• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.37-49
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• 2023

The drought risk has been increasing recently due to climate change causing the extreme climate to be more frequent. In order to supply agricultural water stably under drought, it is necessary to operate an agricultural reservoir in response to drought. To this end, it is crucial to establish appropriate drought response operation rules considering weather conditions and reservoir status. In the reservoir operation simulation, the supply amount differs from the actual reservoir supply for many reasons, including maintaining water levels for supply and accommodating farmers' requests. So, for a more realistic reservoir operation simulation, it is necessary to reflect the reservoir operation rules of the actual water management site. Therefore, in this study, through a survey, the standards for limitation of agricultural water supply applied to agricultural reservoirs in Korea were investigated, and the criteria for drought response reservoir operation (DRO) were established based on the survey. Then, the DRO was applied to the irrigation period for nine subject reservoirs. The applicability was evaluated by comparing the DRO result to the operation result of HOMWRS (Hydrological Operation Model for Water Resources System). The reservoir drought index, storage rate, and daily supply were compared for evaluation. From the result, DRO showed more stable operation results in most cases against drought as it has fewer days of water supply limitation and a somewhat reservoir storage rate which can be utilized for prolonged drought.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.3-12
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• 2004

It is necessary to manage water resources in rural areas in order to achieve proper development of new water resources, sustainable usage and reasonable distribution. This paper aims to analyze multi-temporal Landsat-7 ETM+data for soil moisture that is essential for crops in Ahnsung area. The ETM data was also fused with KOMPSAT-1 images in order to be used as backdrop watershed maps at first. Multi-temporal Images showed also the characteristics of soil moisture distribution. Images taken in April showed that rice paddy had as low reflectance as artificial features. Compared with April scenes, those taken in Hay and June showed wetness index increased in the rice paddies. The mountainous areas have almost constant moisture index, so the difference between the dates was very low while reservoirs and livers had dramatic changes. We can calculate total potential areas of distribution of moisture content within the basin and estimate the areas being sensitive to drought. Finally we can point out the sites of small rice paddies lack of water and visualize their distribution within the same basin. It can be said that multi-temporal Landsat-7 ETM+ and KOMPSAT data can be used to show broad drought with quick and simple analysis. Drought sensitiveness maps may enable the decision makers on rural water to evaluate the risk of drought and to measure mitigation, accompanied with proper data on the hydrological and climatic drought.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.261-266
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• 2006

전국의 수문학적인 가뭄평가를 위하여 SWSI 가뭄지수를 보완한 MSWSI 개발하였다. MSWSI의 적용을 위하여 가뭄에 영향을 미치는 수문인자가 동일한 지역 즉, 댐, 하천, 지하수, 강수 유역으로 전국을 32개 및 112개의 유역으로 분할하여 적용함으로서 준분포형으로 수문학적 가뭄을 평가하는 동시에 개발된 가뭄평가 기법의 유역분할 개수에 따른 적용성을 검토하였다. 각 유역에 MSWSI를 적용하여 공간적으로 준분포형의 수문학적 가뭄 정보를 획득하였으며, 시간적으로 1974년부터 2001년까지의 1개월 및 1주 간격으로 평가하여 가뭄평가 분석시간 단위에 따른 적용성을 검토하였다. 과거 가뭄사상년도(1994, 1995, 2001년)의 가뭄조사 기록에 대하여 본 연구 결과를 검증하였으며, 기상학적 가뭄지수인 PDSI와 개발된 수문학적인 가뭄평가지수의 결과에 대하여 비교, 분석하였다.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.1-9
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• 2020

Reservoir storage and water level information is essential for accurate drought monitoring and prediction. In particular, the agricultural drought has increased the risk of agricultural water shortages due to regional bias in reservoirs and water supply facilities, which are major water supply facilities for agricultural water. Therefore, it is important to evaluate the available water capacity of the reservoir, and it is necessary to determine the water surface area and water capacity. Remote sensing provides images of temporal water storage and level variations, and a combination of both measurement techniques can indicate a change in water volume. In areas of ungauged water volume, satellite remote sensing image acts as a powerful tool to measure changes in surface water level. The purpose of this study is to estimate of reservoir storage and level variations using satellite remote sensing image combined with hydrological statistical data and the Normalized Difference Water Index (NDWI). Water surface areas were estimated using the Sentinel-2 satellite images in Seosan, Chungcheongnam-do from 2016 to 2018. The remote sensing-based reservoir storage estimation algorithm from this study is general and transferable to applications for lakes and reservoirs. The data set can be used for improving the representation of water resources management for incorporating lakes into weather forecasting models and climate models, and hydrologic processes.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.40-40
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• 2020

가뭄은 발생과정과 피해 영향에 따라 기상학적, 수문학적, 농업적, 사회경제학적 가뭄으로 분류할 수 있으며, 각 가뭄은 서로 직·간접적으로 영향을 미친다. 본 연구에서는 기상학적 가뭄에서 수문학적 가뭄으로의 전이 분석을 위하여 WRF-Hydro(Weather Research and Forecasting and Model Hydrological modeling extension package)모형을 한반도 대상으로 구축하였다. WRF-Hydro 모형을 한반도에 적절히 사용하기 위하여 표면유출, 보수깊이, 표면 거칠기와 같은 파라미터 보정을 모형의 유출량 결과 값과 관측된 유출량 값을 비교 평가하여 수행하였다. 수문학적 가뭄을 정의하기 위해 Standardized Runoff Index(SRI)를 도출하였고, 기상학적 가뭄 정의에는 Standardized Precipitation Index(SPI)를 사용하였다. 한반도 가뭄이 발생한 2008년부터 2015년까지 SPI와 SRI의 기간 및 심도를 정량화하고 가뭄 전이 분석하였다. 분석 결과에 따르면 수문학적 가뭄은 기상학적 가뭄이 발생 5일에서 49일 이후에 발생하며, 발생 횟수가 적으며 크기가 작으나, 상대적으로 긴 가뭄 기간을 보였다. 이러한 분석은 지면 및 수문 모형 기반 한반도 가뭄 사상 예측 및 이해에 기여할 것으로 예상된다.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.475-488
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• 2017

