Distributed hydrologic model with Bayesian Monte Carlo technique to estimate surface loading in urban area

D. Sutani, T. Kawaguchi & M. Shirahama
There are a lot of uncertain factors involved in runoff analysis for urban area. Among others, accumulated non-point loadings on urban surface and in ditch or drains are eminent parameters, which are generally introduced as definite values into runoff model. However, it is desirable that these parameters are treated as continuous probability variables so as to discuss and make decision for effective counter measures based on the degree-of-belief of the model parameters. In order to...

1 Related Work

Distributed hydrologic model with Bayesian Monte Carlo technique to estimate surface loading in urban area

D. Sutani, T. Kawaguchi & M. Shirahama
There are a lot of uncertain factors involved in runoff analysis for urban area. Among others, accumulated non-point loadings on urban surface and in ditch or drains are eminent parameters, which are generally introduced as definite values into runoff model. However, it is desirable that these parameters are treated as continuous probability variables so as to discuss and make decision for effective counter measures based on the degree-of-belief of the model parameters. In order to...

Resource Types

  • Event
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Publication Year

  • 2005
    1

Data Centers

  • DTIC Datacenter
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