• Title/Summary/Keyword: seeding data

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Verification of precipitation enhancement by weather modification experiments using radar data (레이더 자료를 이용한 기상조절 실험에 의한 강수 증가 검증 연구)

  • Ro, Yonghun;Cha, Joo-Wan;Chae, Sanghee
    • Journal of Korea Water Resources Association
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    • v.53 no.11
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    • pp.999-1013
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    • 2020
  • Weather modification research has been actively performed worldwide, but a technology that can more quantitatively prove the research effects are needed. In this study, the seeding effect, the efficiency of precipitation enhancement in weather modification experiment, was verified using the radar data. Also, the effects of seeding material on hydrometeor change was analyzed. For this, radar data, weather conditions, and numerical simulation data for diffusion were applied. First, a method to analyze the seeding effect in three steps was proposed: before seeding, during seeding, and after seeding. The proposed method was applied to three cases of weather modification experiments conducted in Gangwon-do and the West Sea regions. As a result, when there is no natural precipitation, the radar reflectivity detected in the area where precipitation change is expected was determined as the seeding effect. When natural precipitation occurs, the seeding effect was determined by excluding the effect of natural precipitation from the maximum reflectivity detected. For the application results, it was found that the precipitation intensity increased by 0.1 mm/h through the seeding effect. In addition, it was confirmed that ice crystals, supercooled water droplets, and mixed-phase precipitation were distributed in the seeding cloud. The results of these weather modification research can be used to secure water resources as well as for future study of cloud physics.

Effect of seeding depth on seedling growth and dry matter partitioning in American ginseng

  • Proctor, John T.A.;Sullivan, J. Alan
    • Journal of Ginseng Research
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    • v.37 no.2
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    • pp.254-260
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    • 2013
  • Greenhouse and field experiments with American ginseng (Panax quinquefolius L.) stratified seed sown at depths of 10 to 100 mm were carried out to determine effects of seeding depth on seedling emergence, growth and development and to calculate optimum seeding depth. The time to 50% seedling emergence ($E_{50}$) in the field increased linearly from 17 d at 20 mm seeding depth to 42.5 d at 80 mm. Seedling emergence and root weight (economic yield) at the end of the first year each increased quadratically with the increase of seeding depth. Maximum emergence and root yields were produced at sowing depths of 26.9 and 30.6 mm respectively. In a greenhouse pot experiment, increasing seeding depth from 10 to 100 mm increased partitioning of dry matter to leaves from 23.6% to 26.1%, to stems from 6.9% to 14.2%, and decreased dry matter to roots from 69.5% to 59.7%. Optimum seeding depth was 31.1 mm for a corresponding maximum root weight of 119.9 mg. A predictor equation [X (seeding depth, mm)=Y (seed weight, mg)/9.1+20.96] for seeding depth for ginseng, based on data for ten vegetable crops, their seed weights and suggested seeding depths, predicted a seeding depth of 28.3 mm for ginseng similar to that reported above for most pot and field experiments.

Analysis of Available Time of Cloud Seeding in South Korea Using Radar and Rain Gauge Data During 2017-2022 (2017-2022년 남한지역 레이더 및 지상 강수 자료를 이용한 인공강우 항공 실험 가능시간 분석)

  • Yonghun Ro;Ki-Ho Chang;Yun-kyu Lim;Woonseon Jung;Jinwon Kim;Yong Hee Lee
    • Journal of Environmental Science International
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    • v.33 no.1
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    • pp.43-57
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    • 2024
  • The possible experimental time for cloud seeding was analyzed in South Korea. Rain gauge and radar precipitation data collected from September 2017 to August 2022 in from the three main target stations of cloud seeding experimentation (Daegwallyeong, Seoul, and Boryeong) were analyzed. In this study, the assumption that rainfall and cloud enhancement originating from the atmospheric updraft is a necessary condition for the cloud seeding experiment was applied. First, monthly and seasonal means of the precipitation duration and frequency were analyzed and cloud seeding experiments performed in the past were also reanalyzed. Results of analysis indicated that the experiments were possible during a monthly average of 7,025 minutes (117 times) in Daegwallyeong, 4,849 minutes (81 times) in Seoul, and 5,558 minutes (93 times) in Boryeong, if experimental limitations such as the insufficient availability of aircraft is not considered. The seasonal average results showed that the possible experimental time is the highest in summer at all three stations, which seems to be owing to the highest precipitable water in this period. Using the radar-converted precipitation data, the cloud seeding experiments were shown to be possible for 970-1,406 hours (11-16%) per year in these three regions in South Korea. This long possible experimental time suggests that longer duration, more than the previous period of 1 hour, cloud seeding experiments are available, and can contribute to achieving a large accumulated amount of enhanced rainfall.