To simulate accurate drought, a drought index is needed to reflect the hydrometeorological phenomenon. Several studies have been conducted in Korea using the Modified Surface Water Supply Index (MSWSI) to simulate hydrological drought. This study analyzed the limitations of MSWSI and quantified the uncertainties of MSWSI. The influence of hydrometeorological components selected as the MSWSI components was analyzed. Although the previous MSWSI dealt with only one observation for each input component such as streamflow, ground water level, precipitation, and dam inflow, this study included dam storage level and dam release as suitable characteristics of the sub-basins, and used the areal-average precipitation obtained from several observations. From the MSWSI simulations of 2001 and 2006 drought events, MSWSI of this study successfully simulated drought because MSWSI of this study followed the trend of observing the hydrometeorological data and then the accuracy of the drought simulation results was affected by the selection of the input component on the MSWSI. The influence of the selection of the probability distributions to input components on the MSWSI was analyzed, including various criteria: the Gumbel and Generalized Extreme Value (GEV) distributions for precipitation data; normal and Gumbel distributions for streamflow data; 2-parameter log-normal and Gumbel distributions for dam inflow, storage level, and release discharge data; and 3-parameter log-normal distribution for groundwater. Then, the maximum 36 MSWSIs were calculated for each sub-basin, and the ranges of MSWSI differed significantly according to the selection of probability distributions. Therefore, it was confirmed that the MSWSI results may differ depending on the probability distribution. The uncertainty occurred due to the selection of MSWSI input components and the probability distributions were quantified using the maximum entropy. The uncertainty thus increased as the number of input components increased and the uncertainty of MSWSI also increased with the application of probability distributions of input components during the flood season.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.397-397
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• 2020

가뭄을 전망하는 방법으로는 통계적 방법과 물리적 방법으로 구분할 수 있다. 통계적 방법은 과거의 기상 및 수문현상이 미래에도 재현될 수 있다는 전제하에 미래 가뭄상황을 전망하는 방법이다. 그러나 이 방법은 예측된 결과들이 모두 과거의 경향에 국한됨에 따라 최근에 급변하는 수문기상의 특성을 고려하는데 한계가 있다(Trenberth, 1994). 물리적 방법은 주어진 초기 수문기상조건으로부터 역학적 알고리즘이 탑재된 기상 및 수문모형의 연계모의를 통하여 미래 가뭄을 전망하는 방법으로 모형에 따른 불확실성이 발생할 수 있으나 최근 수문순환의 변화를 예측가능하다는 장점이 있어 활용도가 높다. 본 연구에서는 기상예보자료와 지표수문모형을 연계한 물리적 기반의 수문학적 가뭄전망정보를 산정하고, 활용성을 평가하였다. 기상예보자료는 기상청 현업예보 모델인 GloSea5로부터 생산된 자료를 이용하였으며, 수문학적 가뭄전망을 위해 MSWSI (Modified Surface Water Supply Index)를 활용하였다. 수문학적 가뭄전망정보는 현재의 수문조건이 지속된다는 가정하에 예보선행시간 3개월까지 산정하였다. 2015~16년 기간에 중권역별 가뭄전망정보를 산정하였으며, 전망정보의 예측성은 통계분석을 이용하여 정량적으로 평가하였다. 금회 제시한 연구방법은 현재의 수문조건이 지속될 시 기상예보에 따른 중권역별 수문학적 가뭄을 예측할 수 있다는 점에서 활용성이 높을 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1141-1180
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• 2022

The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1041-1053
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• 2018

In this study, a real-time storage level and capacity monitoring and forecasting system for Yongdam Dam watershed was developed using high resolution satellite image. The drought indices such as Standardized Precipitation Index (SPI) from satellite data were used for storage level monitoring in case of drought. Moreover, to predict storage volume we used a statistical method based on Principle Component Analysis (PCA) of Singular Spectrum Analysis (SSA). According to this study, correlation coefficient between storage level and SPI (3) was highly calculated with CC=0.78, and the monitoring and predictability of storage level was diagnosed using the drought index calculated from satellite data. As a result of analysis of principal component analysis by SSA, correlation between SPI (3) and each Reconstructed Components (RCs) data were highly correlated with CC=0.87 to 0.99. And also, the correlations of RC data with Normalized Water Surface Level (N-W.S.L.) were confirmed that has highly correlated with CC=0.83 to 0.97. In terms of high resolution satellite image we developed a water detection algorithm by applying an exponential method to monitor the change of storage level by using Multi-Spectral Instrument (MSI) sensor of Sentinel-2 satellite. The materials of satellite image for water surface area detection in Yongdam dam watershed was considered from 2016 to 2018, respectively. Based on this, we proposed the possibility of real-time drought monitoring system using high resolution water surface area detection by Sentinel-2 satellite image. The results of this study can be applied to estimate of the reservoir volume calculated from various satellite observations, which can be used for monitoring and estimating hydrological droughts in an unmeasured area.