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

2021 ◽  
Author(s):  
Mohit Nain ◽  
B. K. Hooda
Keyword(s):  
Return Period ◽  
Goodness Of Fit ◽  
Regional Distribution ◽  
Rain Gauge ◽  
Monthly Rainfall ◽  
Regional Frequency Analysis ◽  
Goodness Of Fit Test ◽  
Pearson Type ◽  
L Moments ◽  
Regional Frequency

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.

scholarly journals Regional frequency analysis of daily maximum rainfall in Haryana

MAUSAM ◽  
2021 ◽  
Vol 72 (4) ◽  
pp. 835-846
Author(s):  
MOHIT NAIN ◽  
B. K. HOODA
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Regional Distribution ◽  
Rain Gauge ◽  
Quantile Estimation ◽  
Regional Frequency Analysis ◽  
Daily Maximum ◽  
Maximum Rainfall ◽  
L Moments ◽  
Regional Frequency

This paper is sets-out for the regional frequency analysis of daily maximum rainfall from the 27 rain gauge stations in Haryana using L-moments. As the distribution of rainfall varies spatially in Haryana, the 27 rain gauge stations are grouped into three clusters namely, cluster C1, C2 and C3 using Ward’s clustering method and homogeneity of clusters was confirmed using L-moments-based Heterogeneity measure (H). Using goodness-of-fit measure ( DIST Z ) and L-moment ratios diagram, suitable regional frequency distributions were selected among five candidate distributions;Generalized Logistic (GLO), Generalized Extreme Value (GEV),Generalized Normal (GNO), Generalized Pareto (GPA), and Pearson Type-3 (PE3) for each cluster. Results showed that PE3 and GNO were good fitted regional distribution for the cluster C1 and GEV, PE3 and GNO fitted for cluster C2 while for cluster C3; GLO and GEV were good fitted regional distribution. To select a robust distribution among good fitted distributions accuracy measures calculated using Monte Carlo simulations for each cluster. The simulation result showed that PE3 was the best choice for quantile estimation for cluster C1. For cluster C2, PE3 was the best choicefor a large return period and GEV was best for a small return period. For cluster C3, GEV was the most suitable distribution for quantile estimation. Using these robust distributions rainfall quantiles were estimated at each rain gauge station from 2 to 100 year return periods. These estimated rainfall quantiles may be rough guideline for planning and designing hydraulic structures by policy makers and structural engineers.

Regional frequency analysis of daily maximum rainfall in Haryana

MAUSAM ◽  
2021 ◽  
Vol 72 (4) ◽  
pp. 835-846
Author(s):  
MOHIT NAIN ◽  
B. K. HOODA
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Regional Distribution ◽  
Rain Gauge ◽  
Quantile Estimation ◽  
Regional Frequency Analysis ◽  
Daily Maximum ◽  
Maximum Rainfall ◽  
L Moments ◽  
Regional Frequency

This paper is sets-out for the regional frequency analysis of daily maximum rainfall from the 27 rain gauge stations in Haryana using L-moments. As the distribution of rainfall varies spatially in Haryana, the 27 rain gauge stations are grouped into three clusters namely, cluster C1, C2 and C3 using Ward’s clustering method and homogeneity of clusters was confirmed using L-moments-based Heterogeneity measure (H). Using goodness-of-fit measure (  ) and L-moment ratios diagram, suitable regional frequency distributions were selected among five candidate distributions; Generalized Logistic (GLO), Generalized Extreme Value (GEV),Generalized Normal (GNO), Generalized Pareto (GPA), and Pearson Type-3 (PE3) for each cluster. Results showed that PE3 and GNO were good fitted regional distribution for the cluster C1 and GEV, PE3 and GNO fitted for cluster C2 while for cluster C3; GLO and GEV were good fitted regional distribution. To select a robust distribution among good fitted distributions accuracy measures calculated using Monte Carlo simulations for each cluster. The simulation result showed that PE3 was the best choice for quantile estimation for cluster C1. For cluster C2, PE3 was the best choicefor a large return period and GEV was best for a small return period. For cluster C3, GEV was the most suitable distribution for quantile estimation. Using these robust distributions rainfall quantiles were estimated at each rain gauge station from 2 to 100 year return periods. These estimated rainfall quantiles may be rough guideline for planning and designing hydraulic structures by policy makers and structural engineers.

scholarly journals Regional Rainfall Frequency Analysis on Seven Sites of Punjab, Pakistan using L-moments

2020 ◽  
Vol 2 (2) ◽  
pp. 25-35
Author(s):  
Uzma Nawaz ◽  
Zamir Hussain ◽  
Tooba Nihal ◽  
Saira Usman
Keyword(s):  
Frequency Analysis ◽  
Goodness Of Fit ◽  
Regional Distribution ◽  
Return Periods ◽  
Goodness Of Fit Test ◽  
Rainfall Frequency ◽  
Pearson Type ◽  
L Moments ◽  
Rainfall Frequency Analysis ◽  
Regional Rainfall

