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A list of all pages that have property "Describe available calibration data" with value "Module tested here: https://www.geosci-model-dev.net/11/4873/2018/". Since there have been only a few results, also nearby values are displayed.

Showing below up to 26 results starting with #1.

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List of results

  • Model:Kirwan marsh model  + (Biomass productivity and marsh accretion rates from 1984-present, described in Morris et al. (2002).)
  • Model:GNE  + (Calibration data consist of compilations of river N, P, Si and C annual yields by form.)
  • Model:SINUOUS  + (Calibration must be based on external hydraulic and channel morphology data. Optimal parameters can be determined by test simulations.)
  • Model:Cliffs  + (Cliffs is benchmarked as described in: E. Cliffs is benchmarked as described in: E. Tolkova. Land-Water Boundary Treatment for a Tsunami Model With Dimensional Splitting</br>Pure and Applied Geophysics, Vol. 171, Issue 9 (2014), pp. 2289-2314</br></br>Examples of modeling with Cliffs (complete set-ups included) are described in Cliffs User Manual at http://arxiv.org/abs/1410.0753r Manual at http://arxiv.org/abs/1410.0753)
  • Model:Area-Slope Equation Calculator  + (Cohen, S., G. Willgoose, and G. Hancock (2008), A methodology for calculating the spatial distribution of the area-slope equation and the hypsometric integral within a catchment, J. Geophys. Res., 113, F03027, doi:10.1029/2007JF000820.)
  • Model:WEPP  + (Data available from 1986-88 field experimentation (in compendium) using rainfall simulation. Also, validation data sets are available from USLE database.)
  • Model:MARSSIM V4  + (Default parameter and input files will produce steady state landscape with stream power erosion and mass wasting)
  • Model:NearCoM  + (Duck 94 data set and laboratory experiments.)
  • Model:Plume  + (Eel River (California), Knight and Bute Inlet (British Columbia))
  • Model:Physprop  + (EuroSTRATAFORM Po River margin)
  • Model:KnickZone-Picker  + (Example and validation datasets are available on the github page.)
  • Model:TwoPhaseEulerSedFoam  + (Experiment data for steady channel flow caExperiment data for steady channel flow can be found in:</br>Sumer, B. M., Kozakiewicz, A., Fredsoe, J., Deigaard, R., 1996. Velocity and concentration profiles in sheet-flow layer of movable bed. Journal of Hydraulic Engineering, (1996) 549-558.</br></br>Experiment for oscillatory flow can be found in:</br>O'Donoghue, T., Wright, S., 2004. Concentrations in oscillatory sheet flow for well sorted and graded sands. Coastal Engineering 50 (2004) 117-138.ds. Coastal Engineering 50 (2004) 117-138.)
  • Model:FVCOM  + (FVCOM was originally developed for the estFVCOM was originally developed for the estuarine flooding/drying process in estuaries and the tidal-, buoyancy- and wind-driven circulation in the coastal region featured with complex irregular geometry and steep bottom topography. This model has been upgraded to the spherical coordinate system for basin and global applications. A non-hydrostatic version of FVCOM has been coded and is being tested.</br>See also website for model validations.d. See also website for model validations.)
  • Model:GOLEM  + (Few or none, unfortunately)
  • Model:QDSSM  + (Have successfully tested the model on the Colorado river shelf system, and along analogue models.)
  • Model:WACCM-EE  + (Haze microphysics can be checked against Bardeen 2008 for initial accuracy.)
  • Model:ILAMB  + (ILAMB has integrated testing of overall scores on a coarsened subset of observational data which runs via Azure pipelines.)
  • Model:CEM  + (In one application, the rate of change in In one application, the rate of change in the model has been calibrated to a state data set averaging shoreline change over 50 years (from the North Carolina Department of Transportation; see Slott et al., 2007). Numerous other shoreline change data sets are available, based on surveys of various sorts, aerial photography, and recently LIDAR (e.g. Lazarus and Murray, 2007).tly LIDAR (e.g. Lazarus and Murray, 2007).)
  • Model:SEDPAK  + (Included in distribution)
  • Model:EstuarineMorphologyEstimator  + (Included with the ZIP file)
  • Model:GRLP  + (Laboratory experiments; long-term surveyed rivers; long profiles of transport-limited rivers)
  • Model:CSt ASMITA  + (Like most morphodynamical models the user is to supply long-term coastal change data from measured data.)
  • Model:HydroTrend  + (Long term sediment routine: *Syvitksi & Milliman, Journal of Geology, 115, 2007. Short term sediment routine: *Morehead et al., Global and Planetary Change, 39, 2003.)
  • Model:Auto marsh  + (Model description and calibration can be fModel description and calibration can be found in:</br></br>Leonardi, N., and S. Fagherazzi (2014), How waves shape salt marshes, Geology , doi:10.1130/G35751.1.</br></br>Leonardi, N., and S. Fagherazzi (2015), Local variability in erosional resistance affects large scale morphodynamic response of salt marshes to wind waves, Geophysical Research Letters, 2015GL064730, doi:10.1002/2015GL064730.s, 2015GL064730, doi:10.1002/2015GL064730.)
  • Model:ThawLake1D  + (Model is designed and calibrated for Alaska Coastal Plain. We calibrated the model against temperature data in the subsurface from the Drew point, AK, USGS meteorological station.)
  • Model:Frost Model  + (N/A)
  • Model:HexWatershed  + (National Hydrography Dataset (NHD) flowline datasets were used to evaluated the model.)
