Global warming due to climate change is expected to significantly affect the hydrological cycle of agriculture. Therefore, in order to predict the magnitude of climate impact on agricultural water resources in the future, it is necessary to estimate the water demand for irrigation as the climate change. This study aimed at evaluating the future changes in water demand for irrigation under two Shared Socioeconomic Pathways (SSPs) (SSP2-4.5 and SSP5-8.5) scenarios for paddy rice in Gimje, South Korea. The APEX-Paddy model developed for the simulation of paddy environment was used. The model was calibrated and validated using the H2O flux observation data by the eddy covariance system installed at the field. Sixteen General Circulation Models (GCMs) collected from the Climate Model Intercomparison Project phase 6 (CMIP6) and downscaled using Simple Quantile Mapping (SQM) were used. The future climate data obtained were subjected to APEX-Paddy model simulation to evaluate the future water demand for irrigation at the paddy field. Changes in water demand for irrigation were evaluated for Near-future-NF (2011-2040), Mid-future-MF (2041-2070), and Far-future-FF (2071-2100) by comparing with historical data (1981-2010). The result revealed that, water demand for irrigation would increase by 2.3%, 4.8%, and 7.5% for NF, MF and FF respectively under SSP2-4.5 as compared to the historical demand. Under SSP5-8.5, the water demand for irrigation will worsen by 1.6%, 5.7%, 9.7%, for NF, MF and FF respectively. The increasing water demand for irrigating paddy field into the future is due to increasing evapotranspiration resulting from rising daily mean temperatures and solar radiation under the changing climate.
Experimental Evaluation of Shear Strength of Surface Soil Beneath Greenhouse Varying Compaction Rate
Greenhouses have been damaged due to the uplift pressure from strong wind, for which rebar piles are often installed near the greenhouse to resist the pressure. For the effective design of rebar piles, it is necessary to access the shear strength of soil on which the greenhouse is constructed. This study experimentally evaluates the shear strength of the soil beneath the greenhouse. Four soil samples were collected from four agricultural sites, and prepared for testing with 75, 80, 85, and 90% compaction rates. One-dimensional unconfined compression test (UC), consolidated-undrained triaxial test (CU), and resonant column test (RC) were performed for the evaluation of shear strength and shear modulus. Generally, the higher shear strength and modulus were observed with the higher compaction rates. In particular, the UC shear strength increases with the increase of #200 sieve passing rate. Resulting from the CU test, the sample with the most of coarse soil had the highest friction angle, but the variation is small among samples. Resulting from the CU and RC tests, the ratio of maximum shear modulus with the major principle stress at failure was the higher at the finer soil. The ratio was two to three times greater than the ratio from the standard sand. This indicates that the shear strength is lower for the fine soil than the coarse soil at the same shear modulus. The results of this study will be a useful resource for the estimation of the pull-out strength of the rebar pile against the uplift pressure.
Analysis of Land Cover Change from Paddy to Upland for the Reservoir Irrigation Districts
권채린 Kwon Chaelyn , 박진석 Park Jinseok , 장성주 Jang Seongju , 신형진 Shin Hyungjin , 송인홍 Song Inhong
Conversion of rice paddy field to upland has been accelerated as the central government incentivizes more profitable upland crop cultivation. The objective of this study was to investigate the current status and conversion trend from paddy to upland for the reservoir irrigation districts. Total 605 of reservoir irrigation districts whose beneficiary area is greater than 200 ha were selected for paddy-to-upland conversion analysis using the land cover maps provided by the EGIS of the Ministry of Environment. The land cover data of 2019 was used to analyze up-to-date upland conversion status and its correlation with city proximity, while land cover change between 2007 and 2019 was used for paddy-to-upland conversion trend analysis. Overall 14.8% of the entire study reservoir irrigation area was converted to upland cultivation including greenhouse and orchard areas. Approximately the portion of paddy area was reduced by 17.8% on average, while upland area was increased by 4.9% over the 12 years from 2007 to 2019. This conversion from paddy to upland cultivation was more pronounced in the Gyoenggi and Gyeongsang regions compared to other the Jeolla and Chungcheong provinces. The increase of upland area was also more notable in proximity of the major city. This study findings may assist to identify some hot reservoir districts of the rapid conversion to upland cultivation and thus plan to transition toward upland irrigation system.
Evaluation of Optical Porosity of Thuja occidentalis by Image Analysis and Correlation with Aerodynamic Coefficients
장동화 Jang Dong-hwa , 양가영 Yang Ka-young , 김종복 Kim Jong-bok , 권경석 Kwon Kyeong-seok , 하태환 Ha Taehwan
Reduction effect of the spread of odorant and fine dust through windbreak trees can be predicted through numerical analysis. However, there is a disadvantage that a large space and destructive experiments must be carried out each time to calculate the aerodynamic coefficient of the tree. In order to overcome these shortcomings, In this study, we aimed to estimate the aerodynamic coefficient (C0, C1, C2) by using image processing. Thuja occidentalis, which can be used as windbreak were used as the material. The leaf area index was estimated from the leaf area ratio using image processing with leaf weight, and the optical porosity was calculated through image processing of photos taken from the side while removing the leaves step-by-step. Correlation analysis was conducted with the aerodynamic coefficient of Thuja occidentalis calculated from the wind tunnel test and leaf area index and optical porosity calculated from the image analysis. The aerodynamic coefficient showed positive and negative correlations with the leaf area index and optical porosity, respectively. The results showed that the possibility of estimating the aerodynamic coefficient using image processing.
