Application of regional rainfall frequency analysis on seven sites of Sindh, Pakistan

Hussain, Zamir; Shahzad, Mirza Naveed; Abbas, Kamran

doi:10.1007/s12205-016-0946-y

Cited by 7 publications

(11 citation statements)

References 23 publications

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“…The principal statistical assumptions of at-site and RFA include independence, stationarity and randomness of data series at each gauging site (see e.g., Ul Hassan et al 2019;Hussain et al 2017;Shahzadi et al 2013 andKousar et al 2020). To investigate the serial correlation of the observed data series at each gauging site, we use the lag-1 correlation coefficient (r).…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, further modelling is required to estimate the index rainfall at ungauged sites in the region (Hosking and Wallis, 1997). The use of simple/multiple linear regression (MLR) model to estimate the extreme quantiles at gauges/ungauged sites is commonly traced in the literature (see e.g., Al Mamun et al 2018;Hussain et al 2017;Modarres 2008;Um et al 2010;Naoum and Tsanis 2004b;Hailegeorgis and Alfredsen 2017). To estimate the flood quantiles at ungauged sites, Desai and Ouarda (2021) have utilized random forest (RF) regression.…”

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confidence: 99%

“…Malekinezhad and Zare-Garizi (2014) and Forestieri et al (2018) use mean annual precipitation as an explanatory variable in a simple linear regression model to predict index rainfall. Szolgay et al (2009) and Hussain et al (2017) develop a linear regression model to predict index rainfall using elevation as an explanatory variable.…”

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confidence: 99%

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Regional frequency analysis of annual daily rainfall maxima in Skåne, Sweden

Hassan

Noreen

Ahmed

2021

Intl Journal of Climatology

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Extreme daily rainfall events are critical for the urban drainage system, human life, agriculture and small catchments. The information about extreme rainfall magnitudes and frequencies is immensely important for civil engineers, city planners, scientists related to water management, rescue operations and flood control works. This study illustrates the results of regional frequency analysis (RFA) of annual maximum daily rainfall (AMDR) of Skåne County, Sweden. L-moments based heterogeneity measure (H) reveals that the Skåne County is a homogeneous region. Based on the L-moment ratio diagram and Z Dist statistic results, the generalized normal (GNO) distribution is selected as the most suitable regional distribution. The accuracy measures used in K-fold cross validation indicate that support vector machine (SVM) model is an appropriate model to find the index rainfall at ungauged sites in the region. The sites characteristics, elevation and latitude are identified as the most important variables to explain the variation in mean annual maximum daily rainfall (MAMDR). Finally, spatial maps of predicted MAMDR for different return periods are constructed by using index rainfall combined with regional quantiles. Spatial maps offer an overall view of the expected MAMDR in the region that is helpful for multiple decision makers including infrastructure planners, city planners, emergency managers, engineers and many others. K E Y W O R D S K-fold cross validation, L-moments, Monte Carlo simulation, quantile estimates, regional frequency analysis, spatial map 1 | INTRODUCTION Daily extreme rainfall is one of the utmost environmental events which cause sizeable damages throughout the world. The rainfall recorded in the last century was the highest over the past 8,500 years (Hong et al., 2014). A reliable estimate of extreme rainfall magnitude is important for flood management, irrigation, rescue operations, water management, construction of urban drainage systems and many other purposes. Skåne is the tenth largest county of Sweden. It has the best agricultural land and is known as a breadbasket of Sweden. It stands for about half of Sweden's food production (Skåne Region, 2014). Rainfall is an important factor for agriculture in Skåne. Skåne agriculture and food industries are highly dependent on this hydrological

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

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Regional frequency analysis of annual daily rainfall maxima in Skåne, Sweden

