• Title/Summary/Keyword: Drought indices

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Combined analysis of meteorological and hydrological drought for hydrological drought prediction and early response - Focussing on the 2022-23 drought in the Jeollanam-do - (수문학적 가뭄 예측과 조기대응을 위한 기상-수문학적 가뭄의 연계분석 - 2022~23 전남지역 가뭄을 대상으로)

  • Jeong, Minsu;Hong, Seok-Jae;Kim, Young-Jun;Yoon, Hyeon-Cheol;Lee, Joo-Heon
    • Journal of Korea Water Resources Association
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    • v.57 no.3
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    • pp.195-207
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    • 2024
  • This study selected major drought events that occurred in the Jeonnam region from 1991 to 2023, examining both meteorological and hydrological drought occurrence mechanisms. The daily drought index was calculated using rainfall and dam storage as input data, and the drought propagation characteristics from meteorological drought to hydrological drought were analyzed. The characteristics of the 2022-23 drought, which recently occurred in the Jeonnam region and caused serious damage, were evaluated. Compared to historical droughts, the duration of the hydrological drought for 2022-2023 lasted 334 days, the second longest after 2017-2018, the drought severity was evaluated as the most severe at -1.76. As a result of a linked analysis of SPI (StandQardized Precipitation Index), and SRSI (Standardized Reservoir Storage Index), it is possible to suggest a proactive utilization for SPI(6) to respond to hydrological drought. Furthermore, by confirming the similarity between SRSI and SPI(12) in long-term drought monitoring, the applicability of SPI(12) to hydrological drought monitoring in ungauged basins was also confirmed. Through this study, it was confirmed that the long-term dryness that occurs during the summer rainy season can transition into a serious level of hydrological drought. Therefore, for preemptive drought response, it is necessary to use real-time monitoring results of various drought indices and understand the propagation phenomenon from meteorological-agricultural-hydrological drought to secure a sufficient drought response period.

Spatial Analysis of Drought Characteristics in Korea Using Cluster Analysis (군집분석을 이용한 우리나라 가뭄특성의 공간적 분석)

  • Yoo, Ji-Young;Choi, Min-Ha;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.43 no.1
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    • pp.15-24
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    • 2010
  • Regional frequency analysis is often used to overcome the limitation of point frequency analysis to estimate probability rainfall depths. However, point frequency analysis is still used in drought analyses. This study proposed a practical method to categorize the homogeneous regions of drought characteristics for the analyses of regional characteristics of droughts in Korea. Using rainfall data from 58 observation stations managed by the Korea Meteorological Administration, this study calculated drought attributes, i.e., mean drought indices for various durations using the Standardized Precipitation Index (SPI) and drought severities expressed by durations, depth, and intensity. The drought attributes provided useful information for categorizing stations into the hydrological homogeneous regions. This study introduced a cluster analysis with K-means techniques to group observation stations. The cluster analysis grouped observation stations into 6 regions in Korea. The data in the hydrological homogeneous region would be used in spatial analysis of drought characteristics and drought regional frequency analysis.

Probabilistic Assessment of Drought Characteristics based on Homogeneous Hidden Markov Model (동질성 은닉 마코프 모형을 적용한 가뭄특성의 확률론적 평가)

  • Yoo, Ji-Young;Kwon, Hyun-Han;Kim, Tae-Woong;Lee, Seung-Oh
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.1
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    • pp.145-153
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    • 2014
  • Several studies regarding drought indices and criteria have been widely studied in the literature. If one defines the onset, severity, and end of droughts, in general, a certain threshold needs to be set to assess the drought events. However, the uncertainty associated with the threshold is a critical problem in drought analysis. To take full advantage of the inherent features in the rainfall series, a Hidden Markov Model (HMM) based probabilistic drought analysis was proposed rather than using the existing threshold based analysis. As a result, the proposed HMM based probabilistic drought analysis scheme shows better performance in terms of defining drought state and understanding underlying characteristics of the drought. In addition, the HMM based approach is capable of quantifying the uncertainties associated with the classifying meteorological drought condition in a systematic way.

