HR: 0800h
AN: H11F-0344    [Abstracts]
TI: Recession Flow Analysis for Selection of a Basin Drainage Model and Estimation of Basin-Wide Hydraulic Parameters
AU: * Rupp, D E
EM: ruppd@engr.orst.edu
AF: Oregon State University Department of Bioengineering, 116 Gilmore Hall, Corvallis, OR 97331 United States
AU: Uribe, H
EM: huribe@quilamupa.inia.cl
AF: Instituto de Investigaciones Agropecuarias, CRI Quilamapu, Chill n, none Chile
AU: Lagos, O
EM: olagos@quilamupa.inia.cl
AF: Instituto de Investigaciones Agropecuarias, CRI Quilamapu, Chill n, none Chile
AU: Selker, J S
EM: selkerj@engr.orst.edu
AF: Oregon State University Department of Bioengineering, 116 Gilmore Hall, Corvallis, OR 97331 United States
AB: To guide us toward a correct description of the drainage processes in the coastal range of central Chile, we evaluated several analytical models for post-rainfall aquifer drainage: the Boussinesq model, various TOPMODEL expressions, and non-linear reservoirs. Based on discharge recession curves from one large basin and three sub-basins with areas on the order of 0.1, 1, 10 and 1000 km2, we argue for the Boussinesq model and against the TOPMODEL expressions and non-linear reservoirs, principally because all but the Boussinesq model would necessitate making non-physical assumptions to explain a significant portion of the recession curve. Although the Boussinesq model allows for estimation of hydraulic properties at the scale of the basins, uncertainty in the model parameters, including aquifer width, length of the drainage network, initial water table height, and drainable porosity, complicate the analysis. This uncertainty notwithstanding, reasonable values of the spatial parameters for the three smaller basins can result in values of saturated hydraulic conductivity (Ks) that are consistent with estimates from recovery tests of nearly 100 wells. However, the largest basin has a Ks about one order of magnitude greater using the same, albeit scaled, spatial parameterization. Though it would be easy to attribute this higher Ks to some sort of scaling phenomenon, there can be other interpretations. For example, we show how the same recession features at the largest scale can be recreated by assuming that the river network lies within a wide, highly-permeable fluvial deposition surrounded by material that is much less permeable.
DE: 1829 Groundwater hydrology
DE: 1860 Runoff and streamflow
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting