Carbon dioxide is one of the major driving forces causing climate changes, and many countries have been trying to reduce carbon dioxide emissions from various sources. Soil stores more carbon dioxide(two to three times) amounts than atmosphere indicating that soil organic carbon emission management are a pivotal issue. In this study, we developed a Soil Organic Carbon(SOC) storage estimation model to predict SOC storage amounts in soils. Also, SOC storage values were assessed based on the carbon emission price provided from Republic Of Korea(ROK). Here, the SOC model calculated the soil hydraulic properties based on the soil physical and chemical information. Base on the calculated the soil hydraulic properties and the soil physical·chemical information, SOC storage amounts were estimated. In validation, the estimated SOC storage amounts were 486,696 tons(3.526 kg/m2) in Jindo-gun and shown similarly compared to the previous literature review. These results supported the robustness of our SOC model in estimating SOC storage amounts. The total SOC storage amount in ROK was 305 Mt, and the SOC amount at Gyeongsangbuk-do were relatively higher than other regions. But the SOC storage amount(per unit) was highest in Jeju island indicating that volcanic ashes might influence on the relatively higher SOC amount. Based on these results, the SOC storage value was shown as 8.4 trillion won in ROK. Even though our SOC model was not fully validated due to lacks of measured SOC data, our approach can be useful for policy-makers in reducing soil organic carbon emission from soils against climate changes.
A Study on Regularization Methods to Evaluate the Sediment Trapping Efficiency of Vegetative Filter Strips
배주현 Bae Joohyun , 한정호 Han Jeongho , 양재의 Yang Jae E , 김종건 Kim Jonggun , 임경재 Lim Kyoung Jae , 장원석 Jang Won Seok
Vegetative Filter Strip (VFS) is the best management practice which has been widely used to mitigate water pollutants from agricultural fields by alleviating runoff and sediment. This study was conducted to improve an equation for estimating sediment trapping efficiency of VFS using several different regularization methods (i.e., ordinary least squares analysis, LASSO, ridge regression analysis and elastic net). The four different regularization methods were employed to develop the sediment trapping efficiency equation of VFS. Each regularization method indicated high accuracy in estimating the sediment trapping efficiency of VFS. Among the four regularization methods, the ridge method showed the most accurate results according to R2, RMSE and MAPE which were 0.94, 7.31% and 14.63%, respectively. The equation developed in this study can be applied in watershed-scale hydrological models in order to estimate the sediment trapping efficiency of VFS in agricultural fields for an effective watershed management in Korea.
Evaluation of Odor Dispersion from Livestock Building through Field Experiment
여욱현 Yeo Uk-hyeon , 이인복 Lee In-bok , 하태환 Ha Tae-hwan , 데카노크리스티나 Decano Cristina , 김락우 Kim Rack-woo , 이상연 Lee Sang-yeon , 김준규 Kim Jun-gyu , 최영배 Choi Young-bae , 박유미 Park You-me
Livestock odor is comprised of mixed type of odorous compounds. Among these, ammonia (NH3) and hydrogen sulfide (H2S) are the two known major odor causing substances. Because high odor concentration reduces productivity of livestock and causes damage to the surrounding communities, quantitative analysis is needed to manage the odor inside and outside the livestock facilities. It is also necessary to evaluate odor dispersion according to the distance between the receptors taking into account the influence of odor source and weather condition. Therefore, in this study, we tried to evaluate the internal environment and odor dispersion from experimental pig house considering weather conditions. An experimental farm was specifically selected to eliminate the interference of odors generated by adjacent farms. NH3 and complex odor were quantitatively analyzed using a gas detector and air dilution sensory method. The concentration of NH3 and complex odor in pig house showed a distinct concentration difference according to the cleaning and ventilation conditions. NH3 concentration and complex odor was lower than emission standard in the pig house and at the site boundary. The average NH3 concentration (P1∼P3) and the NH3 concentration at the site boundary (S1) were strongly correlated with R=0.77. While the correlation for complex odor inside and at the site boundary had R=0.52. The correlation coefficient between NH3 and the complex odor was 0.80.
Assessing Vulnerability to Agricultural Drought of Pumping Stations for Preparing Climate Change
In order to implement practical alternatives to proactively cope with the agricultural drought, the potential vulnerability of irrigation pumping stations to agricultural drought was quantitatively evaluated. Data for the 124 pumping stations which are correlatable to the three proxy variables, i.e. exposure, sensitivity, and adaptive capacity was collected by the Korea Rural Community Corporation, and then standardized considering distribution of each data set. Finally, the vulnerability index was calculated by multiplying the weights determined by the expert survey. The results showed that the vulnerability index ranged from 0.709 to 0.331 and the most vulnerable pumping stations such as Judam, Wongoo and Jinahn were mostly located in Gyeongbuk province likely because of the climatological characteristics with high temperature and low rainfall around this area. In addition, it was found that the adaptive capacity was a dominant factor comparing to exposure or sensitivity proxy variables in contributing to the vulnerability. It is therefore recommended that more practical alternatives should be employed to effectively reduce the vulnerability of an individual pumping station to agricultural drought. Furthermore, the corresponding data related to adaptive capacity should be systematically organized and managed at a field level to design reliable adaptation strategies.