  • Model:Quad  + (No calibration data sets. We validate the model against available analytical solutions and use it to analyze the system behavior under a general base-level fall and base-level rise. See Lorenzo-Trueba et al. 2012.)
  • Model:GENESIS  + (No specific calibration data sets available. GENESIS has enjoyed many practical applications within the engineering and scientific community, results routinely published in proceedings of coastal conferences.)
  • Model:Zscape  + (None)
  • Model:GPM  + (None available)
  • Model:AquaTellUs  + (Not readily available; theoretical experiments are available as examples.)
  • Model:OrderID  + (One test facies succession CSDMStestSection.txt and one test facies code, colour code and name file CSDMStestSectionLithoCol.txt)
  • Model:OptimalCycleID  + (One test facies succession CSDMStestSection.txt and one test facies code, colour code and name file CSDMStestSectionLithoCol.txt)
  • Model:ParFlow  + (ParFlow contains a directory of test cases that may be automated as a check of the code.)
  • Model:DeltaClassification  + (Proof of concept was applied for the Ganges-Brahmaputra delta system)
  • Model:TreeThrow  + (Requires calibration for relationship betwRequires calibration for relationship between:</br># soil plate volume and tree diameter;</br>#soil plate width and tree diameter;</br>#soil plate depth and tree diameter.</br>These relationships have been calibrated based on field data in the Southern Blue Ridge (Appalachian Mountains).uthern Blue Ridge (Appalachian Mountains).)
  • Model:SBEACH  + (SBEACH was "validated" using a large suite of laboratory and field data sets. See SBEACH Report 4: Cross-Shore Transport Under Random Waves and Model Validation with SUPERTANK and Field Data. http://chl.erdc.usace.army.mil/chl.aspx?p=s&a=Software;31)
  • Model:HSPF  + (SPF and the earlier models from which it wSPF and the earlier models from which it was developed have been extensively applied in a wide variety of hydrologic and water quality studies (3,4), including pesticide runoff model testing (5), aquatic fate and transport model testing (6,7), and analyses of agricultural best management practices (8,9). An application of HSPF in a screening methodology for pesticide review is described by Donigian et al. (10). In addition, HSPF has been validated with both field data and model experiments, and has been reviewed by independent experts (11-20).</br></br>The Stream Transport and Agricultural Runoff for Exposure Assessment Methodology (STREAM) applies the HSPF program to various test watersheds for five major crops in four agricultural regions in the United States, defines a "representative" watershed based on regional conditions and an extrapolation of the calibration for the test watershed, and performs a sensitivity analysis on key pesticide parameters to generate cumulative frequency distributions of pesticide loads and concentrations in each regions. The resulting methodology requires the user to evaluate only the crops and regions of interest, the pesticide application rate, and three pesticide parameters -- the partition coefficient, the soil/sediment decay rate, and the solution decay rate.</br></br>The EPA Chesapeake Bay Program has been using the HSPF model as the framework for modeling total watershed contributions of flow, sediment, and nutrients (and associated constituents such as water temperature, DO, BOD, etc.) to the tidal region of the Chesapeake Bay (21,22). The watershed modeling represents pollutant contributions from an area of more than 68,000 sq. mi., and provides the input to drive a fully dynamic three-dimensional, hydrodynamic/water quality model of the Bay. The watershed drainage area is divided into land segments and stream channel segments. The land areas modeled include forest, agricultural cropland (conventional and conservation tillage systems), pasture, urban (pervious and impervious areas), and uncontrolled animal waste contributions. The stream channel simulation includes flow routing and oxygen and nutrient biochemical modeling (through phytoplankton) in order to account for instream processes affecting nutrient delivery to the Bay.</br></br>Currently, buildup/washoff type algorithms are being used for urban impervious areas, potency factors for all pervious areas, and constant (or seasonally variable) concentrations for all subsurface contributions and animal waste components. Enhancements are underway to utilize the detailed process (i.e. Agrichemical modules) simulation for cropland areas to better represent the impacts of agricultural BMPs and to include nitrogen cycling in forested systems to evaluate the impacts of atmospheric deposition of nitrogen on Chesapeake Bay. The watershed modeling is being used to evaluate nutrient management alternatives for attaining a 40% reduction in nutrient loads delivered to the Bay, as defined in a joint agreement among the governors of the member states. among the governors of the member states.)
  • Model:Rescal-snow  + (See 'test' folder)
  • Model:BEDLOAD  + (See Slingerland et al. (1994))
  • Model:ENTRAIN  + (See Slingerland et al. (1994))
  • Model:ENTRAINH  + (See Slingerland et al. (1994))
  • Model:FLDTA  + (See Slingerland et al. (1994))
  • Model:LONGPRO  + (See Slingerland et al. (1994))
  • Model:MIDAS  + (See Slingerland et al. (1994))
  • Model:SETTLE  + (See Slingerland et al. (1994))
  • Model:SUSP  + (See Slingerland et al. (1994))
  • Model:TURB  + (See Slingerland et al. (1994))
  • Model:STORM  + (See Slingerland et al. (1994))