A Bayesian perspective on input uncertainty in model calibration: Application to hydrological model “abc”
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Summary
This paper presents a Bayesian uncertainty framework allowing one to account for input, output, and structural (model) uncertainties in the calibration of a model, and studies the impact of input uncertainty on the parameters of the hydrological model ‘‘abc’’.
- Type
- article
- Published
- 2006-07-01
- Cited by
- 95
- References
- 32
- Access
- Open access
- OpenAlex
- https://openalex.org/W1544621030
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:129456985
Keywords
Calibration, Bayesian probability, Computer science, Sensitivity analysis, Sensitivity (control systems)
References
- Which potential evapotranspiration input for a lumped rainfall-runoff model?. Part 2: Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling
- Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation
- Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter
- Validation of a watershed model without calibration
- Towards improved treatment of parameter uncertainty in hydrologic modeling
- Why environmental scientists are becoming Bayesians
- Stochastic parameter estimation procedures for hydrologie rainfall‐runoff models: Correlated and heteroscedastic error cases
- Least-squares fitting of a straight line.
- Bayesian calibration of computer models
- An analysis of input errors in precipitation‐runoff models using regression with errors in the independent variables
- Sensitivity of optimized parameters in watershed models
- Why Isn't Everyone a Bayesian?
- A Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data
- Proper posteriors from improper priors for an unidentified errors-in-variables model
- Impact of imperfect rainfall knowledge on the efficiency and the parameters of watershed models
- LEAST SQUARES WHEN BOTH VARIABLES HAVE UNCERTAINTIES
- Linear least‐squares fits with errors in both coordinates
- The future of distributed models: model calibration and uncertainty prediction.
- The Selection of Prior Distributions by Formal Rules
- Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information
Cited by
- REALTIME GUIDANCE FOR FLASH FLOOD RISK MANAGEMENT
- Diagnostic evaluation of watershed models
- Using Coupled Modeling Approaches To Quantify Hydrologic Prediction Uncertainty And To Design Effective Monitoring Networks
- Bayesian optimization and uncertainty analysis of complex environmental models, with applications in watershed management
- Bayesian calibration of fluvial flood models for risk analysis
- Global sensitivity analysis for large-scale socio-hydrological models using Hadoop
- Calibration of hydrological model GR2M using Bayesian uncertainty analysis
- Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality
- Product‐error‐driven generator of probable rainfall conditioned on WSR‐88D precipitation estimates
- Evaluating the information content of data for uncertainty reduction in hydrological modelling
- Quantifying the change in soil moisture modeling uncertainty from remote sensing observations using Bayesian inference techniques
- An approach for improving the sampling efficiency in the Bayesian calibration of computationally expensive simulation models
- Parameter Estimation for Groundwater Models under Uncertain Irrigation Data
- Engaging uncertainty in hydrologic data sets using principal component analysis: BaNPCA algorithm
- Improving runoff risk estimates: Formulating runoff as a bivariate process using the SCS curve number method
- Multisite seasonal forecast of arid river flows using a dynamic model combination approach
- Integrated uncertainty assessment of discharge predictions with a statistical error model
- Ensemble evaluation of hydrological model hypotheses
- Is point uncertain rainfall likely to have a great impact on distributed complex hydrological modeling?
- Separately accounting for uncertainties in rainfall and runoff: Calibration of event‐based conceptual hydrological models in small urban catchments using Bayesian method
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