Obtaining Useful Answers from Groundwater Models

NWRA       8:00 am – 12:00 pm,     Tuesday, January 31, 2023

01_GWmodels_INTRO+Basics+Real.v1.pptx

  • Groundwater models developed to address questions
  • Conceptual model should be developed before groundwater model
  • Groundwater models are only as good as supporting data
  • Water levels and discharges only direct measurements of groundwater system

02_GWmodels_Flow+Calibration.v1.pptx

  • Flow models provide consistent stories that can be compared to data
  • Lateral and vertical extents should be enough to solve problem without going too far
  • Hydraulic properties, stresses, and boundaries must be defined for entire model
  • Parameter estimation formalizes model calibration, where measured and simulated quantities are compared in an objective function
  • Parameters are changed so that objective function is reduced
  • Parameters typically define arrays of hydraulic properties with zones or pilot points
  • Parameter-to-array example and tube-model workbooks in SupportingMaterial\02_Interpolate+TubeMODEL subfolder

03_HydProp+GeoFrameworks.v1.pptx

  • Geologic frameworks distribute hydraulic properties through groundwater-flow models
  • Groundwater controlled by hydraulically connected fractures
  • Detailed, complex frameworks do not improve hydraulic-property estimates
  • Compare transmissivity, not hydraulic conductivity, to rock types

04_AQtests+T-COMP.v1.pptx

  • Best transmissivity estimates from aquifer tests with known volumes and drawdowns
  • Estimate transmissivity within factor of 5 from specific capacity on 10-20% of NDWR logs
  • Hydrogeologic units predict possible transmissivities well and hydraulic conductivities poorly
  • Comparing transmissivity in objective functions requires little additional data and most affects results where low transmissivity rocks are prevalent  
  • Example of zones and Tikhonov regularization applied to a 1-D model is in RegularizeParameters-Compare.xlsm workbook and explained in the guide RegularizeParameters_GUIDE.pdf in SupportingMaterial\04_Regularization+PP subfolder

05_WaterBudgets+Recharge.pptx

  • Groundwater-discharge estimates define annual volumes in water budgets of basins
  • Recharge volumes extrapolated from known discharge estimates, where
    a precipitation map is basis of extrapolation 
  • Spatial distribution of recharge unknown and simulated distribution depends on conceptualization of subsurface hydraulic conductivity (K) 
  • Simulated recharge in groundwater model should be consistent with measured/assumed groundwater discharge

06_GeologicFrameworks_Dos+Donts.v1.pptx

  • Geologic frameworks are not data, Distinguish between interpretation and reality
  • Geologic frameworks are foundations for distributing hydraulic properties
  • Revise geologic framework based on hydrologic data
  • Truncate geologic frameworks based on groundwater model purpose
  • Detailed, complex frameworks are not always better than simplified frameworks

07_Looking_CheckingShapes.v1.pptx

  • Looking necessary to cross bar of “Not obviously wrong”
  • Broad visualization of simulated results uncovers undefined badness,
    which leads to better models
  • Simplifying model features and integrating results for mapping eases comprehension
  • Cheap tools such as Model Viewer and Google Earth encourage looking by more users
  • Transmissivity distributions simplify presenting model results and aids comprehension
  • Water-level profiles are processed quickly and function
    like hydrographs for steady state models

08_ViewingResults.v1.pptx

  • Calibration should be evaluated with more than statistics, such as RMS error
  • Visual comparison of model results required to evaluate model plausibility
  • Maps and plots provide better visualization, compared to tables

09_Uncertainy+Decide.v1.pptx

  • Calibration & uncertainty analysis depend on judgement 
  • Model developers’ judgement explicitly embedded in objective function and parameters
    • Objective function—Data exclusion, data inclusion, and weighting of included data
    • Parameters—Spatial extent of faults or zones and pilot-point density,
                          Ranges of defined parameters, where textbook ranges allow too much
  • Uncertainty analysis is not free and can cost measuring useful data
  • Selecting an operational model from existing models should consider
    • Fidelity to data and concepts that directly affect predictions
    • Arguing that selected model “Sucks less,” than other options is more convincing than selected model is “The best”

10_Apply+Report.v1.pptx

  • Results not overly sensitive to detail of model grid
  • Increasing discretization increases model run time, which weakens calibration and post-processing of results
  • Models flexible—Answer many questions and are improved by clear purpose
  • Data and questions should drive model complexity
    • Additional data dispels ignorance, not more models
    • Show added details improve answers
  • Clear ties to measurements increase confidence
  • A figure of integrated model results is easier to comprehend than multiple figures and tables that need to be integrated mentally.
  • Require complete reporting
    • Interior of Earth can be mysterious,
    • No aspect of a model should be mysterious
  • Workbook 01_DD_CoarseFineGRID_Compare.xlsm and supporting files for creating, executing, and viewing coarse and fine models in SupportingMaterial\10_Apply+Grid+Report subfolder