scholarly journals Storm event-based frequency analysis method

2017 ◽  
Vol 49 (3) ◽  
pp. 700-710 ◽  
Author(s):  
Changhyun Jun ◽  
Xiaosheng Qin ◽  
Yeou-Koung Tung ◽  
Carlo De Michele
Keyword(s):  
Conventional Method ◽  
Frequency Analysis ◽  
Return Period ◽  
Rainfall Data ◽  
Storm Event ◽  
Analysis Method ◽  
Rainfall Characteristics ◽  
Study Results ◽  
Rainfall Depth ◽  
Event Based

Abstract In this study, a storm event-based frequency analysis method was proposed to mitigate the limitations of conventional rainfall depth–duration–frequency (DDF) analysis. The proposed method takes the number, rainfall depth, and duration of rainstorm events into consideration and is advantageous in estimation of more realistic rainfall quantiles for a given return period. For the purpose of hydraulics design, the rainfall depth thresholds are incorporated to retrieve the rainstorm events for estimating design rainfalls. The proposed method was tested against the observed rainfall data from 1961 to 2010 at Seoul, Korea and the computed rainfall quantiles were compared with those estimated using the conventional frequency analysis method. The study results indicated that the conventional method was likely to overestimate the rainfall quantiles for short rainfall durations. It represented that the conventional method could reflect rainfall characteristics of actual rainstorm events if longer durations (like 24 hours) were considered for estimation of design rainfalls.

Multivariate frequency analysis of urban rainfall characteristics using three-dimensional copulas

2018 ◽  
Vol 2017 (1) ◽  
pp. 206-218 ◽  
Author(s):  
Chenglin Liu ◽  
Yuwen Zhou ◽  
Jun Sui ◽  
Chuanhao Wu
Keyword(s):  
Probability Distribution ◽  
Frequency Analysis ◽  
Three Dimensional ◽  
Rainfall Data ◽  
Rainfall Characteristics ◽  
Design Rainfall ◽  
Rainfall Depth ◽  
Multivariate Frequency Analysis ◽  
Continuous Rainfall

Abstract Urban runoff is a major cause of urban flooding and is difficult to monitor in the long term. In contrast, long term continuous rainfall data are generally available for any given region. As a result, it has become customary to use design rainfall depth as a proxy for runoff in urban hydrological analyses, with an assumption of the same frequency for runoff and rainfall. However, this approach has lack of overall coordination and cannot fully reflect the variability of rainfall characteristics. To address this issue, this study presents a three-dimensional copula-based multivariate frequency analysis of rainfall characteristics based on a long term (1961–2012) rainfall data from Guangzhou, China. Firstly, continuous rainfall data were divided into individual rainfall events using the rainfall intensity method. Then the characteristic variables of rainfall (design rainfall depth, DRD; total rainfall depth, TRD; peak rainfall depth, PRD) were sampled using the annual maximum method. Finally, a copula method was used to develop the multivariate joint probability distribution and the conditional probability distribution of rainfall characteristics. The results showed that the copula-based method is easy to implement and can better reflect urban rainstorm characteristics. It can serve a scientific reference for urban flood control and drainage planning.

scholarly journals How Is the Intensity of Rainfall Events Best Characterised? A Brief Critical Review and Proposed New Rainfall Intensity Index for Application in the Study of Landsurface Processes

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 929 ◽  
Author(s):  
David Dunkerley
Keyword(s):  
Rainfall Intensity ◽  
Clock Period ◽  
Event Duration ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Convective Storms ◽  
Intensity Index ◽  
Rainfall Depth ◽  
Minute Interval ◽  
Event Based

In many studies of landsurface processes, the intensity of rainfall events is expressed with clock-period indexes such as I30, the wettest 30-minute interval within a rainfall event. Problematically, the value of I30 cannot be estimated for rainfall events shorter than 30 min, excluding many intense convective storms. Further, it represents a diminishing proportion of increasingly long rainfall events, declining to <2% of the duration of a 30-hour event but representing 25% of the duration of a two-hour event. Here, a new index termed EDf5 is proposed: It is the rainfall depth in the wettest 5% of the event duration. This can be derived for events of any duration. Exploratory determinations of EDf5 are presented for two Australian locations with contrasting rainfall climatologies—one arid and one wet tropical. The I30 index was similar at both sites (7.7 and 7.9 mm h−1) and was unable to differentiate between them. In contrast, EDf5 at the arid site was 7.4 mm h−1, whilst at the wet tropical site, it was 3.8 mm h−1. Thus, the EDf5 index indicated a greater concentration of rain at the arid site where convective storms occurred (i.e., the intensity sustained for 5% of event duration at that site is higher). The EDf5 index can be applied to short, intense events that can readily be included in the analysis of event-based rainfall intensity. I30 therefore appears to offer less discriminatory power and consequently may be of less value in the investigation of rainfall characteristics that drive many important landsurface processes.

Bias introduced in rainfall risk assessment by a rain gauges network

1998 ◽  
Vol 37 (11) ◽  
pp. 97-104
Author(s):  
L. Neppel ◽  
M. Desbordes ◽  
J. M. Masson
Keyword(s):  
Risk Assessment ◽  
Frequency Analysis ◽  
Return Period ◽  
Return Periods ◽  
Rainfall Events ◽  
Rain Gauges ◽  
Spatial Approach ◽  
Rainfall Depth ◽  
Rain Gauges Network