Vulnerability Evaluation of Groundwater Well Efficiency and Capacity in Drought Vulnerable Areas
신형진 Shin Hyung-jin , 이재영 Lee Jae-young , 조성문 Jo Sung-mun , 전상민 Jeon Sang-min , 김미솔 Kim Mi-sol , 차상선 Cha Sang-sun , 박찬기 Park Chan-gi
Recently, the damage caused by climate change has been distinguished in the world. The Korean Peninsula is also suffering from drought, so it is necessary to study the vulnerability assessment to identify and predict the state of the irrigation facility, which is a irrigation facility. As the damage caused by drought is occurring in the Korean peninsula, it is necessary to study the vulnerability assessment to know the condition of the irrigation facility, and to predict it. The target areas were Yeongdong-gun, Cheonan-si, Mungyeong-si, Geochang-gun, Muju-gun, and Yeonggwang-gun. The survey items were selected as positive impacts survey items, including precipitation, groundwater level, and pumping capacity per groundwater well. The negative impacts were selected as the cultivation acreage, Number of days without rain, and the ratio of private underground wells. The survey method was investigated by various methods such as “weather data portal”, “groundwater level status information”, “agricultural drought management system”, “groundwater survey yearbook”. The results of vulnerability assessment were expressed by the score by conducting survey and standardization. As a result, Yeonggwang-gun showed normal vulnerability, and other areas showed “vulnerable” or “very vulnerable”.
A Study to Determine the Slope Length and Steepness Factor of Universal Soil Loss Equation with Determining and Adapting Major Slope Length at Field Scale
박윤식 Park Youn Shik , 박종윤 Park Jong-yoon , 장원석 Jang Won Seok , 김종건 Kim Jonggun
A Study to Determine the Slope Length and Steepness Factor of Universal Soil Loss Equation with Determining and Adapting Major Slope Length at Field Scale
박윤식 Park Youn Shik , 박종윤 Park Jong-yoon , 장원석 Jang Won Seok , 김종건 Kim Jonggun
Universal Soil Loss Equation (USLE) is to estimate potential soil loss and has benefit in use with its simplicity. The equation is composed of five factors, one of the factors is the slope length and steepness factor (LS factor) that is for topographic property of fields to estimate potential soil loss. Since the USLE was developed, many equations to compute LS was suggested with field measurement. Nowadays the factor is often computed in GIS software with digital elevation model, however it was reported that the factor is very sensitive to the resolution of digital elevation model. In addition, the digital elevation model of high resolution less than 3 meter is required in small field application, however these inputs are not associate with the empirical models’ backgrounds since the empirical models were derived in 22.1 meter field measurements. In the study, four equation to compute LS factor and two approaches to determine slope length and steepness were examined, and correction factor was suggested to provide reasonable precision in LS estimations. The correction factor is computed with field area and cell size of digital elevation model, thus the correction factor can be adapted in any USLE-based models using LS factor at field level.
A Comparative Study on the Spacing and Discharge Performance of Subsurface Drainage Culvert to Increase Drainage Efficiency
김현태 Hyuntai Kim , 유전용 Jeonyong Ryu , 정기열 Kiyuol Jung , 박영준 Youngjun Park
This study compared the theory of a culvert spacing and analytical results of the seepage flow for the subsurface drainage. i) If culvert spacing (Sc) is within 5 m, the unit drainage (q) is very larger; in contrast, if Sc is 5 m or more, there is very little drainage in the middle between drains. Therefore, the drain spacing should be within 5 m to ensure high drainage efficiency. ii) Since the planned culvert drainage increases linearly with the soil’s permeability coefficient (k), k must be taken into account when determining the drain diameter by the planned culvert drainage. iii) As a result of analyzing the drainage performance of the absorbing culvert, the drainage performance is sufficient with the diameter of the corrugated drain pipe Dc = 50 mm at the length of the drain Lc = 100 m. iv) Therefore, if the drain spacing (Sc) is less than 5 m using the low-cost non-excavated drainage pipe method (Φ50 mm the corrugated drain pipe and fiber mat) rather than the conventional trench drain method (Sc > 10 m, Dc > 100 mm), uniform and high drainage efficiency can be ensured as well as low construction cost. v) The sub-irrigation+drainage culvert requires narrower drain spacing (Sc < 2-3 m) for irrigation. As a result of examining the condition of 35 mm in diameter (Dc) and 2∼3 m in drain spacing, it is possible to apply the non-excavated drainage pipe method to the sub-irrigation+drainage culvert because drainage performance is sufficient at the drain length Lc = 50 m.
