MULTI-OBJECTIVE PARAMETER OPTIMIZATION AND UNCERTAINTY ASSESSMENT IN A LAND SURFACE MODEL BY MULTIPLE SATELLITES’ OBSERVATIONS

Abstract

 Land surface modeling is important for hydraulic engineering and water resources management. To improve the accuracy of land surface models, it is necessary to optimize their unknown parameters and assess their uncertainties. However, the multi-objective parameter optimization and uncertainty assessment, which realizes to improve all relevant state variables such as soil moisture, vegetation dynamics, and surface temperature, are yet to be developed. We developed the method of multi-objective parameter optimization with uncertainty assessment by multiple satellites’ observations. Soil moisture, LAI, and land surface temperature are chosen as land surface conditions, and optimization was done in order to simultaneously decrease the 3 types of errors between the observation and the corresponding model’s variable. As a result, the RMSE between the observations and the model’s variables are generally decreased. Also, it was revealed that ecologilcal observation has the strongest impact on the improvement of the model’s accuracy.