• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Economic and Environmental Geology
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• v.57 no.2
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• pp.161-175
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• 2024

Aggregate typically refers to sand and gravel formed by the transportation of rocks in rivers or artificially crushed, constituting a core resource in the construction industry. Gyeongsangbuk-do, the largest administrative area in South Korea, produces various sources of gravel, including forest, land (excluding other sources), river, and crushed stone. As of 2022, it has extracted approximately 6.96 million cubic meters of aggregate, with permitted production totaling around 4.07 million cubic meters and reported production of about 2.88 million cubic meters. The aggregate demand in Gyeongsangbuk-do is estimated to be 12.39 million cubic meters according to the estimation method in Ready-Mix Concrete. From the supply perspective, about 120 extraction sites are operational, with most municipalities maintaining an appropriate balance between aggregate demand and supply. However, in some areas, there is inbound and outbound transportation of aggregate to neighboring regions. Regions with significant inbound and outbound aggregate transportation in Gyeongsangbuk-do are areas connected to Daegu Metropolitan City and Pohang City along the Gyeongbu rail line, showing a high correlation with population distribution. Gyeongsangbuk-do faces challenges such as population decline, aging rural areas, and insufficient balanced regional development. Analysis using GIS reveals these trends in gravel demand and supply. Currently in this study, Gyeongsangbuk-do meets its demand for aggregate through the supply of various aggregate sources, maintaining stable aggregate procurement. River and terrestrial aggregates may be sustained as short-term supply strategies due to the difficulty of longterm development. Considering the reliance on raw material supply for selective crushing, it suggests the need for raw material management to maintain stability. Gyeongsangbuk-do highlights quarries in the forest as an important resource for sustainable aggregate supply, advocating for the development of large-scale aggregate quarries as a long-term alternative. These research findings are expected to provide valuable insights for formulating strategies for sustainable management and stable utilization of aggregate resources.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.6
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• pp.460-466
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• 2009

Carbon fixation and density of crops are important to estimate carbon uptake or emission by agricultural production activities and to establish life cycle inventory of crops for assessment of climate change impact. In this study, regional carbon fixation and density in each part of 14 crops, harvest index, and ratio of aboveground to underground were investigated to estimate biomass of 14 crops in Korea by using agricultural statistics data. Biomass yield of potato was $16.5ton\;ha^{-1}$, which was the highest, and those of rice, sweet potato, and garlic were $10.5ton\;ha^{-1}$, $8.7ton\;ha^{-1}$, and $7.5ton\;ha^{-1}$ respectively. Biomass yield of Green onion was the lowest as $2.8ton\;ha^{-1}$. Carbon density of 14 crops were in the order of potato ($6.4ton\;ha^{-1}$), rice ($4.2ton\;ha^{-1}$), sweet potato ($3.4ton\;ha^{-1}$), rape ($2.9ton\;ha^{-1}$) and garlic ($2.8ton\;ha^{-1}$). Regional distribution of carbon contents for each crop mapped revealed that carbon fixation of rice, soybean, sesame, garlic, and green onion were the highest in Jeonnam province, barley, red pepper, and watermelon in Gyeongnam, perilla in Chungnam, peanut in Gyeongbuk, rape and carrot in Jeju, sweet potato in Gyeonggi, potato in Gangwon. The results can be applied for assessing life cycle inventory of crops and crop productivity using remotely sensed data.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.1
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• pp.1-15
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• 2015

Impacts of Sea Surface Temperature (SST) assimilation to the prediction of upper ocean temperature is investigated by using a regional ocean forecasting system, in which 3-dimensional optimal interpolation is applied. In the present study, Sea Surface Temperature and Sea Ice Analysis (OSTIA) dataset is adopted for the daily SST assimilation. This study mainly compares two experimental results with (Exp. DA) and without data assimilation (Exp. NoDA). When comparing both results with OSTIA SST data during Sept. 2011, Exp. NoDA shows Root Mean Square Error (RMSE) of about $1.5^{\circ}C$ at 24, 48, 72 forecast hour. On the other hand, Exp. DA yields the relatively lower RMSE of below $0.8^{\circ}C$ at all forecast hour. In particular, RMSE from Exp. DA reaches $0.57^{\circ}C$ at 24 forecast hour, indicating that the assimilation of daily SST (i.e., OSTIA) improves the performance in the early SST prediction. Furthermore, reduction ratio of RMSE in the Exp. DA reaches over 60% in the Yellow and East seas. In order to examine impacts in the shallow costal region, the SST measured by eight moored buoys around Korean peninsula is compared with both experiments. Exp. DA reveals reduction ratio of RMSE over 70% in all season except for summer, showing the contribution of OSTIA assimilation to the short-range prediction in the coastal region. In addition, the effect of SST assimilation in the upper ocean temperature is examined by the comparison with Argo data in the East Sea. The comparison shows that RMSE from Exp. DA is reduced by $1.5^{\circ}C$ up to 100 m depth in winter where vertical mixing is strong. Thus, SST assimilation is found to be efficient also in the upper ocean prediction. However, the temperature below the mixed layer in winter reveals larger difference in Exp. DA, implying that SST assimilation has still a limitation to the prediction of ocean interior.

