Developing efficient multi-sensor Data Assimilation frameworks for integrating Earth ObservatioN Satellite data into Land Surface Models (DANSk-LSM)

Project Details


The main goal of DANSk-LSM is to develop and demonstrate accurate and efficient, physically and mathematically consistent Data Assimilation (DA) systems that robustly integrate synergistically and complementary available satellite data with the state-of-the-art of hydrological models. Thus, we will build the capacity for cutting-edge next generation high-resolution global hydrological early warning systems that are open-access. DANSk-LSM uniquely integrates multi-sensor geodetic and remotely sensed Earth Observation (EO) data, implements innovative DA and calibration frameworks, and has unprecedented high spatial-temporal resolution.
Effective start/end date01/09/202231/08/2026

Collaborative partners

  • Technical University of Denmark
  • DHI Water - Environment - Health
  • Ohio State University
  • UCL University College Lillebaelt
  • German Aerospace Center
  • University of California at Berkeley

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 1 - No Poverty
  • SDG 2 - Zero Hunger
  • SDG 6 - Clean Water and Sanitation
  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action


  • Large Scale
  • Hydrology
  • Data Assimilation
  • Early warning
  • Hazards
  • Forecasting
  • Geodesy
  • Earth Observation
  • Altimetry
  • Soil Moisture
  • Groundwater


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