The hydro-meteorological variables of extreme rainfall are not easy to explain due to unexpected changes in climate and varied usage of water with growing population. Regional rainfall frequency analysis is the one such method that is useful for the requirement of more accurate estimates of rainfall yearly or desineally for the regions having lack of fresh water resources. The series of Annual Maximum Monthly Rainfall Totals (AMMRT) has been used for the seven sites of northern Punjab, Pakistan using L-moments. The results of different test, the run test, lag-1 correlation and Mann-Whitney U test illustrate that the data series of the seven sites of northern Punjab were found random and independently and identically distributed and have no serial correlation. Heterogeneity measure exposed that the region is homogeneous and discordancy measure gives the evidence that no site is discordant among the seven. The result of goodness of fit test including L-moment Ratio diagrams, ZDIST statistic and Mean Absolute Deviation Index exposed the Pearson Type III (PE3), Generalized Normal (GNO) and Generalized Extreme Value(GEV) are best suitable of the regional distribution for the quantiles estimation. The quantiles estimates obtained for different return periods. A linear regression model was developed with good fit between the at site characteristics and the mean of the AMMRT of the sites. The estimates of the study may be used for the estimation of the rainfall quantiles of the seven sites for different return periods. The estimates will be useful to design future preventive measures for the harmful impact of hydro meteorological events at these sites in Punjab Pakistan.

scholarly journals Drought Analysis in East Nusa Tenggara (Indonesia) Using Regional Frequency Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Heri Kuswanto ◽  
Anggi Wahyu Puspa ◽  
Imam Safawi Ahmad ◽  
Fausania Hibatullah
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Extreme Drought ◽  
Regional Frequency Analysis ◽  
Drought Risk ◽  
Drought Analysis ◽  
Daily Precipitation Data ◽  
Pearson Type ◽  
Normal Rainfall ◽  
Regional Frequency

Drought is a condition of a shortage of water that has an impact on economic activity. This research studies the severe drought area in Indonesia using Regional Frequency Analysis (RFA), based on daily precipitation data recorded at nine stations. The analysis reveals five homogeneous regions, based on discordancy and heterogeneity tests. Furthermore, the L-moment approach is applied to investigate the regional distribution and suggests that the Pearson type III distribution is the distribution that best fits the five regions. This distribution is also used to calculate the regional growth curve that is employed in the drought analysis. The drought return period analysis, for conditions of 40% of normal rainfall, concludes that the region containing the Fransiskus Xaverius, Gewayantana, and Mali stations has the highest drought risk, indicated by the fastest return period estimate of 2 years and 4 months. Moreover, the extreme drought analysis shows that two of the regions have the potential to experience the return of extreme drought, with less than 20% of normal rainfall, in less than four years.

scholarly journals Maximum Monthly Rainfall Analysis Using L-Moments for an Arid Region in Isfahan Province, Iran

2007 ◽  
Vol 46 (4) ◽  
pp. 494-503 ◽  
Author(s):  
S. Saeid Eslamian ◽  
Hussein Feizi
Keyword(s):  
Frequency Analysis ◽  
Water Resource Management ◽  
Arid Zone ◽  
Meteorological Drought ◽  
Monthly Rainfall ◽  
Regional Frequency Analysis ◽  
Model Parameters ◽  
Rainfall Analysis ◽  
Pearson Type ◽  
L Moments

Abstract Developing methods that can give a suitable prediction of hydrologic events is always interesting for both hydrologists and statisticians, because of its importance in designing hydraulic structures and water resource management. Because of the computer revolution in statistical computation and lack of robustness in at-site frequency analysis, since early 1990 the application of regional frequency analysis based on L-moments has been considered more for flood analysis. In this study, the above-mentioned method has been used for the selection of parent distributions to fit maximum monthly rainfall data of 18 sites in the Zayandehrood basin, Iran, and as a consequence the generalized extreme-value and Pearson type-III distributions have been selected and model parameters have been estimated. The obtained extreme rainfall values can be used for meteorological drought management in the arid zone.

scholarly journals Regional Frequency Analysis of Drought Severity and Duration in Karkheh River Basin - Iran Using Univariate L-Moments Method

2021 ◽  
Author(s):  
Saeideh Parvizi ◽  
Saeid Eslamian ◽  
Mahdi Gheysari ◽  
Alireza Gohari ◽  
Saeid Soltani Kopai
Keyword(s):  
River Basin ◽  
Frequency Analysis ◽  
Hydrological Drought ◽  
The Other ◽  
Agricultural Drought ◽  
Regional Frequency Analysis ◽  
Goodness Of Fit Test ◽  
L Moments ◽  
Karkheh River Basin ◽  
Regional Frequency

