• Title/Summary/Keyword: Drought index

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Projection of Future Drought of Korea Based on Probabilistic Approach Using Multi-model and Multi Climate Change Scenarios (다양한 기후변화 시나리오와 기후모델에 의한 남한지역 미래가뭄의 확률론적 전망)

  • Park, Beom-Seop;Lee, Joo-Heon;Kim, Chang-Joo;Jang, Ho-Won
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.5
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    • pp.1871-1885
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    • 2013
  • In this study, spatio-temporal distribution of future drought in South Korea was predicted by using the meteorological data generated from GCMs on which a variety of climate changing scenarios are applied. Drought phenomena was quantitatively analyzed using SPI(Standardized Precipitation Index). In addition, potential drought hazard maps for different drought duration and return period were made for the South Koreaby drought frequency analysis after deriving SDF(Severity-Duration-Frequency) curves using the 54 weather stations throughout the country. From the potential drought hazard maps, drought is expected to be severer in Nakdong River basin and Seomjin River basin under A2 scenario. It was also predicted that drought would be severe in the Han River basin by RCP8.5 scenario. In the future, potential drought hazard area would be expanded until the Eastern part of Nakdong River basin as compared with that of past under A2 scenario condition. Research results indicated that future drought would be extensively occurred all areas of South Korea not limiting in the southern part of country.

Analysis of the Possibility for Practical Use of MSI/ MidIR/ II Vegetation Indices for Drought Detection of Spring Season (MSI/ MidIR/ II 식생지수를 이용한 봄 가뭄탐지 활용 가능성 분석)

  • Kim, Sung-Jae;Choi, Kyung-Sook;Chang, Eun-Mi;Hong, Seong-Wook
    • Spatial Information Research
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    • v.19 no.5
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    • pp.37-46
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    • 2011
  • In recent years, utilizations of satellite imagery have been extensively conducted in order to obtain accurate information on drought detection in spring season. This research also carried out utilization of satellite imagery through the various vegetation indices such as NDVI(Normalized Difference Vegeation Index), MSI(Moisture Stress Index), MidIR Index, II(Infrared Index) to find better methodology to detect drought phenomena, especially occurring in spring season. For this purpose, Landsat TM(Thematic Mapper) images were used and applied on the Yeong-cheon city. In this study, the characteristics of DN(Digital Number) for each vegetation index is analyzed, and the correlation analysis between indices and DN according to the number of days with no rain is performed. The results shows high correlation between NDVI and MSI and II with positive correlation on MSI, and negative correlation on II. This indicates the possibility for practical use of MSI, II indices with NDVI to obtain better credibility for detecting spring droughts.

Drought index forecast using ensemble learning (앙상블 기법을 이용한 가뭄지수 예측)

  • Jeong, Jihyeon;Cha, Sanghun;Kim, Myojeong;Kim, Gwangseob;Lim, Yoon-Jin;Lee, Kyeong Eun
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.5
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    • pp.1125-1132
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    • 2017
  • In a situation where the severity and frequency of drought events getting stronger and higher, many studies related to drought forecast have been conducted to improve the drought forecast accuracy. However it is difficult to predict drought events using a single model because of nonlinear and complicated characteristics of temporal behavior of drought events. In this study, in order to overcome the shortcomings of the single model approach, we first build various single models capable to explain the relationship between the meteorological drought index, Standardized Precipitation Index (SPI), and other independent variables such as world climate indices. Then, we developed a combined models using Stochastic Gradient Descent method among Ensemble Learnings.

Drought Assessment of Agricultural District using Modified SWSI (SWSI 가뭄지수를 보완한 농촌용수구역 단위의 가뭄 평가)

  • Kwon, Hyung-Joong;Lim, Hyuk-Jin;Kim, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.1
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    • pp.22-34
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    • 2007
  • The purpose of this study is to assess agricultural drought using modified SWSI(Surface Water Supply Index) in Ango and Anseo agricultural district. Precipitation, reservoir inflow and storage data were used for input data of modified SWSI. Precipitation data was obtained from KMA(Korea Meteorological Administration) and reservoir storage data was obtained from KARICO(Korea Agricultural & Rural Infrastructure Corporation) and reservoir inflow data was simulated by SLURP(Simple LUmped Reservoir Parametric). SWSI based agricultural drought index was evaluated for the period of 1983 and 2001. As results, for the drought periods(July-1994, June-1995, May-2001) agricultural drought indices represented extremely drought states. The result was compared with PDSI and SWSI and checked the applicability of the suggested index in our agricultural drought situation.

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Projection and Analysis of Drought according to Future Climate and Hydrological Information in Korea (미래 기후·수문 정보에 따른 국내 가뭄의 전망 및 분석)

  • Sohn, Kyung Hwan;Bae, Deg Hyo;Ahn, Jae Hyun
    • Journal of Korea Water Resources Association
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    • v.47 no.1
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    • pp.71-82
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    • 2014
  • The objective of this study is to project and analyze drought conditions using future climate and hydrology information over South Korea. This study used three Global Climate Models (GCMs) and three hydrological models considering the uncertainty of future scenario. Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI) and Standardized Soil moisture Index (SSI) classified as meteorological, hydrological and agricultural droughts were estimated from the precipitation, runoff and soil moisture. The Mann-Kendall test showed high increase in future drought trend during spring and winter seasons, and the drought frequency of SRI and SSI is expected higher than that of SPI. These results show the high impact of climate change on hydrological and agriculture drought compared to meteorological drought.

