H44E:
Monitoring and Modeling Spatial Patterns in Hydrology: Integrating Distributed Earth Observations for the Seamless Calibration and Evaluation of Hydrological and Land Surface Models I


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Session ID#: 62061

Session Description:
Currently, hydrological model evaluations remain focused on comparing simulations to time series representing either point scale or a spatially aggregated catchment scale observation in the form of streamflow. A paradigm shift is required for moving away from the aggregated evaluation of hydrological and land surface models towards a spatially distributed approach. Recent advances in fully distributed and grid based model codes, computational power and spatial data availability have prepared the ground for bringing the science forward. However, most model calibration and evaluation techniques lack methodologies for incorporating spatial pattern information.

Targeted areas:

  • Development of remote sensing based data sets to confront simulated spatial patterns.
  • Development of performance metrics specifically suited for evaluating spatial model performance.
  • Identification and quantification of driving forces that generate spatial patterns of hydrological states and fluxes.
  • Model parameter regionalization and regularization approaches.
  • Calibration frameworks focusing on spatial model performance from regional to global scales.
Primary Convener:  Simon Stisen, Geological Survey of Denmark and Greenland, København K, Denmark
Convener:  Luis Samaniego, Helmholtz Centre for Environmental Research GmbH – UFZ, Computational Hydrosystems, Leipzig, Germany
Primary Liaison:  Simon Stisen, Geological Survey of Denmark and Greenland, København K, Denmark
Chairs:  Simon Stisen, Geological Survey of Denmark and Greenland, København K, Denmark and Luis Samaniego, Helmholtz Centre for Environmental Research GmbH – UFZ, Computational Hydrosystems, Leipzig, Germany
OSPA Liaison:  Simon Stisen, Geological Survey of Denmark and Greenland, København K, Denmark
Index Terms:

1804 Catchment [HYDROLOGY]
1843 Land/atmosphere interactions [HYDROLOGY]
1846 Model calibration [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]

Abstracts Submitted to this Session:

How Can GRACE and GRACE-FO Global Hydrology Inform Land Surface Model Development and Evaluation? (Invited) (343641)
James S Famiglietti, University of Saskatchewan, School of Environment and Sustainability, Saskatoon, Canada, Matthew Rodell, NASA GSFC HSL, Greenbelt, United States, John T Reager II, NASA Jet Propulsion Laboratory, Pasadena, CA, United States, Cedric H David, NASA Jet Propulsion Laboratory, Pasadena, United States, Dimitrios Stampoulis, Arizona State University, Future H2O, Knowledge Enterprise Development, Tempe, AZ, United States, Min-Hui Lo, National Taiwan University, Department of Atmospheric Sciences, Taipei, Taiwan, Yoshihide Wada, International Institute for Applied Systems Analysis, Laxenburg, Austria, Hiroko K Kato-Beaudoing, SAIC, Greenbelt, MD, United States, David N Wiese, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States and Felix W Landerer, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
Distributed hydrologic modelling of the Rhine river: towards high resolution calibration-free hydrological models with seamless large-domain parameter estimates (348647)
Albrecht Weerts, Deltares, Operational Water Management & Early Warning, Delft, Netherlands, Ruben Olaf Imhoff, Wageningen University and Research, Hydrology and Quantitative Water Management Group, Wageningen, Netherlands, Bart van Osnabrugge, Deltares, Delft, Netherlands and Willem van Verseveld, Deltares, Inland Water Systems, Delft, Netherlands
In quest of calibration density and consistency in hydrologic modeling: distributed parameter calibration against streamflow characteristics (356575)
Yuan Yang1,2, Ming Pan3, Hylke Beck4, Colby K Fisher5, Edward Beighley6, Shih-Chieh Kao7, Yang Hong8 and Eric F Wood4, (1)University of California San Diego, Scripps Institution of Oceanography, Center for Western Weather and Water Extremes, La Jolla, CA, United States, (2)Princeton University, Civil and Environmental Engineering, Princeton, United States, (3)Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, University of California San Diego, La Jolla, United States, (4)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (5)Princeton Climate Analytics, Princeton, United States, (6)Northeastern University, Civil and Environmental Engineering, Boston, United States, (7)Oak Ridge National Laboratory, Environmental Science Division, Oak Ridge, TN, United States, (8)Tsinghua University, Department of Hydraulic Engineering, Beijing, China
Improvement of Hyperresolution Hydrologic Simulations through Spatial Pattern Validation (375965)
Ara Ko1, Giuseppe Mascaro2 and Enrique R Vivoni2, (1)Arizona State University, Tempe, AZ, United States, (2)Arizona State University, School of Sustainable Engineering and the Built Environment, Tempe, AZ, United States
Using satellite soil moisture data for spatio-temporal calibration of a distributed eco-hydrological model (429728)
Felix Frances, Polytechnic University of Valencia, Research Institute of Water and Environmental Engineering, Valencia, Spain, Carlos Echeverria, Polytechnic University of Valencia, Valencia, Spain and Guiomar Ruiz-Perez, SLU Swedish University of Agricultural Sciences Uppsala, Uppsala, Sweden
Hydrologic Classification as a New Approach to Parameter Regionalization for the National Water Model (356699)
Yuqiong Liu1, Aubrey L Dugger2, Arezoo Rafieeinasab3, Xia Feng4,5, Wanru Wu1, Brian A. Cosgrove6, Tomislava Vukicevic7, Logan Ray Karsten8,9 and David Gochis9, (1)NOAA/NWS/OWP, Silver Spring, United States, (2)National Center for Atmospheric Research, Boulder, United States, (3)NSF National Center for Atmospheric Research, Research Applications Laboratory, Boulder, United States, (4)NOAA/NWS/NWC, Tuscaloosa, AL, United States, (5)University Corporation for Atmospheric Research, Boulder, CO, United States, (6)NOAA/NWS Office of Water Prediction, Silver Spring, United States, (7)NOAA/NWS/OWP, Tuscaloosa, AL, United States, (8)Durham, United Kingdom, (9)National Center for Atmospheric Research, Boulder, CO, United States
On Radiative Transfer Model and its Relationship with Thermal Fluxes Across Space, Time, and Hydroclimates (454885)
Binayak Mohanty, Texas A&M University, Department of Biological and Agricultural Engineering, College Station, United States and Maheshwari Neelam, Texas A&M University, College Station, TX, United States

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