• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.75-88
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• 2024

It would be advantageous to predict acreage and yield of crops in major grain-exporting countries, which would improve decisions on policy making and grain trade in Korea. A climate suitability model can be used to assess crop acreage and yield in a region where the availability of observation data is limited for the use of process-based crop models. The objective of this study was to determine the climate suitability index of wheat by province in Ukraine, which would allow for the spatial assessment of acreage and yield for the given crop. In the present study, the official data of wheat acreage and yield were collected from the State Statistics Service of Ukraine. The EarthStat data, which is a data product derived from satellite data and official crop reports, were also gathered for the comparison with the map of climate suitability index. The Fuzzy Union model was used to create the climate suitability maps under the historical climate conditions for the period from 1970 to 2000. These maps were compared against actual acreage and yield by province. It was found that the EarthStat data for acreage and yield of wheat differed from the corresponding official data in several provinces. On the other hand, the climate suitability index obtained using the Fuzzy Union model explained the variation in acreage and yield at a reasonable degree. For example, the correlation coefficient between the climate suitability index and yield was 0.647. Our results suggested that the climate suitability index could be used to indicate the spatial distribution of acreage and yield within a region of interest.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.3
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• pp.315-328
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• 2024

Precipitation is a crucial meteorological variable widely used as essential input data in most hydrological models. However, due to climate change, there is an escalating precipitation variability. Trend analysis plays an important role in planning and operating water resources systems. As recently developed, Innovative Polygon Trend Analysis (IPTA) is useful in identifying and and analyzing the trends of hydrologic variables. In this study, the IPTA was applied to monthly precipitation data obtained from 13 meteorological observatories in Jeolla province, along with synthesized precipitation data according to Shared Socioeconomic Pathways (SSP) scenarios. The trend results were compared those obtained from the Mann-Kendall test and the Sen's slope estimation which are generally used in practice. The results revealed monthly precipitations from February to July and November had increasing trends, and monthly precipitation in October had a decreasing trend. IPTA, Mann-Kendall test, and Sen's slope estimation detected trends in 75.00 %, 5.13 %, and 5.13 % of 156(13 stations × 12 months) time series of monthly precipitation, respectively, which indicates that the IPTA is more sensitive in trend detection compared to the Mann-Kendall test and Sen's slope estimation.

• Korean Journal of Environmental Agriculture
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• v.13 no.1
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• pp.39-46
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• 1994

Two types of sunshine recorders, Jordan and bimetal, were used for measuring the duration of sunshine and percentage of sunshine in Weather Forecast Offices(WFO) and Weather Observation Stations(WOS) in Korea, respectively.These two gauges showed different values in each element observation. To evaluate the solar energy resources by duration and percentage of sunshine, relevant parameter should be adapted to use the two kinds of data for zoning of agricultural climatic area and comparison of regional solar energy distributions. In this respect, the correlation and distribution pattern were found by analyzing data from the two types of sunshine recorders. The results were as follows. The monthly duration of sunshine by the Jordan type was $50{\sim}60$ hours lower than the bimetal type and its value in May was the highest in a year. The percentage of sunshine by the Jordan type was $5{\sim}10%$ lower than the bimetal type. The seasonal difference of sunshine hour data by two types of sunshine recorder became small in winter but large in summer. Standard deviation of monthly duration of sunshine of WFO and WOS was $11{\sim}32$ and $17{\sim}25$ hours and percentage of sunshine was $3{\sim}11$ and $4{\sim}9$ % respectively. The range of deviation in WOS data was smaller than WFO. The highest distribution of duration and percentage of sunshine was in the Southern Coastal Area, whereas the lowest in the Central North Western Area.

• Journal of the Korean association of regional geographers
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• v.19 no.2
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• pp.234-245
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• 2013

In order to examine the amount and rate of soil erosion on Ridge Traversing Trail in Jirisan National Park, a cross-sectional area of hiking trail were monitored at 16 sites in Nogodan - Samdobong section from November 2011 to April 2012. Although all sites demonstrates an enlarged cross-section of trail, the amount of soil erosion varies from site to site: 54.9 to $908.8cm^2$. It suggests that the erosional rate ranges from $0.1cm^2/day$ to $1.72cm^2/day$. The erosional amount is also varied with a trail type: $109.3cm^2$ for a shallow gully-like trail to $573.2cm^2$ for a unilateral trail. However, the cross-sectional change is larger on a sidewall than a tread irrespective of a trail type. The erosional amounts of November to April are smaller than that of May to October. In particular, the erosional amount of November 2011 to April 2012 is smaller than the depositional amount, implying a reduced cross-section of trail. Pipkrake action puts loose soil particles on a sidewall on March and April, and then rainwash due to a heavy rainfall takes them away after May. It seems to be the most predominant erosional process in Ridge Traversing Trail. A sidewall facing north shows a larger amount of erosion than a sidewall facing south. It also implies a difference in the development of a pipkrake according to an aspect. The small amount of erosion and cross-sectional decrease, which is usually observed on April, results from the combined effect of frost heaving, pipkrake action, a small rainfall and a temporary suspension of trampling. It is necessary to establish the monitoring system of trail erosion in terms of the management of hiking trail in a mountain national park.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.146-154
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• 2023

