Structural Shape Estimation Based on 3D LiDAR Scanning Method for On-site Safety Diagnostic of Plastic Greenhouse
서병훈 Seo Byung-hun , 이상익 Lee Sangik , 이종혁 Lee Jonghyuk , 김동수 Kim Dongsu , 김동우 Kim Dongwoo , 조예림 Jo Yerim , 김유용 Kim Yuyong , 이정민 Lee Jeongmin , 최원 Choi Won
Structural Shape Estimation Based on 3D LiDAR Scanning Method for On-site Safety Diagnostic of Plastic Greenhouse
서병훈 Seo Byung-hun , 이상익 Lee Sangik , 이종혁 Lee Jonghyuk , 김동수 Kim Dongsu , 김동우 Kim Dongwoo , 조예림 Jo Yerim , 김유용 Kim Yuyong , 이정민 Lee Jeongmin , 최원 Choi Won
In this study, we applied an on-site diagnostic method for estimating the structural safety of a plastic greenhouse. A three-dimensional light detection and ranging (3D LiDAR) sensor was used to scan the greenhouse to extract point cloud data (PCD). Differential thresholds of the color index were applied to the partitions of raw PCD to separate steel frames from plastic films. Additionally, the K-means algorithm was used to convert the steel frame PCD into the nodes of unit members. These nodes were subsequently transformed into structural shape data. To verify greenhouse shape reproducibility, the member lengths of the scan and blueprint models were compared with the measurements along the X-, Y-, and Z-axes. The error of the scan model was accurate at 2%-3%, whereas the error of the blueprint model was 5.4%. At a maximum snow depth of 0.5 m, the scan model revealed asymmetric horizontal deflection and extreme bending stress, which indicated that even minor shape irregularities could result in critical failures in extreme weather. The safety factor for bending stress in the scan model was 18.7% lower than that in the blueprint model. This phenomenon indicated that precise shape estimation is crucial for safety diagnostic. Future studies should focus on the development of an automated process based on supervised learning to ensure the widespread adoption of greenhouse safety diagnostics.
Evaluation of Non-Point Pollution Loads in Corn-Autumn Kimchi Cabbage Cultivation Areas by Fertilizer Application Levels Using the APEX Model
이종문 Lee Jong-mun , 엽소진 Yeob So-jin , 전상민 Jun Sang-min , 이병모 Lee Byungmo , 양예린 Yang Yerin , 최순군 Choi Soon-kun
Agriculture is recognized as an important anthropogenic cause of non-point source loads. Improved understanding of non-point source loads according to fertilization practices can promote climate change and eutrophication mitigation. Thus, this study evaluated the impact of conventional and standard fertilization practices on non-point pollution (NPP) loads in a dual-cropping system, utilizing the Agricultural Policy/Environmental eXtender (APEX) model. Our research objectives were twofold: firstly, to calibrate and validate the APEX model with observed data through experiments from 2018 to 2023; and secondly, to compare the NPP loads under conventional and standard fertilization practices. The model calibration and validation showed satisfactory performance in simulating nitrogen (N) and phosphorus (P) loads, illustrating the model’s applicability in a Korean agricultural setting. The simulation results under conventional fertilization practices revealed significantly higher NPP loads compared to the standard fertilization, with P loads under conventional practices being notably higher. Our findings emphasize the crucial role of recommended fertilization practices in reducing non-point source pollution. By providing a quantitative assessment of NPP loads under different fertilization practices, this study contributes valuable information to sustainable nutrient management in agricultural systems facing the dual challenges of climate change and environmental conservation.
Evaluation of Water Supply Reliability in Agricultural Reservoirs Using Water Balance Analysis
양미혜 Yang Mi-hye , 남원호 Nam Won-ho , 신지현 Shin Ji-hyeon , 윤동현 Yoon Dong-hyun , 양희충 Yang Hee-chung
Most agricultural reservoirs were built between the 1940s and 1970s. Therefore, it is necessary to evaluate the current water supply safety, considering changes in water capacity, the water management, and environment in relation to the passage of time.. The design frequency of drought, the number of years areservoir needs to be able to withstand a drought phenomenon, foragricultural water resources in Korea is the 10-year drought. As the water supply system and water supply patterns change, it is necessary to establish a concept of water supply reliability, which refers to the stability of water supply. This study evaluated the water supply reliability of agricultural reservoirs based on the designed frequency. The previously designed frequency and water balance analysis were used to calculate and analyze reservoir storage capacity, water supply turnover, water supply amount, water supply potential, water utilization safety, and water supply reliability. As a result, Yongmyeon Reservoir was found to be stable in terms of water supply reliability, whereas Seongho and Yongpung Reservoirs were found to be unstable using all methods. In particular, when converting the water utilization safety and the water supply reliability to the frequency of drought, Seongho and Yongpung Reservoir were in the lowest class, with a frequency of drought less than four years. Thus, we recommend that the consideration of water supply reliability be included in the preparation of adaptive measures and water supply strategies as changes in environmental conditions continue to develop.
