A unified approach for process‐based hydrologic modeling: 1. Modeling concept

This work advances a unified approach to process‐based hydrologic modeling to enable controlled and systematic evaluation of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. In this paper, we introduce the general approach used in SUMMA, detailing the spatial organization and model simplifications, and how different representations of multiple physical processes can be combined within a single modeling framework. We discuss how SUMMA can be used to systematically pursue the method of multiple working hypotheses in hydrology. In particular, we discuss how SUMMA can help tackle major hydrologic modeling challenges, including defining the appropriate complexity of a model, selecting among competing flux parameterizations, representing spatial variability across a hierarchy of scales, identifying potential improvements in computational efficiency and numerical accuracy as part of the numerical solver, and improving understanding of the various sources of model uncertainty.

[1]  Dmitri Kavetski,et al.  A unified approach for process‐based hydrologic modeling: 2. Model implementation and case studies , 2015 .

[2]  Balaji Rajagopalan,et al.  Are we unnecessarily constraining the agility of complex process‐based models? , 2015 .

[3]  R. Maxwell,et al.  Simulation of groundwater and surface water over the continental US using a hyperresolution, integrated hydrologic model , 2014 .

[4]  Martyn P. Clark,et al.  The Use of Similarity Concepts to Represent Subgrid Variability in Land Surface Models: Case Study in a Snowmelt-Dominated Watershed , 2014 .

[5]  Dmitri Kavetski,et al.  Catchment properties, function, and conceptual model representation: is there a correspondence? , 2014 .

[6]  Olaf Kolditz,et al.  Surface‐subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks , 2014 .

[7]  S. Sorooshian,et al.  The distributed model intercomparison project - Phase 2: Experiment design and summary results of the western basin experiments , 2013 .

[8]  John Doherty,et al.  Parameter and predictive outcomes of model simplification , 2013 .

[9]  J. McDonnell,et al.  A decade of Predictions in Ungauged Basins (PUB)—a review , 2013 .

[10]  Robert J. Gurney,et al.  Simulating wind-affected snow accumulations at catchment to basin scales , 2013 .

[11]  Yves Lejeune,et al.  A comparison of 1701 snow models using observations from an alpine site , 2013 .

[12]  Jaap Schellekens,et al.  The Delft-FEWS flow forecasting system , 2013, Environ. Model. Softw..

[13]  Mary C. Hill,et al.  Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland , 2013 .

[14]  David M. Lawrence,et al.  A new fractional snow-covered area parameterization for the Community Land Model and its effect on the surface energy balance , 2012 .

[15]  Keith Beven,et al.  Comment on “Pursuing the method of multiple working hypotheses for hydrological modeling” by P. Clark et al. , 2012 .

[16]  Dmitri Kavetski,et al.  Reply to comment by K. Beven et al. on “Pursuing the method of multiple working hypotheses for hydrological modeling” , 2012 .

[17]  Demetris Koutsoyiannis,et al.  A blueprint for process‐based modeling of uncertain hydrological systems , 2012 .

[18]  Julie A. Vano,et al.  Hydrologic Sensitivities of Colorado River Runoff to Changes in Precipitation and Temperature , 2012 .

[19]  D. Lawrence,et al.  The CCSM4 Land Simulation, 1850-2005: Assessment of Surface Climate and New Capabilities , 2012 .

[20]  Mariana Vertenstein,et al.  A new flexible coupler for earth system modeling developed for CCSM4 and CESM1 , 2012, Int. J. High Perform. Comput. Appl..

[21]  H. Savenije,et al.  Hydrology and Earth System Sciences Hydrological Landscape Classification: Investigating the Performance of Hand Based Landscape Classifications in a Central European Meso-scale Catchment , 2022 .

[22]  Dmitri Kavetski,et al.  Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development , 2011 .

[23]  Dmitri Kavetski,et al.  Pursuing the method of multiple working hypotheses for hydrological modeling , 2011 .

[24]  P. Cox,et al.  The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes , 2011 .

[25]  C. Rennó,et al.  Height Above the Nearest Drainage – a hydrologically relevant new terrain model , 2011 .

[26]  Kevin W. Manning,et al.  The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements , 2011 .

[27]  Philipp Kraft,et al.  CMF: A Hydrological Programming Language Extension For Integrated Catchment Models , 2011, Environ. Model. Softw..

