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Multi-scale modeling and big-data analysis opportunities in vadose zone hydrology

Explore the opportunities of multi-scale modeling and big data analysis in vadose zone hydrology. Understand the controls of soil moisture variability and the influence of factors such as soil texture, vegetation, topography, and atmospheric forcings. Use topography-based upscaling and data assimilation techniques for improved predictions. Collaborate with the NTI Center for Excellence in Internet of Things for comprehensive data repository and modeling advancements.

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Multi-scale modeling and big-data analysis opportunities in vadose zone hydrology

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  1. Multi-scale modeling and big-data analysis opportunities in vadose zone hydrology Raghavendra B JanaIvan V Oseledets

  2. The Hydrologic Cycle Precipitation Interception Runoff Infiltration Soil Storage Groundwater Recharge Transpiration Evaporation (Canopy) Evaporation (Ground) Root Water Uptake Capillary Action Groundwater

  3. Dominant controls of SM variability Continent Region Watershed Field Met. Forcings . Spatial Scale Land Cover Patterns . Topographic Features Soil Texture and Structure Soil Texture and Structure Point Continent

  4. Challenge • To understand how soil moisture and/or hydraulic parameters are affected at different scales by the spatio-temporal variability of influencing factors • Soil texture & structure • Vegetation • Topography • Atmospheric forcings • …

  5. Topography-based Upscaling • Influence of topography on upscaled soil hydraulic parameters • To provide a mathematical form for the influence of topography on the scaling characteristics of soil hydraulic parameters • Approach • Study behavior of fluxes and soil moisture states under different configurations of an hillslope at successive scales

  6. Topography-based Upscaling

  7. Simulation for Soil Moisture and Fluxes • HYDRUS-3D simulation model • Solves Richards’ equation • Can account for 3D flows • No inverse estimation of soil hydraulic parameters in 3D

  8. Mean Soil Moisture Variation Mean Soil Moisture (v/v)

  9. 60m resolution 240m resolution Topography-based Upscaling 150 days 150 days 225 days 225 days 365 days 365 days

  10. Real-World Validation Selected pixels for analysis Meteorological Stations Stream Gage

  11. Surface Soil Moisture

  12. Correlation: Coarse Scale vs. ESTAR SM 0.82 0.78 0.74 0.55

  13. Sensor Location for Future Networks • Make use of mode decomposition techniques • Dynamic Mode Decomposition • Discrete Empirical Interpolation Method • Based on history data • Provide minimum number of locations and positions to enable populating entire domain with quantity of interest

  14. Mode Decomposition Methods for Sensor Location and SM Prediction

  15. Mode Decomposition Methods for Sensor Location and SM Prediction

  16. Mode Decomposition Methods for Sensor Location and SM Prediction

  17. Mode Decomposition Methods for Sensor Location and SM Prediction 10 Snapshots 20 Snapshots 30 Snapshots 40 Snapshots

  18. Resolving multi-resolution information • Multiscale Data and/or FE Grids • Simultaneous up- or down-scaling • Output at scale of interest • Applicable to diverse quantities

  19. Data Assimilation for Downscaling Convergence towards true state

  20. Opportunities – Data • Comprehensive data repository and visualization platform • Data from proposed sensor network – NTI project • Information extraction • Patterns and extreme events • Detect “hotspots” • Interpolation and spatial refinement • Disease prediction • Data assimilation for improved forecasting • Edge computing

  21. Opportunities – Modeling • Multi-scale, multi-physics modeling of unsaturated flow through porous media • Surface and sub-surface hydrological/water resources modeling • Regional climate simulation for hydrology • Agricultural monitoring, modeling and assessment • Environmental monitoring and analysis • Modeling of groundwater contamination and/or remediation

  22. Can we … … estimate soil hydraulic and transport parameters across the globe with a single technique!? … transfer techniques developed for one hydroclimateto model processes in another?

  23. NTI Center for Excellence in Internet of Things We invite collaborations on multi-scale modeling Contact Ivan Oseledets (i.oseledets@skoltech.ru)

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