Fertilizers are crucial for increasing crop yield, but using too much of them without taking into account the nutrients that the crops need can increase costs for farm management and have a negative impact on the environment. Through smart agriculture, fertilizers can be applied as needed at the right time to reflect the growth characteristics of crops, reducing the burden of fertilizer losses and providing economical nutrient management. In this study, we use the total dry weight of field-cultivated red pepper and green onion grown in various growing environments to fit a nonlinear model-based crop growth model using different growth curves (logistic, Gompertz, Richards, and double logistic curve), and we propose a fertilizer distributed algorithm based on crop growth rate.
The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.
To reveal and classify site characteristics in densely populated areas in Chuncheon, Korea, Rayleigh-waves were recorded at 50 sites including four sites in the forest area using four 1-Hz velocity sensors and 24 4.5-Hz vertical geophones during the period of January 2011 to May 2013. Dispersion curves of the Rayleigh waves obtained by the extended spatial autocorrelation method were inverted to derive shear-wave velocity ($v_s$) models comprising 40 horizontal layers of 1-m thickness. Depths to weathered rocks ($D_b$), shear wave velocities of these basement rocks ($v_s^b$), average velocities of the overburden layer ($\bar{v}_s^s$), and the average velocity to a depth of 30 m ($v_s30$), were then derived from those models. The estimated values of $D_b$, $v_s^b$, $\bar{v}_s^s$, and $v_s30$ for 46 sites at lower altitudes were in the ranges of 5 to 29 m, 404 to 561 m/s, 208 to 375 ms/s, and 226 to 583 m/s, respectively. According to the Korean building code for seismic design, the estimated $v_s30$ indicates that the lower altitude areas in Chuncheon are classified as $S_C$ (very dense soil and soft rock) or $S_D$ (stiff soil). To determine adequate proxies for $v_s30$, we compared the computed values with land cover, lithology, topographic slope, and surface elevation at each of the measurement sites. Due to a weak correlation (r = 0.41) between $v_s30$ and elevation, the best proxy of them, applications of this proxy to Chuncheon of a relatively small area seem to be limited.
KSCE Journal of Civil and Environmental Engineering Research
/
v.1
no.1
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pp.53-68
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1981
Most clays under sustained load exhibit time-dependent deformation because of creep movement of soil particles and many investigators have attempted to relate their findings to the creep behavior of natural ground and to the long-term stability of slopes. Since the creep behavior of clays may assume a variety of forms depending on such factors as soil plasticity, activity and water content, it is difficult and complicated to analyse the creep behavior of clays. Rheological models composed of linear springs in combination with linear or nonlinear dashpots and sliders, are generally used for the mathematical description of the time-dependent behavior of soils. Most rheological models, however, have been proposed to simulate the behavior of secondary compression for saturated clays and few definitive data exist that can evaluate the behavior of non-saturated clays under the action of sustained stress. The clays change gradually from a solid state through plastic state to a liquid state with increasing water content, therefore, the rheological models also change. On the other hand, creep is time-dependent, and also the effect of thixotropy is time-function. Consequently, there may be certain correlations between creep behavior and the effects of thixotropy in compacted clays. In addition, the states of clay depend on water content and hence the height of the specimen under drained conditions. Futhermore, based on present and past studies, because immediate elastic deformation occurs instantly after the pressure increment without time-delayed behavior, the factor representing immediate elastic deformations in the rheological model is necessary. The investigation described in this paper, based on rheological model, is designed to identify the immediate elastic deformations and the effects of thixotropy and height of clay specimens with varing water content and stress level on creep deformations. For these purposes, the uniaxial drain-type creep tests were performed. Test results and data for three compacted clays have shown that a linear top spring is needed to account for immediate elastic deformations in the rheological model, and at lower water content below the visco-plastic limit, the effects of thixotropy and height of clay specimens can be represented by the proposed rheological model not considering the effects. Therefore, the rheological model does not necessitate the other factors representing these effects. On the other hand, at water content higher than the visco-plastic limit, although the state behavior of clays is visco-plastic or viscous flow at the beginning of the test, the state behavior, in the case of the lower height sample, does not represent the same behavior during the process of the test, because of rapid drainage. In these cases, the rheological model does not coincide with the model in the case of the higher specimens.