[28]  H. Gupta,et al.  Correcting the mathematical structure of a hydrological model via Bayesian data assimilation , 2011 .

[29]  M. Ek,et al.  Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water , 2011 .

[30]  Dmitri Kavetski,et al.  Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes , 2010 .

[31]  S. Attinger,et al.  Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale , 2010 .

[32]  Jan Vanderborght,et al.  Proof of concept of regional scale hydrologic simulations at hydrologic resolution utilizing massively parallel computer resources , 2010 .

[33]  Dennis P. Lettenmaier,et al.  Modeling snow accumulation and ablation processes in forested environments , 2009 .

[34]  Kelly Elder,et al.  Evaluation of forest snow processes models (SnowMIP2) , 2009 .

[35]  Martyn P. Clark,et al.  Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models , 2008 .

[36]  Yuqiong Liu,et al.  Reconciling theory with observations: elements of a diagnostic approach to model evaluation , 2008 .

[37]  Reed M. Maxwell,et al.  Quantifying the effects of three-dimensional subsurface heterogeneity on Hortonian runoff processes using a coupled numerical, stochastic approach , 2008 .

[38]  Miroslav Šejna,et al.  Development and Applications of the HYDRUS and STANMOD Software Packages and Related Codes , 2008 .

[39]  D. Marks,et al.  Radiative transfer modeling of a coniferous canopy characterized by airborne remote sensing , 2008 .

[40]  J. Thielen,et al.  The European Flood Alert System – Part 1: Concept and development , 2008 .

[41]  R. Maxwell,et al.  Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model , 2008 .

[42]  S. P. Anderson,et al.  Critical Zone Observatories: Building a network to advance interdisciplinary study of Earth surface processes , 2008, Mineralogical Magazine.

[43]  William L. Quinton,et al.  The cold regions hydrological model: a platform for basing process representation and model structure on physical evidence , 2007 .

[44]  Jimy Dudhia,et al.  Conservative Split-Explicit Time Integration Methods for the Compressible Nonhydrostatic Equations , 2007 .

[45]  C. Duffy,et al.  A semidiscrete finite volume formulation for multiprocess watershed simulation , 2007 .

[46]  Richard P. Hooper,et al.  Moving beyond heterogeneity and process complexity: A new vision for watershed hydrology , 2007 .

[47]  Stephen J. Burges,et al.  A framework for classifying and comparing distributed hillslope and catchment hydrologic models , 2007 .

[48]  Erwin Zehe,et al.  Dynamical process upscaling for deriving catchment scale state variables and constitutive relations for meso-scale process models , 2006 .

[49]  Sujay V. Kumar,et al.  Land information system: An interoperable framework for high resolution land surface modeling , 2006, Environ. Model. Softw..

[50]  Keith Beven,et al.  Searching for the Holy Grail of scientific hydrology: Q t =( S, R, Δt ) A as closure , 2006 .

[51]  Keith Loague,et al.  Physics‐based hydrologic‐response simulation: Seeing through the fog of equifinality , 2006 .

[52]  Martyn P. Clark,et al.  One-Way Coupling of an Atmospheric and a Hydrologic Model in Colorado , 2006 .

[53]  R. Maxwell,et al.  Integrated surface-groundwater flow modeling: A free-surface overland flow boundary condition in a parallel groundwater flow model , 2006 .

[54]  R. Rigon,et al.  GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets , 2006 .

[55]  Murugesu Sivapalan,et al.  Pattern, Process and Function: Elements of a Unified Theory of Hydrology at the Catchment Scale , 2006 .

[56]  Keith Beven,et al.  A manifesto for the equifinality thesis , 2006 .

[57]  Benjamin B. Mirus,et al.  Physics‐based hydrologic‐response simulation: foundation for hydroecology and hydrogeomorphology , 2006 .

[58]  Soroosh Sorooshian,et al.  Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops , 2006 .

[59]  J. Kirchner.  Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology , 2006 .

[60]  Tom Rientjes,et al.  Flux parameterization in the representative elementary watershed approach: Application to a natural basin , 2005 .

[61]  Dara Entekhabi,et al.  Embedding landscape processes into triangulated terrain models , 2005, Int. J. Geogr. Inf. Sci..

