• Title/Summary/Keyword: Grid climate data

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Study of the Construction of a Coastal Disaster Prevention System using Deep Learning (딥러닝을 이용한 연안방재 시스템 구축에 관한 연구)

  • Kim, Yeon-Joong;Kim, Tae-Woo;Yoon, Jong-Sung;Kim, Myong-Kyu
    • Journal of Ocean Engineering and Technology
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    • v.33 no.6
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    • pp.590-596
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    • 2019
  • Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.

Analysis of Water Quality Characteristics Using Simulated Long-Term Runoff by HEC-HMS Model and EFDC Model (HEC-HMS 모형에 의한 장기유출량과 EFDC 모형을 이용한 호소 내 수질특성 분석)

  • Kim, Yon-Soo;Kim, Soo-Jun;Kim, Hung-Soo
    • Journal of Wetlands Research
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    • v.13 no.3
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    • pp.707-720
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    • 2011
  • For the lake case, the detention phenomenon of water body occurs and stays for a long time. Especially, following the layer of water depth direction, the lake body and water quality problems are different from the water quality of river. So according to time, the stream and water quality can be simulated by the 3-Dimensional Model, which can divide water layer for reservoir or lake. The water quality simulation result will become more reliability. For this study, the 3-Dimension Model - EFDC was used to simulate water quality of Unam reservoir in the Sumjin Dam. The HEC-GeoHMS and HEC-HMS Rainfall - Runoff Model based on GIS were used to estimate long-term runoff, and input data was constructed to the observed water level, meteorological data, water temperature, T-N and T-P. In order to apply the EFDC model, water depth was divided into 3 layers and 5,634 grids were extracted. After constructing the grid net, the water quality change of Unam reservoir in time and space was simulated. Overall, long term runoff simulation reflected the actual observed runoff well, through the water quality simulation, according to the pollution factors, the behavior characteristics can be checked, and the simulated water quality can be properly reflected. The function of EFDC has been confirmed, which water quality can be properly simulated. In the near future, to establish countermeasures for Intake Facilities of Watershed and Management, this support which some basic tools can be applied is in expectation.

Flood Runoff Analysis using Radar Rainfall and Vflo Model for Namgang Dam Watershed (레이더강우와 Vflo모형을 이용한 남강댐유역 홍수유출해석)

  • Park, Jin-Hyeog;Kang, Boo-Sik;Lee, Geun-Sang;Lee, Eul-Rae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.3
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    • pp.13-21
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    • 2007
  • Recently, very short-term rainfall forecast using radar is required for regional flash flood according to climate change. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. Vflo model which was developed Oklahoma university was used as physical based distributed model, and Namgang dam watershed ($2,293km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using K-RainVieux, preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model(Vflo). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

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A Study on Development of the Tidal Database for the Philippines (필리핀을 위한 조석 데이터베이스 개발에 관한 연구)

  • PARK, Eung-Hyun;AHN, Se-Jin;SHIM, Moon-Bo;JEON, Hae-Yeon;KANG, Ho-Yun;KIM, Dae-Hyun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.4
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    • pp.158-168
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    • 2019
  • Korea Hydrographic and Oceanographic Agency(KHOA) carried out a research project named 'Marine Fisheries Infrastructure Construction and Technology Training for the Philippines' as part of the 1st Official Development Assistance(ODA) from 2015 to 2018. It is preparing for the 2nd ODA project which will begin in 2020. Besides, recently, the Philippines is paying attention to marine territory management and response capability due to problems such as the sea-level rise and coastal erosion caused by climate change. Therefore, before 2nd ODA to the Philippines, this study analyzed the vertical ocean model on the vertical datum in Korea and suggests the direction of development of the vertical ocean modeling system for the vertical datum in the Philippines using the observed data from the permanent tide station which was built by the Philippines ODA research project over the last four years. Moreover, as a pilot study, the Sulu Sea in the Philippines was selected and analyzed by harmonic analysis method. At each tide station, constants for correction had been computed. And the grid-based tidal model was constructed based on this study. As a result of the study, similar tidal characteristic were observed when the prediction and the measured tide were compared by applying the constants for correction between two station in the sea area with similar tidal level. These results could be used as basic data for the 2nd ODA to the Philippines, and contributed to construct and maintain a close cooperation and friendship between Korea and the Philippines.

Selection framework of representative general circulation models using the selected best bias correction method (최적 편이보정 기법의 선택을 통한 대표 전지구모형의 선정)

  • Song, Young Hoon;Chung, Eun-Sung;Sung, Jang Hyun
    • Journal of Korea Water Resources Association
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    • v.52 no.5
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    • pp.337-347
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    • 2019
  • This study proposes the framework to select the representative general circulation model (GCM) for climate change projection. The grid-based results of GCMs were transformed to all considered meteorological stations using inverse distance weighted (IDW) method and its results were compared to the observed precipitation. Six quantile mapping methods and random forest method were used to correct the bias between GCM's and the observation data. Thus, the empirical quantile which belongs to non-parameteric transformation method was selected as a best bias correction method by comparing the measures of performance indicators. Then, one of the multi-criteria decision techniques, TOPSIS (Technique for Order of Preference by Ideal Solution), was used to find the representative GCM using the performances of four GCMs after the bias correction using empirical quantile method. As a result, GISS-E2-R was the best and followed by MIROC5, CSIRO-Mk3-6-0, and CCSM4. Because these results are limited several GCMs, different results will be expected if more GCM data considered.

