• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.1-12
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• 2020

The extreme 2017 spring drought affected a large portion of South Korea in the Southern Gyeonggi-do and Chungcheongnam-do districts. This drought event was one of the climatologically driest spring seasons over the 1961-2016 period of record. It was characterized by exceptionally low reservoir water levels, with the average water level being 36% lower over most of western South Korea. In this study, we consider drought response methods to alleviate the shortage of agricultural water in times of drought. It could be to store water from a stream into a reservoir. There is a cyclical method for reusing water supplied from a reservoir into streams through drainage. We intended to present a decision-making plan for water supply based on the calculation of the quantity of water supply and leakage. We compared the rainfall-runoff equation with the TANK model, which is a long-term run-off model. Estimations of reservoir inflow during non-irrigation seasons applied to the Madun, Daesa, and Pungjeon reservoirs. We applied the run-off flow to the last 30 years of rainfall data to estimate reservoir storage. We calculated the available water in the river during the non-irrigation season. The daily average inflow from 2003 to 2018 was calculated from October to April. Simulation results show that an average of 67,000 tons of water is obtained during the non-irrigation season. The report shows that about 53,000 tons of water are available except during the winter season from December to February. The Madun Reservoir began in early October with a 10 percent storage rate. In the starting ratio, a simulated rate of 4 K, 6 K, and 8 K tons is predicted to be 44%, 50%, and 60%. We can estimate the amount of water needed and the timing of water pump operations during the non-irrigation season that focuses on fresh water reservoirs and improve decision making for efficient water supplies.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.202-202
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• 2023

전 세계적으로 지구 온난화로 인해 발생한 가뭄은 사회적, 경제적, 환경적으로 막대한 피해를 야기하고 있다. 국내의 경우, 2022년부터 현재까지 지속되고 있는 가뭄 상황은 강수의 지역적 편차로 인해 남부 지역 중심으로 극심한 피해가 발생하였다. 남부 지역의 주요 용수공급원인 영산강, 섬진강권역의 용수 공급율은 예년의 57%(3.8억 톤)에 불과하며, 일부 도서·산간 지역은 용수공급이 제한되는 현상까지 발생하였다. 이러한 가뭄 피해를 대비하기 위해 초기에 모니터링을 통한 선제적 대응 방안을 구축해야 한다. 가뭄 모니터링의 경우 미계측 지역에 대한 모니터링 방법으로 주기적이고 균질한 자료를 제공 받을 수 있는 위성영상을 활용한 연구가 수행되고 있다. 가뭄을 정량적으로 분석하고 판단하기 위해 가뭄지수를 활용하고 있으며, 대표적인 가뭄지수는 지상 관측강수량자료를 활용한 확률분포 기반의 표준강수지수 (Standardized Precipitation Index, SPI)와 강수 및 기온의 변동성이 포함된 표준강수증발산지수 (Standardized Precipitation Evapotranspiration Index, SPEI)가 있으며, 위성영상 자료를 활용한 가뭄지수인 증발스트레스지수(Evaporative Stress Index, ESI) 등이 있다. 본 연구에서는 강수와 기온을 고려한 가뭄지수인SPEI와 위성영상 기반의 가뭄지수인 ESI를 활용하여 2022년 남부 지역의 가뭄 사상을 중심으로 지표별 시공간적 변화를 분석하고자 한다. SPEI의 경우 기상관측소 지점자료의 기온과 강수량을 활용하였으며, Terra 위성의 MODIS (Moderate Resolution Imaging Spectroradiometer) 센서에서 제공되는 위성영상자료를 활용한 ESI는 미계측 지역에 대한 가뭄 판단을 위해 시·군별로 세분화하여 산정하였다.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.90-97
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• 2019

