• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.47-47
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• 2018

최근 이상기후로 인한 강우 패턴의 변화, 홍수와 가뭄 등으로 인하여 하천 환경은 급격한 변화를 경험하고 있다. 급격한 외부 조건에 따른 하천 환경의 변화를 평가하고 예측하기 위하여, 현재까지의 하천의 유황 조건 변화와 그에 따른 하천 지형과 생물상 변화를 토대로 대상하천의 기존의 변화 프로세스를 이해하는 것은 필수적이다. 본 연구에서는 향후 금강유역의 하천관리 및 복원사업에 이용하기 위하여 1960년대부터 현재까지의 금강의 하천 지형 변화를 파악하고 변화 양상을 분석하고자 한다. 본 연구에서는 금강 하구둑의 건설 전 후, 용담댐과 대청댐의 건설 전 후, 4대강 보(세종보, 공주보, 백제보)건설 전 후의 대상 하천의 평면적 지형 변화를 년도 별 항공사진을 통하여 지형 변수 (굴곡도, 하폭 등) 변화를 분석하고, 4대강 보 건설 구역에 대하여 건설 전 후의 지형 변화 모델링 및 생물 서식처 평가 모의를 실시한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.173-173
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• 2018

본 연구는 기상-수문 분야에서 고해상도 수문기상요소를 산출하기 위해 WRF-Hydro(Weather Research and Forecasting and Model Hydrological modeling extension package) 모형을 한반도 대상으로 구축하였다. 모형은 미국 대기 연구 국립센터(NOAA)에서 개발된 커뮤니티형 고해상도 예측모델이므로 미국 등에서 활발히 활용되기 시작하였으나 아직 우리나라 적용성에 대한 연구는 많지 않다. 본 연구에서는 WRF-Hydro 모형을 한반도에 적절히 사용하기 위해 표면유출, 보수깊이, 표면거칠기와 같은 파라미터를 보정하였다. WRF-Hydro는 지역 기상모형인 WRF와 연계하여 coupled WRF/WRF-Hydro 모형을 구동하였으며, 고해상도 유출값을 얻기 위해 미국 지질조사국(USGS)에서 제공한 HydroSHEDS(Hydrological data and map based on SHuttle Elevation Derivatives at multiple Scales)를 이용하였다. 본 연구에서는 관측된 유출값을 Markov Chain Monte Carlo(MCMC) 방법을 활용하여 모형값과 비교하여 파라미터 보정을 수행하였으며, 파라미터 보정된 WRF/WRF-Hydro를 활용해 한반도 과거 홍수 및 가뭄 사상을 모의하여 결과를 분석하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1043-1046
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• 2011

본 연구는 노지에서의 와인용 포도 재배에 있어서 영향을 받는 환경적 요인을 유비쿼터스 센서 네트워크(Ubiquitous Sensor Network)를활용하여 실시간 모니터링하며 적절한 조치를 신속히 취함으로써 와인용 포도의 품질을 높이고 안정적으로 와인용 포도 재배자가 원하는 수준에서 수확될 수 있도록 하는 시스템에 관한 것이다. USN 을 구성하고 있는 센서 노드는 재배자가 설치를 원하는 다수의 지점에 설치되어 온도 습도 등 환경 데이터를 수집하며 이 데이터를 바탕으로 서리, 강추위, 가뭄 등의 와인용 포도 재배에 피해가 예상되는 현상을 미리 예측하여 재배자가 선제적으로 대처할 수 있도록 하여 피해를 최소화하였다. 이 연구는 USN 기술을 통해 와인용 포도의 수확 품질을 향상시킬 수 있음을 보여준다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• 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 Wetlands Research
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• v.20 no.4
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• pp.353-362
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• 2018

The purpose of this study is to suggest a structure plan for improving the utilization of inactive storage in the dam for overcoming the drought. Inactive storage in the dam is composed of the emergency storage and dead storage. The emergency storage can be used for the case of emergency such as drought. But, in general, the dead storage for sedimentation is not used even for the emergency. Therefore, this study considers the part of dead storage that the sedimentation is not progressed yet can be used during the severe drought period and is called "drought storage in a dam". The accurate Sediment Level(SL) analysis for the computation of the drought storage should be performed and so the present and future SL in the dam reservoir is estimated using SED-2D linked with RMA-2 model of SMS. After the consideration of additionally available storage capacity based on the estimated SL, the drought storage is finally determined. Present data based on historical data, future predicted future climate factors by Representative Concentrarion Pathways(RCP) 8.5 scenario. Then, using the TANK model, dam inflows were determined, and future period such as SL and drought storage were suggested. As the results, we have found that the available drought storage will be reduced in the future when we compare the present drought storage with the future one. This is due to a increase variability of climate change. Therefore, we should take the necessary study for the increase of available drought storage in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.120-129
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• 2017