Soil Moisture Estimation and Drought Assessment at the Spatio-Temporal Scales using Remotely Sensed Data: (II) Drought (원격탐사자료를 이용한 시⋅공간적으로 분포되어 있는 토양수분산정 및 가뭄평가: (II) 가뭄)

  • Shin, Yongchul;Choi, Kyung-Sook;Jung, Younghun;Yang, Jae E.;Lim, Kyoung-Jae
    • Journal of Korean Society on Water Environment
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    • v.32 no.1
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    • pp.70-79
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    • 2016
  • Based on the soil moisture data assimilation suggested in the first paper (I), we estimated root zone soil moisture and evaluated drought severity using remotely sensed (RS) data. We tested the impacts of various spatial resolutions on soil moisture variations, and the model outputs showed that resolutions of more than 2-3 km resulted in over-/under-estimation of soil moisture values. Thus, we derived the 2 km resolution-scaled soil moisture dynamics and assessed the drought severity at the study sites (Chungmi-cheon sites 1 and 2) based on the estimated soil/root parameters and weather forcings. The drought indices at the sites were affected mainly by precipitation during the spring season, while both the precipitation and land surface characteristics influence the spatial distribution of drought during the rainy season. Also, the drought severity showed a periodic cycle, but additional research on drought cycles should be conducted using long-term historical data. Our proposed approach enabled estimation of daily root zone soil moisture dynamics and evaluation of drought severity at various spatial scales using MODIS data. Thus, this approach will facilitate efficient management of water resources.

A Study of Drought Susceptibility on Cropland Using Landsat ETM+ Imagery (Landsat ETM+ 영상을 활용한 경작지역내 가뭄민감도의 연구)

  • 박은주;성정창;황철수
    • Korean Journal of Remote Sensing
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    • v.19 no.2
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    • pp.107-115
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    • 2003
  • This research investigated the 2001 spring drought on croplands in South Korea using satellite imagery. South Korea has suffered from spring droughts almost every year. Meteorological indices have been used for monitoring droughts, however they don't tell the local severity of drought. Therefore, this research aimed at detecting the local, spatial pattern of drought severity at a cropland level. This research analyzed the agricultural drought using the wetness of remotely sensed pixels that affects the growth of early crops significantly in the spring. This research, specifically, analyzed the spatial distribution and severity of drought using the tasseled cap transformation and topographical factors. The wetness index from the tasseled cap transformation of Landsat 7 ETM/sub +/ imagery was very useful for detecting the 2001 spring drought susceptibility in agricultural croplands. Especially, the wetness values smaller than -0.2 were identified as the croplands that were suffering from serious water deficit. Using the water deficit pixels, drought severity was modeled finally.

Evaluation of Photochemical Reflectance Index (PRI) Response to Soybean Drought stress under Climate Change Conditions (기후변화 조건에서 콩 한발스트레스에 대한 광화학 반사 지수 반응 평가)

  • Sang, Wan-Gyu;Kim, Jun-Hwan;Shin, Pyeong;Baek, Jae-Kyeong;Lee, Yun-Ho;Cho, Jung-Il;Seo, Myung-Chul
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.4
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    • pp.261-268
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    • 2019
  • Climate change and drought stress are having profound impacts on crop growth and development by altering crop physiological processes including photosynthetic activity. But finding a rapid, efficient, and non-destructive method for estimating environmental stress responses in the leaf and canopy is still a difficult issue for remote sensing research. We compared the relationships between photochemical reflectance index(PRI) and various optical and experimental indices on soybean drought stress under climate change conditions. Canopy photosynthesis trait, biomass change, chlorophyll fluorescence(Fv/Fm), stomatal conductance showed significant correlations with midday PRI value across the drought stress period under various climate conditions. In high temperature treatment, PRI were more sensitive to enhanced drought stress, demonstrating the negative effect of the high temperature on the drought stress. But high CO2 concentration alleviated the midday depression of both photosynthesis and PRI. Although air temperature and CO2 concentration could affect PRI interpretation and assessment of canopy radiation use efficiency(RUE), PRI was significantly correlated with canopy RUE both under climate change and drought stress conditions, indicating the applicability of PRI for tracking the drought stress responses in soybean. However, it is necessary to develop an integrated model for stress diagnosis using PRI at canopy level by minimizing the influence of physical and physiological factors on PRI and incorporating the effects of other vegetation indices.

Multi-Spectral Reflectance of Warm-Season Turfgrasses as Influenced by Deficit Irrigation (난지형 잔디의 가뭄 스트레스 상태로 인한 멀티스팩트럴 반사광 연구)

