• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.190-190
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• 2021

우리나라는 전체 면적의 63.0%가 산림으로 구성되어 있고, 일정면적 내 나무들의 총 부피를 의미하는 입목축적의 경우 1973년에 11.3 m³/ha에서 2015년에 146.0 m³/ha로 43년 동안 1292.0% 증가하였다. 이에 본 연구에서는 유역 면적의 70.2%가 산림에 해당하는 용담댐 상류 유역(930.2 km²)을 대상으로 SWAT(Soil and Water Assessment Tool)을 이용하여 장기간 산림 성장에 따른 수문 변화를 평가하였다. 산림 성장 변화 분석을 위해 산림청의 전국산림자원조사에서 제공하는 침엽수, 활엽수, 혼효림 식생 자료를 1980년부터 2019년까지 40년의 산림 성장 자료를 10년 단위(1980s; 1980~1989, 1990s; 1990~1999, 2000s; 2000~2009, 2010s; 2010~2019)로 구축하였으며, Terra MODIS MOD15A2 엽면적지수(LAI) 자료를 2010년부터 2019년까지 구축하였다. LAI는 연대별 식생 높이의 상관성을 고려하여 1980년부터 2019년까지 회귀하여 총 40년 자료를 구축하고 10년 단위로 활용하였다. SWAT의 검보정은 2010년부터 2019년까지 실측된 유량, 증발산량 및 토양수분을 이용하였으며 검보정 결과 유량의 평균 NSE는 0.57, R²는 0.69, RMSE는 1.66 mm/day, PBIAS는 4.95%이며, 증발산량 및 토양수분의 R²는 0.60, 0.52로 나타났다. 산림 성장에 따른 수문 변화를 관찰하기 위해 기상자료를 2010s로 고정하고 연대별 산림 정보를 입력하여 산림 성장이 물순환에 미치는 영향을 시공간적으로 평가할 예정이며, 침엽수, 활엽수, 혼효림 생장을 개별적으로 분석하여 식생별 영향을 비교 및 평가할 예정이다.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.47-47
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• 2017

Rice cropping in Cambodia was commonly classified into 4 types: rainfed rice, irrigated rice, floating rice and recession rice. The cropping type has been selected by farmers depended on water condition in each locations. However, recent technological and social change enforce famers to adapt new management of rice cropping. This study aimed to clarify the change in rice cropping and problems for future. Interviews to farmers has been conducted several times in Pursat province, which is one of the major rice production provinces in Cambodia. The last interview was conducted in March 2017, and focused on change in rice cropping for 10 years. Statistical data was obtained from Provincial Ministry of Agriculture in Pursat. The satellite data (LAI products derived from MODIS) was used to quantify change in cropping pattern. The statistical data shows increase in production and yield of rice, dry season rice and so on.

• Journal of Korean Society on Water Environment
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• v.29 no.2
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• pp.247-258
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• 2013

A grid-based configuration of Land Surface Models (LSMs) coupled with a climate model can be advantageous in impact assessment of climate change for a large scale area. We assessed the applicability of Common Land Model (CoLM) to runoff and land surface temperature (LST) simulations at the domain that encompasses the Nakdong river basin. To establish a high resolution model configuration of a $1km{\times}1km$ grid size, both surface boundary condition and atmospheric inputs from the observed weather data in 2009 were adjusted to the same resolution. The Leaf Area Index (LAI) was collected from MODerate esolution Imaging Spectroradiometer (MODIS) and the downward short wave flux was produced by a nonstationary multi-site weather state model. Compared with the observed runoffs at the stations on Nakdong river, simulated runoffs properly responded to rainfall. The spatial features and the seasonal variations of the domain fairly well were captured in the simulated LSTs as well. The monthly and seasonal trend of LST were described well compared to the observations, however, the monthly averaged simulated LST exceeded the observed up to $2^{\circ}C$ at the 24 stations. From the results of our study, it is shown that high resolution LSMs can be used to evaluate not only quantity but also quality of water resources as it can capture the geographical features of the area of interest and its rainfall-runoff response.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.121-131
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• 2018

Climate change has caused changes in environmental factors that have a direct impact on agriculture such as temperature and precipitation. The meteorological disaster that has the greatest impact on agriculture is drought, and its forecasts are closely related to agricultural production and water supply. In the case of terrestrial data, the accuracy of the spatial map obtained by interpolating the each point data is lowered because it is based on the point observation. Therefore, acquisition of various meteorological data through satellite imagery can complement this terrestrial based drought monitoring. In this study, Evaporative Stress Index (ESI) was used as satellite data for drought determination. The ESI was developed by NASA and USDA, and is calculated through thermal observations of GOES satellites, MODIS, Landsat 5, 7 and 8. We will identify the difference between ESI and other satellite-based drought assessment indices (Vegetation Health Index, VHI, Leaf Area Index, LAI, Enhanced Vegetation Index, EVI), and use it to analyze the drought in South Korea, and examines the applicability of ESI as a new indicator of agricultural drought monitoring.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.337-346
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• 2010

Climate change has a huge impact on various parts of the world. This study quantified and analyzed the effects on hydrological behavior caused by climate, vegetation canopy and land use change of Soyanggang dam watershed (2,694.4 $km^2$) using the semi-distributed model SWAT (Soil Water Assessment Tool). For the 1997-2006 daily dam inflow data, the model was calibrated with the Nash-Sutcliffe model efficiencies between the range of 0.45 and 0.91. For the future climate change projection, three GCMs of MIROC3.2hires, ECHAM5-OM, and HadCM3 were used. The A2, A1B and B1 emission scenarios of IPCC (Intergovernmental Panel on Climate Change) were adopted. The data was corrected for each bias and downscaled by Change Factor (CF) method using 30 years (1977-2006, baseline period) weather data and 20C3M (20th Century Climate Coupled Model). Three periods of data; 2010-2039 (2020s), 2040-2069 (2050s), 2070-2099 (2080s) were prepared for future evaluation. The future annual temperature and precipitation were predicted to change from +2.0 to $+6.3^{\circ}C$ and from -20.4 to 32.3% respectively. Seasonal temperature change increased in all scenarios except for winter period of HadCM3. The precipitation of winter and spring increased while it decreased for summer and fall for all GCMs. Future land use and vegetation canopy condition were predicted by CA-Markov technique and MODIS LAI versus temperature regression respectively. The future hydrological evaluation showed that the annual evapotranspiration increases up to 30.1%, and the groundwater recharge and soil moisture decreases up to 55.4% and 32.4% respectively compared to 2000 condition. Dam inflow was predicted to change from -38.6 to 29.5%. For all scenarios, the fall dam inflow, soil moisture and groundwater recharge were predicted to decrease. The seasonal vapotranspiration was predicted to increase up to 64.2% for all seasons except for HadCM3 winter.