Abstract Drought is one of the natural disasters that causes a great damage to the human life and natural ecosystems. The main differences are in the gradual effect of drought over a relatively long period; impossibility of accurately determining time of the beginning and end of drought; and geographical extent of the associated effects. On the other hand, lack of a universally accepted definition of drought has added to the complexity of this phenomenon. In the last decade, due to increasing frequency of drought in Iran and reduction of water resources, its consequences have become apparent and have caused problems for planners and managers. Therefore, in this study, to investigate severity and duration of meteorological, hydrological and agricultural drought in Karkheh River basin, regional frequency analysis of standardized precipitation index ( SPI ), standardized evapotranspiration index ( SEI ), standardized runoff index ( SRI ) and standardized soil moisture index ( SSI ) was performed using L-moments. Then, using Hosking and Wallis heterogeneity test, basin was divided into four homogeneous areas. After that, based on the Z statistic of goodness-of-fit test for each distribution, the best regional distribution function for each homogeneous region was selected. The results showed that hydrological drought occurs with a very short time delay in Karkheh River Basin after the meteorological drought and two indicators show meteorological and hydrological drought conditions well. Agricultural drought occurs after meteorological and hydrological drought, respectively, and its severity and duration are less than the other indicators. Meteorological, hydrological and agricultural droughts do not occur at the same time in all of the years and in general, the SPI drought Index shows the most severe droughts compared with the other three indices.

scholarly journals Regional frequency analysis of extreme precipitation in northeastern Algeria

2018 ◽  
Vol 39 (1) ◽  
pp. 27-37
Author(s):  
Soufiane Dad ◽  
Tamara Benabdesselam
Keyword(s):  
Frequency Analysis ◽  
Regional Distribution ◽  
Regional Frequency Analysis ◽  
Study Region ◽  
Site Model ◽  
L Moments ◽  
Definition Of ◽  
Homogeneous Regions ◽  
Regional Frequency

AbstractThe aim of the study is to improve the quality of estimating of the annual maximum daily precipitations of the northeastern area of Algeria. The regional frequency analysis based on L-moments was used. The investigated area is represented by 58 measuring stations. The main stages of the study were the definition of homogeneous regions and the identification of the regional distribution. It has been defined that the study region is homogeneous in terms of L-moments ratios despite the climatic differences within the region. Among the different tested distributions; the generalised extreme value (GEV) distribution has been identified as the most appropriate regional distribution for modelling precipitation in the region. The growth curve, derived from the regional distribution, was established. Therefore, to estimate the different return period’s precipitation quantiles in a given site of the region, the mean precipitation of the site has to be multiplied by the corresponding regional quantile (growth factor). Comparison of the quantiles estimated from the regional and at-site frequency analysis showed that in the majority of stations (82.8%) at-site model underestimates the quantiles having high return periods.

scholarly journals At-site and regional frequency analysis of extreme precipitation from radar-based estimates

2017 ◽  
Author(s):  
Edouard Goudenhoofdt ◽  
Laurent Delobbe ◽  
Patrick Willems
Keyword(s):  
Confidence Interval ◽  
Frequency Analysis ◽  
Extreme Precipitation ◽  
Rain Gauge ◽  
Regional Frequency Analysis ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Rain Gauges ◽  
Rainfall Extremes ◽  
Regional Frequency

Abstract. In Belgium, only rain gauge time-series have been used so far to study extreme precipitation at a given location. In this paper, the potential of a 12-year quantitative precipitation estimation (QPE) from a single weather radar is evaluated. For the period 2005–2016, independent sliding 1 h and 24 h rainfall extremes from automatic rain gauges and collocated radar estimates are compared. The extremes are fitted to the exponential distribution using regression in QQ-plots with a threshold rank which minimises the mean squared error. A basic radar product used as reference exhibits unrealistic high extremes and is not suitable for extreme value analysis. For 24 h rainfall extremes, which occur partly in winter, the radar-based QPE needs a bias correction. A few missing events are caused by the wind drift of convective cells and strong radar signal attenuation. Differences between radar and gauge values are caused by spatial and temporal sampling, gauge rainfall underestimations and radar errors due to the relation between reflectivity and rain rate. Nonetheless the fit to the QPE data is within the confidence interval of the gauge fit, which remains large due to the short study period. A regional frequency analysis is performed on radar data within 20 km of the locations of 4 rain gauges with records from 1965 to 2008. Assuming that the extremes are correlated within the region, the fit to the two closest rain gauge data is within the confidence interval of the radar fit, which is small due to the sample size. In Brussels, the extremes on the period 1965–2008 from a rain gauge are significantly lower than the extremes from an automatic gauge and the radar on the period 2005–2016. For 1 h duration, the location parameter varies slightly with topography and the scale parameter exhibits some variations from region to region. The radar-based extreme value analysis can be extended to other durations.

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