Repository logo
 

Evaluating the parameter identifiability and structural validity of a probability-distributed model for soil moisture

dc.contributor.authorTripp, Danielle R., author
dc.contributor.authorNiemann, Jeffrey D., advisor
dc.contributor.authorButters, Greg, committee member
dc.contributor.authorOad, Ramchand, committee member
dc.date.accessioned2022-09-28T21:27:42Z
dc.date.available2022-09-28T21:27:42Z
dc.date.issued2007
dc.descriptionCovers not scanned.
dc.descriptionPrint version deaccessioned 2022.
dc.description.abstractModels that use probability distributions to describe spatial variability within a watershed have been proposed as a parsimonious alternative to fully distributed hydrologic models. This study evaluates the performance of a probability-distributed model that simulates local and spatial average soil moisture in a watershed. The model uses well-known expressions for infiltration, evapotranspiration, and groundwater recharge to describe soil moisture dynamics at the local scale. Then, the spatial mean soil moisture is simulated by integrating the local behavior over a probability distribution that characterizes the spatial variability of soil saturation. Ultimately, the model requires time series for precipitation and potential evapotranspiration and calibration of six parameters to simulate the dynamics of the spatial average soil moisture. The model is applied to the Fort Cobb watershed in Oklahoma using one year of data from September 2005 through August 2006. Model performance is evaluated in three main ways. First, the model's ability to reproduce observed local and spatial average soil moisture through calibration is examined. Second, the identifiability and stability of the parameter values are evaluated to assess parameter uncertainty and errors in the mathematical structure of the model. Third, the identifiability and stability of the sensitivities to changes in annual precipitation and potential evapotranspiration are evaluated to assess the impacts of parameter uncertainty and structural errors on forecasts for unobserved conditions. At the local scale, the calibrated model reproduces the soil moisture with a similar degree of accuracy as a more physically-based model (HYDRUS ID), and both models exhibit some structural errors. For the spatial average soil moisture, the calibration is acceptable simulating soil moisture with a similar degree of accuracy as the model applied at the local scale. Among all the parameters, the standard deviation of soil saturation is the most stable and identifiable. The probability-distributed model produces a relatively wide range of plausible sensitivities for both the local soil moisture and the spatial mean soil moisture, suggesting that parameter uncertainty and model structural errors produce significant uncertainty for unobserved conditions.
dc.format.mediummasters theses
dc.identifier.urihttps://hdl.handle.net/10217/235793
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relationCatalog record number (MMS ID): 991024447849703361
dc.relationS594.T775 2007
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subject.lcshSoil moisture -- Mathematical models
dc.subject.lcshHydrologic models
dc.titleEvaluating the parameter identifiability and structural validity of a probability-distributed model for soil moisture
dc.typeText
dc.typeStillImage
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCivil and Environmental Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
ETDF_2007_Summer_Tripp_Danielle_R_DIP.pdf
Size:
12.23 MB
Format:
Adobe Portable Document Format