Journal of the Korean Institute of Landscape Architecture
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v.48
no.3
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pp.34-44
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2020
In order to suggest performance analysis directions of ecological components based on a vegetation-based LID system model, this study seeks to analyze the statistical significance between monitoring results by using SWMM computer simulation and rainfall and run-off simulation devices and provide basic data required for a preliminary system design. Also, the study aims to comprehensively review a vegetation-based LID system's soil, a vegetation model, and analysis plans, which were less addressed in previous studies, and suggest a performance quantification direction that could act as a substitute device-type LID system. After monitoring artificial rainfall for 40 minutes, the test group zone and the control group zone recorded maximum rainfall intensity of 142.91mm/hr. (n=3, sd=0.34) and 142.24mm/hr. (n=3, sd=0.90), respectively. Compared to a hyetograph, low rainfall intensity was re-produced in 10-minute and 50-minute sections, and high rainfall intensity was confirmed in 20-minute, 30-minute, and 40-minute sections. As for rainwater run-off delay effects, run-off intensity in the test group zone was reduced by 79.8% as it recorded 0.46mm/min at the 50-minute point when the run-off intensity was highest in the control group zone. In the case of computer simulation, run-off intensity in the test group zone was reduced by 99.1% as it recorded 0.05mm/min at the 50-minute point when the run-off intensity was highest. The maximum rainfall run-off intensity in the test group zone (Dv=30.35, NSE=0.36) recorded 0.77mm/min and 1.06mm/min in artificial rainfall monitoring and SWMM computer simulation, respectively, at the 70-minute point in both cases. Likewise, the control group zone (Dv=17.27, NSE=0.78) recorded 2.26mm/min and 2.38mm/min, respectively, at the 50-minutes point. Through statistical assessing the significance between the rainfall & run-off simulating systems and the SWMM computer simulations, this study was able to suggest a preliminary design direction for the rainwater run-off reduction performance of the LID system applied with single vegetation. Also, by comprehensively examining the LID system's soil and vegetation models, and analysis methods, this study was able to compile parameter quantification plans for vegetation and soil sectors that can be aligned with a preliminary design. However, physical variables were caused by the use of a single vegetation-based LID system, and follow-up studies are required on algorithms for calibrating the statistical significance between monitoring and computer simulation results.
Two models, TANK and SWAT (Soil and Water Assessment Tool) were compared for simulating natural flows in the Paldang Dam upstream areas of the Han River basin in order to understand the limitations of TANK and to review the applicability and capability of SWAT. For comparison, simulation results from the previous research work were used. In the results for the calibrated watersheds (Chungju Dam and Soyanggang Dam), two models provided promising results for forecasting of daily flows with the Nash-Sutcliffe model efficiency of around 0.8. TANK simulated observations during some peak flood seasons better than SWAT, while it showed poor results during dry seasons, especially its simulations did not fall down under a certain value. It can be explained that TANK was calibrated for relatively larger flows than smaller ones. SWAT results showed a relatively good agreement with observed flows except some flood flows, and simulated inflows at the Paldang Dam considering discharges from upper dams coincided with observations with the model efficiency of around 0.9. This accounts for SWAT applicability with higher accuracy in predicting natural flows without dam operation or artificial water uses, and in assessing flow variations before and after dam development. Also, two model results were compared for other watersheds such as Pyeongchang-A, Dalcheon-B, Seomgang-B, Inbuk-A, Hangang-D, and Hongcheon-A to which calibrated TANK parameters were applied. The results were similar to the case of calibrated watersheds, that TANK simulated poor smaller flows except some flood flows and had same problem of keeping on over a certain value in dry seasons. This indicates that TANK application may have fatal uncertainties in estimating low flows used as an important index in water resources planning and management. Therefore, in order to reflect actually complex and complicated physical characteristics of Korean watersheds, and to manage efficiently water resources according to the land use and water use changes with urbanization or climate change in the future, it is necessary to utilize a physically based watershed model like SWAT rather than an existing conceptual lumped model like TANK.