A stratified random sampling design for paddy fields: Optimized stratification and sample allocation for effective spatial modeling and mapping of the impact of climate changes on agricultural system in Korea (농지 공간격자 자료의 층화랜덤샘플링: 농업시스템 기후변화 영향 공간모델링을 위한 국내 농지 최적 층화 및 샘플 수 최적화 연구)

  • Minyoung Lee;Yongeun Kim;Jinsol Hong;Kijong Cho
    • Korean Journal of Environmental Biology
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    • v.39 no.4
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    • pp.526-535
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    • 2021
  • Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

Estimation of Precipitable Water from the GMS-5 Split Window Data (GMS-5 Split Window 자료를 이용한 가강수량 산출)

  • 손승희;정효상;김금란;이정환
    • Korean Journal of Remote Sensing
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    • v.14 no.1
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    • pp.53-68
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    • 1998
  • Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

Restoration planning of the Seoul Metropolitan area, Korea toward eco-city

  • Lee, Chang Seok
    • Proceedings of the Korea Society of Environmental Biology Conference
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    • 2003.06a
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    • pp.1-5
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    • 2003
  • In order to prepare a basis for ecological restoration of the Seoul Metropolitan area, ecological diagnoses on soil physico-chemical properties and vegetation structure were carried out. Land use patterns, actual vegetation, and biotope patterns were also investigated based on aerial photograph interpretation and field checks. I formulated landscape elements overlaying those data and evaluated the ecological value of each element. Soil pollution was evaluated by analyzing soil samples collected in each grid on the mesh map, divided by 2km $\times$ 2km intervals. Soil samples were collected in forests or grasslands escaped from direct human interference. Soil pollution evaluated from pH, and SO$_4$, Ca, Mg, and Al contents of soil was more severe in the urban outskirts than in the urban center. Those soil environmental factors showed significant correlation with each other. Vegetation in the urban area was different in species composition from that in suburban areas and showed lower diversity compared with that in the suburban areas. Successional process investigated by population structure of major species also showed a difference. That is, successional trend was normal in suburban areas, but that in urban areas showed a retrogressive pattern. The landscape ecological map of Seoul indicates that the urban center lacks vegetation and greenery space is restricted in urban outskirts. Such an uneven distribution of vegetation has caused a specific urban climate and thereby contributed to aggravation of air and soil pollution, furthermore causing vegetation decline. From this result, it was estimated that such uneven distribution of vegetation functioned as a trigger factor to deteriorate the urban environment. I suggested, therefore, a restoration plan based on landscape ecological principles, which emphasizes connectivity and even distribution of green areas throughout the whole area of the Seoul to solve this complex environmental problem. In this restoration plan, first of all, I decided the priority order for connection of the fragmented greenery spaces based on the distances from the core reserves comprised of green belt and rivers, which play roles as habitats of wildlife as well as for improvement of urban environment. Next, I prepared methods to restore each landscape element included in the paths of green network to be constructed in the future on the bases of such preferential order. Rivers and roads, which hold good connectivity, were chosen as elements to play important roles in constructing green network by linking the fragmented greenery spaces.

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Drought Analysis and Assessment by Using Land Surface Model on South Korea (지표수문해석모형을 활용한 국내 가뭄해석 적용성 평가)

  • Son, Kyung-Hwan;Bae, Deg-Hyo;Chung, Jun-Seok
    • Journal of Korea Water Resources Association
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    • v.44 no.8
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    • pp.667-681
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    • 2011
  • The objective of this study is to evaluate the applicability of a Land Surface Model (LSM) for drought analysis in Korea. For evaluating the applicability of the model, the model was calibrated on several upper dam site watersheds and the hydrological components (runoff and soil moisture) were simulated over the whole South Korea at grid basis. After converting daily series of runoff and soil moisture data to accumulated time series (3, 6, 12 months), drought indices such as SRI and SSI are calculated through frequency analysis and standardization of accumulated probability. For evaluating the drought indices, past drought events are investigated and drought indices including SPI and PDSI are used for comparative analysis. Temporal and spatial analysis of the drought indices in addition to hydrologic component analysis are performed to evaluate the reproducibility of drought severity as well as relieving of drought. It can be concluded that the proposed indices obtained from the LSM model show good performance to reflect the historical drought events for both spatially and temporally. From this point of view, the LSM can be useful for drought management. It leads to the conclusion that these indices are applicable to domestic drought and water management.

Application Analysis of GIS Based Distributed Model Using Radar Rainfall (레이더강우를 이용한 GIS기반의 분포형모형 적용성 분석)

  • Park, Jin-Hyeog;Kang, Boo-Sik;Lee, Geun-Sang
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.23-32
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    • 2008
  • According to recent frequent local flash flood due to climate change, the very short-term rainfall forecast using remotely sensed rainfall like radar is necessary to establish. This research is to evaluate the feasibility of GIS-based distributed model coupled with radar rainfall, which can express temporal and spatial distribution, for multipurpose dam operation during flood season. $Vflo^{TM}$ model was used as physically based distributed hydrologic model. The study area was Yongdam dam basin ($930\;km^2$) and the 3 storm events of local convective rainfall in August 2005, and the typhoon.Ewiniar.and.Bilis.collected from Jindo radar was adopted for runoff simulation. Distributed rainfall consistent with hydrologic model grid resolution was generated by using K-RainVieux, pre-processor program for radar rainfall. The local bias correction for original radar rainfall shows reasonable results of which the percent error from the gauge observation is less than 2% and the bias value is $0.886{\sim}0.908$. The parameters for the $Vflo^{TM}$ were estimated from basic GIS data such as DEM, land cover and soil map. As a result of the 3 events of multiple peak hydrographs, the bias of total accumulated runoff and peak flow is less than 20%, which can provide a reasonable base for building operational real-time short-term rainfall-runoff forecast system.

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