Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model

By Misgana K. Muleta, John W. Nicklow. 2005

566 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Ocean Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/86e4da919dc7d2938c934c0506cf0e83850b0bba

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In Global and Planetary Change

In Ocean Engineering

In Water Science and Technology

Citations in the corpus

Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments (2013, methodology): “Following previous studies (Muleta and Nicklow 2005, Yang et al. 2008), prior parameter estimates are assumed to follow a uniform distribution.”
Calibration and uncertainty analysis of the SWAT model using Genetic Algorithms and Bayesian Model Averaging (2009, methodology): “Muleta and Nicklow (2005) combined Genetic Algorithms (GA) and Generalized Likelihood Uncertainty Estimation (GLUE) methods to conduct parameter calibration and uncertainty analysis of SWAT.”
Predictive Analysis and Simulation Uncertainty of a Distributed Hydrological Model (2010, background): “precipitation, streamflow, topography) and because no simulation model is an entirely true reflection of the physical process being modeled (Muleta and Nicklow 2004).”
One decade of multi-objective calibration approaches in hydrological modelling: a review (2010, methodology): “…focused on lumped rainfall–runoff models, there is a growing number of recent studies on semi-distributed and distributed schemes, usually involving a small portion of the total model parameters (Madsen, 2003; Ajami et al., 2004; Muleta & Nicklow, 2005; Vrugt et al., 2005; Kunstmann et al., 2006).”
Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling? (2009, unknown): “Recent applications of GLUE are also found in distributed hydrologic modeling (McMichael et al. 2006; Muleta and Nicklow 2005).”
The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions (2007, background): “, 2006), and relatively short calibration and validation periods (Muleta and Nicklow, 2005b).”
Model Performance Sensitivity to Objective Function during Automated Calibrations (2012, methodology): “Automated calibration is favored as manual calibration is often tedious, time-consuming, and requires experienced personnel (Muleta and Nicklow 2005).”
Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications (2015, methodology): “In addition, in view of the limitations of the Morris one-at-a-time (OAT) design, the LH-OAT method, which takes the Latin Hypercube samples as initial points for an OAT design, was proposed to apply to the SWAT model (Holvoet et al., 2005; van Griensven et al., 2006).”
Bridging the gap between GLUE and formal statistical approaches: approximate Bayesian computation (2013, background): “Applications of GLUE are also found in distributed hydrologic modeling (McMichael et al., 2006; Muleta and Nicklow, 2005).”