A Vegetation Characteristics of a Cut-Slope Affected by Seeding Periods of the Winter Season (동절기 파종시기에 따른 훼손비탈면의 녹화특성)

  • Kim, Jae-Hwan;Shim, Sang-Ryul
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.12 no.2
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    • pp.29-39
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    • 2009
  • Research was initiated to investigate a vegetation characteristics of the winter season by seeding periods. 3 seeding periods (Mid-December seeding plot, Late January seeding plot and Early March seeding plot) and 3 zones (the top zone, the middle zone and the bottom zone) in each plot were treated with 3 replications on the experimented slope. Data such as vegetation coverage (%), soil hardness (MPa), temperature ($^{\circ}C$) and moisture (%) content were analyzed. The vegetation coverage was high in Early March seeding plot, medium in Mid-December, and low in Late January seeding plot. Early March seeding plot was effective in moisture content, soil hardness, and temperature for the growth of vegetation when compared to Late January seeding plot and Mid-December seeding plot. From the standpoint of coverage ratio of plant species, the coverage of Dianthus sinensis and Albizzia julibrissin were high in the Late January seeding plot whereas the coverage of Lotus corniculatus and Cool-season turfgrass were high in Early March seeding plot. These results indicated that the high vegetation coverage of Dianthus sinensis and Albizzia julibrissin in Early March seeding plot was caused by scarification during winter season. There was no difference observed in plant height regardless of seeding periods except in early surveying time of May and June after seeding. As far as each zone of the plot was concerned, the vegetation coverage was high. in the bottom zone, medium in the middle zone and low in the top zone. The bottom area of the experimented slope was high in moisture content when compared to the middle zone and the top zone.

Meteorological Conditions for the Cloud Seeding Experiment by Aircraft in Korea (인공강우 항공실험을 위한 한반도 기상조건의 예비결과)

  • Jung, Woonseon;Chang, Ki-Ho;Ko, A-Reum;Ku, Jung Mo;Ro, Yonghun;Chae, Sanghee;Cha, Joo Wan;Lee, Chulkyu
    • Journal of Environmental Science International
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    • v.30 no.12
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    • pp.1027-1039
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    • 2021
  • In this study, we investigated the optimal meteorological conditions for cloud seeding using aircraft over the Korean Peninsula. The weather conditions were analyzed using various data sources such as a weather chart, upper air observation, aircraft observation, and a numerical model for cloud seeding experiments conducted from 2018 to 2019 by the National Institute of Meteorological Sciences, Korea Meteorological Administration. Cloud seeding experiments were performed in the seasons of autumn (37.0%) and winter (40.7%) in the West Sea and Gangwon-do. Silver iodide (70.4%) and calcium chloride (29.6%) were used as cloud seeding materials for the experiments. The cloud seeding experiments used silver iodide in cold clouds. Aircraft observation revealed relatively low temperatures, low liquid water content, and strong wind speeds in clouds with a weak updraft. In warm clouds, the cloud seeding experiments used calcium chloride. Observations included relatively high temperatures, high liquid water content, and weak wind speeds in clouds with a weak updraft. Based upon these results, we determined the comprehensive meteorological conditions for cloud seeding experiments using aircraft over the Korean Peninsula. The understanding of optimal weather conditions for cloud seeding gained from this study provide information critical for performing successful cloud seeding and rain enhancement.

Changes in quantity and quality of rice at different sowing date under wet-hill seeding in Jeonbuk plain area

  • Cho, Seung-Hyun;Lee, Deok-Ryeol;Lee, Songyee;Kim, Kab-Cheol;So, Sun-young;Lee, Ki-Kwon
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2017.06a
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    • pp.261-261
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    • 2017
  • This study was carried out to provide basic data for spreading rice direct seeding by inducing stabilization of seedlings, yield and quality according to sowing times in rice direct seeding cultivation. In 2016, 'Sukwang' was seeded 3 times by 10 days interval on May. 10, 20, 30 and 6kg/10ha of seeding rate respectively in Iksan. In summary, the number of rice seedling establishment was higher than the optimum seedling establishment level at all sowing periods and the seeding rate was better as the sowing period was delayed. Weed development by sowing was the highest at early sowing, May 10, and decreased at late sowing. Heading dates were delayed by 3days for sowing on May 10, 7days for sowing on May 20, and 11 days on sowing on May 30. Rice yield increased with the delay sowing time and compared to the transplanting. It was 84% in sowing on May 10, 94% in sowing on May 20, and 99% in sowing on May 30. In addition, head rice ratio and head rice yield increased according to delayed of seedling.

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An Assessment of the Effectiveness of Cloud Seeding as a Measure of Air Quality Improvement in the Seoul Metropolitan Area (서울에서의 미세먼지 저감을 위한 인공강수 가능성 진단)

  • Song, Jae In;Yum, Seong Soo
    • Atmosphere
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    • v.29 no.5
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    • pp.609-614
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    • 2019
  • Cloud seeding experiment has been proposed as a way to alleviate severe air pollution problem because, if successful, artificially produced precipitation through cloud seeding could scavenge out some portion of air pollutants. As a first step to verify the practicality of such experiment, seedability of the clouds observed in Seoul is assessed by examining statistical characteristics of some relevant meteorological variables. Analyses of 9 years of Korea Meteorological Agency Seoul station data indicate that as PM10 mass concentration increases, cloud amount, liquid water path, and ice water path decrease, but the difference between temperature and dew point temperature tends to increase. Such finding suggests that cloud seeding becomes less feasible as air pollution becomes more severe in the Seoul metropolitan area, at least in a statistical sense. For some individual severe air pollution events, however, seedable clouds may exist and indeed cloud seeding experiments can be successful. Therefore, detailed investigation on cloud seedability for individual severe air pollution events are highly required to make a concrete assessment of cloud seeding as a way to alleviate severe air pollution problem.