In recent years, flood due to the consecutive storm events have been occurred and property damage and casualties are in increasing trend. This study calls the consecutively occurred storm events as a mega rainfall scenario and the discharge by the scenario is defined as a mega flood discharge. A mega rainfall scenario was created on the assumption that 100-year frequency rainfall events were consecutively occurred in the Gyeongancheon stream basin. The SSARR (Streamflow Synthesis and Reservoir Regulation) model was used to estimate the mega flood discharge using the scenario in the basin. In addition, in order to perform more reasonable runoff analysis, the parameters were estimated using the SCE_UA algorithm. Also, the calibration and verification were performed using the objective functions of the weighted sum of squared of residual(WSSR), which is advantageous for the peak discharge simulation and sum of squared of residual(SSR). As a result, the mega flood discharge due to the continuous occurrence of 100-year frequency rainfall events in the Gyeongan Stream Basin was estimated to be 4,802㎥/s, and the flood discharge due to the 100-year frequency single rainfall event estimated by "the Master Plan for the Gyeongancheon Stream Improvement" (2011) was 3,810㎥/s. Therefore, the mega flood discharge was found to increase about 992㎥/s more than the single flood event. The results of this study can be used as a basic data for Comprehensive Flood Control Plan of the Gyeongan Stream basin.

• Water for future
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• v.28 no.6
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• pp.193-202
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• 1995

The subjective research attempts to apply a rainfall-runoff model capable of considering time-variation of soil water contents which are highly correlated to the river flows on the qpqyungchang river basin and to evaluate its performance for flow forecasting. The model used in this study is a physically-based conceptual time-continuous model, which is composed of the Sacramento soil moisture accounting model and the nonlinear multiple conceptual reservoirs model. The daily precipitation and evaporation data for 7 years and for 3 years were used for the parameter estimation and the model verification, respectively. As a result, the flows including a significant flood event were well simulated, and the cross-correlation coefficient between observed flows and computed flows for the verification periods was 0.87, but in general computed flows were underestimated for the low-flow periods. Also, the effects of precipitation and soil water content to the river flows were analysed for the flood and the drought.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.280-292
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• 2017

Hail is not a frequently occurring weather event, and there are even fewer reports of hail damages to forest stands. Since the 2000s, an increase in hail incidence has been documented in Europe and the United States. In Korea, severe hails occurred in Jeollanam-do province on May 31 and in Gyeongsangbuk-do province on June 1, 2017. Hail size was ranged from 0.5 to 5.0 cm in diameter in Jeollanam-do, and from 1.5 to 3.0 cm in Gyeongsangbuk-do. This study was aimed to analyze the hail damages to forests by species and topography based on damage-categorized maps created by using drones and aerial photographs, and to analyze relationships of the damages with meteorological factors. The total damaged forest area was 1,163.1ha in Jeollanam-do, and 2,942.3ha in Gyeongsangbuk-do. Among the 'severe' damaged area 326.7ha, 91% was distributed in Jeollanam-do, and concentrated in the city of Hwasun which covers 57.2% of the total 'severe' damaged area. The most heavily damaged species was Korean red pine(Pinus densiflora S. & Z.) followed by P. rigida. Most broad-leaved trees species including oaks were recovered without any dead trees found. Liliodendron tulipifera was the most severely damaged in terms of the rate of 'severe' degree individuals which are needed to be checked whether they will die or be recovered. Cause of the death of pines was considered as the combination of physical damage caused by the hail and long-lasting drought with high air temperature that occurred before and after the hail event. No pathogens and insects were found which might have affected to tree deaths. We suggested a dieback mechanism of the pine trees damaged by hail and drought.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.35-44
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• 1998

An integrated system of GIS and water quality model was suggested including the pollutant loads from the watershed. The developed system consists of two parts. First part is the GIS module. The geographic information system of the study area was built to provide the information on landuse and several surface factors concerning the overland flow processes of water and pollutants. Second part is the modeling modules which include storm event pollutant load model(SEPLM)., non-storm event pollutant load model(NSPLM), and river water quality simulation model(RWQSM). Models can calculate the pollutant load from the study area. The databases and models are linked through the interface modules resided in the overall system, which incorporate the graphical display modules and the operating scheme for the optimal use of the system. The developed system was applied to the Chungju multi-purpose reservoir to estimate the pollutant load during the four selected rainfall events between 1991 and 1993,. based upon monthly basis and seasonal basis in drought flow, low flow, normal flow and wet flow.

