• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.392-402
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• 2021

The present study investigated the effects of tillage practices (deep cultivation [DC] and conventional tillage [CT]) and extended planting dates (mid-June to July) for maize-onion rotation in paddy fields. The silage corn (Zea mays L.) cultivar 'Kwangpyeongok' and the waxy corn cultivar 'Ilmichal' were planted on June 14, July 3, and July 15 in 2019. In both maize, the plant height of June 14 planted was up to 100 cm greater than that of July 15 planted on August 16 and up to 40 cm on August 30. At 30 Days after planting, the leaf area index (LAI) of silage corn planted on July 3 and 15 greater than that of corn planted on June 14 due to high temperature in the early season; however, there were no differences in the LAI of waxy corn according to the planting date. Despite favorable temperature, plants sown on July 3 and 15 experienced high moisture stress during the seedling stage due to consistent rainfall, and waxy corn was highly sensitive to high moisture stress. The total yield of silage corn was 1,232 (845 in TDN), 860 (598 in TDN), and 765 (508 in TDN) DW kg·10a^-1 for plants sown on June 14, July 3, and July 15, respectively. The fresh marketable ear yield of waxy corn was 872, 814, and 525 FW kg·10a^-1 for plants sown on June 14, July 3, and July 15, respectively. After the completion of maize cultivation, onion seedlings (Allium cepa L.) were transplanted on November 12, 2019, and harvested on May 27, 2020. Neither summer tillage nor maize planting date affected onion growth or yield. The marketable onion yield was 8,305 and 7,848 kg·10a^-1 with DC and CT, respectively. In conclusion, DC did not improve maize growth or yield under paddy conditions. Mid-June to early July is a practical window for maize planting for growers in this region.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.903-913
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• 2021

In the flood season, the measurement of the river discharge has many restrictions due to reasons such as budget, manpower, safety, convenience in measurement and so on. In particular, when heavy rain events occur due to typhoons, etc., it is difficult to measure the amount of flood due to the above problems. In order to improve this problem, in this study, a method was developed that can measure the river discharge in a flood season simply and safely in a short time with minimal manpower by combining the functions of a drone and a surface velocity doppler radar. To overcome the mechanical limitations of drones caused by weather issues such as wind and rainfall derived from the measurement of the river discharge using the conventional drone, we developed a drone with P56 grade dustproof and waterproof performance, stable flight capability at a wind speed of up to 36 km/h, and a payload weight of up to 10 kg. Further, to eliminate vibration which is the most important constraint factor in the measurement with a surface velocity doppler radar, a damper plate was developed as a device that combines a drone and a surface velocity Doppler radar. The velocity meter DSVM (Dron and Surface Veloctity Meter using doppler radar) that combines the flight equipment with the velocity meter was produced. The error of ±3.5% occurred as a result of measuring the river discharge using DSVM at the point of Geumsan-gun (Hwangpunggyo) located at Bonghwang stream (the first tributary stream of the Geum River). In addition, when calculating the mean velocity from the measured surface velocity, the measurement was performed using ADCP simultaneously to improve accuracy, and the mean velocity conversion factor (0.92) was calculated by comparing the mean velocity. In this study, the discharge measured by combining a drone and a surface velocity meter was compared with the discharge measured using ADCP and floats, so that the application and utility of DSVM was confirmed.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.179-188
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• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.256-266
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• 2022

Empirical models including the Angstrom-Prescott (AP) model have been used to estimate solar radiation at sites, which would support a wide use of crop models. The objective of this study was to estimate two sets of solar radiation estimates using the AP coefficients derived for climate zone (AP_Frere) and specific site (AP_Choi), respectively. The daily solar radiation was estimated at 18 sites in Korea where long-term measurements of solar radiation were available. In the present study, daily solar radiation and sunshine duration were collected for the period from 2012 to 2021. Daily weather data including maximum and minimum temperatures and rainfall were also obtained to prepare input data to a process-based crop model, CERES-Rice model included in Decision Support System for Agrotechnology Transfer (DSSAT). It was found that the daily estimates of solar radiation using the climate zone specific coefficient, SFrere, had significantly less error than those using site-specific coefficients S_Choi (p<0.05). The cumulative values of S_Frere for the period from march to September also had less error at 55% of study sites than those of S_Choi. Still, the use of S_Frere and S_Choi as inputs to the CERES-Rice model resulted in slight differences between the outcomes of crop growth simulations, which had no significant difference between these outputs. These results suggested that the AP coefficients for the temperate climate zone would be preferable for the estimation of solar radiation. This merits further evaluation studies to compare the AP model with other sophisticated approaches such as models based on satellite data.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.65-81
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• 2021

