• Title/Summary/Keyword: Standardized Precipitation Index(SPI)

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Analysis on Trends, Periodicities and Frequencies of Korean Drought Using Drought Indices (가뭄지수를 활용한 한반도 가뭄의 경향성, 주기성 및 발생빈도 분석)

  • Lee, Joo-Heon;Seo, Ji-Won;Kim, Chang-Joo
    • Journal of Korea Water Resources Association
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    • v.45 no.1
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    • pp.75-89
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    • 2012
  • This study attempted to analyze statistical characteristics of historical drought of Korea through trend, periodicity and drought spell analysis by using the drought indices. Standard Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI) were calculated using weather data of 59 weather stations under Korea Meteorological Administration (KMA). As a result of analysis, SP13 and SP16 showed trend of drier spring, drier winter and wetter summer in all basin of Korea. However, SPI12 and PDSI showed different trends with shorter duration drought indices. In case of wavelet transform analysis for drought periodicities, in a band of 1~2 years or below 6 years showed significant spectrum. SP13 showed strongest power spectrum near the band of 1~2 year variance, and SPI12 and PDSI showed 6 years periodicities. The results from drought spell showed that Nakdong River Basin, Geum River Basin and Youngsan River Basin were appeared as severe drought vulnerable area of Korea.

Short Term Drought Forecasting using Seasonal ARIMA Model Based on SPI and SDI - For Chungju Dam and Boryeong Dam Watersheds - (SPI 및 SDI 기반의 Seasonal ARIMA 모형을 활용한 가뭄예측 - 충주댐, 보령댐 유역을 대상으로 -)

  • Yoon, Yeongsun;Lee, Yonggwan;Lee, Jiwan;Kim, Seongjoon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.1
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    • pp.61-74
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    • 2019
  • In this study, the SPI (Standardized Precipitation Index) of meteorological drought and SDI (Streamflow Drought Index) of hydrological drought for 1, 3, 6, 9, and 12 months duration were estimated to analyse the characteristics of drought using rainfall and dam inflow data for Chungju dam ($6,661.8km^2$) with 31 years (1986-2016) and Boryeong dam ($163.6km^2$) watershed with 19 years (1998-2016) respectively. Using the estimated SPI and SDI, the drought forecasting was conducted using seasonal autoregressive integrated moving average (SARIMA) model for the 5 durations. For 2016 drought, the SARIMA had a good results for 3 and 6 months. For the 3 months SARIMA forecasting of SPI and SDI, the correlation coefficient of SPI3, SPI6, SPI12, SDI1, and SDI6 at Chungju Dam showed 0.960, 0.990, 0.999, 0.868, and 0.846, respectively. Also, for same duration forecasting of SPI and SDI at Boryeong Dam, the correlation coefficient of SPI3, SPI6, SDI3, SDI6, and SDI12 showed 0.999, 0.994, 0.999, 0.880, and 0.992, respectively. The SARIMA model showed the possibility to provide the future short-term SPI meteorological drought and the resulting SDI hydrological drought.

Generation of Fine Resolution Drought Index using Satellite Data (위성영상 자료를 이용한 고해상도 가뭄지수 산정모형 개발)

  • Kim, Gwang-Seob;Park, Han-Gyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.1607-1611
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    • 2009
  • 본 연구에서는 현재 가뭄을 관측하는데 주로 이용되는 가뭄지수의 단점 등을 보완하고자 가뭄에 관련되는 식생지수를 연계한 공간해상도 높은 가뭄지수를 제시하였다. 우리나라 지상관측을 통해 산출할 수 있는 PDSI(Palmer Drought Severity Index)와 SPI(Standardized Precipitation Index) 같은 가뭄지수는 기온과 강수량 등의 기후자료만을 이용하여 산정할 수 있다. 두 가뭄지수는 관측하기 어려운 가뭄의 시기와 심도를 설명하고자 여러 연구를 통해 개발한 지수이지만, 두 가뭄지수만을 가지고 우리나라 전역의 가뭄의 공간적인 분포를 설명하기에는 다소 무리가 있다. PDSI의 경우 강수량과 기온과 토양의 수분함유량을 가지고 산출하는데, 전 관측지점을 똑같은 토양수분함유량을 가지고 있다는 가정 하에 계산되고, SPI의 경우 강수량만을 이용하여 산정한다. PDSI의 경우 과거의 가뭄의 정도를 판단하는데 매우유용하다고 알려져 있다. 하지만, 현재의 가뭄정도를 나타내는 데는 문제를 가지고 있고, SPI의 경우는 누적강수량을 가지고 시간단위로 계산한다는 점에서 다양한 가뭄의 정도를 예측할 수 있지만, 입력 자료로 강수량만 들어간다는 점에서 약점을 가진다. 이런 기후지수만을 이용한 가뭄정보 생산이 공간정보를 구현하는데 한계를 가지는 문제점을 개선하고자 가뭄에 직간접적으로 관련이 있는 보다 세밀한 공간정보를 가진 식생, 토지이용, 고도 등의 자료와 기후정보로부터 산정된 가뭄지수간의 관계를 분석하였다. 나아가 기존의 기후지수보다 고해상도를 가진 위성의 정규식생지수(NDVI; Normalized Difference Vegetation Index)와 같은 식생지수를 이용하여 기존보다 더 향상된 해상도의 가뭄지수를 산정하고자 하였다. 우리나라 지상관측소 76개 지점 중에 MODIS(Moderate Resolution Imaging Spectroradiometer) 정규식생지수 자료와의 관계를 분석하고자 자료의 보유기간이 짧은 지점과 섬지점 등을 제외한 57개 지점을 선정하고, 연구기간동안의 강수량과 기온자료를 이용하여 PDSI와 SPI를 산출하였다. PDSI와 SPI자료를 고해상도 가뭄지수 산정의 기본 변수로 사용하기 위하여 역거리가중평균법을 이용한 연구기간동안의 한반도 지역 PDSI와 SPI 가뭄지수 지도를 생산하였다. 각각의 가뭄지수와 식생 상태를 나타내는 NDVI와의 상관특성과 계절 변화에 따른 변화특성을 분석하고, CART(Classification and Regression Trees) 알고리즘을 이용하여, 지상 자료만을 사용한 가뭄지수가 가지는 시공간적 변화 특성 제시에 대한 문제점을 개선한 보다 해상도가 높은 조합가뭄지수를 제시하였다.