[62]  Christina L. Tague,et al.  RHESSys: Regional Hydro-Ecologic Simulation System—An Object- Oriented Approach to Spatially Distributed Modeling of Carbon, Water, and Nutrient Cycling , 2004 .

[63]  E. Vivoni,et al.  Catchment hydrologic response with a fully distributed triangulated irregular network model , 2004 .

[64]  Dong-Jun Seo,et al.  The distributed model intercomparison project (DMIP): Motivation and experiment design , 2004 .

[65]  David G. Tarboton,et al.  Application of TOPNET in the distributed model intercomparison project , 2004 .

[66]  Henrik Madsen,et al.  An evaluation of the impact of model structure on hydrological modelling uncertainty for streamflow simulation , 2004 .

[67]  Dara Entekhabi,et al.  Generation of triangulated irregular networks based on hydrological similarity , 2004 .

[68]  Robert E. Dickinson,et al.  A Two-Big-Leaf Model for Canopy Temperature, Photosynthesis, and Stomatal Conductance , 2004 .

[69]  Michael Smith,et al.  Hydrology laboratory research modeling system (HL-RMS) of the US national weather service , 2004 .

[70]  Reed M. Maxwell,et al.  On the Development of a Coupled Land Surface and Groundwater Model , 2004 .

[71]  J. D. Tarpley,et al.  The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system , 2004 .

[72]  C. Paniconi,et al.  Hillslope‐storage Boussinesq model for subsurface flow and variable source areas along complex hillslopes: 2. Intercomparison with a three‐dimensional Richards equation model , 2003 .

[73]  C. Paniconi,et al.  Hillslope‐storage Boussinesq model for subsurface flow and variable source areas along complex hillslopes: 1. Formulation and characteristic response , 2003 .

[74]  C. Perrin,et al.  Improvement of a parsimonious model for streamflow simulation , 2003 .

[75]  Murugesu Sivapalan,et al.  Downward approach to hydrological prediction , 2003 .

[76]  D. Mocko,et al.  Simulation of high latitude hydrological processes in the Torne-Kalix basin : PILPS phase 2(e) - 2: Comparison of model results with observations , 2003 .

[77]  Kumiko Takata,et al.  Development of the minimal advanced treatments of surface interaction and runoff , 2003 .

[78]  Dennis P. Lettenmaier,et al.  Variable infiltration capacity cold land process model updates , 2003 .

[79]  R. Koster,et al.  Simulation of high-latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2(e) 3: Equivalent model representation and sensitivity experiments , 2003 .

[80]  D. Mocko,et al.  Simulation of high-latitude hydrological processes in the Torne-Kalix basin: PILPS phase 2(e) - 1: Experiment description and summary intercomparisons , 2003 .

[81]  P. Troch,et al.  Analytical solutions to a hillslope-storage kinematic wave equation for subsurface flow , 2002 .

[82]  Keith W. Oleson,et al.  Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models , 2002 .

[83]  George H. Leavesley,et al.  A modular approach to addressing model design, scale, and parameter estimation issues in distributed hydrological modelling , 2002 .

[84]  Keith Beven,et al.  Towards an alternative blueprint for a physically based digitally simulated hydrologic response modelling system , 2002 .

[85]  Eric F. Wood,et al.  Predicting the Discharge of Global Rivers , 2001, Journal of Climate.

[86]  Keith Beven,et al.  A dynamic TOPMODEL , 2001 .

[87]  K. Loague,et al.  Hydrologic‐Response simulations for the R‐5 catchment with a comprehensive physics‐based model , 2001 .

[88]  W. Gray,et al.  A unifying framework for watershed thermodynamics: constitutive relationships , 1999 .

[89]  David G. Tarboton,et al.  Sub-grid parameterization of snow distribution for an energy and mass balance snow cover model , 1999 .

[90]  K. Mitchell,et al.  A parameterization of snowpack and frozen ground intended for NCEP weather and climate models , 1999 .

[91]  Ann Henderson-Sellers,et al.  Recent progress and results from the project for the intercomparison of landsurface parameterization schemes , 1998 .

[92]  M. Sivapalan,et al.  A unifying framework for watershed thermodynamics: balance equations for mass, momentum, energy and entropy, and the second law of thermodynamics , 1998 .

[93]  David G. Tarboton,et al.  The Influence of the Spatial Distribution of Snow on Basin-Averaged Snowmelt , 1998 .

