficiency Coefficient
  • Sensitivity analysis
  • Uncertainty

ASJC Scopus subject areas

  • Bioengineering
  • Agronomy and Crop Science

Cite this

Prada, A. F., Chu, M. L., Guzman Jaimes, J. A., Moriasi, D., King, K. W., Bosch, D., ... Teet, S. (2015). Uncertainty and equifinality driven by rainfall in the APEX model. In American Society of Agricultural and Biological Engineers Annual International Meeting 2015 (pp. 2384-2393). (American Society of Agricultural and Biological Engineers Annual International Meeting 2015; Vol. 3). American Society of Agricultural and Biological Engineers.

Uncertainty and equifinality driven by rainfall in the APEX model. / Prada, Andres F.; Chu, Maria Librada; Guzman Jaimes, Jorge Alberto; Moriasi, Daniel; King, Kevin W.; Bosch, David; Bjorneberg, David; Teet, Stephen.

American Society of Agricultural and Biological Engineers Annual International Meeting 2015. American Society of Agricultural and Biological Engineers, 2015. p. 2384-2393 (American Society of Agricultural and Biological Engineers Annual International Meeting 2015; Vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Prada, AF, Chu, ML, Guzman Jaimes, JA, Moriasi, D, King, KW, Bosch, D, Bjorneberg, D & Teet, S 2015, Uncertainty and equifinality driven by rainfall in the APEX model. in American Society of Agricultural and Biological Engineers Annual International Meeting 2015. American Society of Agricultural and Biological Engineers Annual International Meeting 2015, vol. 3, American Society of Agricultural and Biological Engineers, pp. 2384-2393, American Society of Agricultural and Biological Engineers Annual International Meeting 2015, New Orleans, United States, 7/26/15.
Prada AF, Chu ML, Guzman Jaimes JA, Moriasi D, King KW, Bosch D et al. Uncertainty and equifinality driven by rainfall in the APEX model. In American Society of Agricultural and Biological Engineers Annual International Meeting 2015. American Society of Agricultural and Biological Engineers. 2015. p. 2384-2393. (American Society of Agricultural and Biological Engineers Annual International Meeting 2015).
Prada, Andres F. ; Chu, Maria Librada ; Guzman Jaimes, Jorge Alberto ; Moriasi, Daniel ; King, Kevin W. ; Bosch, David ; Bjorneberg, David ; Teet, Stephen. / Uncertainty and equifinality driven by rainfall in the APEX model. American Society of Agricultural and Biological Engineers Annual International Meeting 2015. American Society of Agricultural and Biological Engineers, 2015. pp. 2384-2393 (American Society of Agricultural and Biological Engineers Annual International Meeting 2015).
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