In this study, soil moisture and evapotranspiration were calculated throughout South Korea using the Korea Land Data Assimilation System(KLDAS) of the Korea-Land Surface Information System(K-LIS) built on the basis of the Land Information System (LIS). The hydrometeorological data sets used to drive K-LIS and build KLDAS are MERRA-2(Modern-Era Retrospective analysis for Research and Applications, version 2) GDAS(Global Data Assimilation System) and ASOS(Automated Synoptic Observing System) data. Since ASOS is a point-based observation, it was converted into grid data with a spatial resolution of 0.125° for the application of KLDAS(ASOS-S, ASOS-Spatial). After comparing the hydrometeorological data sets applied to KLDAS against the ground-based observation, the mean of R² ASOS-S, MERRA-2, and GDAS were analyzed as temperature(0.994, 0.967, 0.975), pressure(0.995, 0.940, 0.942), humidity (0.993, 0.895, 0.915), and rainfall(0.897, 0.682, 0.695), respectively. For the hydrologic output comparisons, the mean of R² was ASOS-S(0.493), MERRA-2(0.56) and GDAS (0.488) in soil moisture, and the mean of R² was analyzed as ASOS-S(0.473), MERRA-2(0.43) and GDAS(0.615) in evapotranspiration. MERRA-2 and GDAS are quality-controlled data sets using multiple satellite and ground observation data, whereas ASOS-S is grid data using observation data from 103 points. Therefore, it is concluded that the accuracy is lowered due to the error from the distance difference between the observation data. If the more ASOS observation are secured and applied in the future, the less error due to the gridding will be expected with the increased accuracy.

• Proceedings of the Mineralogical Society of Korea Conference
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• 2001.06a
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• pp.38-39
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• 2001

The seasonal changes in pH, Fe, Al and SO$_4$$\^$2-/ contents of acid drainage released from coal mine dumps play a major role in precipitation of metal hydroxides in the Taebaek coal field area, southeastern Korea. Precipitates in the creeks underwent a cycle of the color change showing white, reddish brown and brownish yellow, which depends on geochemical factors of the creek waters. White precipitates consist of Al-sulfate (basaluminite and hydrobasaluminite) and reddish brown ones are composed of ferrihydrite and brownish yellow ones are of schwertmannite. Goethite coprecipitates with ferrihydrite and schwertmannite. Ferrihydrite formed at higher values than pH 5.3 and schwertmannite precipitated below pH 4.3, and goethite formed at the intermediate pH range between the two minerals. With the pH being increased from acid to intermediate regions, Fe is present both as schwertmannite and goethite. From the present observation, the most favorable pH that basauluminte can precipitate is in the range of pH 4.45-5.95. SEM examination of precipitates at stream bottom shows that they basically consist of agglomerates of spheroid and rod-shape bacteria. Bacteria species are remarkably different among bottom precipitates and, to a less extent, there are slightly different chemical compositions even within the same bacteria. The speciation and calculation of the mineral saturation index were made using MINTEQA2. In waters associated with yellowish brown precipitates mainly composed of schwertmannite, So$_4$ species is mostly free So$_4$$\^$2-/ ion with less AlSo$_4$$\^$+/, CaSo$\sub$(aq)/, and MgSo$\sub$4(aq)/. Ferrous iron is present mostly as free Fe$\^$2+/, and FeSo$\sub$4(aq)/ and ferric iron exists predominantly as Fe(OH)$_2$$\^$+/, with less FeSo$\sub$4(aq)/, Fe(OH)$_2$$\^$-/, FeSo$_4$$\^$-/ and Fe$\^$3+/, respectively Al exists as free Al$\^$3+/, AlOH$_2$$\^$-/, (AlSo$_4$)$\^$+/, and Al(So$_4$)$\^$2-/. Fe is generally saturated with respect to hematite, magnetite, and goethite, with nearly saturation with lepidocrocite. Aluminum and sulfate are supersaturated with respect to predominant alunite and less jubanite, and they approach a saturation state with respect to diaspore, gibbsite, boehmite and gypsum. In the case of waters associated with whitish precipitates mainly composed of basaluminite, Al is present as predominant Al$\^$3+/ and Al(SO$_4$)$\^$+/, with less Al(OH)$\^$2+/, Al(OH)$_2$$\^$+/ and Al(SO$_4$)$\^$2-/. According to calculation for the mineral saturation, aluminum and sulfate are greatly supersaturated with respect to basaluminite and alunite. Diaspore is flirty well supersaturated while jubanite, gibbsite, and boehmite are already supersaturated, and gypsum approaches its saturation state. The observation that the only mineral phase we can easily detect in the whitish precipitate is basaluminite suggests that growth rate of alunite is much slower than that of basaluminite. Neutralization of acid mine drainage due to the dilution caused by the dilution effect due to mixing of unpolluted waters prevails over the buffering effect by the dissolution of carbonate or aluminosilicates. The main factors to affect color change are variations in aqueous geochemistry, which are controlled by dilution effect due to rainfall, water mixng from adjacent creeks, and the extent to which water-rock interaction takes place with seasons. pH, Fe, Al and SO$_4$ contents of the creek water are the most important factors leading to color changes in the precipitates. A geochemical cycle showing color variations in the precipitates provides the potential control on acid mine drainage and can be applied as a reclamation tool in a temperate region with four seasons.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.139-153
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• 2023

