Item talk:Q299360
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "Conference Paper", "name": "Evaluating the effect of Tikhonov regularization schemes on predictions in a variable-density groundwater model", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70156775", "url": "https://pubs.usgs.gov/publication/70156775" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70156775 } ], "inLanguage": "en", "datePublished": "2010", "dateModified": "2021-10-28", "abstract": "Calibration of highly\u2010parameterized numerical models typically requires explicit Tikhonovtype regularization to stabilize the inversion process. This regularization can take the form of a preferred parameter values scheme or preferred relations between parameters, such as the preferred equality scheme. The resulting parameter distributions calibrate the model to a user\u2010defined acceptable level of model\u2010to\u2010measurement misfit, and also minimize regularization penalties on the total objective function. To evaluate the potential impact of these two regularization schemes on model predictive ability, a dataset generated from a synthetic model was used to calibrate a highly-parameterized variable\u2010density SEAWAT model. The key prediction is the length of time a synthetic pumping well will produce potable water. A bi\u2010objective Pareto analysis was used to explicitly characterize the relation between two competing objective function components: measurement error and regularization error. Results of the Pareto analysis indicate that both types of regularization schemes affect the predictive ability of the calibrated model.", "description": "5 p.", "publisher": { "@type": "Organization", "name": "Wechselnde Verlagsorte" }, "author": [ { "@type": "Person", "name": "Hughes, Joseph D. jdhughes@usgs.gov", "givenName": "Joseph D.", "familyName": "Hughes", "email": "jdhughes@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-1311-2354", "url": "https://orcid.org/0000-0003-1311-2354" }, "affiliation": [ { "@type": "Organization", "name": "WMA - Integrated Modeling and Prediction Division", "url": "https://www.usgs.gov/mission-areas/water-resources" } ] }, { "@type": "Person", "name": "Langevin, Christian D. langevin@usgs.gov", "givenName": "Christian D.", "familyName": "Langevin", "email": "langevin@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0001-5610-9759", "url": "https://orcid.org/0000-0001-5610-9759" }, "affiliation": [ { "@type": "Organization", "name": "WMA - Integrated Modeling and Prediction Division", "url": "https://www.usgs.gov/mission-areas/water-resources" } ] }, { "@type": "Person", "name": "White, Jeremy T. jwhite@usgs.gov", "givenName": "Jeremy T.", "familyName": "White", "email": "jwhite@usgs.gov", "affiliation": [ { "@type": "Organization", "name": "FLWSC-Tampa", "url": "https://www.usgs.gov/centers/car-fl-water" } ] } ], "funder": [ { "@type": "Organization", "name": "Florida Water Science Center-Ft. Lauderdale", "url": "https://www.usgs.gov/centers/car-fl-water" } ] }
}