Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-6541-2017
https://doi.org/10.5194/hess-21-6541-2017
Research article
 | 
22 Dec 2017
Research article |  | 22 Dec 2017

Development and evaluation of a stochastic daily rainfall model with long-term variability

A. F. M. Kamal Chowdhury, Natalie Lockart, Garry Willgoose, George Kuczera, Anthony S. Kiem, and Nadeeka Parana Manage

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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by Editor and Referees) (26 Apr 2017) by Carlo De Michele
AR by Garry Willgoose on behalf of the Authors (07 Jul 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (17 Aug 2017) by Carlo De Michele
RR by Venkat Lakshmi (17 Aug 2017)
RR by Sri Srikanthan (12 Sep 2017)
ED: Publish as is (09 Oct 2017) by Carlo De Michele
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Short summary
Stochastic rainfall models are required to be be able to assess the reliability of dams used for urban water supply. Traditional Markov chain stochastic models do well at reproducing the mean and variance of rainfall at daily to weekly resolution but fail to simultaneously reproduce the variability of monthly to decadal rainfall. This paper presents four new extensions to Markov chain models that address this decadal deficiency and compares their performance for two field sites.