In this study, the peak wave period T_p and mean wave period T₀₂ and T_{m-1, 0}, which are major parameters for classifying ocean characteristics, were calculated using water surface elevation data observed from the second west coast oceanographic and meteorological observation tower. In addition, the ratio of abnormal data, correlation analysis, and optimal probability density function were estimated. In the case of T_p among the calculated representative periods, the proportion of abnormal data was 5.73% and 0.67% at each point, and T₀₂ was 4.35% and 0.01%. T_{m-1, 0} was found to be 2.82% and 0.03%. Meanwhile, as a result of analyzing the relationship between T₀₂ and T_p, the relationship was calculated to be 0.53 and 0.63 for each point. The relationship between T_{m-1, 0} and T_p was 1.15 and 1.32, respectively, and T₀₂, T_{m-1, 0} was 1.18 and 1.22. As a result of estimating the optimal probability density function of the calculated representative period, T_p followed the 'Log-normal' and 'Normal' distributions at each point, and T₀₂ was 'Gamma', 'Normal' distribution and T_{m-1, 0} showed that 'Log-normal' and 'Normal' distribution were dominant, respectively. It is decided that these results can be used as basic data for wave analysis conducted on the west coast.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.731-741
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• 2008

Previous studies on the numerical simulation at the tidal reach of Han River tend to restrict downstream boundary as Jeon-ryu station due to difficulties in gaining cross section data and tidal elevation values at Yu-do. But, in this study, geometries beyond the confluence of Gok-reung stream and Im-jin River are constructed based on the numerical sea map; tidal elevation at the downstream boundary, Yu-do is estimated by harmonic analysis of In-cheon tide gage station so that hydrodynamic and diffusion behavior have been analyzed. The domain ranging from Shin-gok submerged weir to Yu-do is selected (which is 36.8 km in length). RMA-2 and RAM4 developed by Il Won Seo (2008) are applied to simulate flow and diffusion behavior, respectively. Numerical results of flow characteristic are compared with the measured data at Jeon-ryu station. Simulation is carried out from June 23 to 25 in 2006 on the ground that hydrologic data is satisfactory and tidal difference is huge during that period. The result shows that reverse flow occurs 5 times according to the tidal elevation at Yu-do and the maximum reverse flow is observed up to Jang-hang IC, which is 32.9 km in length. Also analysis is focused on the process of generation and disappearance of reverse flow, the distribution of water surface elevation and velocity along the maximum velocity line, and the transport of nonconservative pollutant. Pollutant injected from Gul-po stream spreads widely across the river; however, the size of BOD cloud entering from Gok-reung stream is relatively small because water depth at the mid and left side becomes deeper and maximum velocity occurs along the right bank so that transverse mixing is completed quickly. Finally, mixing characteristic of horizontal salinity distribution is obtained by estimating the salinity input with analytical solution of 1D advection-dispersion equation.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.919-932
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• 2019

Fine particulate matter (PM2.5) is not only affected by anthropogenic emissions, but also intensifies, migrates, decreases by hydrometeorological factors. Therefore, it is essential to understand relationships between the hydrometeorological factors and PM2.5 concentration. In Korea, PM2.5 concentration is measured at the ground observatories and estimated data are given to locations where observatories are not present. In this way, the data is not suitable to represent an area, hence it is impossible to know accurate concentration at such locations. In addition, it is hard to trace migration, intensification, reduction of PM2.5. In this study, we analyzed the relationships between hydrometeorological factors, acquired from Global Land Data Assimilation System (GLDAS), and PM2.5 by means of Bayesian Model Averaging (BMA). By BMA, we also selected factors that have meaningful relationship with the variation of PM2.5 concentration. 4 PM2.5 concentration models for different seasons were developed using those selected factors, with Aerosol Optical Depth (AOD) from MODerate resolution Imaging Spectroradiometer (MODIS). Finally, we mapped the result of the model, to show spatial distribution of PM2.5. The model correlated well with the observed PM2.5 concentration (R ~0.7; IOA ~0.78; RMSE ~7.66 ㎍/㎥). When the models were compared with the observed PM2.5 concentrations at different locations, the correlation coefficients differed (R: 0.32-0.82), although there were similarities in data distribution. The developed concentration map using the models showed its capability in representing temporal, spatial variation of PM2.5 concentration. The result of this study is expected to be able to facilitate researches that aim to analyze sources and movements of PM2.5, if the study area is extended to East Asia.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.613-623
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• 2019

Over the past decades, daily sea surface temperature (SST) composite data have been produced using periodically and extensively observed satellite SST data, and have been used for a variety of purposes, including climate change monitoring and oceanic and atmospheric forecasting. In this study, we evaluated the accuracy and analyzed the error characteristic of the SST composite data in the sea around the Korean Peninsula for optimal utilization in the regional seas. We evaluated the four types of multi-satellite SST composite data including OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis), OISST (Optimum Interpolation Sea Surface Temperature), CMC (Canadian Meteorological Centre) SST, and MURSST (Multi-scale Ultra-high Resolution Sea Surface Temperature) collected from January 2016 to December 2016 by using in-situ temperature data measured from the Ieodo Ocean Research Station (IORS). Each SST composite data showed biases of the minimum of 0.12℃ (OISST) and the maximum of 0.55℃ (MURSST) and root mean square errors (RMSE) of the minimum of 0.77℃ (CMC SST) and the maximum of 0.96℃ (MURSST) for the in-situ temperature measurements from the IORS. Inter-comparison between the SST composite fields exhibited biases of -0.38-0.38℃ and RMSE of 0.55-0.82℃. The OSTIA and CMC SST data showed the smallest error while the OISST and MURSST data showed the most obvious error. The results of comparing time series by extracting the SST data at the closest point to the IORS showed that there was an apparent seasonal variation not only in the in-situ temperature from the IORS but also in all the SST composite data. In spring, however, SST composite data tended to be overestimated compared to the in-situ temperature observed from the IORS.