HR: 1330h
AN: H12B-0994    [PDF]
TI: Incorporating Field Intelligence Into Conceptual Rainfall-runoff Models
AU: * Vache, K
EM: kellie.vache@oregonstate.edu
AF: Forest Engineering Oregon State University, Peavy Hall, Corvallis, OR 97333 United States
AU: McDonnell, J
EM: jeff.mcdonnell@orst.edu
AF: Forest Engineering Oregon State University, Peavy Hall, Corvallis, OR 97333 United States
AU: McGuire, K
EM: kevin.mcguire@orst.edu
AF: Forest Engineering Oregon State University, Peavy Hall, Corvallis, OR 97333 United States
AB: A major challenge in the hydrological sciences is to incorporate observed physical processes into general hydrological models with minimal data requirements and limited model complexity. One approach is to move away from discharge-based calibration schemes, which often assume model structures to be correct, and allow field observations to inform and test new model structures. The use of this knowledge will contribute to (1) the development of an expanded set of variables to verify hydrological model performance and reflect the overall watershed function and (2) provide useful information regarding the development of model structures and landscape discretizations. We identify a set of three variables that focus on the composition of stream water, using artificial hydrograph separations to provide estimates of the time source (e.g., event vs. pre-event) and the geographic source (e.g., hillslope vs. riparian) of streamflow, and explicitly accounting for mass transfer to provide estimates of residence time. In addition to these variables, we present a set of methods and data designed to incorporate experimental understanding directly into the model structure and catchment discretization. These ideas are illustrated through application at the H.J. Andrews Experimental Forest's Lookout Creek watershed in the western Cascades of Oregon.
DE: 1800 HYDROLOGY
DE: 1860 Runoff and streamflow
SC: Hydrology [H]
MN: 2003 Fall Meeting