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Conceptual model uncertainty in groundwater modeling: Combining generalized likelihood uncertainty estimation and Bayesian model averaging

Rodrigo Rojas, Luc Feyen, Alain Dassargues
2008 Water Resources Research  
that arise from errors in model structure, 8 inputs and parameters.  ...  1 Uncertainty assessments in groundwater modeling applications typically attribute all sources 2 of uncertainty to errors in parameters and inputs, neglecting what may be the primary source 3 of uncertainty  ...  of model structures, input and parameter vectors.  ... 
doi:10.1029/2008wr006908 fatcat:bfmngyvj25gsdfy3l4ayu67sdq

Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis

Edom Moges, Yonas Demissie, Laurel Larsen, Fuad Yassin
2020 Water  
Despite progresses in representing different processes, hydrological models remain uncertain. Their uncertainty stems from input and calibration data, model structure, and parameters.  ...  Compared to parameter uncertainty, UA application for structural uncertainty is limited while input and calibration data uncertainties are mostly unaccounted.  ...  Predictive uncertainty can be quantified by propagating parameter, structure and input uncertainties to the model output.  ... 
doi:10.3390/w13010028 fatcat:ufs7u4ba6fb5nigfiakr7ekzia

On the value of conditioning data to reduce conceptual model uncertainty in groundwater modeling

R. Rojas, L. Feyen, O. Batelaan, A. Dassargues
2010 Water Resources Research  
Recent applications of multi-model methods have demonstrated their potential in quantifying conceptual model uncertainty in groundwater modeling applications.  ...  Amongst multi-model methods based on model performance, the classical idea of Bayesian Model Averaging (In short, BMA weights the predictions of competing models by their corresponding posterior model  ...  This work was greatly improved by the thorough and constructive reviews provided by the Associate Editor, Shlomo Neuman, and three anonymous reviewers.  ... 
doi:10.1029/2009wr008822 fatcat:rd6iq5parbdpdin3lhmamq5o74

Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios

Syed M. Touhidul Mustafa, M. Moudud Hasan, Ajoy Kumar Saha, Rahena Parvin Rannu, Els Van Uytven, Patrick Willems, Marijke Huysmans
2019 Hydrology and Earth System Sciences  
This multi-model ensemble approach was applied to a drought-prone study area in Bangladesh.  ...  Uncertainties are present in these groundwater-level predictions and originate from greenhouse gas scenarios, climate models, conceptual hydro(geo)logical models (CHMs) and groundwater abstraction scenarios  ...  We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their  ... 
doi:10.5194/hess-23-2279-2019 fatcat:osec2ezzrbh7bp26izf4pq47we

Multi-model ensemble hydrologic prediction and uncertainties analysis

S. Jiang, L. Ren, X. Yang, M. Ma, Y. Liu
2014 Proceedings of the International Association of Hydrological Sciences  
Modelling uncertainties (i.e. input errors, parameter uncertainties and model structural errors) inevitably exist in hydrological prediction.  ...  A lot of recent attention has focused on these, of which input error modelling, parameter optimization and multi-model ensemble strategies are the three most popular methods to demonstrate the impacts  ...  model input, model parameter and model structure uncertainties.  ... 
doi:10.5194/piahs-364-249-2014 fatcat:j5ivs4nsvbdh7c5beptjcidcny

Incorporating uncertainty into adaptive, transboundary water challenges: a conceptual design for the Okavango River basin

Gregory A. Kiker, Rafael Munoz Carpena, Piotr Wolski, Anna Cathey, Andrea Gaughan, Jongbum Kim
2008 International Journal of Risk Assessment and Management  
In this paper, we present a review and conceptual design to integrate hydrological/ecological models, global uncertainty and sensitivity analysis, integrative modelling and decision analysis for complex  ...  The objective of this paper is to present a design that integrates a set of tools that builds systematically on past basin modelling research to incorporate the inherent uncertainty within the system and  ...  ., Campolongo, F. and Ratto, M. (2004) Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models, Chichester, England: John Wiley & Sons, Ltd., p.219.  ... 
doi:10.1504/ijram.2008.022130 fatcat:jab3hzg5wvb5jl6276p7zbuf2q

Decision Support Systems and Processes for Groundwater [chapter]

Suzanne A. Pierce, John M. Sharp, David J. Eaton
2016 Integrated Groundwater Management  
Integrated Assessment and Modeling (IAM) presents an approach for merging discipline and case-specific knowledge, such as those in hydrogeological sciences, with social drivers for use in decision support  ...  Information and knowledge management challenges abound in groundwater sciences.  ...  The authors would like to thank the editors, Muhammed Arshad and Dr. Anthony Jakeman for their patience and constructive comments throughout the editorial process.  ... 
doi:10.1007/978-3-319-23576-9_25 fatcat:sl7zdvof2rblbaa4zzhpygjv44

Multi-model approach to quantify groundwater level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios

Syed M. Touhidul Mustafa, M. Moudud Hasan, Ajoy Kumar Saha, Rahena Parvin Rannu, Els Van Uytven, Patrick Willems, Marijke Huysmans
2018 Hydrology and Earth System Sciences Discussions  
This multi-model ensemble approach was applied to a drought prone study area in Bangladesh.  ...  Uncertainties are present in these groundwater level predictions and originate from greenhouse gas scenarios, climate models, conceptual hydro(geo)logical models (CHMs) and groundwater abstraction scenarios  ...  Acknowledgements 751 We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is  ... 
doi:10.5194/hess-2018-580 fatcat:3u2nynr4ovdg5o3k7cq4nc5to4