Comparative Evaluation on Applicability of Fuzzy Time Series Method for Predicting Overtopping of Reservoir Embankment
An increasing pattern of extreme rainfall recently affected the rural infrastructures with catastrophic damage, especially the overtopping of a fill dam embankment in the Republic of Korea. The overtopping was caused by the sudden increase in reservoir water level over the dam crest level, and it was not easy work to predict a priori because of its non-linear behavior. Fuzzy time series (FTS) is a fuzzy-logic inference procedure and is suited to apply to non-linear prediction methods such as machine learning. This study used the Wangshin reservoir and Goesan-dam cases, which experienced overtopping in 2023 and 2022, respectively. Wangshin Reservoir was a typical agricultural fill dam and needed to stack more available data, with only the daily storage rate (water level) of 7 years, starting on 2 May 2016. Therefore, we used Goesan-dam data to select appropriate variables and compare the analysis result, which was stacked with about 17 years of records. The analyses adapted LSTM to compare with FTS. As a result, the reservoir water level was applied to predict the overtopping water level, and it was shown that the FTS method could predict the actual water levels effectively according to the result of comparison with LSTM. Then, the FTS method was expected to predict reservoir water level a priori to make appropriate countermeasures on overtopping events as one of the alternatives.
Analysis of Drone Downwash and Droplet Deposition for Improved Aerial Spraying Efficiency in Agriculture
이세연 Lee Se-yeon , 박진선 Park Jinseon , 이채린 Lee Chae-rin , 최락영 Choi Lak-yeong , Daniel Kehinde Favour , 박지연 Park Ji-yeon , 홍세운 Hong Se-woon
With the advancement of Unmanned Aerial Vehicles (UAV) technology, aerial spraying has been rapidly increasing in the agricultural field. Drones offer many advantages compared to traditional applicators, but they pose challenges such as spray drift risk and spray uniformity. To address these issues, it is essential to understand the characteristics of complex airflow generated by drones and its consequences for the spray performance. This study aims to identify the air velocity distribution of drone downwash and the resulting spray deposition distribution on the ground, ultimately proposing optimized spraying widths and criteria. Experiments were conducted using two agricultural drones with different propeller arrangements under various flight and measurement conditions. The results showed that during hovering, the downward airflow affected the area within a distance of the radius of the blade (R) from the center of the drone. When the drone was flying, the downward airflow was effective up to a distance of 2R. Droplet deposition was concentrated at the center of the drone during hovering. However, during flying, the droplet deposition was more evenly distributed up to the distance of R. The drone downwash and droplet deposition were significantly different during flying compared to the hovering state. At an effective spray width of 3R, the coefficient of variation (CV) was generally less than 16%, indicating a significant improvement in spray uniformity. These findings help optimize effective spraying techniques in drone-based applications.
Application of DIROM Model for Water Balance Analysis of Consecutively Linked Reservoir System
Water balance analysis in heightened reservoirs, which have been raised to ensure a stable supply of irrigation water and secure water against floods and heavy rainfall, is essential for evaluating water supply capacity and reservoir maintenance. The consecutively linked reservoir system, which involves preserving the existing embankment while constructing a new one, affects the water balance between the existing and new reservoirs. This study aims to analyze the linked water balance between reservoirs in a consecutively linked reservoir system using the DIROM (Daily Irrigation Reservoir Operation Model) model. Surveys were conducted to investigate actual water use, and multiple water supply quantities were estimated based on these findings. Methods to supplement missing data and improve the limitations of simulated inflow were proposed and applied, and the performance of the daily storage simulation was evaluated. By supplementing the missing water use data, the NSE (Nash-Sutcliffe Efficiency) of the Sonhang reservoir storage rate simulation improved by approximately 30%. Additionally, result of using inflow coefficients significantly enhanced the simulation performance for the Sonhang2 and Sonhang reservoirs. This study confirms the necessity of incorporating appropriate inflow coefficients in reservoir design to overcome the model’s tendency to overestimate inflow, highlighting the critical importance of quality control in observational data. The findings are expected to be useful for the design and analysis of future reservoir systems through embankment heightening.