Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/70561
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Type: Journal article
Title: Continuous rainfall simulation: 1. A regionalized subdaily disaggregation approach
Author: Westra, S.
Mehrotra, R.
Sharma, A.
Srikanthan, R.
Citation: Water Resources Research, 2012; 48(1):W01535-1-W01535-16
Publisher: Amer Geophysical Union
Issue Date: 2012
ISSN: 0043-1397
1944-7973
Statement of
Responsibility: 
Seth Westra, Rajeshwar Mehrotra, Ashish Sharma and Ratnasingham Srikanthan
Abstract: This paper is the first of two in the current issue that presents a framework for generating continuous (uninterrupted) rainfall sequences at both gaged and ungaged point locations. The ultimate objective is to present a methodology for stochastically generating continuous subdaily rainfall sequences at any location such that the statistics at a range of aggregation scales are preserved. This first paper presents a regionalized nonparametric daily disaggregation model in which, conditional on a daily rainfall amount and previous and next-day wetness states at the location of interest, subdaily fragments are resampled using continuous records at nearby locations. The second paper then focuses on a regionalized daily rainfall generation model.To enable the substitution of subdaily rainfall at nearby locations for subdaily rainfall at the location of interest, it is necessary to identify locations with ‘‘similar’’ daily to subdaily scaling characteristics. We use a two-sample, two-dimensional Kolmogorov-Smirnov (K-S) test to identify whether the daily to subdaily scaling relationships are statistically similar between all possible station pairs sampled from 232 gages located throughout Australia. This step is followed by a logistic regression to determine the influence of the covariates of latitude, longitude, elevation, and distance to the coast on the probability that the scaling at any two locations will be similar. The model is tested at five locations, where recorded subdaily data was available for comparison, and results indicate good model performance, particularly in preserving the probability distribution of extremes and the antecedent rainfall prior to the storm event.
Rights: Copyright 2012 by the American Geophysical Union
RMID: 0020116233
DOI: 10.1029/2011WR010489
Appears in Collections:Civil and Environmental Engineering publications
Environment Institute publications

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