Statistical Analysis of Determining Optimal Monitoring Time Schedule for Crop Water Stress Index (CWSI)
최용훈 Choi Yonghun , 김민영 Kim Minyoung , 오우현 Oh Woohyun , 조정건 Cho Junggun , 윤석규 Yun Seokkyu , 이상봉 Lee Sangbong , 김영진 Kim Youngjin , 전종길 Jeon Jonggil
Continuous and tremendous data (canopy temperature and meteorological variables) are necessary to determine Crop Water Stress Index (CWSI). This study investigated the optimal monitoring time and interval of canopy temperature and meteorological variables (air temperature, relative humidity, solar radiation and wind speed) to determine CWSIs. The Nash-Sutcliffe model efficiency coefficient (NSE) was used to quantitatively describe the accuracy of sampling method depending upon various time intervals (t=5, 10, 15, 20, 30 and 60 minutes) and CWSIs per every minute were used as a reference. The NSE coefficient of wind speed was 0.516 at the sampling time of 60 minutes, while the ones of other meteorological variables and canopy temperature were greater than 0.8. The pattern of daily CWSIs increased from 8:00 am, reached the maximum value at 12:00 pm, then decreased after 2:00 pm. The statistical analysis showed that the data collection at 11:40 am produced the closest CWSI value to the daily average of CWSI, which indicates that just one time of measurement could be representative throughout the day. Overall, the findings of this study contributes to the economical and convenient method of quantifying CWSIs and irrigation management.
Assessing Hydrologic Impacts of Climate Change in the Mankyung Watershed with Different GCM Spatial Downscaling Methods
김동현 Kim Dong-hyeon , 장태일 Jang Taeil , 황세운 Hwang Syewoon , 조재필 Cho Jaepil
The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.
Analysis of Water Supply Reliability of Agricultural Reservoirs Based on Application of Modified Penman and Penman-Monteith Methods
조건호 Gun Ho Cho , 한경화 Kyung Hwa Han , 최경숙 Kyung Sook Choi
This study aims to analyze the influences of applications of two different evapotranspiration (ET) estimation methods on the irrigation water requirements (IWR) for paddy rice and water supply reliability of agricultural reservoirs. The modified Penman (MP), traditional method, and the Penman-Monteith (PM), the new adopted method, were applied on 149 reservoirs located in Honam province for this study. The weather date was used from 1987 to 2016, and analysed the trends of temperature and rainfall during rice growing season between past and current 10 years respectively. The increased average temperature and rainfall were observed from the current 10 years compared to the past years. This phenomena impacts on the results of ET and IWR estimations with decreased IWR obtained from high rainfall regions and increased ET obtained high temperature regions. For the comparisons of application results of two ET approaches, the PM method showed lower ET and IWR, and hence more reliable storage capacity of the reservoirs respect to water supply to paddy fields. The results also showed that the influences of different ET methods applications on the water supply reliability of reservoirs are negligible for the cases of over 3.7 watershed ratio and 670 mm unit reservoir storage, while significant variations of the results obtain from the applications between two ET approaches for the opposite cases. Further studies are necessary to consider various field conditions for practical applications of the PM method estimating ET in the fields of paddy farming.
A Study on Cementation Reaction Mechanism for Weathered Granite Soil and Microbial Mixtures
오종신 Oh Jongshin , 이성열 Lee Sungyeol , 김진영 Kim Jinyung , 권성진 Kwon Sungjin , 정창성 Jung Changsung , 이재수 Lee Jaesoo , 이정훈 Lee Jeonghoon , 고화빈 Ko Hwabin , 백원진 Baek Wonjin
The purpose of this study is to investigate the reaction mechanism of soil and bacteria solution by various mixing ratios. For this purpose, in order to understand the reaction mechanisms of microorganisms and weathered granite soil, the tests were carried out under various mixing ratios additives such as soil, bacteria solution, Ca(OH)2 and fixture. The test results from this study are summarized as follows. Firstly, the reaction between the bacteria solution and fixture produced a precipitate called vaterite, a type of silicate and calcium carbonate. Secondly, as a result of SEM analysis, the resulting precipitates generated from the test results using the specimens with various mixing ratios except SW condition and the irregular spherical microscopic shapes were formed in the size of 150 μm to 20 μm. In addition, it can be seen that the bacteria solution and the fixture reacted between the granules to form an adsorbent material layer on the surface, and the microorganisms had a biological solidifying effect when the pores are combined into hard particles. Finally, The XRD analysis of the sediment resulting from the reaction between the microorganism and the deposit control agent confirmed the presence of a type of calcium carbonate (CaCO3) vaterite, which affects soil strength formation, as well as silicate(SiO2).
Estimation of Reference Crop Evapotranspiration Using Backpropagation Neural Network Model
김민영 Minyoung Kim , 최용훈 Yonghun Choi , 수잔오샤네시 Susan O’shaughnessy , 폴콜레이지 Paul Colaizzi , 김영진 Youngjin Kim , 전종길 Jonggil Jeon , 이상봉 Sangbong Lee
Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, ETo). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole ETo method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating ETo from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating ETo. The overall findings of this study indicated that ETo could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.
RNN-LSTM Based Soil Moisture Estimation Using Terra MODIS NDVI and LST
장원진 Jang Wonjin , 이용관 Lee Yonggwan , 이지완 Lee Jiwan , 김성준 Kim Seongjoon
This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015∼2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm∼30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination (R2), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.
