Rupa, C R and Mujumdar, P P (2018) Modeling high-intensity precipitation for urban hydrologic designs. [Book Chapter]
Full text not available from this repository.Abstract
Quantifying extreme precipitation in urban areas is important for risk assessment and employing mitigation measures. Significant spatial and temporal variability of precipitation along with sparse observations in urban areas introduce uncertainty in modeling precipitation extremes. Bayesian methods provide a framework for quantifying the uncertainties in precipitation extremes. In this chapter, methods for modeling precipitation return levels, both spatial and temporal, are discussed with reference to urban areas. The temporal modeling is based on a single-station analysis, quantifying uncertainties due to the parameters of the model fitted to the observed data, and due to multiple general circulation models considered for obtaining projected return levels. The methods to model spatial variation of return levels in urban areas use Bayesian hierarchical models, assuming independence in observations and using max-stable process considering dependence are discussed. The advantages and disadvantages of employing Bayesian methods in the context of modeling extreme precipitation are discussed. © 2019 Elsevier Inc. All rights reserved.
Item Type: | Book Chapter |
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Publication: | Trends and Changes in Hydroclimatic Variables: Links to Climate Variability and Change |
Publisher: | Elsevier |
Additional Information: | Copyright of this article belongs to Elsevier |
Department/Centre: | Division of Mechanical Sciences > Civil Engineering |
Date Deposited: | 07 Apr 2021 07:23 |
Last Modified: | 07 Apr 2021 07:23 |
URI: | http://eprints.iisc.ac.in/id/eprint/65271 |
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