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United States Department of Agriculture

Agricultural Research Service

Title: The Tarrawarra Project: High Resolution Spatial Measurement, Modelling and Analysis of Soil Moisture and Hydrological Response.

Authors
item Western, Andrew - UNIVERSITY OF MELBOURNE
item Green, Timothy
item Grayson, Rodger - UNIVERSITY OF MELBOURNE

Submitted to: Hydrological Processes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 11, 1998
Publication Date: N/A

Interpretive Summary: Detailed spatial patterns of soil moisture were measured for 13 dates at the 10-5 ha Tarrawarra catchment in southern Victoria, Australia. Several analyses of the data are summarized. These include: hydrological behaviour, including preferred states, spatial organization and the performance of terrain indices; geostatistical properties of the soil moisture patterns; and remote sensing of the soil moisture patterns. In the second part of th paper, the patterns along with surface runoff and meteorological data are used in applications of the Thales and VIC models at Tarrawarra. Thales is a process-based distributed parameter hydrological model which explicitly simulates the spatio-temporal patterns of soil moisture, while VIC uses a lumped statistical distribution approach to model the spatial variability of soil moisture storage. Both models simulate saturation excess runoff and are forced by rainfall and potential evapotranspiration. VIC was calibrated dto observed runoff at the catchment outlet. Limited manual calibration of Thales to runoff and the soil moisture patterns was performed. Internal testing was achieved by comparison of predicted and observed spatial soil moisture patterns for the Thales model and of predicted and observed cumulative distributions of active soil moisture storage for the VIC model. With limited calibration effort, Thales was able to simulate the seasonal changes in characteristics of the spatial soil moisture patterns. Detailed examination of the errors in the simulated patterns allowed identification of structural problems in the model, including problems with simulating lateral redistribution as the catchment wets in autumn. For the VIC model, time=series of spatially averaged internal state variables (total storage) were consistent with observations. However, the statistical distribution

Technical Abstract: Detailed spatial patterns of soil moisture were measured for 13 dates at the 10-5 ha Tarrawarra catchment in southern Victoria, Australia. Several analyses of the data are summarized. These include: hydrological behaviour, including preferred states, spatial organization and the performance of terrain indices; geostatistical properties of the soil moisture patterns; and remote sensing of the soil moisture patterns. In the second part of th paper, the patterns along with surface runoff and meteorological data are used in applications of the Thales and VIC models at Tarrawarra. Thales is a process-based distributed parameter hydrological model which explicitly simulates the spatio-temporal patterns of soil moisture, while VIC uses a lumped statistical distribution approach to model the spatial variability of soil moisture storage. Both models simulate saturation excess runoff and are forced by rainfall and potential evapotranspiration. VIC was calibrated dto observed runoff at the catchment outlet. Limited manual calibration of Thales to runoff and the soil moisture patterns was performed. Internal testing was achieved by comparison of predicted and observed spatial soil moisture patterns for the Thales model and of predicted and observed cumulative distributions of active soil moisture storage for the VIC model. With limited calibration effort, Thales was able to simulate the seasonal changes in characteristics of the spatial soil moisture patterns. Detailed examination of the errors in the simulated patterns allowed identification of structural problems in the model, including problems with simulating lateral redistribution as the catchment wets in autumn. For the VIC model, time=series of spatially averaged internal state variables (total storage) were consistent with observations. However, the statistical distribution

Last Modified: 11/27/2014
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