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

Author(s):  
Younghun Jung ◽  
Kyungwon Joo ◽  
JoonHak Lee ◽  
Jun-Haeng Heo

<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>

2017 ◽  
Vol 21 (10) ◽  
pp. 5385-5399 ◽  
Author(s):  
Edouard Goudenhoofdt ◽  
Laurent Delobbe ◽  
Patrick Willems

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.


Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 486
Author(s):  
Mengrui Li ◽  
Xiaodong Li ◽  
Tianqi Ao

Hydrological frequency analysis plays an indispensable role in the construction of national flood control projects. This study selects the stations with the smallest and largest discordances in the nine homogeneous regions of Sichuan Province as the representative stations, and results obtained by regional frequency analysis are compared with those obtained by traditional at-site hydrological frequency analysis. The results showed that the optimal frequency distribution of each representative station obtained by traditional at-site hydrological frequency analysis and the ones of corresponding homogeneous regions obtained by regional frequency analysis were not necessarily consistent, which was related to the site and homogeneous regions. At the same time, there were also differences between the fitting of the theoretical rainstorm frequency curve obtained by the two methods and the observation. In general, in each homogeneous region, the results obtained by regional frequency analysis and traditional at-site hydrological frequency analysis at the stations with the largest frequency analysis were quite different. The design values obtained by the two methods were also increasingly different with the increase of the return period. The study has specific reflections on the differences between regional frequency analysis and traditional at-site hydrological frequency analysis.


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

2013 ◽  
Vol 15 (1) ◽  
pp. 125-137 ◽  
Author(s):  
Chang Woo Song ◽  
Yon Soo Kim ◽  
Na Rae Kang ◽  
Dong Ryul Lee ◽  
Hung Soo Kim

2017 ◽  
Vol 11 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Masato Sugi ◽  
Yukiko Imada ◽  
Toshiyuki Nakaegawa ◽  
Kenji Kamiguchi

2020 ◽  
Author(s):  
Matteo Pampaloni ◽  
Virginia Vannacci ◽  
Enrica Caporali ◽  
Chiara Bocci ◽  
Valentina Chiarello ◽  
...  

<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>


Sign in / Sign up

Export Citation Format

Share Document