In this study, a farm map utilization strategy for sustainable agricultural environmental resource management was derived. In addition, it is intended to present an efficient method of providing farm map-related services. As a result of the demand survey, the additional information required for the farm map includes 29% of information on crops grown on farmland, 21% of management-related information such as the owner or business entity, 17% of topographical information including slope, 15% of agricultural water information, 17% of land status information, and the addition of functions. 2% was investigated. As a result of intensive interview survey, it was found that it can be used for information on crops cultivated by agricultural businesses, actual cultivated area by township, arable land consolidation division boundary, and management of agricultural promotion zones. The farm map can be used as basic data to efficiently manage agricultural environmental resources. Since the status of support for individual farms or lots, such as soil improvement agent support and organic fertilizer support, may belong to personal information, it can be processed and provided in units required by administration or policies, such as administrative boundaries, subwatersheds, and watersheds. It can serve as a basis for executing the direct payment currently supported only by individual farms, even in a community unit that manages environmental direct payments.
Analysis of the Optimal Window Size of Hampel Filter for Calibration of Real-time Water Level in Agricultural Reservoirs
주동혁 Joo Dong-hyuk , 나라 Na Ra , 김하영 Kim Ha-young , 최규훈 Choi Gyu-hoon , 권재환 Kwon Jae-hwan , 유승환 Yoo Seung-hwan
Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.
Characteristics of Fine Particulate Matter (PM2.5) in the Atmosphere of Saemangum Reclaimed Land Area
송지한 Song Ji-han , 김정수 Kim Jeong-soo , 홍성창 Hong Sung-chang , 김진호 Kim Jin-ho
To understand the distribution characteristics of PM2.5 concentration in the Saemangeum Reclamation Area and nearby areas, three points of the background area, the occurrence area, and the affected area were selected and samples were collected for each season. The chemical composition was determined. As a result of analyzing the chemical composition contained in PM2.5, NO3- (7.2 μg/m3), SO42- (4.3 μg/m3), NH4+ (4.3 μg/m3), OC (2.5 μg/m3), Si (1.3 μg/m3) m3) and EC (0.5 μg/m3) seemed to be the main components, and NO3-, SO42-, NH4+, which are components that form secondary particles, occupied a large proportion. The composition ratio of PM2.5 was investigated in the order of ion component (56.8%) > Unknown (27.4%) > carbon component (11.8%) > heavy metal component (4.0%). During the PM2.5 high concentration case days, the ionic component accounted for 90.7% during atmospheric stagnation cases, whereas the chemical composition ratio was in the order of ionic component (51.7%) > heavy metal component (41.5%) > carbon component (6.8%) during yellow dust cases. It was found that the characteristic of PM2.5 in the Saemangeum reclaimed land and surrounding areas is mainly influenced by outside (domestic and overseas) throughout the year. Ion components accounted for the largest portion of PM2.5 components in this area, but there were few sources of SOx and NOx emission in the Seamangeum area, which are precursors for secondary particle formation. Therefore, it is judged that most of these are generated and influenced as a secondary reaction in the atmosphere from the outside.
Evaluation of Furrow Mulching Methods for Controlling Non-Point Source Pollution Load from a Sloped Upland
엽소진 Yeob So-jin , 김민경 Kim Min-kyeong , 김명현 Kim Myung-hyun , 방정환 Bang Jeong-hwan , 최순군 Choi Soon-kun
South Korea’s agricultural nitrogen balance and phosphorus balance rank first and second, respectively, among OECD countries, and proper nutrient management is required to preserve the water quality of rivers and lakes. This study evaluates the effects of furrow mulching on the reduction of non-point source pollution (NPS) load from a sloped upland. The study site was Wanju-gun, Jeollabuk-do, and the survey period was from 2018 to 2019. The slope of the testbed was 13%, and the soil type was sandy loam. The cropping system consisted of maize-autumn Chinese cabbage rotation. The testbed was composed of bare soil (bare), control (Cont.), furrow vegetation mulching (FVM), and furrow nonwoven fabric mulching (FFM) plots. Runoff was collected for each rainfall event with a 1/100 sampler, and the NPS load was calculated by measuring the concentrations of SS, T-N, and T-P. The NPS load was then analyzed for the entire monitoring and crop cultivation periods. During the monitoring period, the effect of reducing the NPS load was 1.5%∼44.5% for FVM and 13.1%∼55.2% for FFM. During the crop cultivation period, it was 1.2%∼80.5% for FVM and 27.0%∼65.1% for FFM, indicating that FFM was more effective than FVM. As the NPS load was fairly high during the crop conversion period, an appropriate management method needs to be implemented during this period.
