• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.13-13
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• 2023

디지털 기술은 오늘날 플랫폼과 디지털 트윈의 기술도입을 통해 현실 세계를 네트워크와 가상세계와의 연결이 통합되어진 가상 현실 세계의 입문 도약이다. 현실에서 가상현실의 사이의 디지털 전환(digital transformation)에는 디지털 기술과 솔루션을 비즈니스의 모든 영역에 통합하는 것이 포함된다. 이러한 디지털 전환의 핵심은 데이터에 관한 것이며, 데이터를 활용하여 가치를 창출하고 고객경험과 비즈니스 영역을 극대화하는 방식을 제공한다. 최적의 데이터를 제공하기 위한 플랫폼과 가상 현실세계 구현을 위한 디지털 트윈의 상호연계 관한 기본 개념은 데이터 수집, 데이터 분석, 데이터 시각화 및 데이터 보고와 같은 데이터 비즈니스이다. 현장 데이터는 디지털 양식을 통해 수집, 기록, 저장된다. 현장 IoT 기반 데이터(사진 및 비디오 매체 등)는 지속적으로 수집되고 종종 다른 데이터베이스에 저장되지만 지리 공간적 위치에 연결되지 않는다. 모든 디지털 발전을 조화시키고 지하수 데이터에서 더 빠른 이해를 도출하기 위해서는 디지털 트윈이 시작되어야 한다. 단일 지하수플랫폼에서 현장 조건을 시각화하고 실시간 데이터를 스트리밍하며, 과거 3D 데이터와 상호작용하여지질 또는 지화학 데이터를 선택적 사용을 위해 지하수 플랫폼과 디지털 트윈이 연계되어야 한다. 데이터를 디지털 정보모델과 연결하면 디지털 트윈에 생명을 불어넣을 수 있지만 디지털 트윈의 가치를 극대화하려면 여전히 데이터 플랫폼 서비스와 전달 방식을 선택해야 한다. 지하수 플랫폼동시성을 갖는 디지털 트윈은 정적 및 동적 데이터를 저장하는 데이터베이스 또는 크라우드 서비스에서 데이터를 가져오는 API(애플리케이션 프로그래밍 인터레이스), 디지털 트윈을 위한 호스팅 공간, 디지털 대상을 구축하는 소프트웨어, 구성 요소 간 읽기/쓰기를 위한 스크립트, chatGPT 및 API를 활용할 수 있다. 이를 통해 수집된 데이터의 실시간 양방향 통신기술인 지하수 플랫폼 기술을 활용하여 디지털 트윈을 적용하고 완성할 수 있고, 이를 지하수 분야에도 그대로 적용할 수 있다. 지하수 분야의 디지털 트윈 기술의 근간은 지하수 모니터링을 위한 관측장치와 이를 활용한 지하수 플랫폼의 구축 및 양방향 자료전송을 통한 분석 및 예측기술이다. 특히 낙동강과 같이 유역면적이 넓고 유역 내 지자체가 많아 이해관계가 다양하며, 가뭄과 홍수/태풍 등 기후위기에 따른 극한 기상이변가 자주 발생하고, 또한 보 및 하굿둑 개방 등 정부정책 이행에 따른 민원이 다수 발생하는 지역의 경우 하천과 유역에 대한 지하수 플랫폼과 디지털 트윈의 동시성 기술적용 시 지하수 데이터에 대한 고려가 반드시 수반되어야 한다.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1465-1483
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• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.441-448
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• 2015