• Journal of the Korean earth science society
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• v.30 no.6
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• pp.734-743
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• 2009

In order to examine how climatological condition can influence on urban scale particulate air pollutants, single and cross spectrum analysis have been performed to daily mean concentrations of particulate matters ($PM_{10}$) in Busan together with the climatological variables over the Asian dust source regions. Single power spectrum analysis of $PM_{10}$ concentrations in Busan shows that, aside from the typical and well-known periodicities, 3-4 year of peak periodicity of power spectrum density was identified. In cross spectrum analysis, this 3-4 year periodicity is found to have a strong positive correlation with the wind speed and pressure, and negative with the temperature and relative humidity, which is rather consistent with both characteristics of air mass during the Asian dust event whose periodicities have been recorded inter-annually over the Korean urban cities. Over the Asian dust source regions, $PM_{10}$ vs. precipitation shows no significant periodicity from the time series of precipitation data, but the periodicity of EDI (Effective Drought Index) shows some interannual variabilities ranging from 2 to 4 years over the various source regions, suggesting that, rather than precipitation itself, the EDI could be more closely associated with the occurrence frequency of Asian dust and interannual variability of urban particle concentrations in Korean cities.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.499-505
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• 2015

Trend Impact Analysis(: TIA) is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. An adaptive neuro-fuzzy inference system is a kind of artificial neural network that integrates both neural networks and fuzzy logic principles, It is considered to be a universal estimator. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using Adaptive Neuro-Fuzzy Inference System(: ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes. The trigger attributes can be calculated by a stochastic dynamic model; then different scenarios are generated using Monte-Carlo simulation. To compare the proposed method, a simple simulation is provided concerning the impact of river basin drought on the annual flow of water into a lake.

• Journal of Korea Water Resources Association
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• v.39 no.2 s.163
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• pp.121-126
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• 2006

Snowmelt effect is identified from the analysis of the relationship between precipitation and groundwater level(GWL) data and Severe drawdown of GWL is observed in drought. Groundwater dam Operation Index (GOI), which is developed for the optimal operation of groundwater dam, is calculated by taking common logarithm of the moving average(MA) of precipitation data for a certain period. The period can vary from watershed to watershed because the period is decided by picking the maximum correlation coefficient between GWL and GOI of several MAs of precipitation. For Ssangchun watershed, the correlation was the strongest when we apply 70 day MA for GOI calculation. Snowmelt effect is considered by applying the temperature change by elevation($0.5^{\circ}C$ decrease per 100m) and examining the areal distribution of the watershed by elevation. Snow event is assumed when the daily average temperature is below $0^{\circ}C$ and snowmelt is assumed when the temperature is above zero degree Celsius. Total snowmelt is assumed for the day. When the snow event is occurred the precipitation data is separated into two components, snow and rainfall. The areal distribution by elevation is used for the calculation in the separation. The correlation between GWL and GOI is higher when we consider snowmelt effect than we neglected it.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1133-1148
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• 2019

Tree growth and vitality in forest shows seasonal changes. So, in order to detect forest damage accurately, we have to use satellite images before and after damages taken at the same season. However, temporal resolution of high or medium resolution images is very low,so it is not easy to acquire satellite images of the same seasons. Therefore, in this study, we estimated spectral information of the same DOY using time-series Landsat images and used the estimates as reference values to assess forest damages. The study site is Hwasun, Jeollanam-do, where forest damage occurred due to hail and drought in 2017. Time-series vegetation index (NDVI, EVI, NDMI) maps were produced using all Landsat 8 images taken in the past 3 years. Daily normal vegetation index maps were produced through cloud removal and data interpolation processes. We analyzed the difference of daily normal vegetation index value before damage event and vegetation index value after event at the same DOY, and applied the criteria of forest damage. Finally, forest damage map based on daily normal vegetation index was produced. Forest damage map based on Landsat images could detect better subtle changes of vegetation vitality than the existing map based on UAV images. In the extreme damage areas, forest damage map based on NDMI using the SWIR band showed similar results to the existing forest damage map. The daily normal vegetation index map can used to detect forest damage more rapidly and accurately.