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




Tripp, Danielle R., author
Niemann, Jeffrey D., advisor
Butters, Greg, committee member
Oad, Ramchand, committee member

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Models 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.


2007 Summer.
Covers not scanned.
Includes bibliographical references.
Print version deaccessioned 2022.

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Soil moisture -- Mathematical models
Hydrologic models


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