Lack of agricultural information for food supply and demand in Democratic People's republic Korea(DPRK) make people sometimes confused for right and timely decision for policy support. We carried out a study to estimate paddy rice yield in DPRK using MODIS NDVI reflecting rice growth and climate data. Mean of MODIS $NDVI_{max}$ in paddy rice over the country acquired and processed from 2002 to 2014 and accumulated rainfall collected from 27 weather stations in September from 2002 to 2014 were used to estimated paddy rice yield in DPRK. Coefficient of determination of the multiple regression model was 0.44 and Root Mean Square Error(RMSE) was 0.27 ton/ha. Two-way analysis of variance resulted in 3.0983 of F ratio and 0.1008 of p value. Estimated milled rice yield showed the lowest value as 2.71 ton/ha in 2007, which was consistent with RDA rice yield statistics and the highest value as 3.54 ton/ha in 2006, which was not consistent with the statistics. Scatter plot of estimated rice yield and the rice yield statistics implied that estimated rice yield was higher when the rice yield statistics was less than 3.3 ton/ha and lower when the rice yield statistics was greater than 3.3 ton/ha. Limitation of rice yield model was due to lower quality of climate and statistics data, possible cloud contamination of time-series NDVI data, and crop mask for rice paddy, and coarse spatial resolution of MODIS satellite data. Selection of representative areas for paddy rice consisting of homogeneous pixels and utilization of satellite-based weather information can improve the input parameters for rice yield model in DPRK in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.307-316
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• 2010

Complex terrain refers to irregular surface properties of the earth that influence gradients in climate, lateral transfer of materials, landscape distribution in soils properties, habitat selection of organisms, and via human preferences, the patterning in development of land use. Complex terrain of mountainous areas represents ca. 20% of the Earth's terrestrial surface; and such regions provide fresh water to at least half of humankind. Most major river systems originate in such terrain, and their resources are often associated with socio-economic competition and political disputes. The goals of the TERRECO-IRTG focus on building a bridge between ecosystem understanding in complex terrain and spatial assessments of ecosystem performance with respect to derived ecosystem services. More specifically, a coordinated assessment framework will be developed from landscape to regional scale applications to quantify trade-offs and will be applied to determine how shifts in climate and land use in complex terrain influence naturally derived ecosystem services. Within the scope of TERRECO, the abiotic and biotic studies of water yield and quality, production and biodiversity, soil processing of materials and trace gas emissions in complex terrain are merged. There is a need to quantitatively understand 1) the ecosystem services derived in regions of complex terrain, 2) the process regulation occurred to maintain those services, and 3) the sensitivities defining thresholds critical in stability of these systems. The TERRECO-IRTG is dedicated to joint study of ecosystems in complex terrain from landscape to regional scales. Our objectives are to reveal the spatial patterns in driving variables of essential ecosystem processes involved in ecosystem services of complex terrain region and hence, to evaluate the resulting ecosystem services, and further to provide new tools for understanding and managing such areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.297-306
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• 2019

Soil moisture monitoring is an important task to cope with climate change, and soil water prediction can provide large-scale soil moisture information. Therefore, this study was conducted to evaluate the relationship between the measured and predicted soil water content, and to estimate the correlation between the soil characteristics and soil water content. The selected sites in soil moisture monitoring network were 76, and the soil with high sand content (sand, loamy sand, and sandy loam in soil texture) accounted for 77% of the total. Organic matter and bulk density were 0.03 to 3.50% and 1.01 to 1.69 Mg m^-3, respectively. Predicting values of field capacity and wilting point were lower than the measured soil water content, and the correlation coefficient between the measured and predicted values were low as 0.548 to 0.748. However, a significantly high positive correlation (p<0.01) found between the measured and predicted soil water content. Soil water (field water capacity and wilting point) content was highly positively correlated with silt, clay, and organic matter (p<0.01) and highly negatively correlated with sand (p<0.01).

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.19-27
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• 2012