An Analysis of the Management Efficiency for the Rice seeding Farmer in China Using DEA Model (DEA를 활용한 중국 벼 직파농가의 경영효율성 분석)

  • Wang, Xiao-Feng;Yu, Chan-Ju
    • Korean Journal of Organic Agriculture
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    • v.30 no.3
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    • pp.351-374
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    • 2022
  • In recent years, the development of rice industry has been highly valued by the state. In hubei area, due to the development of the modernization and the shortage of labor, traditional way of rice cultivation methods is facing serious challenges, and economic benefits have become the decisive factor for the effective promotion and application of rice cultivation methods. According to the research results, first, in the input-side analysis, in the CCR model, D5, D12, D26, D28, D32, D36 farmers with high efficiency appear. The analysis result shows that among the 60 farmers, the average efficiency is 89%, and there is an inefficiency of 11%. In the BCC model, 14 farmers were identified as high-efficiency farmers, with an average efficiency of 0.9453. Second, in direct seeding cultivation of rice, the average scale efficiency is 0.9227, while the average pure technical efficiency is 0.9644. This shows that the effect of scale efficiency is greater than that of purely technical factors, ignoring the reasons for the low operational efficiency of direct seeding cultivation farmers. It can be predicted that with the further deepening of farmers' understanding of this planting mode, the proportion of rice direct seeding may be further expanded in the future. Relevant agricultural departments should further promote this technology to farmers, study the direct seeding technology using scientific methods, and evaluate the changes of this cultivation mode. The agricultural departments of government should concern about the climate risk assessment of direct seeding rice, the environmental impact assessment caused by the extensive use of herbicides, the application of mechanical technology in the process of direct seeding, the lodging of direct seeding rice, and other related issues.

Estimation of Available Days for a Cloud Seeding Experiment in Korea (한반도 목적별 인공강우 실험가능일 추정)

  • Jung, Woonseon;Chang, Ki-Ho;Cha, Joo Wan;Ku, Jung Mo;Lee, Chulkyu
    • Journal of Environmental Science International
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    • v.31 no.2
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    • pp.117-129
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    • 2022
  • In this study, we investigated the characteristics of the meteorological and environmental conditions for a cloud seeding experiment over the Korean peninsula and estimated the available days for the same. The conditions of available days appropriate for a cloud seeding experiment were classified according to four purposes: water resources, drought relief, forest fire prevention, and air quality improvement. The average number of available days for a cloud seeding experiment were 91.27 (water resources), 45.93-51.11 (drought relief), 40.28-46.00 (forest fire prevention), and 42.19-44.60 days/year (air quality improvement). If six experiments were carried out per available day for a cloud seeding experiment, the number of times cloud seeding experiments could be conducted per year in a continuously operating system were estimated as 547.62 (water resources), 275.58-306.66 (drought relief), 241.68-276.00 (forest fire prevention), and 253.14-267.60 times/year (air quality improvement). From this result, it was possible to determine the appropriate meteorological and environmental conditions and statistically estimate the available days for a cloud seeding experiment. The data on the available days for a cloud seeding experiment might be useful for preparing and performing such an experiment.

Detecting on Optimal Seeding and Harvesting Dates of Whole Crop Maize via Meta Data (사일리지용 옥수수의 메타자료를 이용한 적정 파종 및 수확시기의 탐색)

  • Jo, Hyun Wook;Kim, Si Chul;Kim, Moon Ju;Kim, Ji Yung;Jo, Mu Hwan;Kim, Byong Wan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.40 no.1
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    • pp.66-72
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    • 2020
  • This study aimed to discuss the optimal seeding and harvesting dates with growing degree days(GDD) via meta-data of whole crop maize(WCM). The raw data (n=3,152) contains cultivation year, cultivars, location, seeding and harvesting dates collected from various reports such as thesis, science journals and research reports (1982-2012). The processing was: recording, screening and modification of errors; Then, the final dataset (n=121) consists of seeding cases (n=29), and harvesting cases (n=92) which were used to detect the optimum. In addition, the optimal periods considering tolerance range and GDD also were estimated. As a result, the optimum seeding and harvesting periods were 14th April ~ 3rd May and 15th August ~ 4th September, respectively; where, their GDDs were 23.7~99.6℃ and 1,328.7~1,602.1℃, respectively. These GDDs could be used as a judge standard for selecting the seeding and harvesting dates.