1. Research of hybrid remote sensing retrieve model based on maximum entropy production and penman theory

This project studies on the construction of a mixed model for remote sensing retrieve of evapotranspiration by combining with the latest development of the evapotranspiration in physical theory and based on the three sources P-LSH model and MEP (maximum entropy production) model which are the preliminary research of the project group. Through field experiment, we study the control mechanism of soil moisture content in water vapor conductivity of soil and canopy, and construct a general stress formula. By integrating the evapotranspiration theories based on the “microprocess” (Penman-Monteith formula) and the “macro state” (maximum entropy production), we build a hybrid model framework. We further study on the generalization, optimization and uncertainty of the model parameters. Through this research, we hope to make innovations in the physical mechanism of evapotranspiration, remote sensing retrieve technique, the construction of remote sensing cooperative retrieve algorithm etc..

2. New method of multi-source hydrological data fusion and assimilation

This project studies the new technology of satellite and land multi-source hydrological multi elements. Combined with the big data technology and analysis of experimental observation mechanism, we develop the fusion and assimilation algorithm of precipitation, evapotranspiration and soil moisture based on the big data to reveal the distribution rules of hydrological elements. Besides, we focus on the research of real-time Bayesian fusion algorithm for observation precipitation from rainfall stations and satellite to construct multi scale rainfall field. We also establish a soil water state equation vertical stratification in spatial grid and study the assimilation and extrapolation methods of soil moisture content. Furthermore, a new fusion method of multi-source hydrological multi elements is studied to improve the precision accuracy of input and state variables of hydrological model.

3. Study on remote sensing retrieve of soil moisture in multi satellite platform

The purpose of this study is to establish a microwave remote sensing retrieve model for surface soil moisture based on physical mechanism. Soil moisture is retrieved from the measured brightness temperature data of the open and quasi real time microwave remote sensing at home and abroad. At the same time, a calculation model of soil moisture based on physical mechanism and process is constructed. It takes the multi-source precipitation fusion product as the main input to expand the soil moisture content calculation with high spatial resolution. The data assimilation technology is used to assimilate the soil moisture content retrieved by remote sensing, and a land surface soil moisture product with high temporal and spatial resolution which is consistent and continuous coverage of the country is formed.

4. Remote sensing retrieve of global terrestrial evapotranspiration

The purpose of this study is to develop a method of remote sensing retrieve of surface evapotranspiration based on visible light and near infrared technology; carry out the study of the parameterization scheme for the stomatal conductance of vegetation; establish a remote sensing retrieve model of diurnal evapotranspiration based on process to improve the retrieve accuracy of the actual evapotranspiration; Using satellite long time series products and related meteorological data to retrieve the actual evapotranspiration and energy flux of the global land surface; On this basis, the temporal and spatial variation of real evapotranspiration in the world is studied.

5. Study and modeling of the coupled ecohydrological processes influenced by fine-scale landscape heterogeneity in a typical humid hilly region of China

The study aims to provide new insight and knowledge on ecohydrological mechanisms, landscape simplification and development of ecohydrological model. This research project will first conduct comprehensive field observations in a typical humid hilly region. Second, a synergistic remote sensing retrieval algorithm will be developed to retrieve the vegetation composition and structure using multi-platform, multi-source remote sensing imageries and help understand the spatial heterogeneity of vegetation. Finally, the regulation of fine-scale landscape heterogeneity on the ecohydrological process in the study region will be studied.

6.Evolution and responses of runoff yield and confluence under different land surface conditions and in different hydrometeorological zones

The project focuses on the innovation and perfection of the runoff generation and convergence mechanism and the theory of spatial hydrological similarity to improve the accuracy of flood forecasting in small and medium watersheds. Through prototype experiments, field observations, multi-source remote sensing and big data analysis technologies, it aims to reveal the spatiotemporal dynamic changes and the combination laws of runoff generation modes. The work also includes exploring the impact of reservoirs, over-exploitation of groundwater, and karst geological conditions on the process of runoff generation and convergence, study on the similarity of which and establishing a non-linear measurement method of hydrological spatial similarity is one of the most important parts as well..