Zhu G.F.*, Li X., Su Y.H., Zhang K., Bai Y., Ma J.Z., Li C.B., Hu X. L., He J.H. Simultaneous parameterization of the two-source evapotranspiration model by Bayesian approach: application to spring maize in an arid region of northwest China. Geoscientific Model Development, 7, 741-775, 2014
The uncertainty in quantitatively estimating the model parameters plays a key role in improving the simulation accuracy of the model and identifying the structure of the model. The algorithm estimates the parameters of the eco-hydrological model based on the fusion of multi-source data of Bayesian method, which can effectively overcome the problem of "parameter equifinality" of the eco-hydrologic model. It provides a research framework for reducing the uncertainty of model parameters and identifying the error structural of the model.
Installation: no installation required;
Contact SupportNorthwest Institute of Eco-Environment and Resources, CAS 0931-4967287 firstname.lastname@example.org
LinksNational Tibetan Plateau Data Center