Agrometeorological advisories for farms and orchards are issued when daily weather exceeds a predefined range of the local reference climate, which is a long-term average of daily weather for the location. The reference climate at local scales is prepared by various simplification methods, resulting in uncertainty in the agrometeorological advisories. We restored daily weather data for the 1981-2010 period and analyzed the differences in prediction results of weather risk by comparing with the temporal and spatial simplified normal climate values. For this purpose, we selected the agricultural drought index (ADI) among various disaster related indices because ADI requires many kinds of weather data to calculate it. Ten rural counties within the Seomjin River Basin were selected for this study. The normal value of 'temporal simplification' was calculated by using the daily average value for 30 years (1981-2010). The normal value of 'spatial simplification' is the zonal average of the temporally simplified normal values falling within a standard watershed. For residual moisture index, temporal simplification normal values were overestimated, whereas spatial simplification normal values were underestimated in comparison with non-simplified normal values. The ADI's calculated from January to July 2017 showed a significant deviation in terms of the extent of drought depending on the normal values used. Through this study, we confirmed that the result of weather risk calculation using normal climatic values from 'simplified' methods can affect reliability of the agrometeorological advisories.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.14-26
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• 2016

This study analyzed the correlation between the standardized precipitation index(SPI) and forest fire occurrences using monthly accumulative rainfall data since 1970 and regional fire occurrence data since 1991. To understand the relationship between the SPI and forest fire occurrences, the correlations among the SPI of nine main observatory weather stations including Seoul, number of fire occurrences, and log of fire occurrences were analyzed. We analyzed the correlation of SPI with fire occurrences in the 1990s and 2000s and found that in the 1990s, the SPI of 3 months showed high correlation in Gyeonggi, Gangwon, and Chungnam, while the SPI of 6 months showed high correlation in Chungbuk, and the SPI of 12 months showed high correlation in Gyeongnam, Gyenongbuk, Jeonnam, and Jeonbuk. In the 2000s, the SPI of 6 months showed high correlation with the fire frequency in Gyeonggi, Chungnam, Chungbuk, Jeonnam, and Jeonbuk, whereas the fire frequency in western Gangwon was highly correlated with the SPI of 3 months and, in eastern Gangwon, Gyeongnam, and Gyenongbuk, with the SPI of 1 month. In the 1990s, distinct differences in the drought condition between the SPI of 3 months and 12 months in the northern and southern regions of Korean Peninsula were found, whereas the differences in both the SPI of 1 month and 6 months were found in the Baekdudaegan region except western Gangwon since the 2000s. Therefore, this study suggests that we can develop a model to predict forest fire occurrences by applying the SPI of 1-month and 6-month data in the future.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.145-156
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• 2021

Forest fires have frequently occurred around the world, and the damages are increasing. In Korea, most forest fires are initiated by human activities, but climate factors such as temperature, humidity, and wind speed have a great impact on combustion environment of forest fires. In this study, therefore, based on statistics of forest fires in Gyeonggi-do over the past five years, meteorological and hydrological factors (i.e., temperature, humidity, wind speed, precipitation, and drought) were selected in order to quantitatively investigate causal relationships with forest fire. We applied a partial least squares structural equation model (PLS-SEM), which is suitable for analyzing causality and predicting latent variables. The overall results indicated that the measurement and structural models of the PLS-SEM were statistically significant for all evaluation criteria, and meteorological factors such as humidity, temperature, and wind speed affected by amount of -0.42, 0.23 and 0.15 of standardized path coefficient, respectively, on forest fires, whereas hydrological factor such as drought had an effect of 0.23 on forest fires. Therefore, as a practical method, the suggested model can be used for analyzing and evaluating influencing factors of forest fire and also for planning response and preparation of forest fire disasters.

• Journal of Wetlands Research
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• v.23 no.1
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• pp.27-34
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• 2021

In this study, the main influencing factors of the occurrence of cyanobacteria at each of the eight Multifunctional weirs were derived using a random forest, and a categorical prediction model based on a Algal bloom warning system was developed. As a result of examining the importance of variables in the random forest, it was found that the upstream points were directly affected by weir operation during the occurrence of cyanobacteria. This means that cyanobacteria can be managed through efficient security management. DO and E.C were indicated as major influencers in midstream. The midstream section is a section where large-scale industrial complexes such as Gumi and Gimcheon are concentrated as well as the emissions of basic environmental facilities have a great influence. During the period of heatwave and drought, E.C increases along with the discharge of environmental facilities discharged from the basin, which promotes the outbreak of cyanobacteria. Those monitoring sites located in the middle and lower streams are areas that are most affected by heat waves and droughts, and therefore require preemptive management in preparation for the outbreak of cyanobacteria caused by drought in summer. Through this study, the characteristics of cyanobacteria at each point were analyzed. It can provide basic data for policy decision-making for customized cyanobacteria management.