When large periods of observation are considered, the densest information are often a collection of the daily rain gauges network. As this information is scattered in space, the stochastic results and specially the rainfall risk assessment, are biased because of the rainfall events that are not ‘observed’ by the network. Rainfall risk can be assessed using a punctual approach with the estimation of regional return period of a punctual rainfall depth exceeding a given value, or using a spatial approach with the frequency analysis of the areas of isohyets defined at a given rain threshold τ. This last approach consists, for a given τ, in estimating the return period of isohyet areas. Using simulation, a method of unbiased rainfall risk assessment is proposed for the Languedoc-Roussillon region (France). It has been shown that the bias influence is negligible for the regional return periods of isohyet areas, for 24-hour and 48-hour duration, when compared to their confident limits. On the contrary the return periods of punctual rainfall depths above a given value are more sensitive: for values above 170 mm/24h and 270 mm/48h, the biased return periods could be up to 3 times overestimated.

scholarly journals Flood Frequency Analysis Using Participatory GIS and Rainfall Data for Two Stations in Narok Town, Kenya

Hydrology ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 90 ◽  
Author(s):  
Houessou-Dossou ◽  
Gathenya ◽  
Njuguna ◽  
Gariy
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Computational Modelling ◽  
Flood Frequency ◽  
Meteorological Station ◽  
Distribution Functions ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Return Periods ◽  
Participatory Gis

Flood management requires in-depth computational modelling through assessment of flood return period and river flow data in order to effectively analyze catchment response. The participatory geographic information system (PGIS) is a tool which is increasingly used for collecting data and decision making on environmental issues. This study sought to determine the return periods of major floods that happened in Narok Town, Kenya, using rainfall frequency analysis and PGIS. For this purpose, a number of statistical distribution functions were applied to daily rainfall data from two stations: Narok water supply (WS) station and Narok meteorological station (MS). The first station has a dataset of thirty years and the second one has a dataset of fifty-nine (59) years. The parameters obtained from the Kolmogorov–Smirnov (K–S) test and chi-square test helped to select the appropriate distribution. The best-fitted distribution for WS station were Gumbel L-moment, Pareto L-moment, and Weibull distribution for maximum one day, two days, and three days rainfall, respectively. However, the best-fitted distribution was found to be generalized extreme value L-moment, Gumbel and gamma distribution for maximum one day, two days, and three days, respectively for the meteorological station data. Each of the selected best-fitted distribution was used to compute the corresponding rainfall intensity for 5, 10, 25, 50, and 100 years return period, as well as the return period of the significant flood that happened in the town. The January 1993 flood was found to have a return period of six years, while the April 2013, March 2013, and April 2015 floods had a return period of one year each. This study helped to establish the return period of major flood events that occurred in Narok, and highlights the importance of population in disaster management. The study’s results would be useful in developing flood hazard maps of Narok Town for different return periods.

Analisis Karakteristik Curah Hujan pada Kawasan Hunian dan Komersial Pantai Indah Kapuk (PIK) 2 Cluster “C”

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Nur Afifah Sari ◽  
Etih Hartati ◽  
M. Candra Nugraha
Keyword(s):  
Return Period ◽  
Rainfall Intensity ◽  
Hydrological Cycle ◽  
Regional Scale ◽  
Daily Rainfall ◽  
Global Scale ◽  
Rainfall Data ◽  
Rainfall Characteristics ◽  
Climate Conditions ◽  
Drainage Channels

<p class="IJOPCMKeywards">Based on the hydrological cycle, one of the main water sources is rainwater. weather or climate conditions that occur will greatly affect the nature and condition of a rain or rainy season. On a global scale, the existence of water naturally is constant, only occurs in variations both in time and space on a regional scale. Analysis of the rainfall characteristics of Pantai Indah Kapuk (PIK) residential and commercial areas 2  Cluster "C" in Tangerang Regency, Banten Province, is for to find out the intensity of rainfall used for drainage planning. The daily rainfall data used includes 5 rain catching stations with a duration of 25 years (1994 - 2018). The Van Breen method is used to process rainfall data within a certain period into rainfall intensity with various times for drainage planning used. In the planning of drainage channels the rainfall return period used is PUH 2 for tertiary lines with selected rainfall data of 192 mm / day and PUH 5 for secondary lines with selected rainfall data of 219 mm / day. The IDF curve shows that rainfall intensity is affected by the time and return period of rainfall, where the shorter the rainfall time and the greater the return period of rainfall, the higher the intensity of rainfall produced.</p>

scholarly journals Application of Frequency Analysis on Peak River Discharge toward the Cumulative Floatable Litter Load at Log Boom Sungai Batu

2019 ◽  
Vol 266 ◽  
pp. 02002
Author(s):  
Nur Khaliesah Abdul Malik ◽  
Nor Rohaizah Jamil ◽  
Latifah Abd Manaf ◽  
Mohd Hafiz Rosli ◽  
Zulfa Hanan Ash’aari ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
River Discharge ◽  
Linear Regression Analysis ◽  
Gumbel Distribution ◽  
Environmental Issues ◽  
Decision Making Process ◽  
Rapid Urbanization ◽  
Distribution Method ◽  
Period 2

The accumulation of floatable litter in the river is mainly influenced by the increasing number of human population, rapid urbanization and development which indirectly lead to the changes of hydrological processes in river discharge, decreasing the water quality and aesthetical value of the river. The main objective of this paper is to determine the cumulative floatable litter load captured at the log boom during the extreme events by using the Gumbel distribution method for frequency analysis in river discharge of Sungai Batu. The annual maximum river discharge for a period of 35 years (1982 to 2016) was used in Gumbel distribution method to obtain the discharge for different return period (2, 5, 10, 25, 50, 100, and 200). The result shows that the estimated discharge (103.17 m³/s) can estimate the cumulative floatable litter load (53267.27 kg/day) at 50 years return period. The R2 value obtained from non – linear regression analysis is 0.9986 indicate that Gumbel distribution is suitable to predict the expected discharge of the river. This study is very crucial for the related agencies in highlighting this environmental issues for their future references which can be used as a guidelines during the decision making process in making better improvement.

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