HR: 0800h
AN: H11B-1270    [Abstracts]
TI: Calibration of a Monthly Water Table-Runoff Scheme Representing Spatial Aggregation of Major Runoff Processes in Humid Watersheds of Illinois
AU: * Su, H
EM: edward_su@mail.utexas.edu
AF: Department of Geological Sciences, John R. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, 1 University Station #C1100, Austin, TX 78712 United States
AU: Niu, G
EM: niu@speer.geo.utexas.edu
AF: Department of Geological Sciences, John R. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, 1 University Station #C1100, Austin, TX 78712 United States
AU: Yang, Z
EM: liang@mail.utexas.edu
AF: Department of Geological Sciences, John R. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, 1 University Station #C1100, Austin, TX 78712 United States
AB: The interplay between surface hydrological processes and underlying aquifer dynamics is one of the key components for current research on land surface models (LSM). This interaction involves several mutually dependent runoff schemes such as infiltration excess runoff, saturation excess runoff and groundwater runoff. The mathematical description of these schemes in the horizontal direction based on classical point-scale hydrologic theory is computationally expensive for LSMs, since it requires high spatial resolution to facilitate the assumption of homogeneity. A recently developed SIMTOP model improved this deficiency by spatially integrating saturation excess and groundwater runoff processes to LSM compatible grid size, using an exponential relationship between area averaged runoff flux and the water table to accomplish this upscaling algorithm. Because the parameters in this scheme are assumed as function of topographic features in the analyzed region, this scheme also represents the topographic influence on regional hydrologic process. However, calibration work based on real-time measurements for this method is desirable, especially for the purpose of finding out the optimal parameters, which are applied in the upscaling scheme, to each specific LSM grid. This paper performed a monthly data based calibration in six USGS monitoring watersheds of Illinois. These watersheds are all in humid mid-latitude climate, with more than 20 years monthly water table measurements available. The precipitation data are derived from North American Regional Reanalysis (NARR) dataset at the same period. A differential evolution method is employed to optimize the difference between simulated runoff and observed runoff. Calibration results show that the proposed water table-runoff scheme agrees well with the measured data, and the parameters in exponential function are optimized for each watershed within reasonable range. Experiments on the sensitivity of model performance and calibrated parameters to the measurement data length used in optimization algorithm are conducted and the results in most watersheds remain stable, representing that the model structure is robust. Future research would be concentrated on interpretation of relationship between optimized parameters and land surface characteristics of the watersheds, in order to quantify the land surface properties(vegetation,soil,topography) on regional scale runoff within the framework of land surface model.
DE: 1829 Groundwater hydrology
DE: 1833 Hydroclimatology
DE: 1866 Soil moisture
SC: Hydrology [H]
MN: Fall Meeting 2005