Journal ArticleDOI
Hydrological modelling of the Chaohe Basin in China: Statistical model formulation and Bayesian inference
TLDR
In this paper, the authors developed a procedure to overcome the problem of non-identifiability of distributed parameters by introducing aggregate parameters and using Bayesian inference, and they demonstrated the good performance of this approach to uncertainty analysis, particularly with respect to the fulfilment of statistical assumptions of the error model.About:
This article is published in Journal of Hydrology.The article was published on 2007-07-15. It has received 221 citations till now. The article focuses on the topics: Hydrological modelling & Statistical model.read more
Citations
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Journal ArticleDOI
Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China
TL;DR: Five uncertainty analysis procedures for watershed models are compared and if computationally feasible, Bayesian-based approaches are most recommendable because of their solid conceptual basis, but construction and test of the likelihood function requires critical attention.
Journal ArticleDOI
Parameter and modeling uncertainty simulated by GLUE and a formal Bayesian method for a conceptual hydrological model
TL;DR: The main findings of the study are that the parameter posterior distributions generated by the Bayesian method are slightly less scattered than those by the GLUE method, and GLUE is sensitive to the threshold value used to select behavioral parameter sets resulting in a wider uncertainty interval of the posterior distribution of parameters, and a wider confidence interval of model uncertainty.
Journal ArticleDOI
Hydrological Modelling in the Lake Tana Basin, Ethiopia Using SWAT Model
TL;DR: In this article, the SWAT2005 model was applied to the Lake Tana Basin for modeling of the hydrological water balance and the sensitivity analysis of the model to sub-basin delineation and HRU definition thresholds showed that the flow is more sensitive to the HRU defined thresholds than subbasin discretization effect.
Journal ArticleDOI
Modelling blue and green water resources availability in Iran
TL;DR: In this article, the authors used SWAT and SUFI-2 to calibrate and validate a hydrologic model of Iran based on river discharges and wheat yield, taking into consideration dam operations and irrigation practices.
Journal ArticleDOI
So just why would a modeller choose to be incoherent
Keith Beven,Paul Smith,Jim Freer +2 more
TL;DR: This article provides an extended response to the criticisms of the GLUE methodology by Mantovan and Todini and shows that the formal Bayesian identification of models is a special case of GLUE that can be used where the modeller is prepared to make very strong assumptions about the nature of the modelling errors.
References
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Journal ArticleDOI
River flow forecasting through conceptual models part I — A discussion of principles☆
J.E. Nash,J.V. Sutcliffe +1 more
TL;DR: In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.
Book
Bayesian Data Analysis
TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
Journal ArticleDOI
An Analysis of Transformations
George E. P. Box,David Cox +1 more
TL;DR: In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.
Journal ArticleDOI
Large Area Hydrologic Modeling and Assessment Part i: Model Development
TL;DR: A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins as discussed by the authors.
Book
Numerical Solution of Stochastic Differential Equations
Peter E. Kloeden,Eckhard Platen +1 more
TL;DR: In this article, a time-discrete approximation of deterministic Differential Equations is proposed for the stochastic calculus, based on Strong Taylor Expansions and Strong Taylor Approximations.
Related Papers (5)
River flow forecasting through conceptual models part I — A discussion of principles☆
J.E. Nash,J.V. Sutcliffe +1 more
The future of distributed models: model calibration and uncertainty prediction.
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