An Evaluation of Urban Design Storm Sensitivity

Wenzel, Harry G.; Voorhees, Michael L.

doi:10.2166/wst.1984.0193

Cited by 14 publications

(14 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The calculation of storm properties is based on the identification of a single storm event. Various methods exist for identifying independent storm events [ Bonta and Rao , ; Pagan‐Trindad , ], such as arbitrary separation [ Huff , ], the autocorrelation method [ Wenzel and Voorhees , ], and a procedure based on rank correlation coefficients [ Grace and Eagleson , ]. We identify the independent storm events in each location using the criterion of a specified minimum dry period [ Jiang et al ., ; Menabde and Sivapalan , ; Palecki et al ., ; Restrepo‐Posada and Eagleson , ; Robinson and Sivapalan , ; Samuel and Sivapalan , ].…”

Section: Methodology Developmentsmentioning

confidence: 99%

Changes of seasonal storm properties in California and Nevada from an ensemble of climate projections

Jiang

Gautam³

et al. 2015

JGR Atmospheres

View full text Add to dashboard Cite

Precipitation characteristics, such as intensity, frequency, duration, and event pattern, are changing due to the increases in greenhouse gases, transition of ocean oscillation phases, etc. In this paper, we evaluate the ability of 11 realizations from multiple regional climate model (RCM)/global climate model pairs in the North American Regional Climate Change Assessment Program (NARCCAP) to simulate the seasonal variability and magnitude of storm properties, including storm duration, interstorm period, and storm intensity. The results indicate that NARCCAP RCMs simulate the seasonal variability better in the Greater Sacramento and San Joaquin than in Las Vegas, which may be due to the RCMs' inability to simulate local convective precipitation associated with the North American Monsoon. We also investigate the impacts of climate change on these storm characteristics by comparing the percentage change and absolute change of storm properties determined from NARCCAP historical runs and future runs. We find that individual RCMs exhibit great uncertainty in the percentage changes in storm duration, interstorm period, and average storm intensity. The ensemble means of storm properties across 11 future NARCCAP RCM projections show different responses to climate change in different locations. Our analyses provide guidelines for selecting the appropriate RCMs for hydrologic studies related to storm properties and provide forecasters and water managers with detailed information of future changes in storm properties so that they can sustainably manage water resources. Our results may also contribute to the nonstationary precipitation scenario development by incorporating the percentage changes of storm properties caused by human-induced warming into the stochastic precipitation model.

show abstract

Section: Methodology Developmentsmentioning

confidence: 99%

Changes of seasonal storm properties in California and Nevada from an ensemble of climate projections

Jiang

Gautam³

et al. 2015

JGR Atmospheres

View full text Add to dashboard Cite

show abstract

“…According to Bonta and Rao (1988), there are several methods for delimitating independent rainfall events, such as choosing a minimum inter-event time dry period (Dunkerley, 2008b), either arbitrarily or based on some reasoned criteria, such as an autocorrelation analysis (Asquith et al, 2005;Wenzel and Voorhees, 1981), choosing a rank correlation coefficient (Grace and Eagleson, 1967) or using the exponential method (Restrepo-Posada and Eagleson, 1982). The works that employ autocorrelation choose a minimum period based on the lag time at which the autocorrelation coefficient falls below a certain threshold.…”

Section: Introductionmentioning

confidence: 99%

Rainfall timing and runoff: The influence of the criterion for rain event separation

Molina-Sanchis

Lázaro

Arnau-Rosalén

et al. 2016

Journal of Hydrology and Hydromechanics

View full text Add to dashboard Cite

Rain is not uniform in time and space in semiarid areas and its distribution is very important for the runoff process. Hydrological studies usually divide rainfall into events. However, defining rain events is complicated, and rain characteristics vary depending on how the events are delimited. Choosing a minimum inter-event time (MIT) is a commonly used criterion. Our hypothesis is that there will be an optimal MIT that explains the maximum part of the variance of the runoff, with time to runoff used as a surrogate. The objective is to establish a procedure in order to decide upon this optimal MIT. We developed regressions between time to runoff (T 0 ) and three descriptive variables of rain. Our results show that the optimum MIT is 1 hour, which seems to be the minimum period of time required for water in larger macropores to drain and sufficiently modify the effect of antecedent soil moisture on the runoff generation process. Rain events are classified into three significantly different groups: (1) large and intense rains, (2) light rains on wet soil, and (3) light rains on dry soil. Intense rains produce most of the runoff, but there were significant differences between small events in the runoff generated. Of rain events, 63.75% are single-tip events, and many could be dew.

show abstract

“…Several methods (such as arbitrary separation, auto-correlation, the exponential method and the range of correlation) have been used to identify individual storms [55][56][57][58].…”

Section: Storm Events Identification and Selectionmentioning

confidence: 99%

Fully Stochastic Distributed Methodology for Multivariate Flood Frequency Analysis

Flores-Montoya

Sordo‐Ward

Mediero

et al. 2016

Water

View full text Add to dashboard Cite

An adequate estimation of the extreme behavior of basin response is essential both for designing river structures and for evaluating their risk. The aim of this paper is to develop a new methodology to generate extreme hydrograph series of thousands of years using an event-based model. To this end, a spatial-temporal synthetic rainfall generator (RainSimV3) is combined with a distributed physically-based rainfall-runoff event-based model (RIBS). The use of an event-based model allows simulating longer hydrograph series with less computational and data requirements but need to characterize the initial basis state, which depends on the initial basin moisture distribution. To overcome this problem, this paper proposed a probabilistic calibration-simulation approach, which considers the initial state and the model parameters as random variables characterized by a probability distribution though a Monte Carlo simulation. This approach is compared with two other approaches, the deterministic and the semi-deterministic approaches. Both approaches use a unique initial state. The deterministic approach also uses a unique value of the model parameters while the semi-deterministic approach obtains these values from its probability distribution through a Monte Carlo simulation, considering the basin variability. This methodology has been applied to the Corbès and Générargues basins, in the Southeast of France. The results show that the probabilistic approach offers the best fit. That means that the proposed methodology can be successfully used to characterize the extreme behavior of the basin considering the basin variability and overcoming the basin initial state problem.

show abstract

An Evaluation of Urban Design Storm Sensitivity

Cited by 14 publications

References 0 publications

Changes of seasonal storm properties in California and Nevada from an ensemble of climate projections

Changes of seasonal storm properties in California and Nevada from an ensemble of climate projections

Rainfall timing and runoff: The influence of the criterion for rain event separation

Fully Stochastic Distributed Methodology for Multivariate Flood Frequency Analysis

Contact Info

Product

Resources

About