The Quest for Hydrological Signatures: Effects of Data Transformation on Bayesian Inference of Watershed Models
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DOI: 10.1007/s11269-018-1908-6
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- Xuesong Zhang & Kaiguang Zhao, 2012. "Bayesian Neural Networks for Uncertainty Analysis of Hydrologic Modeling: A Comparison of Two Schemes," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2365-2382, June.
- T. Reshma & K. Reddy & Deva Pratap & Mehdi Ahmedi & V. Agilan, 2015. "Optimization of Calibration Parameters for an Event Based Watershed Model Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4589-4606, October.
- Deg-Hyo Bae & Kyung-Hwan Son & Jae-Min So, 2017. "Utilization of the Bayesian Method to Improve Hydrological Drought Prediction Accuracy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3527-3541, September.
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- Mojtaba Sadegh & Amir AghaKouchak & Alejandro Flores & Iman Mallakpour & Mohammad Reza Nikoo, 2019. "A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3011-3024, July.
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Keywords
Data transformation; Hydrological signatures; Bayesian inference; MCMC; Parameter identifiability; Prediction reliability;All these keywords.
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