Application of Bias-Correction and Stochastic Analogue Method (BCSA) to Statistically Downscale Daily Precipitation over South Korea
황세운 Hwang Syewoon , 정임국 Jung Imgook , 김시호 Kim Siho , 조재필 Cho Jaepil
BCSA (Bias-Correction and Stochastic Analog) is a statistical downscaling technique designed to effectively correct the systematic errors of GCM (General Circulation Model) output and reproduce basic statistics and spatial variability of the observed precipitation filed. In this study, the applicability of BCSA was evaluated using the ASOS observation data over South Korea, which belongs to the monsoon climatic zone with large spatial variability of rainfall and different rainfall characteristics. The results presented the reproducibility of temporal and spatial variability of daily precipitation in various manners. As a result of comparing the spatial correlation with the observation data, it was found that the reproducibility of various climate indices including the average spatial correlation (variability) of rainfall events in South Korea was superior to the raw GCM output. In addition, the needs of future related studies to improve BCSA, such as supplementing algorithms to reduce calculation time, enhancing reproducibility of temporal rainfall patterns, and evaluating applicability to other meteorological factors, were pointed out. The results of this study can be used as the logical background for applying BCSA for reproducing spatial details of the rainfall characteristic over the Korean Peninsula.
Estimation of Crop Water Requirement Changes Due to Future Land Use and Climate Changes in Lake Ganwol Watershed
김시내 Kim Sinae , 김석현 Kim Seokhyeon , 황순호 Hwang Soonho , 전상민 Jun Sang-min , 송정헌 Song Jung-hun , 강문성 Kang Moon-seong
This study aims to assess the changes in crop water requirement of paddy and upland according to future climate and land use changes scenarios. Changes in the spatiotemporal distribution of temperature and precipitation are factors that lower the stability of agricultural water supply, and predicting the changes in crop water requirement in consideration of climate change can prevent the waste of limited water resources. Meanwhile, due to the recent changes in the agricultural product consumption structure, the area of paddy and upland has been changing, and it is necessary to consider future land use changes in establishing an appropriate water use plan. Climate change scenarios were derived from the four GCMs of the CMIP6, and climate data were extracted under two future scenarios, namely SSP1-2.6 and SSP5-8.5. Future land use changes were predicted using the FLUS (Future Land Use Simulation) model. Crop water requirement in paddy was calculated as the sum of evapotranspiration and infiltration based on the water balance in a paddy field, and crop water requirement in upland was estimated as the evapotranspiration value by applying Penman-Monteith method. It was found that the crop water requirement for both paddy and upland increased as w e go to the far future, and the degree of increase and variability by time showed different results for each GCM. The results derived from this study can be used as basic data to develop sustainable water resource management techniques considering future watershed environmental changes.
Estimation of Duck House Litter Evaporation Rate Using Machine Learning
김다인 Kim Dain , 이인복 Lee In-bok , 여욱현 Yeo Uk-hyeon , 이상연 Lee Sang-yeon , 박세준 Park Sejun , 크리스티나 Cristina Decano , 김준규 Kim Jun-gyu , 최영배 Choi Young-bae , 조정화 Cho Jeong-hwa , 정효혁 Jeong Hyo-hyeog , 강솔뫼 Kang Solmoe
Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.
Estimation of Fish Habitat Suitability Index for Stream Water Quality - Case Species of Zacco platypus -
홍록기 Hong Rokgi , 박진석 Park Jinseok , 장성주 Jang Seongju , 송인홍 Song Inhong
The conservation of stream habitats has been gaining more public attention and fish habitat suitability index (HSI) is an important measure for ecological stream habitat assessment. The fish habitat preference is affected not only by physical stream conditions but also by water quality of which HSI was not available due to the lack of field data. The purpose of this study is to estimate the HSI of Zacco platypus for water quality parameters of water temperature, dissolved oxygen (DO), and biochemical oxygen demand (BOD) using the water environment monitoring data provided by the Ministry of Environment (ME). Fish population data merged with water quality were constructed by spatio-temporal matching of nationwide water quality monitoring data with bio-monitoring data of the ME. Two types of the HSI were calculated by the Instream Flow and Aquatic Systems Group (IFASG) method and probability distribution (Weibull) fitting for the four major river basins. Both the HSIs by the IFASG and Weibull fitting appeared to represent the overall distribution and magnitude of fish population and this can be used in stream fish habitat evaluation considering water quality.
