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Inverse Modeling with RZWQM2 to Predict Water Quality

Dates

Year
2010

Citation

Nolan, Bernard T., Malone, Robert W., Ma, Liwang, Green, Christopher T., Fienen, Michael N., and Jaynes, Dan B., 2010, Inverse Modeling with RZWQM2 to Predict Water Quality: Methods of Introducing System Models into Agricultural Research, v. advancesinagric, no. methodsofintrod, p. 327-363.

Summary

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST [...]

Contacts

Communities

  • National and Regional Climate Adaptation Science Centers
  • Northeast CASC

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Additional Information

Identifiers

Type Scheme Key
DOI http://sciencebase.gov/vocab/identifierScheme 10.2134/advagricsystmodel2.c12

Citation Extension

journalMethods of Introducing System Models into Agricultural Research
parts
typePages
value327-363
typeVolume
valueadvancesinagric
typeNumber
valuemethodsofintrod
citationTypeJournal Article

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