search for




 

Generalized extreme value distribution for a drought based on inter-amount time
Journal of the Korean Data & Information Science Society 2019;30:563-71
Published online May 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.3.563
© 2019 Korean Data and Information Science Society.

Hyeju Oh1 · Sanghoo Yoon2

1Department of Statistics, Daegu University, 2Division of Mathematics and Big Data Science, Daegu University
Correspondence to: Assistant professor, Division of Mathematics and big data science, Daegu University, Gyeongbuk 38453, Republic of Korea. E-mail: statstar@daegu.ac.kr
Received April 8, 2019; Revised May 8, 2019; Accepted May 15, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Drought refers to periods when the water supply is scarce and generally occurs in regions. A drought has an economic and environmental adverse impact on the interaction between water supply and demand. The drought was evaluated on the number of days without rainfall. Inter-amount time means the time to reach a certain amount of precipitation. Therefore, the data does not contain 0 values. In addition, it can be used to quantitatively evaluate both floods and droughts. This study assessed drought by region using the time data to fill a small amount between 10mm and 30mm. The data were collected by 63 weather stations between 1986 and 2016. The annual maximum precipitation were applied to the generalized extreme value distribution. The estimated parameters were estimated by L-moments estimation that is suitable for the small sample. The goodness of fit test was performed by Cramer-von Mises test. Finally, the spatial interpolation map of return levels, 25 years, 50 years, 100 years, and 200 years were calculated to quantify the risk of drought respectively.
Keywords : GEV distribution, inter amount time, L-moment, return level.