• Journal of the Korea Organic Resources Recycling Association
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• v.29 no.1
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• pp.19-27
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• 2021

Hydroponic farming is a method to grow a plant without soil. Plants can be grown on water or hydroponic growing media, and they are fed with mineral nutrient solutions, which are fertilizers dissolved into water. Hydroponic farming has the advantage of increasing plant productivity over conventional greenhouse farming. Previous studies of hydroponic nutrient wastewater from acyclic hydroponic farms pointed out that hydroponic nutrient wastewater contained residual nutrients, and they were drained to a nearby river bank which causes several environmental issues. Also, previous studies suggest that excessive use of the nutrient solution and disposal of used hydroponic growing media and crop wastes in hydroponic farms are major problems to hydroponic farming. This study was conducted to determine the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment by analyzing water quality and soil analysis of the above three factors. Three soil cultivation farms and several hydroponic farms in the Gangwon C region were selected for this study. Samples of water and soils were collected from both inside and outside of each farm. Also, a sample of soil and leachate from crop waste piles stacked near the farm was collected for analysis. Hydroponic nutrient wastewater from acyclic hydroponic farm contained an average of 402 mg/L of total nitrogen (TN) concentration, and 77.4 mg/L of total phosphate (TP) concentration. The result of TP in hydroponic nutrient wastewater exceeds the living environmental standard of the river in enforcement decree of the framework act on environmental policy by 993.7 times. Also, it exceeds the standard of industrial wastewater discharge standards under the water environment conservation act by 6~19 times in TN, and 2~27 times in TP. Leachate from crop waste piles contained 11,828 times higher COD and 395~2662 times higher TP than the standard set by the living environmental standard of the river in enforcement decree of the framework act on environmental policy and exceeds 778 times higher TN and 5 times higher TP than the standard of industrial wastewater discharge standards under the water environment conservation act. For more precise studies of the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment, additional information regarding a number of hydroponic farms, arable area(ha), hydroponic farming area, seasonal, weather, climate factor around the river, and the property of the area and farm is needed. Analysis of these factors and additional water and soil samples are needed for future studies.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1465-1483
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• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.1
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• pp.68-77
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• 2022

The human thermal environment in an apartment complex located in Seoul was quantitatively analyzed to devise methods to modify human heat-related stresses in landscape and urban planning. Microclimatic data (air temperature, relative humidity, wind speed, and short- and long-wave radiation) were collected at 6 locations [Apt-center, roof (cement), roof (grass), ground, playground, and a tree-lined road] in the late spring and summer, and the data were used to estimate the human thermal sensation, physiological equivalent temperature (PET) and universal thermal climate index (UTCI). As a result, the playground location had the highest thermal environment, and the roof (grass) location had the lowest. The mean difference between the two locations was 0.8-1.1℃ in air temperature, 1.8-4.0% in relative humidity, and 7.5-8.0℃ in mean radiant temperature. In open space locations, the wind speed was 0.4-0.5 ms-1 higher than others. Also, a wind tunnel effect happened at the Apt-center location during the afternoon. For the human thermal sensation, PET and UTCI, the mean differences between the playground and roof (grass) locations were: 5.2℃ (Max. 11.7℃) in late spring and 5.4℃ (Max. 18.1℃) in summer in PET; and 3.0℃ (Max. 6.1℃) in late spring and 2.6℃ (Max. 9.8℃) in summer in UTCI. The mean differences indicated a level change in PET and 1/2 level in UTCI, and the maximum differences showed greater changes, 2-3 levels in PET, and 1-1.5 levels in UTCI. Moreover, the roof (grass) location gave 4.6℃ PET reduction and a 2.5℃ UTCI reduction in late spring, and a 4.4℃ PET reduction and a 2.0℃ UTCI reduction in the summer when compared with the roof (cement) location, which results in a 2/3 level change in PET and a 1/3 level in UTCI. Green infrastructure locations [roof (grass), ground, and a tree-lined road] were not statistically significant in the reduction of PET and UTCI in thermal environment modifying effects. The implementation of green infrastructure, such as rooftop gardens, grass pavement, and street tree planting, should be adopted in landscape planning and be employed for human thermal environment modification.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.4
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• pp.356-368
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• 2021

To understand the temporal variation of phytoplankton communities in a coastal area, the biomass and diversity were weekly investigated in the inner bay of Yeong-do, Busan. In the study area, chlorophyll a concentration ranged from 0.43~7.58 mg m^-3 during the study, indicating the study area was in mesotrophic or eutrophic status. The fractions of chlorophyll a occupied by large phytoplankton (> 3 ㎛ diameter) exhibited an average of 80% of total chlorophyll a in this study. Among the large phytoplankton, while Bacillariophyta was the most dominant in spring and summer, Cryptophyceae prevailed in the fall and winter. On the contrary, in the picophytoplankton community less than 3 ㎛ in diameter, Mamiellophyceae was the most dominant in most seasons, Cryptophyceae was relatively high with an average of 17.7 ± 17.6% throughout the year, but seasonal variations were large. Dinophyceae rarely occupied a higher fraction up to 60.4% of the picophytoplankton community. By weekly monitoring at a coastal station for 13 months, it is suggested that phytoplankton communities in coastal waters could be changed on a short time scale. If data are steadily accumulated at the time-series monitoring site for a long time, these will provide important data for understanding the long-term dynamics of phytoplankton as well as the impact of climate and environmental changes.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.102-111
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• 2022