• Journal of the Korean association of regional geographers
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• v.2 no.1
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• pp.51-67
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• 1996

There are three main rice-growing regions in the United States: the prairie region along the Mississippi River Valley in eastern Arkansas; the Gulf Coast prairie region in southwestern Louisiana and southeastern Texas; and the Central Valley of California. The Central Valley of California is producing about 23% of the US rice(Fig. 1). In California. most of the crop has been produced in the Colusa, Sutter, Butte, Glenn Counties of the Sacramento Valley since 1912, when rice was commercially grown for the first time in the state(Fig. 2). Roughly speaking, the average annual area sown to rice in California is about 300,000 acres to 400,000 acres during the last forty years(Fig. 3). California rice is grown under a Mediterranean climate characterized by warm, dry, clear days, and a long growing season favorable to high photosynthetic rates and high rice yields. The average rice yield per acre is probably higher in California than in any other rice-growing regions of the world(Fig. 4). A dependable supply of irrigation water must be available for a successful rice culture. Most of the irrigation water for California rice comes from the winter rain and snow-fed reservoir of the Sierra Nevada mountain ranges. Less than 10 percent of rice irrigation water is pumped from wells in areas where surface water is not sufficient. It is also essential to have good surface drainage if maximum yields are to be produced. Rice production in California is highly mechanized, requiring only about four hours of labor per acre. Mechanization of rice culture in California includes laser-leveler technology, large tractors, self-propelled combines for harvesting, and aircraft for seeding, pest control, and some fertilization. The principal varieties grown in California are medium-grain japonica types with origins from the cooler rice climates of the northern latitudes (Table 1). Long-grain varieties grown in the American South are not well adapted to California's cooler environment. Nearly all the rice grown recently in California are improved into semidwarf varieties. Choice of variety depends on environment, planting date, quality desired, marketing, and harvesting scheduling. The Rice Experiment Station at Biggs is owned, financed, and administered by the rice industry. The station was established in 1912, as a direct result of the foresight and effort of Charles Edward Chambliss of the United States Department of Agriculture. Now, The station's major effort is the development of improved rice varieties for California.

• Journal of the Korean association of regional geographers
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• v.5 no.2
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• pp.133-142
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• 1999

The wetland is very important ecologically as a habitat of diverse organisms. The purpose of this paper is to elucidate the morphogenetic environment of Jilmoe Bog found in the Odae Mountain National Park Jilmoe Bog is located in the high etchplain(1,060m) where Daebo Granite which had intruded in Jura epoch of Mesozoic era has weathered deeply and has uplifted in the Tertiary. The annual mean temperature of study area is $5.3^{\circ}C$, the annual precipitation is 2,888mm. The minimun temperature of the coldest month(january) is below $-30^{\circ}C$ and the depth of frozen soil is over 1.6m. Jilmoe bog consists of a large bog and a small bog. The length of the large bog is 63m and its width is 42m. The basal surface of Jilmoe bog is uneven. Jilmoe bog is a string bog fanned due to frost actions. In String bog, its surface is wavy with stepped dry hills and net-like troughs crossing hill slope. It seems that string bog is related to the permofrost or seasonal permofrost of cold conifer forest(taiga) zone(where the depth of frozen soil is very deep in the least in winters). String bog is a kind of thermokarst that frozen soil thaws differentially locally in declining permofrost and ground surface becomes irregular. There is turf-banked terracette of width $30{\sim}40cm$ in the headwall of small cirque-type nivation hollow formed at footslope of Maebong mountain around Jilmoe bog. This turf-banked terracette is formed by the frost growth of soil water below grass mat in periglacial climate environment. Where water is plentiful such as a nivation follow${\sim}$valley corridor and a headwall of valley, turf patterned grounds of width $30{\sim}50cm$ are found. This turf patterned ground is 'unclassified patterned ground', earth hummock. In conclusion, Jilmoe bog is a string bog of thermokarst that the relief of ground surface is irregular according to locally differentially thawing of permofrost(frozen soil). Jilmoe bog is high moor, its surroundings belongs to periglacial environment that turf-banked terracette and turf patterned ground are fanned actively.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.151-164
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• 1998