A Comparative Analysis of Vegetation and Agricultural Monitoring of Terra MODIS and Sentinel-2 NDVIs
손무빈 Son Moo-been , 정지훈 Chung Jee-hun , 이용관 Lee Yong-gwan , 김성준 Kim Seong-joon
The purpose of this study is to evaluate the compatibility of the vegetation index between the two satellites and the applicability of agricultural monitoring by comparing and v erifying NDVI (Normalized Difference Vegetation Index) based on S entinel-2 and T erra MODIS (Moderate Resolution Imaging Spectroradiometer). Terra MODIS NDVI utilized 16-day MOD13Q1 data with 250 m spatial resolution, and Sentinel-2 NDVI utilized 10-day Level-2A BOA (Bottom Of Atmosphere) data with 10 m spatial resolution. To compare both NDVI, Sentinel-2 NDVIs were reproduced at 16-day intervals using the MVC (Maximum Value Composite) technique. As a result of time series NDVIs based on two satellites for 2019 and compare by land cover, the average R2 (Coefficient of determination) and RMSE (Root Mean Square Error) of the entire land cover were 0.86 and 0.11, which indicates that Sentinel-2 NDVI and MODIS NDVI had a high correlation. MODIS NDVI is overestimated than Sentinel-2 NDVI for all land cover due to coarse spatial resolution. The high-resolution Sentinel-2 NDVI was found to reflect the characteristics of each land cover better than the MODIS NDVI because it has a higher discrimination ability for subdivided land cover and land cover with a small area range.
An Investigation of Emission of Particulate Matters and Ammonia in Comparison with Animal Activity in Swine Barns
박진선 Park Jinseon , 정한나 Jeong Hanna , 이세연 Lee Se Yeon , 최락영 Choi Lak Yeong , 홍세운 Hong Se-woon
The movement of animals is one of the primary factors that influence the variation of livestock emissions. This study evaluated the relationship between animal activity and three major emissions, PM10, PM2.5, and ammonia gas, in weaning, growing, and fattening pig houses through continuous monitoring of the animal activity. The movement score of animals was quantified by the developed image analysis algorithm using 10-second video clips taken in the pig houses. The calculated movement scores were validated by comparison with six activity levels graded by an expert group. A comparison between PMs measurement and the movement scores demonstrated that an increase of the PMs concentrations was obviously followed by increased movement scores, for example, when feeding started. The PM10 concentrations were more affected by the animal activity compared to the PM2.5 concentrations, which were related to the inflow of external PM2.5 due to ventilation. The PM10 concentrations in the fattening house were 1.3 times higher than those in the weaning house because of the size of pigs while weaning pigs were more active and moved frequently compared to fattening pigs showing 2.45 times higher movement scores. The results also indicated that indoor ammonia concentration was not significantly influenced by animal activity. This study is significant in the sense that it could provide realistic emission factors of pig farms considering animal’s daily activity levels if further monitoring is carried out continuously.
Prediction of the Salinization in Reclaimed Land by Soil and Groundwater Characteristics
Jihun Jeon , Donggeun Kim , Taejin Kim , Keesung Kim , Hosup Jung , Younghwan Son
It is becoming more important to utilize reclaimed lands in South Korea, due to the increasing competition for its usage among different sectors. However, the high groundwater level and poor permeability are exposing them to deterioration by salinization. Salinization is difficult to predict because the pattern changes according to various characteristics of soil and groundwater. In this study, the capillary rising time was studied by the water content profile in the soil. The prediction equation of soil salinity was developed based on simulation result of the CHEMFLO model. to enable prediction considering various soil water content and groundwater level. The two terms constituting the equation showed the coefficients of determination of 0.9816 and 0.9824, respectively. Using the prediction equation of the study, the surface salinity can be easily predicted from the initial surface salinity and the salinity of the groundwater. In the future, more precise predictions will be possible with the results of studies on the hydraulic characteristics of various reclaimed soils, changes in water content profile by seasonal and climate events.
Assessing the Potential Impact of Climate Change on Irrigation by Reservoir
In order to assess the impact of climate change on irrigation reservoirs, climate exposure (EI), sensitivity (SI), and potential impact (PI) were evaluated for 1,651 reservoirs nationwide. Climate exposure and sensitivity by each reservoir were calculated using data collected from 2011 to 2020 for seven proxy variables (e.g. annual rainfall) and six proxy variables (e.g. irrigation days), respectively. The potential impact was calculated as the weighted sum of climate exposure and sensitivity, and was classified into four levels: ‘Low (PI<0.4)’, ‘Medium (PI<0.6)’, ‘High (PI<0.8)’, and ‘Critical (PI≥0.8)’. The result showed that both the climate exposure index and the sensitivity index were on average high in Daegu and Gyeongbuk with high temperature and low rainfall. About 79.8% of irrigation reservoirs in Daegu, Gyeongbuk, and Ulsan with high climate exposure and sensitivity resulted in a ‘High’ level of potential impact. On the contrary, 64.5% of the study reservoirs in Gyeongnam and Gangwon showed ‘Low’ in potential impact. In further studies, it is required to reorganize the proxy variables and the weights in accordance with practical alternatives for improving adaptive capacity to drought, and it is expected to contribute to establishing a framework for vulnerability assessment of an irrigation reservoir.
