Impact of the numbers of observations and calibration parameters on equifinality, model performance, and output and parameter uncertainty
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[1] Murugesu Sivapalan,et al. Climate, soil, and vegetation controls upon the variability of water balance in temperate and semiarid landscapes: Downward approach to water balance analysis , 2003 .
[2] Richard P. Hooper,et al. Assessing the Birkenes Model of stream acidification using a multisignal calibration methodology , 1988 .
[3] M. Sivapalan,et al. Improving model structure and reducing parameter uncertainty in conceptual water balance models through the use of auxiliary data , 2007 .
[4] J. H. Dane,et al. Soil Hydraulic Functions Determined from Measurements of Air Permeability, Capillary Modeling, and High‐Dimensional Parameter Estimation , 2011 .
[5] Soroosh Sorooshian,et al. A framework for development and application of hydrological models , 2001, Hydrology and Earth System Sciences.
[6] Konstantine P. Georgakakos,et al. Continuous streamflow simulation with the HRCDHM distributed hydrologic model , 2004 .
[7] Keith Beven,et al. A manifesto for the equifinality thesis , 2006 .
[8] A. Jakeman,et al. How much complexity is warranted in a rainfall‐runoff model? , 1993 .
[9] T. Gan,et al. Automatic Calibration of Conceptual Rainfall-Runoff Models: Optimization Algorithms, Catchment Conditions, and Model Structure , 1996 .
[10] Keith Beven,et al. Uniqueness of place and process representations in hydrological modelling , 2000 .
[11] Yanqing Lian,et al. Uncertainty-based evaluation and comparison of SWAT and HSPF applications to the Illinois River Basin , 2013 .
[12] Darian Raad,et al. Robust multi-objective optimization for water distribution system design using a meta-metaheuristic , 2009, Int. Trans. Oper. Res..
[13] P. Krause,et al. COMPARISON OF DIFFERENT EFFICIENCY CRITERIA FOR HYDROLOGICAL MODEL ASSESSMENT , 2005 .
[14] Murugesu Sivapalan,et al. Downward approach to hydrological prediction , 2003 .
[15] Hubert H. G. Savenije,et al. Model complexity control for hydrologic prediction , 2008 .
[16] Hugo A. Loáiciga,et al. Distributed hydrological modelling in California semi-arid shrublands: MIKE SHE model calibration and uncertainty estimation , 2006 .
[17] Indrajeet Chaubey,et al. SENSITIVITY ANALYSIS, CALIBRATION, AND VALIDATIONS FOR A MULTISITE AND MULTIVARIABLE SWAT MODEL 1 , 2005 .
[18] Patrick M. Reed,et al. A top-down framework for watershed model evaluation and selection under uncertainty , 2009, Environ. Model. Softw..
[19] George Kuczera,et al. Assessment of hydrologic parameter uncertainty and the worth of multiresponse data , 1998 .
[20] Henrik Madsen,et al. An evaluation of the impact of model structure on hydrological modelling uncertainty for streamflow simulation , 2004 .
[21] Hubert H. G. Savenije,et al. On the calibration of hydrological models in ungauged basins: A framework for integrating hard and soft hydrological information , 2009 .
[22] Keith Beven,et al. Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology , 2001 .
[23] Nanée Chahinian,et al. Distributed hydrological modelling of a Mediterranean mountainous catchment – Model construction and multi-site validation , 2007 .
[24] Jasper A Vrugt,et al. Improved evolutionary optimization from genetically adaptive multimethod search , 2007, Proceedings of the National Academy of Sciences.
[25] Keith Beven,et al. Prophecy, reality and uncertainty in distributed hydrological modelling , 1993 .
[26] Henrik Madsen,et al. Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling , 2008 .
[27] Luca Podofillini,et al. Model parameters estimation and sensitivity by genetic algorithms , 2003 .
[28] Jeffrey G. Arnold,et al. Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .
[29] M. Di Luzio,et al. Detection of overparameterization and overfitting in an automatic calibration of SWAT. , 2010 .
[30] P. Mantovan,et al. Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology , 2006 .
[31] Keith Beven,et al. On the sensitivity of soil-vegetation-atmosphere transfer (SVAT) schemes: equifinality and the problem of robust calibration , 1997 .
[32] L. Shawn Matott,et al. Addressing subjective decision-making inherent in GLUE-based multi-criteria rainfall-runoff model calibration , 2015 .
[33] Jim Freer,et al. Towards a limits of acceptability approach to the calibration of hydrological models : Extending observation error , 2009 .
[34] Kuolin Hsu,et al. From lumped to distributed via semi-distributed: Calibration strategies for semi-distributed hydrologic models , 2012 .