I analyzed the correlation between El-Nino phenomenon and our country's temperature and precipitation laying the stress on the anomaly, and the result of this analysis is as follows: (1) The extraction of the occurrences of El-Nino at the place of sea surface around Nino.3 which was known as the sea area under observation for El-Nino reveals that there are 9 years (1969, 1970, 1973, 1977, 1987, 1992, 1995, 1998) when the temperature anomaly in January is more than 1.0 during the period of research years ($1969{\sim}1998$). (2) The tendency of change of sea surface temperature around Nino.3 and that of our country are about the same, but the anomaly of Pusan and Inchon was much greater than that of Jangki in the East Coast. (3) The anomaly of sea surface temperature around Nino.3 and that of the ground temperature showed the similar changing tendency, the temperature of our country has something to do with that of sea surface as the correlation of ground temperature with the temperature of sea surface showed 0.31. Anomaly warm winter has something to do with El-Nino because the temperature of our country was high when El-Nino phenomenon appeared. (4) As for the precipitation, we can see that it has generally increased after 1989 when the phenomenon of warm climate was intense than before that year. But as we study the change of anomaly, the precipitation has less correlation in comparison with the ground temperature. The precipitation in 1973, 1983 and 1987 which were El-Nino years was correlated with El-Nino. While the change of sea surface temperature has showed a tendency of plus(+)increase since 1990, the precipitation has showed a tendency of minus (-)decrease. Therefore it seems that the temperature of sea surface has little correlation with the amount of rainfall.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.174-184
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• 2009

Evapotranspiration (ET) is one of the major hydrologic processes in terrestrial ecosystems. A reliable estimation of spatially representavtive ET is necessary for deriving regional water budget, primary productivity of vegetation, and feedbacks of land surface to regional climate. Moderate resolution imaging spectroradiometer (MODIS) provides an opportunity to monitor ET for wide area at daily time scale. In this study, we applied a MODIS-based ET algorithm and tested its reliability for nine flux tower sites in East Asia. This is a stand-alone MODIS algorithm based on the Penman-Monteith equation and uses input data derived from MODIS. Instantaneous ET was estimated and scaled up to daily ET. For six flux sites, the MODIS-derived instantaneous ET showed a good agreement with the measured data ($r^2=0.38$ to 0.73, ME = -44 to $+31W\;m^{-2}$, RMSE =48 to $111W\;m^{-2}$). However, for the other three sites, a poor agreement was observed. The predictability of MODIS ET was improved when the up-scaled daily ET was used ($r^2\;=\;0.48$ to 0.89, ME = -0.7 to $-0.6\;mm\;day^{-1}$, $RMSE=\;0.5{\sim}1.1\;mm\;day^{-1}$). Errors in the canopy conductance were identified as a primary factor of uncertainty in MODIS-derived ET and hence, a more reliable estimation of canopy conductance is necessary to increase the accuracy of MODIS ET.

• Korean Journal of Plant Resources
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• v.32 no.4
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• pp.355-378
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• 2019

We investigated the flora of vascular plants in Mt. Papyeong which is located in the northern part of Paju and the border of western DMZ through 13 surveys from April 2016 to August 2019. The vascular plants of Mt. Papyeong include 410 taxa; 361 species, 9 subspecies, 36 varieties, and 4 forms from 257 genera of 91 families. Among 410 taxa, we characterize endemic species, rare and endangered plants, floristic regional indicator plants, and climate change adapted plants in Korea. Specifically, there are 9 Korean endemic plants designated by Korea National Arboretum and 6 taxa by Korean Ministry of Environment. According to IUCN evaluation, there are 13 rare and endangered plants in Mt. Papyeong. On the other hand, 2 taxa were listed in a red list suggested by Korean Ministry of Environment. The floristic regional indicator plants include 46 taxa which are composed of 2 species of IV degree, 13 taxa of III degree, 11 taxa of II degree, and 20 taxa of I degree. Also, 27 naturalized plants were identified, and the percentage of Naturalized Index (NI) and Urbanization Index (UI) were 6.58%, and 8.43%, respectively. We hope that this investigation provide a valuable data for applying the further studies on the biodiversity and strategy of conservation of environment in the DMZ and Paju areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.277-283
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• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.