Hassan

Noreen

Ahmed

2021

Intl Journal of Climatology

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“…RFA approach based on the L-moments method involves the suitability of the data, detection of homogeneous regions/groups, and selection of regional frequency distribution and quantiles estimation for selected distribution. Many studies have been conducted using RFA based on the L-method in a different part of the world, some of these are; Malekinezhad and Garizi (2014), Majumder et al (2015), Liu et al (2015), Ahmad et al (2017), Hussain et al (2017), Khan et al (2017) and Dad and Benabdesselam (2018). Past studies of rainfall distribution in Haryana include Hooda (1998Hooda ( , 2006, Babu and Hooda (2018), and Nain and Hooda (2019a).…”

Section: Introductionmentioning

confidence: 99%

Regional Frequency Analysis of Maximum Monthly Rainfall in Haryana State of India Using L-Moments

Nain

Hooda

2021

JRSS

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The paper aims to select the appropriate regional frequency distribution for the maximum monthly rainfall and estimation of quantiles using L-moments for the 27 rain gauge stations in Haryana. These 27 rain gauge stations were grouped into three homogeneous regions (Region-1, Region-2, and Region-3) using Ward’s method of cluster analysis. To confirm the homogeneity of each region, L-moments based measure of heterogeneity was used. For each homogeneous region, a regional distribution was selected with the help of the L-moments ratio diagram and goodness-of-fit test. Results of the goodness-of-fit test and L-moments ratio diagram indicated that Generalized Logistic and Generalized Extreme Value distributions were best- fitted regional frequency distributions for the Region-1 and Region-2 respectively while for Region-3, Pearson Type-3) was best-fitted distribution. The quantiles for each region were calculated and the regional growth curves were developed. The accuracy measurements were determined using Monte Carlo simulations for the regional quantiles. Results of simulations showed that uncertainty in regional quantiles measured by Root Mean Square Error value and 90 percent error limits were small when the return period was low but uncertainty in quantiles increases as the return period increases.

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“…Therefore, a comparison of the estimates provided by Shahzadi et al (2013) with the results of current study has been provided in the later section of the paper, to establish the usefulness of the current methodology. In another study, Hussain et al (2017) illustrated the application of regional rainfall frequency analysis using rainfall data of seven sites of Sindh, Pakistan with annual maximum monthly rainfall totals as variable of analysis. The study concluded that three distributions namely: Generalized Normal, Pearson Type III and Generalized Pareto are suitable for the observed data series of the study region.…”

Section: Introductionmentioning

confidence: 99%

Rainfall Frequency Analysis Using Frechet and Log-Logistic Distributions of Sites of Azad Jammu and Kashmir, Pakistan

Hussain¹

2019

Appl. Ecol. Env. Res.

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The paper illustrates the application of at-site frequency analysis using relatively nontraditional probability distributions adopting four methods of parameter estimation using annual maximum rainfall series (AMRS) (from 1980 to 2015) of three sites; Muzaffarabad, Garhi Dupatta and Kotli of Azad Jammu and Kashmir, Pakistan. Critical assumptions related to AMRS for frequency analysis have been validated through run test (to check the randomness of AMRS at each site) and Mann Whitney test (to check the distribution of AMRS at given sites as identical or not). Two probability distributions; Frechet and Log-logistic have been used as candidate distributions to model AMRS at given sites. The parameters of these distributions have been estimated using four methods; Probability Weighted Moments Estimation (PWME), Maximum Likelihood Estimation (MLE), Bayesian Estimation (BE) and Moments Estimation (ME) methods. The Kolmogorov Smirnov test has been used as goodnessof-fit criteria. The results show suitability of the selected probability distributions for the observed AMRS series at given sites with BE and MLE methods as adequate for estimation. Moreover, the results indicate that ME method is not a preferred choice for the estimation of parameters and quantiles for various return periods.

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Application of regional rainfall frequency analysis on seven sites of Sindh, Pakistan

Cited by 7 publications

References 23 publications

Regional frequency analysis of annual daily rainfall maxima in Skåne, Sweden

Regional frequency analysis of annual daily rainfall maxima in Skåne, Sweden

Regional Frequency Analysis of Maximum Monthly Rainfall in Haryana State of India Using L-Moments

Rainfall Frequency Analysis Using Frechet and Log-Logistic Distributions of Sites of Azad Jammu and Kashmir, Pakistan

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