Characteristics of Deformation Modulus and Poisson’s Ratio of Soil by Unconfined Loading-Reloading Axial Compression Process
송창섭 Song Chang-seob , 김명환 Kim Myeong-hwan , 김기범 Kim Gi-beom , 박오현 Park Oh-hyun
Prediction of soil behavior should be interpreted based on the level of axial strain in the actual ground. Recently numerical methods have been carried out focus on the state of soil failure. However considered the deformation of soil the prior to failure, mostly the small strain occurring in the elastic range is considered. As a result of calculating the deformation modulus to 50% of the maximum unconfined compression strength, Deformation modulus (E50) showed a tendency to increase according to the degree of compaction by region. The Poisson’s ratio during loading-unloading was 0.63, which was higher than the literature value of 0.5. For the unconfined compression test under cyclic loading for the measurement of permanent strain, the maximum compression strength was divided into four step and the test was performed by load step. Changes in permanent strain and deformation modulus were checked by the loading-unloading test for each stage. At 90% compaction, the permanent deformation of the SM sample was 0.21 mm, 0.37 mm, 0.6 mm, and 1.35 mm. The SC samples were 0.1 mm, 0.17 mm, 0.42 mm, and 1.66 mm, and the ML samples were 0.48 mm, 0.95 mm, 1.30 mm, and 1.68 mm.
Designing a Subsurface Drainage System: A Trade-Off Between Environmental Sustainability and Agricultural Productivity
This study evaluated the impacts of subsurface drainage design, i.e., spacing and depth, on agricultural productivity and environmental sustainability in two tile-drained fields (Sites A and E) under a corn-soybean rotation in the Midwestern United States. A calibrated and validated Root Zone Water Quality Model (RZWQM) was used to simulate Nitrate-N (nitrogen) losses to tile drainage and crop yields of 30 tile spacing and depth scenarios over 24 years (1992-2015). Our results presented that the narrower and deeper the tile drains are placed, the greater corn yield and Nitrate-N losses, indicating that the subsurface drainage design may cause a trade-off between agricultural productivity and environmental sustainability. The simulation results also presented that up to about 255.7% and 628.0% increase in Nitrate-N losses in Sites A and E, respectively, far outweigh the rate of increase in corn yield up to about 1.1% and 1.6% from the adjustment of tile spacing and depth. Meanwhile, the crop yield and Nitrate-N losses according to the tile configuration differed depending on the field, and the soybean yield presented inconsistent simulation results, unlike the corn yield, which together demonstrate the heterogeneous characteristic of agro-environmental systems to a subsurface drainage practice. This study demonstrates the applicability of agricultural systems models in exploring agro-environmental responses to subsurface drainage practices, which can help guide the introduction and installation of tile systems into farmlands, e.g., orchards and paddy fields, in our country.
Application of CCTV Image and Semantic Segmentation Model for Water Level Estimation of Irrigation Channel
김귀훈 Kim Kwi-hoon , 김마가 Kim Ma-ga , 윤푸른 Yoon Pu-reun , 방재홍 Bang Je-hong , 명우호 Myoung Woo-ho , 최진용 Choi Jin-yong , 최규훈 Choi Gyu-hoon
A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal’s CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R2 of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.
Ground Subsidence Risk Analysis on Correlation between Rainfall and Rainfall intensity
최창호 Choi Chang-ho , 김진영 Kim Jin-young , 강재모 Kang Jae-mo , 이성열 Lee Sung-yeol , 백원진 Baek Won-jin
Recent settlements and sinkhole openings in urban areas have caused social problems such as damage to roads and structures, fear of the public, and loss of property. Several studies have demonstrated that surface subsidence and sinkhole opening are greatly affected by rainfall and rainfall intensity in urban areas. In this paper, we analyzed the relationship with the characteristics of recorded rainfall data using the ground subsidence database reported in major cities. The correlations were found using sedimentation and precipitation data from 2010 to 2014. The duration and intensity of a given precipitation have evolved to obtain an effect on ground sedimentation rate (SR). The results show that the relationship between SR and precipitation is asymptotic and can be modeled by a hyperbolic equation. Through this study, it is possible to predict the occurrence of ground subsidence due to precipitation in advance.
