Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland
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Mary C. Hill | Laura Foglia | Steffen Mehl | Paolo Burlando | P. Burlando | M. Hill | L. Foglia | S. Mehl | P. Burlando
[1] H. Akaike. A new look at the statistical model identification , 1974 .
[2] Heidi Christiansen Barlebo,et al. Concentration data and dimensionality in groundwater models: evaluation using inverse modelling , 1998 .
[3] D. Sweetkind,et al. Death Valley regional groundwater flow system, Nevada and California : hydrogeologic framework and transient groundwater flow model , 2010 .
[4] Ming Ye,et al. Dependence of Bayesian Model Selection Criteria and Fisher Information Matrix on Sample Size , 2011 .
[5] B. Efron. The jackknife, the bootstrap, and other resampling plans , 1987 .
[6] John Doherty,et al. Use of paired simple and complex models to reduce predictive bias and quantify uncertainty , 2011 .
[7] S. P. Neuman,et al. On model selection criteria in multimodel analysis , 2007 .
[8] Heidi Christiansen Barlebo,et al. Investigating the Macrodispersion Experiment (MADE) site in Columbus, Mississippi, using a three‐dimensional inverse flow and transport model , 2004 .
[9] N. Draper,et al. Applied Regression Analysis , 1967 .
[10] Ming Ye,et al. Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff , 2003 .
[11] George Kuczera,et al. Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation , 2011 .
[12] Mary C. Hill,et al. Comment on ``Two statistics for evaluating parameter identifiability and error reduction'' by John Doherty and Randall J. Hunt , 2010 .
[13] Jens Christian Refsgaard,et al. Review of strategies for handling geological uncertainty in groundwater flow and transport modeling , 2012 .
[14] N. Draper,et al. Applied Regression Analysis: Draper/Applied Regression Analysis , 1998 .
[15] J. Deleeuw,et al. Introduction to Akaike (1973) Information Theory and an Extension of the Maximum Likelihood Principle , 1992 .
[16] Zucchini,et al. An Introduction to Model Selection. , 2000, Journal of mathematical psychology.
[17] M. C. Hill,et al. Unrealistic parameter estimates in inverse modelling: A problem or a benefit for model calibration? , 1996 .
[18] S. P. Neuman,et al. Estimation of Aquifer Parameters Under Transient and Steady State Conditions: 1. Maximum Likelihood Method Incorporating Prior Information , 1986 .
[19] C. Tiedeman,et al. Effective Groundwater Model Calibration , 2007 .
[20] Ming Ye,et al. Analysis of regression confidence intervals and Bayesian credible intervals for uncertainty quantification , 2012 .
[21] J. Kirchner. Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology , 2006 .
[22] George Kuczera,et al. Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors , 2010 .
[23] 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 .
[24] S. P. Neuman,et al. Inverse stochastic moment analysis of steady state flow in randomly heterogeneous media , 2006 .
[25] Jens Christian Refsgaard,et al. Assessment of hydrological model predictive ability given multiple conceptual geological models , 2012 .
[26] L Foglia,et al. Testing Alternative Ground Water Models Using Cross‐Validation and Other Methods , 2007, Ground water.
[27] Ming Ye,et al. A Model‐Averaging Method for Assessing Groundwater Conceptual Model Uncertainty , 2010, Ground water.
[28] Claire R. Tiedeman,et al. OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics , 2014 .
[29] Ming Ye,et al. Towards a comprehensive assessment of model structural adequacy , 2012 .
[30] Martyn P. Clark,et al. Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models , 2008 .
[31] Steffen Mehl,et al. Grid-size dependence of Cauchy boundary conditions used to simulate stream–aquifer interactions , 2010 .
[32] David Anderson,et al. Multimodel Ranking and Inference in Ground Water Modeling , 2004, Ground water.
[33] Dmitri Kavetski,et al. Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment , 2010 .
[34] John Doherty,et al. Two statistics for evaluating parameter identifiability and error reduction , 2009 .
[35] Ming Ye,et al. Comment on “Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window” by Frank T.‐C. Tsai and Xiaobao Li , 2010 .
[36] Saltelli Andrea,et al. Global Sensitivity Analysis: The Primer , 2008 .
[37] D. M. Allen. Mean Square Error of Prediction as a Criterion for Selecting Variables , 1971 .
[38] D. Krabbenhoft,et al. Obtaining parsimonious hydraulic conductivity fields using head and transport observations: A Bayesian geostatistical parameter estimation approach , 2009 .
[39] Mario L. V. Martina,et al. Flood forecasting using a fully distributed model: application of the TOPKAPI model to the Upper Xixian Catchment , 2005 .
[40] S. P. Neuman,et al. Maximum likelihood Bayesian averaging of uncertain model predictions , 2003 .
[41] Frank T.-C. Tsai,et al. Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window , 2008 .
[42] Ming Ye,et al. Combined Estimation of Hydrogeologic Conceptual Model, Parameter, and Scenario Uncertainty with Application to Uranium Transport at the Hanford Site 300 Area , 2006 .
[43] David R. Anderson,et al. Model selection and multimodel inference : a practical information-theoretic approach , 2003 .
[44] Mary C. Hill,et al. UCODE_2005 and six other computer codes for universal sensitivity analysis, calibration, and uncertainty evaluation constructed using the JUPITER API , 2006 .
[45] Mary C Hill,et al. The Practical Use of Simplicity in Developing Ground Water Models , 2006, Ground water.
[46] S. P. Neuman,et al. Sensitivity analysis and assessment of prior model probabilities in MLBMA with application to unsaturated fractured tuff , 2005 .
[47] Mary C. Hill,et al. Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function , 2009 .
[48] John Doherty,et al. A short exploration of structural noise , 2010 .
[49] Frank T.-C. Tsai,et al. Reply to comment by Ming Ye et al. on “Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window” , 2010 .
[50] Frank T.-C. Tsai,et al. Bayesian model averaging for groundwater head prediction and uncertainty analysis using multimodel and multimethod , 2009 .
[51] Dmitri Kavetski,et al. Pursuing the method of multiple working hypotheses for hydrological modeling , 2011 .
[52] Ming Ye,et al. MMA: A Computer Code for Multimodel Analysis , 2010 .
[53] Edward R. Banta,et al. A new streamflow-routing (SFR1) package to simulate stream-aquifer interaction with MODFLOW-2000 , 2004 .
[54] Jeroen P. van der Sluijs,et al. A framework for dealing with uncertainty due to model structure error , 2004 .
[55] R. Liedl,et al. Complexity versus simplicity: an example of groundwater model ranking with the Akaike Information Criterion , 2012 .
[56] C. Faunt,et al. Groundwater availability of the Central Valley Aquifer, California , 2009 .
[57] Sean A. McKenna,et al. Reducing Uncertainty Associated with Ground‐Water Flow and Transport Predictions , 1995 .
[58] Mary C. Hill,et al. Predictive modeling of flow and transport in a two‐dimensional intermediate‐scale, heterogeneous porous medium , 2001 .
[59] Rangasami L. Kashyap,et al. Optimal Choice of AR and MA Parts in Autoregressive Moving Average Models , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[60] David R. Anderson,et al. Multimodel Inference , 2004 .
[61] A. Alcolea,et al. Exact sensitivity matrix and influence of the number of pilot points in the geostatistical inversion of moment equations of groundwater flow , 2010 .
[62] Srikanta Mishra,et al. Model Averaging Techniques for Quantifying Conceptual Model Uncertainty , 2010, Ground water.
[63] Mary C. Hill,et al. Two-dimensional advective transport in ground-water flow parameter estimation , 1996 .