This directory contains Matlab routines used for experiments in papers:
Ait-El-Fquih, Boujemaa, Mohamad El Gharamti, and Ibrahim Hoteit. "A Bayesian Consistent Dual Ensemble Kalman Filter for State-Parameter Estimation in Subsurface Hydrology." Hydrology and Earth System Sciences, 20, no. 8 (2016): 3289-3307.
Gharamti, M. E., Boujemaa Ait-El-Fquih, and Ibrahim Hoteit. "An iterative ensemble Kalman filter with one-step-ahead smoothing for state-parameters estimation of contaminant transport models." Journal of Hydrology 527 (2015): 442-457.
Gharamti, M. E., A. Kadoura, J. Valstar, S. Sun, and Ibrahim Hoteit. "Constraining a compositional flow model with flow‐chemical data using an ensemble‐based Kalman filter." Water Resources Research 50, no. 3 (2014): 2444-2467.
Contact: gharamti@ucar.edu
The following library is designed, for academic purposes, to perform state-parameters estimation using different ensemble techniques. Four different ensembles schemes are available: The Joint EnKF, the Dual EnKF, the Joint OSA EnKF and the Dual OSA EnKF. The library uses two simple models for testing and these are: the Lorenz 63 and 96.
The main script is called SPEL.m and is based on user defined inputs for various parameters. An example is readily available, within SPEL, if you skip the input step; i.e., press enter for all asked questions.
Further explanations of the inputs, the outputs and the usage of the library can be obtained by typing: help SPEL.m
