×K10. Land surface observation and assimilation: data-model integration approach for improved hydrologic prediction and water resources management

Recent advances in sensing technologies from multiple platforms and physically distributed hydrologic models significantly improve our ability to observe and model complex hydrologic systems and land surface processes across scales. This session invites contributions demonstrating

  1. the uses and applications of innovative observations and integration of observations from various sources (e.g., hard and soft data on land surface processes and hydrologic systems) to gain better insights into complex water systems
  2. the modelling strategies (e.g., data assimilation, data fusion, parameter optimisation) to incorporate new types of observations into physical models for improved prediction and uncertainty assessment across scales.

Key topics: Land surface observation, Data assimilation, Data fusion, Prediction uncertainty