• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.3
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• pp.13-26
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• 2021

Recent drought events in the South Korea and the magnitude of drought losses indicate the continuing vulnerability of the agricultural drought. Various studies have been performed on drought hazard assessment at the regional scales, but until recently, drought management has been response oriented with little attention to mitigation and preparedness. A vulnerability assessment is introduced in order to preemptively respond to agricultural drought and to predict the occurrence of drought. This paper presents a method for spatial, Geographic Information Systems-based assessment of agricultural drought vulnerability in South Korea. It was hypothesized that the key 14 items that define agricultural drought vulnerability were meteorological, agricultural reservoir, social, and adaptability factors. Also, this study is to analyze agricultural drought vulnerability by comparing vulnerability assessment according to weighting method. The weight of the evaluation elements is expressed through the Analytic Hierarchy Process (AHP), which includes subjective elements such as surveys, and the Entropy method using attribute information of the evaluation items. The agricultural drought vulnerability map was created through development of a numerical weighting scheme to evaluate the drought potential of the classes within each factor. This vulnerability assessment is calculated the vulnerability index based on the weight, and analyze the vulnerable map from 2015 to 2019. The identification of agricultural drought vulnerability is an essential step in addressing the issue of drought vulnerability in the South Korea and can lead to mitigation-oriented drought management and supports government policymaking.

• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.31-40
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• 2019

In order to implement practical alternatives to proactively cope with the agricultural drought, the potential vulnerability of irrigation pumping stations to agricultural drought was quantitatively evaluated. Data for the 124 pumping stations which are correlatable to the three proxy variables, i.e. exposure, sensitivity, and adaptive capacity was collected by the Korea Rural Community Corporation, and then standardized considering distribution of each data set. Finally, the vulnerability index was calculated by multiplying the weights determined by the expert survey. The results showed that the vulnerability index ranged from 0.709 to 0.331 and the most vulnerable pumping stations such as Judam, Wongoo and Jinahn were mostly located in Gyeongbuk province likely because of the climatological characteristics with high temperature and low rainfall around this area. In addition, it was found that the adaptive capacity was a dominant factor comparing to exposure or sensitivity proxy variables in contributing to the vulnerability. It is therefore recommended that more practical alternatives should be employed to effectively reduce the vulnerability of an individual pumping station to agricultural drought. Furthermore, the corresponding data related to adaptive capacity should be systematically organized and managed at a field level to design reliable adaptation strategies.

• 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.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.1-11
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• 2004

Based on surface energy balance climatology, surface temperatures should respond to drying conditions well before plant response. To test this hypothesis, land surface temperatures (LST) derived from MODIS data were analyzed to determine how the data were correlated with climatic water balance variables and NDVI anomalies during a growing season in Western and Central Kansas. Daily MODIS data were integrated into weekly composites so that each composite data set included the maximum temperature recorded at each pixel during each composite period. Time-integrated, or cumulative values of the LST deviation standardized with mean air temperatures had significantly high correlation coefficients with SM, AE/PE, and MD/PE, ranging from 0.65 to 0.89. The Standardized Thermal Index (STI) is proposed in this study to accomplish the objective. The STI, based on surface temperatures standardized with observed mean air temperatures, had significant temporal relationships with the hydroclimatological factors. STI classes in all the composite periods also had a strong correlation with NDVI declines during a drought episode. Results showed that, based on LST, air temperature observations, and water budget analysis, NDVI declines below normal could be predicted as early as 8 weeks in advance in this study area.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.621-629
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• 2013

Desertification monitoring as a main portion for understand desertification, have been conducted by many scientists. However, the stage of research remains still in the level of comparison of the past and current situation. In other words, monitoring need to focus on finding methods of how to take precautions against desertification. In this study, Vegetation Temperature Condition Index (VTCI), derived from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), was utilized to observe the distribution change of vegetation. The index can be used to monitor drought occurrences at a regional level for a special period of a year, and it can also be used to study the spatial distribution of drought within the region. Techniques of remote sensing and Geographic Information System (GIS) were combined to detect the distribution change of vegetation with VTCI. As a result, assuming that the moisture condition is the only main factor that affects desertification, we found that the distribution of vegetation in Bulgan, Mongolia could be predicted in a certain degree, using VTCI. Although desertification is a complicated process and many factors could affect the result. This study is helpful to provide a strategic guidance for combating desertification and allocating the use of the labor force.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.479-487
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• 2018

The purpose of this study is to analyze photochemical activity of nursery seedlings under drought stress, using chlorophyll fluorescence reaction analysis. Young nursery seedlings of tomato (Lycopersicon esculentum Mill.) and cucumber (Cucumis sativa L.), were grown under drought stress for 8 days. Analysis of chlorophyll fluorescence reaction (OJIP) and parameters, were performed to evaluate photochemical fluctuation in nursery seedlings under drought stress. Chlorophyll fluorescence reaction analysis showed maximal recorded fluorescence (P) decreased from the 5 day after treatment in tomato seedlings, while an amount of chlorophyll fluorescence increased at the J-I step. Thus, physiological activity was reduced. In cucumber seedlings, maximal recorded fluorescence (P) and maximal variable fluorescence ($F_V$) lowered from the 4 day after treatment, and chlorophyll fluorescence intensity of J-I step increased. Chlorophyll fluorescence parameter analysis showed electron transfer efficiency of PSII and PSI were significantly inhibited with decreasing $ET2_O/RC$ and $RE1_O/RC$ from the 5 day after treatment, in tomato seedlings and from the 4 day after treatment, in cucumber seedlings. $ET2_O/RC$ and $PI_{ABS}$ significantly changed. In conclusion, 6 indices such as $F_V/F_M$, $DI_O/RC$, $ET2_O/RC$, $RE1_O/RC$, $PI_{ABS}$ and $PI_{TOTAL}ABS$ were selected for determining drought stress in nursery seedlings. Drought stress factor index (DFI) was used to evaluate whether the crop was healthy or not, under drought stress. Cucumber seedlings were less resistant to drought stress than tomato seedlings, in the process of drought stress.

• Journal of Environmental Policy
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• v.7 no.4
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• pp.35-55
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• 2008

Assessing vulnerability to climate change is the first step to take when setting up appropriate adaptation strategies. Adaptive capacity to climate change is the important factor comprising vulnerability. An adaptive capacity index in agricultural water management system was developed considering agricultural water supply and demand for rice production in Jeolla-do, Korea. The agricultural water supply was assumed to be equal to the amount of water stored in the major agricultural reservoirs, while data on the agricultural water demand was obtained from the dynamic simulation results by Korea Agriculture Corporation(KAC). The spatial unit for analysis was conducted at the county(Si, Gun, Gu) level and temporal scale was based on every month from 1991-2003. Adaptive capacity for drought stress index(ACDS index) was calculated as the percentage of data points where the irrigated water supply was greater than the crop water demand. The ACDS index was compared with SWSCI(Standard Water Storage Capacity Index) and the relationship showed high degree of fit($R^2$=0.84) using the exponential function, indicating that the developed ACDS index is useful for evaluating the status of the balance between agricultural water supply and demand, especially for the small sized agricultural reservoirs. This study provided the methodological basis for developing climate change vulnerability index in agricultural water system which is projected to be more frequently exposed to drought condition in the future due to climate change. Further research should be extended to the study on the water demand of the crops other than rice and to the projection of the change in ACDS index in the future.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.