scholarly journals Design storm estimation in Tuscany (Italy) through regional frequency analysis and generalized additive modelling

2020 ◽  
Author(s):  
Matteo Pampaloni ◽  
Virginia Vannacci ◽  
Enrica Caporali ◽  
Chiara Bocci ◽  
Valentina Chiarello ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Central Italy ◽  
Additive Model ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Extreme Value ◽  
Regional Frequency Analysis ◽  
Annual Maximum ◽  
Design Storm ◽  
Regional Frequency

<p>In the field of extreme hydrological events, design storm identification represents key element due to the links with flood risk as well as water resources availability and management.</p><p>In order to obtain a regional frequency analysis for studying and understanding the annual maximum of daily rainfall, two different statistic methods are proposed here on Tuscany Region (Central Italy). The first method concerns with the hierarchical approach on three levels: the studied area is divided into homogeneous regions and sub-regions, then the statistical homogeneity within the regions is verified through several homogeneity tests. Furthermore, the Two-Component Extreme Value (TCEV) probability distribution of the extreme rainfall is considered identical within each homogeneous region unless a scale factor, i.e. the index rainfall, estimated through a multivariate model based on climatic and geomorphological characteristics.</p><p>A Generalized Additive Model (GAM) for extremes is also implemented on the studied area assuming that the observations follow a Generalized Extreme Value - GEV distribution whose locations are spatially dependent. The research has been carried out starting from a general set of 922 rain gauges (Regional Hydrological Service of Tuscany – SIR), on time series of annual maximum of daily rainfall recorded from 1916 to 2017. The application of the two methods is discussed based on the comparison between the maps of the design storm for daily duration and 2, 20, 50, 100 e 200 years return periods.</p>

scholarly journals Regional frequency analysis of extreme rainfall in Belgium based on radar estimates

2017 ◽  
Vol 21 (10) ◽  
pp. 5385-5399 ◽  
Author(s):  
Edouard Goudenhoofdt ◽  
Laurent Delobbe ◽  
Patrick Willems
Keyword(s):  
Confidence Interval ◽  
Frequency Analysis ◽  
Extreme Rainfall ◽  
Extreme Value ◽  
Regional Frequency Analysis ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Temporal Sampling ◽  
Rainfall Extremes ◽  
Regional Frequency

Abstract. In Belgium, only rain gauge time series have been used so far to study extreme rainfall 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, 1 and 24 h rainfall extremes from automatic rain gauges and collocated radar estimates are compared. The peak intensities are fitted to the exponential distribution using regression in Q-Q 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 associated with convective cells and strong radar signal attenuation. Differences between radar and gauge rainfall values are caused by spatial and temporal sampling, gauge underestimations and radar errors. 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 for 1 h duration is performed at the locations of four gauges with 1965–2008 records using the spatially independent QPE data in a circle of 20 km. The confidence interval of the radar fit, which is small due to the sample size, contains the gauge fit for the two closest stations from the radar. In Brussels, the radar extremes are significantly higher than the gauge rainfall extremes, but similar to those observed by an automatic gauge during the same period. The extreme statistics exhibit slight variations related to topography. The radar-based extreme value analysis can be extended to other durations.

REGIONAL FREQUENCY ANALYSIS OF ANNUAL MAXIMUM RAINFALLS IN MINDANAO

2021 ◽  
Vol 68 (2) ◽  
pp. 151-172
Author(s):  
Noel G. Cuarteros Jr. ◽  
Archemedes A. Lague
Keyword(s):  
Frequency Analysis ◽  
Regional Frequency Analysis ◽  
Annual Maximum ◽  
Regional Frequency

scholarly journals Hujan rancangan berdasarkan analisis frekuensi regional dengan metode tl-moment

2017 ◽  
Vol 12 (1) ◽  
pp. 1-16
Author(s):  
Segel Ginting ◽  
William M Putuhena
Keyword(s):  
Frequency Analysis ◽  
Probability Distributions ◽  
Large Error ◽  
Extreme Value ◽  
Regional Frequency Analysis ◽  
Generalized Extreme Value ◽  
Generalized Pareto ◽  
Moment Ratio ◽  
Moments Method ◽  
Regional Frequency