  • Lee, Joon-Hee;Trenholm, Laurie. E.;Unruh, J. Bryan
    • Asian Journal of Turfgrass Science
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    • v.22 no.1
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    • pp.1-12
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    • 2008
  • Remote sensing using multispectral radiometry may be a useful tool to detect drought stress in turf. The objective of this research was to investigate the correlation between drought stress and multispectral reflectance (MSR) from the turf canopy. St. Augustinegrass (Stenotaphrum secundatum[Walt.] Kuntze.) cultivars 'Floratam' and 'Palmetto', 'SeaIsle 1' seashore paspalum Paspalum vaginatum Swartz.), 'Empire' zoysiagrass (Zoysia japonica Steud.), and 'Pensacola' bahiagrass (Paspalum notatumFlugge) were established in lysimeters in the University of Florida Envirotron greenhouse facility in Gainesville. Irrigation was applied at 100%, 80%, 60%, or 40% of evapotranspiration (ET). Weekly evaluations included: a) shoot quality, leaf rolling, leaf firing b) soil moisture, chlorophyll content index; c) photosynthesis and d) multispectral reflectance. All the measurements were correlated with MSR data. Drought stress affected the infrared spectral region more than the visible spectral region. Reflectance sensitivity to water content of leaves was higher in the infrared spectral region than in the visible spectral region. Grasses irrigated at 100% and 80% of ET had no differences in normalized difference vegetation indices (NDVI), leaf area index (LAI), and stress indices. Grasses irrigated at 60% and 40% of ET had differences in NDVI, LAI, and stress indices. All measured wavelengths except 710nm were highly correlated (P < 0.0001) with turf visual quality, leaf firing, leaf rolling, soil moisture, chlorophyll content index, and photosynthesis. MSR could detect drought stress from the turf canopy.

Assessment of Agricultural Drought Using Satellite-based TRMM/GPM Precipitation Images: At the Province of Chungcheongbuk-do (인공위성 기반 TRMM/GPM 강우 이미지를 이용한 농업 가뭄 평가: 충청북도 지역을 중심으로)

  • Lee, Taehwa;Kim, Sangwoo;Jung, Younghun;Shin, Yongchul
    • Journal of The Korean Society of Agricultural Engineers
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    • v.60 no.4
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    • pp.73-82
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    • 2018
  • In this study, we assessed meteorological and agricultural drought based on the SPI(Standardized Precipitation Index), SMP(Soil Moisture Percentile), and SMDI(Soil Moisture Deficit Index) indices using satellite-based TRMM(Tropical Rainfall Measuring Mission)/GPM(Global Precipitation Measurement) images at the province of Chungcheongbuk-do. The long-term(2000-2015) TRMM/GPM precipitation data were used to estimate the SPI values. Then, we estimated the spatially-/temporally-distributed soil moisture values based on the near-surface soil moisture data assimilation scheme using the TRMM/GPM and MODIS(MODerate resolution Imaging Spectroradiometer) images. Overall, the SPI value was significantly affected by the precipitation at the study region, while both the precipitation and land surface condition have influences on the SMP and SMDI values. But the SMP index showed the relatively extreme wet/dry conditions compared to SPI and SMDI, because SMP only calculates the percentage of current wetness condition without considering the impacts of past wetness condition. Considering that different drought indices have their own advantages and disadvantages, the SMDI index could be useful for evaluating agricultural drought and establishing efficient water management plans.

Estimation of Drought Index Using CART Algorithm and Satellite Data (CART기법과 위성자료를 이용한 향상된 공간가뭄지수 산정)

  • Kim, Gwang-Seob;Park, Han-Gyun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.1
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    • pp.128-141
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    • 2010
  • Drought indices such as SPI(Standard Precipitation Index) and PDSI(Palmer Drought Severity Index) estimated using ground observations are not enough to describe detail spatial distribution of drought condition. In this study, the drought index with improved spatial resolution was estimated by using the CART algorithm and ancillary data such as MODIS NDVI, MODIS LST, land cover, rainfall, average air temperature, SPI, and PDSI data. Estimated drought index using the proposed approach for the year 2008 demonstrates better spatial information than that of traditional approaches. Results show that the availability of satellite imageries and various associated data allows us to get improved spatial drought information using a data mining technique and ancillary data and get better understanding of drought condition and prediction.

Application of Normalized Difference Vegetation Index for Drought Detection in Korea (우리 나라에서의 가뭄 발생 지역 판별을 위한 식생지수(NDVI)의 적용성에 관한 연구)

  • Shin, Sha-Chul;Kim, Chul-Joon
    • Journal of Korea Water Resources Association
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    • v.36 no.5
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    • pp.839-849
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    • 2003
  • Drought is one of the major environmental disasters. Weather data, particularity rainfall, are currently the primary source of information widely used for drought monitoring. However, weather data are often from a very sparse meteorological network, incomplete and/or not always available in good time to enable relatively accurate and timely drought detection. Data from remote sensing platforms can be used to complements weather data in drought. Therefore, data obtained from the Advanced Very High Resolution Radiometer(AVHRR) sensor on board the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring. The normalized difference vegetation index(NDVI)-based vegetation condition index(VCI) were used in this study These indices showed their excellent ability to detect vegetation stress due to drought. The results clearly show that temporal and spatial characteristics of drought in Korea can be detected and mapped by the VCI index.