HYDROLOGICAL DATA ASSIMILATION WITH THE ENSEMBLE KALMAN FILTER: USE OF STREAMFLOW OBSERVATIONS TO UPDATE STATES IN A DISTRIBUTED HYDROLOGICAL MODEL

HR: 10:35h
AN: H42D-02 [Abstracts]
TI: HYDROLOGICAL DATA ASSIMILATION WITH THE ENSEMBLE KALMAN FILTER: USE OF STREAMFLOW OBSERVATIONS TO UPDATE STATES IN A DISTRIBUTED HYDROLOGICAL MODEL
AU: Ibbitt, R P
EM: r.ibbitt@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AU: * Clark, M P
EM: mp.clark@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AU: Woods, R A
EM: r.woods@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AU: Zheng, X
EM: x.zheng@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AU: Slater, A G
EM: aslater@cires.colorado.edu
AF: CIRES, University of Colorado, Boulder, CO 80309, United States
AU: Rupp, D E
EM: d.rupp@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AU: Schmidt, J
EM: j.schmidt@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AU: Uddstrom, M
EM: m.uddstrom@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AB: This paper describes an application of the ensemble Kalman filter (EnKF) in which streamflow observations are used to update states in a distributed hydrological model. We demonstrate that the standard implementation of the EnKF is inappropriate because streamflow is not Normally distributed. Transforming streamflow into log space before computing error covariances improves filter performance. We also demonstrate that model simulations improve when we use a variant of the EnKF that does not require perturbed observations. Our attempt to propagate information to neighbouring basins was unsuccessful, largely due to inadequacies in modeling the spatial variability of hydrological processes. New methods are needed to produce ensemble simulations that both reflect total model error and adequately simulate the spatial variability of hydrological states and fluxes.
DE: 1805 Computational hydrology
DE: 1816 Estimation and forecasting
DE: 1833 Hydroclimatology
DE: 1840 Hydrometeorology
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: 2007 Fall Meeting