The designstorm wereestimated by applying the regional frequency analysis provides benefits to a datasetwith limited amount of data has many advantages. Minimum data used in calculating the amount of design stromhas a very large error for higherreturn period. Therefore, the regional frequency analysis was used based on TL-moments method. There arethree types of probability distributions used in this study, namely the Generalized Extreme Value (GEV), Generalized Pareto (GPA) and the Generalized Logistic (GLO). Two of the three typesprobability distributions are the best choice by the TL-moment ratio diagrams which are Generalized Extreme Value, and Generalized Logistic. Ananother analysis wasconducted by the Z test and the Generalized Extreme Value (GEV) gives the best results. Therefore, the designs strom which was estimated based on the regional frequency analysis in Jakarta watersheds using the Generalized Extreme Value (GEV) has been determined.

scholarly journals Hierarchical Bayesian Model for Assessing Extreme Daily Rainfall Through Combining Climatic and Topographic Information

2021 ◽  
Vol 21 (4) ◽  
pp. 1-12
Author(s):  
Jeonghoon Lee ◽  
Jeongeun Won ◽  
Jeonghyeon Choi ◽  
Sangda Kim
Keyword(s):  
Frequency Analysis ◽  
Bayesian Model ◽  
Daily Rainfall ◽  
Regional Frequency Analysis ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Model ◽  
Model Framework ◽  
Generalized Logistic Distribution ◽  
Topographic Information ◽  
Regional Frequency

Frequency analysis of the annual maximum rainfall time series is essential for designing infrastructures to provide protection against local floods and related events. However, the results of the frequency analysis obtained are ambiguous. In this study, we aimed to develop a spatial hierarchical Bayesian model framework through combining the climatic and topographic information. To confirm the applicability of the proposed method, the results of at-site frequency analysis and regional frequency analysis using the index flood method were compared in the Busan-Ulsan-Gyeongnam region. Furthermore, a hierarchical Bayesian model was developed, in which the parameters of the generalized logistic distribution comprised relatively simple covariate relationships upon considering the possibility of expansion into various probability distributions and more complex covariate structures. The uncertainty of this model was analyzed using the coefficient of variation of rainfall quantile ensemble. The results confirmed that the regional frequency analysis using the hierarchical Bayesian model combined with the climatic and topographic information could provide an accurate estimate of extreme daily rainfall with relatively good agreement with the estimate at a specific site, but is a more reliable approach.

Extreme events Analysis of Short-Duration Rainfall and Intensity-Duration-Frequency curve using Scaling Model in North Korea

2020 ◽  
Author(s):  
Younghun Jung ◽  
Kyungwon Joo ◽  
JoonHak Lee ◽  
Jun-Haeng Heo
Keyword(s):  
Climate Change ◽  
Short Duration ◽  
Frequency Analysis ◽  
21St Century ◽  
North Korea ◽  
Flood Control ◽  
Extreme Rainfall ◽  
Regional Frequency Analysis ◽  
Index Flood ◽  
Regional Frequency

<p>Climate change has emerged as one of the defining issues of the early 21st century. Recent research confirms that the imprint of human induced climate change can be recognized in current accident events. There is a high probability of observed trends, such as increases in heat waves and heavy extreme rainfall events, intensifying over the 21st century. Extreme weather and climate events are anticipated to generate significant risks to societies and ecosystem. This paper focuses on estimation rainfall quantile using sclaling model for short duration IDF curve in North Korea. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storms. For managing flood control facilities in possibly hazardous regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in North Korea Cities using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to determine estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions using variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution(GEV and GLO). Therefore, it could be possible to estimate rainfall quantiles using scale invariance and frequency analysis for Wonsan, Jangjeon, and Pyeonggang rainfall stations in North Korea. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations.</p><p>Acknowledgements</p><p>This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2019R1A2C2010854).</p><p> </p>

Regional frequency analysis of extreme rainfall events in Jakarta

2014 ◽  
Vol 75 (2) ◽  
pp. 1075-1104 ◽  
Author(s):  
Jiandong Liu ◽  
Chi Dung Doan ◽  
Shie-Yui Liong ◽  
Richard Sanders ◽  
Anh Tuan Dao ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Extreme Rainfall ◽  
Regional Frequency Analysis ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Regional Frequency
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