The hydrological cycle is the connection of the earth circle-biocycle-atmosphere system, and therefore responsible for the formation and evolution pattern of water resources. Understanding the hydrological cycle and its variability due to meteorological conditions, underlying surface environment and anthropogenic factors is of critical importance, as the availability of water is one of the most limiting parameters for life, agriculture and economic development.
It is very important for the scientists to improve scientific knowledge and use an integrated approach for a better understanding of the complex hydrological cycle for sustainability of water resources from local to global scale. The catchment hydrological model is an important tool to study the basin-scaled hydrological cycle, and at the same time remote sensing data provides important spatiotemporal distribution of various inputs, boundary conditions and parameters for the catchment hydrological model. However, the accuracy of catchment hydrological modeling, the further application of remote sensing in hydrological model and further development of hydrological model are limited due to measurement uncertainties, deficiencies in models of the physical system, forcing data, less scientific understanding of the modeled errors and scale mismatch problems in the hydrological modeling.
Data assimilation makes best use of the advantages of the model and observation through the fusion and integration of these two means, with its core on producing as accurate as possible, a description of the hydrological state by the fusion of observations distributed discretely in time and space of diļ¬€erent types, accuracies and resolutions in the dynamic framework of land surface process or distributed hydrological model.
The international workshop on catchment hydrological modeling and data assimilation (CAHMDA) had organized six times respectively in 2001 and 2012 in Netherlands, 2008 in Australia, 2010 in China, 2004 and 2014 in USA, which facilitates the research intercourse for scientists come from different countries. This conference will provoke a further discussion about data assimilation methods and applications in Remote sensing-hydrology-climatology research, including observation design, the performance assessment of observation instruments, the use of new instruments, etc. This will prompt the researchers to understand about the latest development, application of new techniques and our scientific research level in catchment hydrological modeling and data assimilation.


Specific objectives include:
- To improve understanding of the operational hydrological forecasting and water resources management
- To raise awareness of recent advances focusing on data assimilation techniques of recent satellites and advanced sensors for states and parameters estimation in hydrology, ecology, and carbon cycle
- To promote assessing problems existing in data assimilation process such as the uncertainties originated from multiple aspects and the adaptation of the mismatch scale, etc.
- To improve understanding of the interactions of different water phases, water bodies, land-atmosphere as well as their changes in the Third Pole Environment
- To share assimilation-derived datasets for the analysis, management and decision of natural resource to support the sustainable development goals
- To exchange experience on integrated multi-source remote sensing to forward model, data assimilation technique and local measurement by up-scaling methods.

Main Topics

- Data Assimilation in Hydrology and Ecology, especially the remote sensing applications
- Uncertainties study: Parameters, Model structure and Forcing data
- Observation and modelling of hydrological processes in the Third Pole
- Application of remote sensing or the assimilated datasets in support of Sustainable Development Goals
- Scaling issue in remote sensing data and data assimilation
Scientists, managers, students as well as representatives of governments, media and funding organizations, who have studied or are interested in hydrology, meteorology, ecology and remote sensing technologies are invited to the conference to share research results and to discuss recent advances in modeling, observing, and data assimilation approaches and applications to acquire more accurate and reliable water information. The official language of the symposium will be English.