HR: 10:50h
AN: H11I-03    [PDF]
TI: Identification of Spatially Distributed Soil Hydraulic Properties in Hydrologic Modeling Using Global Optimization
AU: Vrugt, J A
EM: jvrugt@science.uva.nl
AF: Universiteit van Amsterdam, Institute for Biodiversity and Ecosystem Dynamics, Faculty of Science, Nieuwe Achtergracht 166, Amsterdam, 1018 WV Netherlands
AU: Schoups, G
EM: ghschoups@ucdavis.edu
AF: Hydrology Program, Department of Land, Air and Water Resources, One Shields Avenue, Davis, CA 95616
AU: * Hopmans, J W
EM: jwhopmans@ucdavis.edu
AF: Hydrology Program, Department of Land, Air and Water Resources, One Shields Avenue, Davis, CA 95616
AU: Young, C A
EM: cayoung@ucdavis.edu
AF: Hydrology Program, Department of Land, Air and Water Resources, One Shields Avenue, Davis, CA 95616
AU: Wallender, W W
EM: wwwallender@ucdavis.edu
AF: Universiteit van Amsterdam, Institute for Biodiversity and Ecosystem Dynamics, Faculty of Science, Nieuwe Achtergracht 166, Amsterdam, 1018 WV Netherlands
AU: Harter, T H
EM: thharter@ucdavis.edu
AF: Hydrology Program, Department of Land, Air and Water Resources, One Shields Avenue, Davis, CA 95616
AU: Bouten, W
EM: W.Bouten@science.uva.nl
AF: Universiteit van Amsterdam, Institute for Biodiversity and Ecosystem Dynamics, Faculty of Science, Nieuwe Achtergracht 166, Amsterdam, 1018 WV Netherlands
AB: In the past few years, computational capabilities have evolved to a point, where it is possible to use multi-dimensional physically based hydrologic models to study spatial and temporal patterns of water flow in the vadose zone. However, so far these models based on complex multi-dimensional governing equations have only received very limited attention, in particular because of their computational, distributed input and parameter estimation requirements. The aim of the present paper is to explore the usefulness and applicability of the inverse method to estimate spatially distributed soil hydraulic properties using the solution of a physically-based three-dimensional distributed model combined with spatially distributed measured tile drainage data from the 4000 ha BWD (BWD) in the San Joaquin Valley of California. The inverse problem is posed within a single criterion Bayesian framework and solved by means of the computerized Shuffled Complex Evolution Metropolis (SCEM-UA) global optimization algorithm. To study the benefits of using a complex spatially distributed three-dimensional vadose zone model, the results of the 3D model were compared with those obtained using a simple conceptual bucket model and a spatially-averaged one-dimensional unsaturated water flow model. District-wide results demonstrate that measured spatially distributed patterns of drainage data contain only limited information towards the identification of the vadose zone model parameters, and are particularly inadequate to identify the soil hydraulic properties. In contrast, the drain conductance, and a bypass coefficient were highly identifiable, indicating that the dominant hydrology of the BWD was determined by drain system properties and preferential flow. Despite the significant CPU time needed for model calibration, results indicate that there are advantages of using physically-based hydrologic models to study spatial and temporal patterns of water flow at the scale of a watershed, as these models not only generate consistent forecasts of spatially-distributed drainage data during the calibration and validation period, but also possess unbiased predictive capabilities of measured groundwater table depths not included in the calibration.
DE: 1836 Hydrologic budget (1655)
DE: 1842 Irrigation
DE: 1875 Unsaturated zone
SC: Hydrology [H]
MN: 2003 Fall Meeting