Termites are a group of social insects that are one of the primary causes of damage to wooden architectural heritage. Since termite damage impairs the authenticity and structural stability of cultural heritage, it is imperative to prevent it. This study examines the extent of termite damage to wooden architectural heritage as part of efforts to prevent termite damage to nationally designated wooden architectural heritage sites across the country. The extent of termite damage to each cultural heritage was assessed qualitatively and quantitatively and comparatively analyzed by region using the results of the "Investigation on Biological Damage to Wooden Architectural Heritages" conducted by the National Research Institute of Cultural Heritage from 2016 to 2019. It involved 362 nationally designated wooden architectural heritages(25 national treasures, 157 treasures, 180 national folklore cultural heritages) and 1,104 buildings. The results were as follows: termite detection dogs reacted at 317(87.6%) of the 362 wooden heritages, with visible termite damage observed in 185 cases(51.1%). Furthermore, termite damage was confirmed using one of two methods(detection dogs or visual inspection) in 324 cases(89.5%). Of the 1,104 buildings, termite detection dogs reacted at 668(60.5%), while 339(30.7%) showed visible termite damage. Employing one of the two methods, damage was confirmed in 702 buildings(63.6%). The country was categorized into nine regions(Seoul Metropolitan Area, Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, and Jeju) to examine the termite damage rate and the degree of damage to each cultural heritage according to location. Termite detection dogs reacted to more than 70% of the cultural heritage in all regions. Visible damage was minimal in the Seoul metropolitan area(32.1%) and Gangwon(21.4%) but severe in Chungnam(65.6%), Jeonnam(67.3%), and Gyeongnam(68.2%). By quantifying the degree of termite damage of each cultural heritage as a ratio of the absence of termite damage among the total absence, the average termite damage of the cultural heritage across the country was 9.2%. Regional variance analysis showed that the cultural heritage in Jeonbuk and Jeonnam showed a statistically significantly higher degree of termite damage than the cultural heritage in the Seoul metropolitan area, Chungbuk, and Gyeongbuk. This paper comprehensively analyzed termite damage to nationally designated wooden architectural heritage. The findings are expected to be valuable in establishing policies for the preservation and management of cultural heritage sites in the future.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.327-337
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• 2022

Ecological restoration is considered a good means to prevent biodiversity loss in terms of the ecosystem's health and sustainability. However, there are difficulties in putting it into practice as there is no comprehensive and objective standard for the selection of plant species, such as environmental, ecological factors, and restoration goal setting. Therefore, this study developed an evaluation index necessary for selecting plant species for restoration using the Delphi method that synthesizes the opinions of the expert group. A survey with 38 questionnaires was conducted twice for experts in ecological restoration, etc., and the importance and priority of evaluation indicators were analyzed by dividing the restoration targets into inland and island regions. The result of the importance analysis showed that "native plants" had the highest average of 4.9 among the evaluation indices in both inland and island regions, followed by "seed security", "propagation", and "root growth rate". In the inland region, the index priority was analyzed in the order of "native plants", "appearance frequency", "root growth rate", "distribution range", and "seed security" in the island region, it was analyzed in the order of "native plants", "root growth rate", "appearance frequency", "distribution range", and "tolerance", showing slight differences between the two indicators. As a result of the importance and priority indicator analysis, we set the mean importance and priority of 4.1 and 2.9, respectively, in the inland region and 4.2 and 2.9, respectively, in the island region. As for the criteria of selecting plant species for ecological restoration, the "native plants" had the highest importance and priority. "Seed securing", 'viability", "topography", "proliferation", "tolerance", "soil conditions", "growth characteristics", "early succession", "distribution range", "appearance frequency", and "germination rate" were classified into subgroups of low importance and priority. The lowest indicators were "final stage of succession", "transition period", 'transition stage", "root", "reproduction", "soil", "appearance", "technology", "landscape", "climate", and "germination rate". We expected that the findings through objective verification in this study would be used as evaluation indicators for selecting native plant species for ecological restoration.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.3
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• pp.19-34
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• 2022

This study was conducted to provide basic data that can be used when establishing Net Zero policies and implementation plans for non-urban settlements by quantitatively analyzing the Net Zero contribution to green infrastructure in rural areas corresponding to non-urban settlements. The main purpose is to first, systematize green infrastructure in rural areas, secondly derive basic units for each element of green infrastructure, and thirdly quantify and present the impact on Net Zero in Korea using these. In this study, CVR(Content Validity Ration) analysis was performed to verify the adequacy of green infrastructure elements in rural areas derived through research and analysis of previous studies, is as follows. First, Hubs of Green infrastructure in rural area include village forests, wetlands, farm land, and smart farms with a CVR value of .500 or higher. And Links of Green infrastructure in rural area include streams, village green areas, and LID (rainwater recycling). Second, the basic unit for each green infrastructure element was presented by classifying it into minimum, maximum, and median values using the results of previous studies so that it could be used for spatial planning and design for Net Zero. Third, when Green infrastructure in rural areas is applied to non-urban settlements in Korea, it is analyzed that it has the effect of indirectly reducing CO₂ by at least 70.76 million tons and up to 141.16 million tons. This is 3.4 to 6.7 times the amount of CO₂ emission from the agricultural sector in 2019, and it can be seen that the contribution to Net Zero is very high. It is expected to greatly contribute to the transformation of the ecosystem. This study quantitatively presented the carbon-neutral contribution to settlements located in non-urban areas, and by deriving the carbon reduction unit for each element of green infrastructure in rural areas, it can be used in spatial planning and design for carbon-neutral at the village level. It has significance as a basic research. In particular, the basic unit of carbon reduction for each green infrastructure factors will be usable for Net Zero policy at the village level, presenting a quantitative target when establishing a plan, and checking whether or not it has been achieved. In addition, based on this, it will be possible to expand and apply Net Zero at regional and city units such as cities, counties, and districts.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.