Bayesian hierarchical modelling: Incorporating spatial information in water resources assessment and accounting
Water resources assessment and accounting research requires making the best use of multiple sources of data for producing reliable accounting predictions. For any given quantity of interest, e.g. soil moisture, available sources of data could be directly observed in situ, derived indirectly from a remotely-sensed surrogate (e.g. brightness temperature) using retrieval models, or output from deterministic hydrological models. Whether it be model-data fusion or the evaluation of remotely-sensed...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of MODSIM 2011 International Congress on Modelling and Simulation|
|Access Rights:||Open Access|
|01_Chiu_Bayesian_hierarchical_2011.pdf||1.31 MB||Adobe PDF|
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