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Identification of hydrological model parameter variation using ensemble Kalman filter
2016
Hydrology and Earth System Sciences
<p><strong>Abstract.</strong> Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff
doi:10.5194/hess-20-4949-2016
fatcat:iid3n2voxjgfdecu4zm22lt34e