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A Comparative Study on the Drought Indices for Drought Evaluation (가뭄평가를 위한 가뭄지수의 비교 연구)

  • Ryu, Jae-Hea;Lee, Dong-Ryul;Ahn, Jae-Hyun;Yoon, Yong-Nam
    • Journal of Korea Water Resources Association
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    • v.35 no.4 s.129
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    • pp.397-410
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    • 2002
  • In order to quantitatively identify historical drought conditions and to evaluate their variability, drought indices commonly used. The calculation method for the drought index based on the principal hydrological factors, such as precipitation and reservoir storage, can estimate the duration and intensity of a drought. In this study the Palmer-type formula for drought index is derived for the Nakdong River basin by analyzing the monthly rainfall and meteorological data at 21 stations. The Palmer Drought Severity Index(PDSI) is used for dry land sectors to evaluate the meteorological anomaly in terms of an index which permits time and space comparisons of drought severity. The Surface Water Supply Index(SWSI) is devised for the use in conjunction with the Palmer index to provide an objective indicator of water supply conditions in Nakdong River basin. The SWSI was designed to quantify surface water supply capability of a watershed which depends on river and reservoir water The Standardized Precipitation Index(SPI) is evaluated for various time periods of 1 to 12 months in Nakdong River basin. For the purpose of comparison between drought indices correlation coefficient was calculated between indices and appropriate SPI time period was selected as 10 months for Nakdong River basin. A comparative study is made to evaluate the relative severity of the significant droughts occurred in Nakdong River basin since 1976. It turned out that $'94{\sim}'97$ drought was the worst drought in it's severity. It is found that drought indices are very useful tools in quantitatively evaluating the severity of a drought over a river basin.

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.

Assessment of Upland Drought Using Soil Moisture Based on the Water Balance Analysis (물수지 기반 지역별 토양수분을 활용한 밭가뭄 평가)

  • Jeon, Min-Gi;Nam, Won-Ho;Yang, Mi-Hye;Mun, Young-Sik;Hong, Eun-Mi;Ok, Jung-Hun;Hwang, Seonah;Hur, Seung-Oh
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.5
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    • pp.1-11
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    • 2021
  • Soil moisture plays a critical role in hydrological processes, land-atmosphere interactions and climate variability. It can limit vegetation growth as well as infiltration of rainfall and therefore very important for agriculture sector and food protection. Recently, due to the increased damage from drought caused by climate change, there is a frequent occurrence of shortage of agricultural water, making it difficult to supply and manage stable agricultural water. Efficient water management is necessary to reduce drought damage, and soil moisture management is important in case of upland crops. In this study, soil moisture was calculated based on the water balance model, and the suitability of soil moisture data was verified through the application. The regional soil moisture was calculated based on the meteorological data collected by the meteorological station, and applied the Runs theory. We analyzed the spatiotemporal variability of soil moisture and drought impacts, and analyzed the correlation between actual drought impacts and drought damage through correlation analysis of Standardized Precipitation Index (SPI). The soil moisture steadily decreased and increased until the rainy season, while the drought size steadily increased and decreased until the rainy season. The regional magnitude of the drought was large in Gyeonggi-do and Gyeongsang-do, and in winter, severe drought occurred in areas of Gangwon-do. As a result of comparative analysis with actual drought events, it was confirmed that there is a high correlation with SPI by each time scale drought events with a correlation coefficient.

