Syme, G., Hatton MacDonald, D., Fulton, B. And Piantadosi, J. (Eds) MODSIM2017, 22nd International Congress on Modelling and Si 2017
DOI: 10.36334/modsim.2017.h5.pham
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Assimilating stream flow, evapotranspiration and soil moisture data in AWRA-L model with particle filter

Abstract: The Australian Water Resource Assessment-Landscape model (AWRA-L) is calibrated against a selection of data from ~500 gauged catchments around Australia to identify a single optimised set of model parameter with an emphasis on improving streamflow prediction. However, this regional approach to AWRA-L calibration can lead to high uncertainty in estimation, especially in ungauged catchments. An approach to help improve prediction in ungauged area is the assimilation of remotely sensed data into hydrological mode… Show more

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