This study aimed to understand the spatiotemporal variations in nitrogen content in the Gyeongan stream along the main stream and at the discharge points of the sub-basins, and to identify the origin of the nitrogen. Field surveys and laboratory analyses, including chemical compositions and isotope ratios of nitrate and boron, were performed from November 2021 to November 2022. Based on the flow duration curve (FDC) derived for the Gyeongan stream, the dry season (mid-December 2021 to mid-June 2022) and wet season (mid-June to early November 2022) were established. In the dry season, most samples had the highest total nitrogen(T-N) concentrations, specifically in January and February, and the concentrations continued to decrease until May and June. However, after the flood season from July to September, the uppermost subbasin points (Group 1: MS-0, OS-0, GS-0) where T-N concentrations continually decreased were separated from the main stream and lower sub-basin points (Group 2: MS-1~8, OS-1, GS-1) where concentrations increased. Along the main stream, the T-N concentration showed an increasing trend from the upper to the lower reaches. However, it was affected by those of the Osan-cheon and Gonjiamcheon, the tributaries that flow into the main stream, resulting in respective increases or decreases in T-N concentration in the main stream. The nitrate and boron isotope ratios indicated that the nitrogen in all samples originated from manure. Mechanisms for nitrogen inflow from manure-related sources to the stream were suggested, including (1) manure from livestock wastes and rainfall runoff, (2) inflow through the discharge of wastewater treatment plants, and (3) inflow through the groundwater discharge (baseflow) of accumulated nitrogen during agricultural activities. Ultimately, water quality management of the Gyeongan stream basin requires pollution source management at the sub-basin level, including its tributaries, from a regional context. To manage the pollution load effectively, it is necessary to separate the hydrological components of the stream discharge and establish a monitoring system to track the flow and water quality of each component.

• Research in Plant Disease
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• v.29 no.1
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• pp.23-38
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• 2023

The fire blight caused by Erwinia amylovora (Ea) is a devastating disease of Rosaceae plants, including commercially important apple and pear trees. Since the first report in Korea in May 2015, it has been spreading to neighboring regions gradually. Host plants can be infected by pollinators like bees, rainfall accompanied by wind, and cultural practices such as pruning. Many studies have revealed that wild Rosaceae plants such as Cotoneaster spp., Crataegus spp., Pyracantha spp., Prunus spp., and Sorbus spp. can be reservoirs of Ea in nature. However, wild Rosaceae plants in Korea have not been examined yet whether they are susceptible to fire blight. Therefore, the susceptibility to fire blight was examined with 25 species in 10 genera of wild Rosaceae plants, which were collected during 2020-2022, by artificial inoculation. Bacterial suspension (10⁸ cfu/ml) of Ea type strain TS3128 was inoculated artificially in flowers, leaves, stems, and fruits of each plant species, and development of disease symptoms were monitored. Moreover, the presence of Ea bacteria from inoculated samples were checked by conventional polymerase chain reaction. Total 14 species of wild Rosaceae plants showed disease symptoms of fire blight, and Ea bacteria were detected inside of inoculated plant parts. These results suggest that wild Rosaceae plants growing nearby commercial apple and pear orchards in Korea can be Ea reservoirs, and thus they should be monitored regularly to minimize the damage by Ea infection and spreading.

• Journal of Mushroom
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• v.21 no.1
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• pp.22-32
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• 2023

To investigate the effect of thinning intensity on environmental factors and ectomycorrhizal mushroom fruiting in forest ecosystems, we studied canopy closure, throughfall, soil temperature, soil moisture, light response of understory vegetation, and ectomycorrhizal mushroom fruiting in a 10-year-old pine forest after 34%, 45%, and 60% thinning. Canopy closure was significantly higher in the 34% treatment and control plots, ranging from 80-85% in April. However, in November, all thinning treatment plots showed a decrease of approximately 5-10% compared with the control plot. The 60% treatment plot had over 200 mm of additional throughfall compared with the control plot, and monthly throughfall was significantly higher by more than 100 mm in October. The soil temperature in each treatment plot increased significantly by up to 1℃ or more compared with the control plot as the thinning rate increased. The soil moisture increased by more than 5% in the thinning treatment plots during rainfall, particularly in the 34% treatment plot, where the rate of moisture decrease was slower. The photosynthetic rate of major tree species (excluding Pinus densiflora)was highest in Quercus mongolica, with a rate of 7 µmolCO₂·m^-2·s^-1. At a lightintensity of 800 μmol·m^-2·s^-1, Q. mongolica showed the highest photosynthetic level of 6 ± 0.3 μmolCO₂·m^-2·s^-1 in the 45% treatment. The photosynthetic rate of Fraxinus sieboldiana and Styrax japonicus increased as the thinning intensity increased. The Shannon-Wiener index of mycorrhizal mushrooms did not significantly differ among treatments, but the fresh weight of mushrooms was approximately 360-840 g higher in the 34% and 45% treatments than in the control. Additionally, the fresh weight of fungi in the 60% treatment was 860 g less than that in the control. There were more individuals of Amanita citrina in the control than in the thinning treatment, while Suillus bovinus numbers increased by more than 10 times in the 34% thinning treatment compared with the control.