[94]  R. Leuning,et al.  A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy I:: Model description and comparison with a multi-layered model , 1998 .

[95]  R. Bras,et al.  Analytical solutions to hillslope subsurface storm flow and saturation overland flow , 1998 .

[96]  Göran Lindström,et al.  Development and test of the distributed HBV-96 hydrological model , 1997 .

[97]  Roni Avissar,et al.  Representation of heterogeneity effects in Earth system modeling: Experience from land surface modeling , 1997 .

[98]  Randal D. Koster,et al.  The Interplay between Transpiration and Runoff Formulations in Land Surface Schemes Used with Atmospheric Models , 1997 .

[99]  K. Beven,et al.  Toward a generalization of the TOPMODEL concepts:Topographic indices of hydrological similarity , 1996 .

[100]  Wolfgang-Albert Flügel,et al.  Delineating hydrological response units by geographical information system analyses for regional hydrological modelling using PRMS/MMS in the drainage basin of the River Bröl, Germany , 1995 .

[101]  Murugesu Sivapalan,et al.  Scale issues in hydrological modelling: A review , 1995 .

[102]  J. Famiglietti,et al.  Multiscale modeling of spatially variable water and energy balance processes , 1994 .

[103]  M. Suárez,et al.  A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models , 1994 .

[104]  D. Lettenmaier,et al.  A simple hydrologically based model of land surface water and energy fluxes for general circulation models , 1994 .

[105]  M. Wigmosta,et al.  A distributed hydrology-vegetation model for complex terrain , 1994 .

[106]  Alain Pietroniro,et al.  Grouped Response Units for Distributed Hydrologic Modeling , 1993 .

[107]  Thomas A. McMahon,et al.  Physically based hydrologic modeling: 1. A terrain‐based model for investigative purposes , 1992 .

[108]  Thomas A. McMahon,et al.  Physically based hydrologic modeling: 2. Is the concept realistic? , 1992 .

[109]  Eric F. Wood,et al.  A land-surface hydrology parameterization with subgrid variability for general circulation models , 1992 .

[110]  R. Koster,et al.  Modeling the land surface boundary in climate models as a composite of independent vegetation stands , 1992 .

[111]  K. Beven,et al.  A physically based model of heterogeneous hillslopes: 2. Effective hydraulic conductivities , 1989 .

[112]  Keith Beven,et al.  A physically based model of heterogeneous hillslopes: 1. Runoff production , 1989 .

[113]  Keith Beven,et al.  Effects of spatial variability and scale with implications to hydrologic modeling , 1988 .

[114]  E. Todini.  Rainfall-runoff modeling — Past, present and future , 1988 .

[115]  Keith Beven,et al.  On hydrologic similarity: 2. A scaled model of storm runoff production , 1987 .

[116]  Larry Mahrt,et al.  Grid-Averaged Surface Fluxes , 1987 .

[117]  James C. I. Dooge,et al.  Looking for hydrologic laws , 1986 .

[118]  V. Klemeš.  Conceptualization and scale in hydrology , 1983 .

[119]  R. Moore,et al.  A distribution function approach to rainfall runoff modeling , 1981 .

[120]  K. Beven,et al.  A physically based, variable contributing area model of basin hydrology , 1979 .

[121]  R. Freeze,et al.  Blueprint for a physically-based, digitally-simulated hydrologic response model , 1969 .

[122]  D. Lawrence,et al.  Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model , 2011 .

[123]  J. Randerson,et al.  Technical Description of version 4.0 of the Community Land Model (CLM) , 2010 .

[124]  Peter Troch,et al.  Dealing with Landscape Heterogeneity in Watershed Hydrology: A Review of Recent Progress toward New Hydrological Theory , 2009 .

[125]  G..  SCALE ISSUES IN HYDROLOGICAL MODELLING : A REVIEW , 2006 .

[126]  Q. Duana,et al.  Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops , 2006 .

[127]  Gordon B. Bonan,et al.  Ecological Climatology: Concepts and Applications , 2002 .

[128]  Arlen W. Harbaugh,et al.  MODFLOW-2000, The U.S. Geological Survey Modular Ground-Water Model - User Guide to Modularization Concepts and the Ground-Water Flow Process , 2000 .

[129]  M. Seyfried,et al.  Scale and the Nature of Spatial Variability: Field Examples Having Implications for Hydrologic Modeling , 1995 .