The study was conducted to develop an effective forest resources use models for an alternate use of abandoned quarry by an attitude survey. According to the result of survey, a pessimistic view due to dust, noise pollution, and forest damage was 5% higher than an affirmative view by economic benefits from the development of quarry. The 42% of the respondents preferred the alternate use of abandoned quarry and the 25% of the respondents wanted an art and cultural space. The optimum size of alternate use was 5-10 ha (43%) with the requirement of nearby residents (32%). According to the SWOT analysis for abandoned quarry, the strength factors were an effective use of land, the content development of modern industrial inheritance + cultural and art fusion, attraction for nearby city and visitors, a harmony of beauty landscape and clean environment, and a sustainable increase of domestic and foreign visitors with the 5-day-work week. The opportunity factors were the improvement of traffic networks through KTX and local highway, the creation of the new growth engines with the establishment of artistic creation belts, the providing of unique cultural and art space through grafting of tour and education, the creation of local income through stone processed goods, and the vitalization of local development through eco-city. The weakness factors were a psychological remoteness and backwardness, and the weakness of staying tour infra. The threat factors were a poor financial support for sustainable development in nearby quarry and a modify of legal and institutional system for the alternated use of abandoned quarry. The developed restoration models for the alternate use in abandoned quarry are classified to a sculpture park, a waterfall and lake park, a rock-climbing, a sports park + forest park, a native botanical garden, a culture and art park, a complex park, a water storage site, a water storage site to extinguish forest fire, a geriatric hospital, an agricultural facility, and a school site types etc. The results suggest that the alternate use in the abandoned soil and stone quarry is needed to establish facility use models with consideration of user's preference.
Kim, Dae-Jun;Kim, Soo-Ock;Moon, Kyung-Hwan;Yun, Jin-I.
Korean Journal of Agricultural and Forest Meteorology
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v.14
no.3
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pp.132-141
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2012
Climate change impact assessment of cereal crop production in South Korea was performed using land attributes and daily weather data at a farm scale as inputs to crop models. Farmlands in South Korea were grouped into 68 crop-simulation zone units (CZU) based on major mountains and rivers as well as existing land use information. Daily weather data at a 1-km grid spacing under the A1B- and RCP8.5 scenarios were generated stochastically to obtain decadal mean of daily data. These data were registered to the farmland grid cells and spatially averaged to represent climate conditions in each CZU. Monthly climate data for each decade in 2001~2100 were transformed to 30 sets of daily weather data for each CZU by using a stochastic weather generator. Soil data and crop management information for 68 CZU were used as inputs to the CERES-rice, CERE-barley and CROPGRO-soybean models calibrated to represent the genetic features of major domestic cultivars in South Korea. Results from the models suggested that the heading or flowering of rice, winter barley and soybean could be accelerated in the future. The grain-fill period of winter barley could be extended, resulting in much higher yield of winter barley in most CZUs than that of rice. Among the three major cereal grain crops in Korea, rice seems most vulnerable to negative impact of climate change, while little impact of climate change is expected on soybeans. Because a positive effect of climate change is projected for winter barley, policy in agricultural production should pay more attention to facilitate winter barley production as an adaptation strategy for the national food security.
Min Jeong Ban;Sangwook Shin;Dong Hoon Lee;Jeong-Gyu Kim;Hosik Lee;Young Kim;Jeong-Hun Park;ShunHwa Lee;Seon-Young Kim;Joo-Hyon Kang
Journal of Wetlands Research
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v.25
no.4
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pp.306-314
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2023
Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.
This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.
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