An Analysis of Spatio-temporal Characterisrice of Drought Using Non-stationary Time Dependent-standardized Precipitation (비정상성 기반 SPIt를 이용한 가뭄의 시⋅공간적 특성 분석)

SeJin Jeung (정세진); Kim Byung Sik (김병식); Dong ho Kang (강동호)

doi:10.14251/crisisonomy.2020.16.12.63

An Analysis of Spatio-temporal Characterisrice of Drought Using Non-stationary Time Dependent-standardized Precipitation

Crisisonomy
Abbr : KRCEM
2020, 16(12), pp.63-74
DOI : 10.14251/crisisonomy.2020.16.12.63
Publisher : Crisis and Emergency Management: Theory and Praxis
Research Area : Social Science > Public Policy > Public Policy in general
Received : November 13, 2020
Accepted : December 10, 2020
Published : December 31, 2020

SeJin Jeung ¹, Kim Byung Sik ², Dong ho Kang ²

¹강원대학교 강원종합기술연구원
²강원대학교

Accredited

ABSTRACT

The SPI index was developed based on the fact that when drought occurs when reduced precipitation causes water shortage relative to the required water demand. However, the SPI index works under the assumption of stationarity or normality in which the probabilistic properties of the time series data do not change over time. It has limitations in reflecting information changing over time sufficiently, such as climate change. In this study, we used SPIt, a new frequency analysis method considering non-stationarity, which is different from the existing SPI index calculation. We first used daily precipitation data to construct the time series data of 7-day precipitation. For the duration of drought, both SPI and SPIt indices for 3 months were calculated on a monthly and weekly basis, and the reproducibility of each index was assessed for the areas experiencing restricted water supply. In addition, both indices were calculated for all national meteorological stations in South Korea, which was used to create a spatial distribution map and confirm their spatial reproducibility.

KEYWORDS

non-stationarity, SPIt, SPI, drought, limited water supply

Citation status

* References for papers published after 2023 are currently being built.

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Crisisonomy 2023 KCI Impact Factor : 0.64

An Analysis of Spatio-temporal Characterisrice of Drought Using Non-stationary Time Dependent-standardized Precipitation

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* References for papers published after 2023 are currently being built.

Crisisonomy 2023 KCI Impact Factor : 0.64

An Analysis of Spatio-temporal Characterisrice of Drought Using Non-stationary Time Dependent-standardized Precipitation

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.