Drought Forecasting Using the Multi Layer Perceptron (MLP) Artificial Neural Network Model (다층 퍼셉트론 인공신경망 모형을 이용한 가뭄예측)

  • Lee, Joo-Heon;Kim, Jong-Suk;Jang, Ho-Won;Lee, Jang-Choon
    • Journal of Korea Water Resources Association
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    • v.46 no.12
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    • pp.1249-1263
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    • 2013
  • In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.

The probabilistic drought forecast based on ensemble using improvement of the modified surface water supply index (Modified surface water supply index 개선을 통한 앙상블 기반 확률론적 가뭄전망)

  • Jang, Suk Hwan;Lee, Jae-Kyoung;Oh, Ji Hwan;Jo, Joon Won
    • Journal of Korea Water Resources Association
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    • v.49 no.10
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    • pp.835-849
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    • 2016
  • Accurate drought outlook and drought monitoring have been preceded recently to mitigate drought damages that further deepen. This study improved the limitations of the previous MSWSI (Modified Surface Water Supply Index) used in Korea and carried out probabilistic drought forecasts based on ensemble technique with the improved MSWSI. This study investigated available hydrometeorological components in Geum river basin and supplemented appropriate components (dam water level, dam release discharge) in addition to the four components (streamflow, groundwater, precipitation, dam inflow) usedin the previous MSWSI to each sub-basin. Although normal distribution was fitted in the previous MSWSI, the most suitable probabilistic distributions to each meteorological component were estimated in this study, including Gumbel distribution for precipitation and streamflow data; 2-parameter log-normal distribution for dam inflow, water level, and release discharge data; 3-parameter log-normal distribution for groundwater. To verify the improved MSWSI results using historical precipitation and streamflow, simulated drought situations were used. Results revealed that the improved MSWSI results were closer to actual drought than previous MSWSI results. The probabilistic forecasts based on ensemble technique with improved MSWSI were performed and evaluated in 2006 and 2014. The accuracy of the improved MSWSI was better than the previous MSWSI. Moreover, the drought index of actual drought was included in ranges of drought forecasts using the improved MSWSI.

A Study on Semi-distributed Hydrologic Drought Assessment Modifying SWSI (SWSI 가뭄지수를 보완한 준분포형 수문학적 가뭄평가 연구)

  • Kwon Hyung-Joong;Park Hyun-Jin;Hong Dae-Oui;Kim Seong-Joon
    • Journal of Korea Water Resources Association
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    • v.39 no.8 s.169
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    • pp.645-658
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    • 2006
  • A hydrological drought index, MSWSI (Modified Surface Water Supply Index) was suggested based on SWSI. South Korea was divided into 32 regions considering the distribution of available gauge station of precipitation, dam storage, stream water level and natural groundwater level. The indices estimated in the regions represent a spatially distribution of drought. Monthly MSWSI was evaluated for the period of 1974 and 2001. The result was compared with PDSI and checked the applicability of the suggested index in our hydrologic drought situation.

Quantitative analysis of spatiotemporal characteristics of flash drought using Flash Drought Intensity Index based on soil moisture (토양수분 기반 FDII를 활용한 돌발가뭄의 시공간적 정량화)

  • Hee-Jin Lee;Won-Ho Nam;Jason A. Otkin;Yafang Zhong;Mark D. Svoboda
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.46-46
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    • 2023
  • 돌발가뭄 (Flash drought)은 일반적인 가뭄과 달리 기후변화에 따른 기상 이상으로 인해 단기간 급속하게 발생하는 가뭄이다. 짧은 기간에 식생 스트레스가 증가하며, 작물생산량의 감소로 인해 농업 생태계에 피해를 야기하며, 과도한 증발 수요 및 급격한 토양수분의 감소는 수문학적 영향을 미치게 된다. 본 연구에서는 최근 개발된 Flash Drought Intenisty Index (FDII, 2021)를 활용하여 2014년부터 2018년까지 5년간 발생한 돌발가뭄에 분석하였다. FDII는 가뭄 심화속도, 평균 심각도의 두 가지 요소를 곱하여 나타내며, 일반적으로 가뭄 및 비가뭄에 대한 정도를 나타내는 아노말리 (Anomaly) 대신 백분위수 (Percentile)를 활용한다. 국내 돌발가뭄 분석을 위하여 Gravity Recovery and Climate Experiment (GRACE) 위성영상 기반 근역층 토양수분 자료를 활용하였다. 2014년부터 2018년까지 전국 8도 (경기, 강원, 충남, 충북, 전남, 전북, 경남, 경북)를 대상으로 돌발가뭄 사상에 대하여 토양수분 백분위수의 월별 공간분포 및 FDII를 산정하여 국내 돌발가뭄의 강도를 정량화하였다. 지역 및 시기별로 다르게 발생하는 돌발가뭄을 대상으로 FDII를 활용하여 돌발가뭄의 초기 발생, 가뭄 전이 현상 등 시공간적 특성을 분석하고자 한다. 향후 대상 지역의 세분화 및 장기적인 관점에서의 FDII 적용으로 신뢰성 높은 국내 돌발가뭄 모니터링 및 분석 기술로 활용할 수 있을 것으로 기대된다.

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