International Workshop on Catchment Hydrological Modeling and Data Assimilation (cahmda)
Modeling and observations are two major means to recognize the land surface conditions and data assimilation makes best use of the advantages of the two means through the fusion of modeling and observations. The objective of this workshop is to assess recent advances in modeling, observing, and data assimilation approaches and applications to acquire more accurate and reliable water information. Particular attention will be given to the solutions for the practical problems existing in data assimilation process such as the uncertainties originated from multiple aspects and the adaptation of the mismatch scale, etc. The workshop consists of five sessions and a short description of each session is listed as follows.
1. Data Assimilation in Hydrology and Ecology, especially the remote sensing applications
Plenty hydrological and ecological variables and fluxes play key roles in understanding water, energy, and carbon cycle. This session is a platform for the presentation and discussion of current research focusing on data assimilation techniques of recent satellites and advanced sensors for states and parameters estimation in hydrology, ecology, and carbon cycle. Therefore, contributions that cover aspects on assimilation of remote sensing data with dynamic models are extremely welcome and encouraged.

2. Uncertainties study: Parameters, Model structure and Forcing data
The determination of the uncertainties in parameters, model structure and forcing data are crucial for reliable predictions of states variables in soils, aquifers and across compartments (e.g., stream-aquifer interactions). This session invites contributions that focus on improved parameter estimation and uncertainty quantification techniques in diagnosing, detecting and resolving all sources of errors in state variables forecast, especially studies on: simultaneous estimation of states and parameters, the contribution of different observation types to uncertainty reduction, novel theories and concepts for spatial and temporal analysis of the model (especially the spatial mismatch between model and observation), and forcing data development.

3. Observation and modelling of hydrological processes in the Third Pole
The environment of the Third Pole is complicated, where the western part is typical arid or semi-arid region while the eastern is Asian monsoon zone. The Third Pole is the headwater areas of the major rivers in Asia and possesses a number of glaciers and lakes. It is very important to investigate the exchanges of water and energy fluxes as well as the environment changes in this region. This session invites contributions advancing the understanding of the interactions of different water phases, water bodies, land-atmosphere as well as their changes in the Third Pole Environment. Contributions dealing with the integrated use of satellite observations and ground measurements and modelling of hydro-meteorological processes in the Third Pole (or other high elevation areas) are welcome.

4. Application of assimilated datasets in support of Sustainable Development Goals
The natural resources stored in earth are limited, thus how to rationally and effectively utilize the resources to guarantee the sustainable development of human society becomes important and urgent. Several land surface data assimilation systems have been established to acquire more accurate estimation of the land surface conditions as well as the hydrological assimilation experiments conducted in large scale catchment. Datasets from such research can provide comprehensive and precise cognition of the global / regional environment and effective suggest for the decisions and policies of government. This session invites contributions that commit to offer assimilation-derived datasets which can be and/or have already been used for the analysis, management and decision of natural resource to support the sustainable development goals, especially in terms of the change of the groundwater storage, the demand of the evapotranspiration, the configuration of water resource.

5. Scaling issue in remote sensing data and data assimilation
Scale issues are often encountered in data assimilation especially the application of satellite data which are embodied in the following two aspects. On one hand, the mismatch spatial resolution between the satellite data and the model will have to be solved before or during the process of data assimilation. On the other hand, simple arithmetic-average of the ground station measurements is not suitable for the results validation in a coarser grid because of the representative problem. Methods and applications dealing with such issues are welcomed in this session, in particular, the allocation of the coarser observation information to the finer model resolution (in other words, the aggregation of model states to match the observation resolution) and more complicated upscaling method to obtain footprint-averaged soil moisture as the ground truth.