Comparison of Three Multiobjective Optimization Algorithms for Inverse Modeling of Vadose Zone Hydraulic Properties
By Thomas Wöhling, Jasper A. Vrugt, G. Barkle. 2008
139 citations recorded by the source corpus.
Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/e871508b70dc97019377ce332d0635ec2de0abb7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Civil and Structural Engineering
- Jasper A. Vrugt
- Jirka Šimůnek
- Thomas Wöhling
- Yakov A. Pachepsky
- Alex B. McBratney
- M. T. V. Genuchten
- Budiman Minasny
- M. Šejna
In Environmental Engineering
- Jasper A. Vrugt
- Jirka Šimůnek
- Budiman Minasny
- Alex B. McBratney
- M. T. V. Genuchten
- M. Šejna
- Thomas Wöhling
- Wolfgang Nowak
In Water Science and Technology
- Wolfgang Nowak
- Thomas Wöhling
- Yakov A. Pachepsky
- Jirka Šimůnek
- Jasper A. Vrugt
- Diederik Jacques
- Budiman Minasny
- Alex B. McBratney
Citations in the corpus
- Simultaneous heat and water (SHAW) model: model use, calibration, and validation. (2012, methodology): “By using a multi-objective method, the overall tradeoff between criteria can aid in assessing deficiencies in both model structure and data quality (Wöhling et al., 2008).”
- HYDRUS: Model Use, Calibration, and Validation (2012, methodology): “…have been used in several studies to identify soil hydraulic parameters for multiple soil horizons (e.g., Jacques et al., 2002; Dahiya et al., 2007; Wöhling et al., 2008; Huang et al., 2011), an important question remains: whether the models can also be used to estimate effective soil hydraulic…”
- Modeling Soil Processes: Review, Key Challenges, and New Perspectives (2016, background): “Multimodel ensemble simulations, (e.g., Neuman, 2003; Clark et al., 2008; Wohling et al., 2008; Gupta et al., 2012), such as Bayesian model averaging (BMA) are a promising approach to quantify these uncertainties; BMA reflects conceptual uncertainty through a weighted average of model-wise ensembles”
- Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of soil hydraulic models (2008, methodology): “This decision was made because water flow in the highly porous volcanic vadose zone at the Spydia field site occurs primarily under wet conditions, and the soil hydraulic conductivity declines rapidly with decreasing soil water pressure heads [Wöhling et al., 2008].”
- Multiresponse multilayer vadose zone model calibration using Markov chain Monte Carlo simulation and field water retention data (2011, methodology): “These results support our earlier findings that hydraulic parameters derived from laboratory analysis of small scale soil samples do not accurately represent the larger-scale flow and transport processes in the investigated vadose zone [Wöhling et al., 2008].”