[35] Breanndán Ó Nualláin,et al. Parameter optimisation and uncertainty assessment for large-scale streamflow simulation with the LISFLOOD model , 2007 .
[36] C. Perrin,et al. Towards robust methods to couple lumped rainfall–runoff models and hydraulic models: A sensitivity analysis on the Illinois River , 2012 .
[37] Soroosh Sorooshian,et al. General Review of Rainfall-Runoff Modeling: Model Calibration, Data Assimilation, and Uncertainty Analysis , 2009 .
[38] S. Sorooshian,et al. Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system , 2004, Journal of Hydrology.
[39] Keith Beven,et al. Dalton Medal Lecture: How far can we go in distributed hydrological modelling? , 2001 .
[40] Keith Beven,et al. The future of distributed models: model calibration and uncertainty prediction. , 1992 .
[41] Alberto Montanari,et al. Large sample behaviors of the generalized likelihood uncertainty estimation (GLUE) in assessing the uncertainty of rainfall‐runoff simulations , 2005 .
[42] Francesc Gallart,et al. Sensitivity analysis and multi‐response, multi‐criteria evaluation of a physically based distributed model , 2002 .
[43] K. Beven,et al. Shenandoah Watershed Study: Calibration of a Topography‐Based, Variable Contributing Area Hydrological Model to a Small Forested Catchment , 1985 .
[44] Jasper A. Vrugt,et al. Bridging the gap between GLUE and formal statistical approaches: approximate Bayesian computation , 2013 .
[45] Victor Koren,et al. Parameterization of distributed hydrological models: learning from the experiences of lumped modeling , 2006 .
[46] Teresa B. Culver,et al. Uncertainty Analysis for Watershed Modeling Using Generalized Likelihood Uncertainty Estimation with Multiple Calibration Measures , 2008 .
[47] Alberto Montanari,et al. What do we mean by ‘uncertainty’? The need for a consistent wording about uncertainty assessment in hydrology , 2007 .
[48] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[49] Xuesong Zhang,et al. On the use of multi‐algorithm, genetically adaptive multi‐objective method for multi‐site calibration of the SWAT model , 2010 .
[50] Steen Christensen. A synthetic groundwater modelling study of the accuracy of GLUE uncertainty intervals , 2002 .
[51] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[52] Konstantine P. Georgakakos,et al. Intercomparison of lumped versus distributed hydrologic model ensemble simulations on operational forecast scales , 2006 .
[53] K. Beven,et al. Bayesian Estimation of Uncertainty in Runoff Prediction and the Value of Data: An Application of the GLUE Approach , 1996 .
[54] Performance Evaluation of Physically Based Distributed Hydrologic Models and Lumped Hydrologic Models , 2004 .
[55] S. Sorooshian,et al. Comparison of simple versus complex distributed runoff models on a midsized semiarid watershed , 1994 .
[56] Jeffrey G. Arnold,et al. Soil and Water Assessment Tool Theoretical Documentation Version 2009 , 2011 .
[57] J. Refsgaard,et al. Operational Validation and Intercomparison of Different Types of Hydrological Models , 1996 .
[58] Mazdak Arabi,et al. A Hydrologic/Water Quality Model Applicati1 1 , 2007 .
[59] R. Allan Freeze,et al. A Comparison of Rainfall-Runoff Modeling Techniques on Small Upland Catchments , 1985 .
[60] Jasper A. Vrugt,et al. Semi-distributed parameter optimization and uncertainty assessment for large-scale streamflow simulation using global optimization / Optimisation de paramètres semi-distribués et évaluation de l'incertitude pour la simulation de débits à grande échelle par l'utilisation d'une optimisation globale , 2008 .
[61] Hatim O. Sharif,et al. On the calibration and verification of two‐dimensional, distributed, Hortonian, continuous watershed models , 2000 .
[62] Soroosh Sorooshian,et al. Toward improved streamflow forecasts: value of semidistributed modeling , 2001 .
[63] J. Stedinger,et al. Appraisal of the generalized likelihood uncertainty estimation (GLUE) method , 2008 .
[64] Assefa M. Melesse,et al. SWAT model application and prediction uncertainty analysis in the Lake Tana Basin, Ethiopia , 2009 .
[65] J. Refsgaard. Parameterisation, calibration and validation of distributed hydrological models , 1997 .
[66] Keith Beven,et al. Changing ideas in hydrology — The case of physically-based models , 1989 .
[67] S. Sorooshian,et al. Automatic calibration of conceptual rainfall-runoff models: The question of parameter observability and uniqueness , 1983 .
[68] K. Beven. Towards a coherent philosophy for modelling the environment , 2002, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[69] Murugesu Sivapalan,et al. Scale issues in hydrological modelling: A review , 1995 .