Parameter estimation and uncertainty analysis in hydrological modeling

Paulo A. Herrera, Miguel Angel Marazuela, Thilo Hofmann
2021 WIREs Water  
Therefore, the application of systematic approaches for parameter estimation, sensitivity, and uncertainty analysis to integrate data and models and quantify potential errors, is more necessary now than  ...  We analyze existing methodologies, discuss remaining challenges, and present a survey of emerging trends for the application of parameter estimation and uncertainty analysis in hydrological modeling.  ...  F I G U R E 2 To evaluate the uncertainty of a given conceptual or structural model, it is necessary to generate many sets of input parameters that are coherent with the conceptual model.  ... 
doi:10.1002/wat2.1569 fatcat:y6prdtt5fbhnzpvpov6ec67xea

Assessment and management of risk in subsurface hydrology: A review and perspective

Daniel M. Tartakovsky
2013 Advances in Water Resources  
Uncertainty plagues every effort to model subsurface processes and every decision made on the basis of such models.  ...  parametric uncertainty through a modeling process, computational tools (e.g., random domain decompositions and transition probability based approaches) for quantification of geologic uncertainty, Bayesian  ...  Two conceptual frameworks for quantification of structural uncertainty, Bayesian model averaging and Bayesian model selection, are discussed briefly below.  ... 
doi:10.1016/j.advwatres.2012.04.007 fatcat:4rmf5dur35hvndmp567lizmegy

Prediction Interval Estimation Methods for Artificial Neural Network (ANN)-Based Modeling of the Hydro-Climatic Processes, a Review

Vahid Nourani, Nardin Jabbarian Paknezhad, Hitoshi Tanaka
2021 Sustainability  
Therefore, in recent years, uncertainty analysis of ANN modeling has attracted noticeable attention. Prediction intervals (PIs) are one of the prevalent tools for uncertainty quantification.  ...  This review paper has focused on the different techniques of PI development in the field of hydrology and climatology modeling.  ...  Sustainability 2021, 13, 1633 Acknowledgments: This work has been supported by University of Tabriz, International and Academic Cooperation Directorate, in the framework of TabrizU-300 program.  ... 
doi:10.3390/su13041633 fatcat:6cmwjlqq3nh7tey3n3g75omowm

One decade of multi-objective calibration approaches in hydrological modelling: a review

Andreas Efstratiadis, Demetris Koutsoyiannis
2010 Hydrological Sciences Journal  
Particularly in models of complex parameterization, a multiobjective approach becomes essential for improving the identifiability of parameters and augmenting the information contained in calibration by  ...  After reviewing the fundamentals of vector optimization theory and the algorithmic issues, we link the multi-criteria calibration approach with the concepts of uncertainty and equifinality.  ...  We are grateful to Hoshin Gupta and Keith Beven for their useful and constructive comments, critiques and suggestions, which helped us to substantially improve the paper.  ... 
doi:10.1080/02626660903526292 fatcat:axnmrbuaeja6tiaiejhw7v2e64

Scaling Methods of Sediment Bioremediation Processes and Applications

P. Adriaens, M.-Y. Li, A. M. Michalak
2006 Engineering in Life Sciences  
Unlike conventional geostatistic tools that are based on the pointto-point spatial structures, the new multi-scale model (M-Scale) introduces a new framework for spatial analysis in which regional values  ...  Using the Passaic River (NJ) dioxin data as a model dataset, multiple scaling models were applied to scale and interpolate sampled dioxin data and derive dechlorination signatures in sediments.  ...  Acknowledgements The authors acknowledge support from the DOD/DOE/ EPA Strategic Environmental Research and Development Program (SERDP) through a grant awarded to P.A.  ... 
doi:10.1002/elsc.200520127 fatcat:45dgbb4u3rh7hadyrmria6zs7i

Modeling hydrological consequences of climate and land use change Progress and Challenges

Jan Feyen, Vázquez Zambrano, Raúl Fernando Vázquez Zambrano, Raúl Fernando
2011 MASKANA  
In conclusion, the research challenges are pinpointed, which the community should address as to be able to observe and model, at a regional-scale, the coupled climate-water cycle in response to the human  ...  induced changes in climate and land use.  ...  SENESCYT-PROMETEO); and (ii) the United States Department of State's Bureau of Educational and Cultural Affairs (ECA) through the Fulbright Program awarded to the second author (NEXUS Program).  ... 
doi:10.18537/mskn.02.02.07 fatcat:sst6tumb6jdavn3o2cbfnga4wi

Hydrogeological Bayesian Hypothesis Testing through Trans-Dimensional Sampling of a Stochastic Water Balance Model

Trine Enemark, Luk JM Peeters, Dirk Mallants, Okke Batelaan, Andrew P. Valentine, Malcolm Sambridge
2019 Water  
We present an approach to model-based Bayesian hypothesis testing in a simple groundwater balance model, which involves optimization of a model in function of both parameter values and conceptual model  ...  Conceptual uncertainty is considered one of the major sources of uncertainty in groundwater flow modelling.  ...  Conclusions We presented an approach to model-based Bayesian hypothesis testing in a simple additive groundwater balance model, which involves optimization of a model in function of both parameter values  ... 
doi:10.3390/w11071463 fatcat:s7sg7nqvz5g3xadnkejgnotbjm
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