The open-top chamber (OTC) system is designed for long term studies on the climate change impact on the major tree species and their community in Korea. In Korea Forest Research Institute (KFRI), the modified OTC system has been operating since September 2009. The OTC facility consists of six decagon chambers (10 meters in diameter by 7 meters high) with controlled gas concentration. In each chamber, a series of vertical vent pipes are installed to disperse carbon dioxide or normal air into the center of the chamber. The OTC is equipped with remote controlled computer system in order to maintain a stable and elevated concentration of carbon dioxide in the chamber throughout the experimental period. The experiment consisted of 4 treatments: two elevated $CO_2$ levels ($1.4{\times}$ and $1.8{\times}$ ambient $CO_2$) and two controls (inside and outdoors of the OTC). Average operational rate was the lowest (94.2%) in June 2010 but increased to 98% in July 2010 and was 100% during January to December 2011. In 2010~2011, $CO_2$ concentrations inside the OTCs reached the target programmed values, and have been maintained stable in 2011. In 2011, $CO_2$ concentrations of 106%, 100% and 94% of target values has been recorded in control OTC, $1.4{\times}$ $CO_2$-enriched OTC and $1.8{\times}$ $CO_2$-enriched OTC, respectively. With all OTC chambers, the difference between outside and inside temperatures was the highest ($1.2{\sim}2.0^{\circ}C$) at 10 am to 2 pm. Temperature difference between six OTC chambers was not detected. The relative humidity inside and outside the chambers was the same, with minor variations (0~1%). The system required the highest amount of $CO_2$ for operation in June, and consumed 11.33 and 17.04 ton in June 2010 and 2011, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.11-21
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• 2014

The purpose of this study was to furnish basic information for forest community ecology and to accumulate vegetational datum related to hierarchy of forest community for the efficient management of forest vegetation in Mt. Mani. Samples were collected and analyzed by 32 releves from August to October in 2010 using phytosociological analysis methodology of Z-M school and importance value analysis. The results were summarized that the forest vegetation was classified into 5 units in total. Importance value at vegetation unit 1 indicated Pinus densiflora 54.31 (18.10%), Quercus mongolica 39.21 (13.07%), Carpinus coreana 37.29 (12.43%), at vegetation unit 2 Quercus mongolica 89.43 (22.23%), Rhododendron mucronulatum 57.75 (14.43%), Carpinus coreana 47.19(11.80%), at vegetation unit 3 Styrax japonica 53.97 (13.50%), Acer mono 33.60 (8.40%), Carpinus coreana 26.48 (6.62%), Quercus serrata 22.51 (5.64%), at vegetation unit 4 Carpinus coreana 47.70 (11.92%), Quercus acutissima 38.40 (9.60%) and at vegetation unit 5 Evodia daniellii 80.59 (20.14%), Robinia pseudoacacia 35.00 (8.74%), Pueraria thunbergiana 28.63 (7.15%), Quercus dentata 28.20 (7.05%) in the order, respectively.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.701-715
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• 2020

This study compared several reference evapotranspiration estimated using eight methods such as FAO-56 Penman-Monteith (FAO PM), Hamon, Hansen, Hargreaves-Samani, Jensen-Haise, Makkink, Priestley-Taylor, and Thornthwaite. In addition, by analyzing the monthly deviations of the results by the FAO PM and the remaining seven methods, monthly optimized correction coefficients were derived and the improvement effect was evaluated. These methods were applied to 73 automated synoptic observation system (ASOS) stations of the Korea Meteorological Administration, where the climatological data are available at least 20 years. As a result of evaluating the reference evapotranspiration by applying the default coefficients of each method, a large fluctuation happened depending on the method, and the Hansen method was relatively similar to FAO PM. However, the Hamon and Jensen-Haise methods showed more large values than other methods in summer, and the deviation from FAO PM method was also large significantly. When comparing based on the region, the comparison with FAO PM method provided that the reference evapotranspiration estimated by other methods was overestimated in most regions except for eastern coastal areas. Based on the deviation from the FAO PM method, the monthly correction coefficients were derived for each station. The monthly deviation average that ranged from -46 mm to +88 mm before correction was improved to -11 mm to +1 mm after correction, and the annual average deviation was also significantly reduced by correction from -393 mm to +354 mm (before correction) to -33 mm to +9 mm (after correction). In particular, Hamon, Hargreaves-Samani, and Thornthwaite methods using only temperature data also produced results that were not significantly different from FAO PM after correction. It can be also useful for forecasting long-term reference evapotranspiration using temperature data in climate change scenarios or predicting evapotranspiration using monthly or seasonal temperature forecasted values.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.