Estimation and assessment of long-term drought outlook information using the long-term forecasting data (장기예보자료를 활용한 장기 가뭄전망정보 산정 및 평가)

  • So, Jae-Min;Oh, Taesuk;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.50 no.10
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    • pp.691-701
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    • 2017
  • The objective of this study is to evaluate the long-term drought outlook information based on long-term forecast data for the 2015 drought event. In order to estimate the Standardized Precipitation Index (SPI) for different durations (3-, 6-, 9-, 12-months), we used the observation precipitation of 59 Automated Synoptic Observing System (ASOS) sites, forecast and hindcast data of GloSea5. The Receiver Operating Characteristic (ROC) analysis and statistical analysis (Correlation Coefficient, CC; Root Mean Square Error, RMSE) were used to evaluate the utilization of drought outlook information for the forecast lead-times (1~6months). As a result of ROC analysis, ROC scores of SPI(3), SPI(6), SPI(9) and SPI(12) were estimated to be over 0.70 until the 2-, 3-, 4- and 5-months. The CC and RMSE values of SPI(3), SPI(6), SPI(9) and SPI(12) for forecast lead-time were estimated as (0.60, 0.87), (0.72, 0.95), (0.75, 0.95) and (0.77, 0.89) until the 2-, 4-, 5- and 6-months respectively.

Development of Hydroclimate Drought Index (HCDI) and Evaluation of Drought Prediction in South Korea (수문기상가뭄지수 (HCDI) 개발 및 가뭄 예측 효율성 평가)

  • Ryu, JaeHyun;Kim, JungJin;Lee, KyungDo
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.1
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    • pp.31-44
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    • 2019
  • The main objective of this research is to develop a hydroclimate drought index (HCDI) using the gridded climate data inputs in a Variable Infiltration Capacity (VIC) modeling platform. Typical drought indices, including, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Self-calibrated Palmer Drought Severity Index (SC-PDSI) in South Korea are also used and compared. Inverse Distance Weighting (IDW) method is applied to create the gridded climate data from 56 ground weather stations using topographic information between weather stations and the respective grid cell ($12km{\times}12km$). R statistical software packages are used to visualize HCDI in Google Earth. Skill score (SS) are computed to evaluate the drought predictability based on water information derived from the observed reservoir storage and the ground weather stations. The study indicates that the proposed HCDI with the gridded climate data input is promising in the sense that it can help us to predict potential drought extents and to mitigate its impacts in a changing climate. The longer term drought prediction (e.g., 9 and 12 month) capability, in particular, shows higher SS so that it can be used for climate-driven future droughts.

Sensitivity Assessment of Meteorological Drought Index using Bayesian Network (베이지안 네트워크를 이용한 기상학적 가뭄지수의 민감도 평가)

  • Yoo, Ji-Young;Kim, Jin-Young;Kwon, Hyun-Han;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.6
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    • pp.1787-1796
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    • 2014
  • The main purpose of this study is to assess the sensitivity of meteorological drought indices in probabilistic perspective using Bayesian Network model. In other words, this study analyzed interrelationships between various drought indices and investigated the order of the incident. In this study, a Bayesian Network model was developed to evaluate meteorological drought characteristics by employing the percent of normal precipitation (PN) and Standardized Precipitation Index (SPI) with various time scales such as 30, 60, and 90 days. The sensitivity analysis was also performed for posterior probability of drought indices with various time scales. As a result, this study found out interdependent relationships among various drought indices and proposed the effective application method of SPI to drought monitoring.

Development of Drought Index based on Streamflow for Monitoring Hydrological Drought (수문학적 가뭄감시를 위한 하천유량 기반 가뭄지수 개발)

  • Yoo, Jiyoung;Kim, Tae-Woong;Kim, Jeong-Yup;Moon, Jang-Won
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.4
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    • pp.669-680
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    • 2017
  • This study evaluated the consistency of the standard flow to forecast low-flow based on various drought indices. The data used in this study were streamflow data at the Gurye2 station located in the Seomjin River and the Angang station located in the Hyeongsan River, as well as rainfall data of nearby weather stations (Namwon and Pohang). Using streamflow data, the streamflow accumulation drought index (SADI) was developed in this study to represent the hydrological drought condition. For SADI calculations, the threshold of drought was determined by a Change-Point analysis of the flow pattern and a reduction factor was estimated based on the kernel density function. Standardized runoff index (SRI) and standardized precipitation index (SPI) were also calculated to compared with the SADI. SRI and SPI were calculated for the 30-, 90-, 180-, and 270-day period and then an ROC curve analysis was performed to determine the appropriate time-period which has the highest consistency with the standard flow. The result of ROC curve analysis indicated that for the Seomjin River-Gurye2 station SADI_C3, SRI30, SADI_C1, SADI_C2, and SPI90 were confirmed in oder of having high consistency with standard flow under the attention stage and for the Hyeongsan River-Angang station, SADI_C3, SADI_C1, SPI270, SRI30, and SADI_C2 have order of high consistency with standard flow under the attention stage.