• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.2
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• pp.15-21
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• 2005

This study is to trace the change of stream shape using the past series of aerial photographs, and to compare the land use changes of riparian area along the stream. For the Gyeongan national stream, aerial photographs of 1966, 1981 and 2000 were selected and ortho-photographs were made with interior orientation and exterior orientation, respectively. Apparent changes of the stream were found that the consolidated reaches of stream by levee construction became straight together with widening of their stream widths. Especially the stream width of inlet part of Paldang lake widened almost twice because of the rise of water level by dam construction in 1974. The land use of riparian areas of three selected years were classified into six categories (water, forest, agricultural land, urban area, road, sandbar) by digitizing method. The forest and agricultural lands decreased and urban area increased as the stream maintenance had been performed.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.7
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• pp.1-13
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• 2002

Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.1
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• pp.21-30
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• 2018

In this study, we developed the Soil Moisture Data Assimilation (SMDA) scheme to extract Effective Soil Characteristics-ESC (Sand, Silt, Clay %) from MODerate resolution Imaging Spectroradiometer (MODIS) products. The SMDA scheme was applied to the MODIS-based Soil Moisture (SM) data during the summer (July to September) period. Then the ESC and soil erosion factors (K) were predicted, respectively. Several numerical experiments were conducted to test the performance of SMDA at the study sites under the synthetic and field validation conditions. In the synthetic experiment, the estimated soil moistures values(R: >0.990 and RMSE: <0.005) were identified well with the synthetic observations. The field validation results at the Bangdongri and Chungmicheon sites were also comparable to the TDR-based measurements with the statistics (R: 0.772/0.000 and RMSE: 0.065/0.000). The estimated ESC values were also matched well with the measurements for the synthetic and field validation conditions. Then we tested the SMDA scheme to extract the ESC from the MODIS-based soil moisture products. Although uncertainties exist in the results, the estimated soil moisture and ESC based on the SMDA were comparable to the measurements. Overall, the K factors were similarly distributed based on the derived ESC. Also, the K factors in the mountainous regions were higher than those of the relatively flat areas. Thus, the newly developed SMDA scheme can be useful to estimate spatially and temporally-distributed soil erosion and establish soil erosion management plans.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.41-50
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• 2017

The purpose of this study were to evaluate the effect of best management practices (BMPs) of Haean highland agricultural catchment ($62.8km^2$) under future climate change using SWAT (Soil and Water Assessment Tool). Before future evaluation, the SWAT was setup using 3 years (2009~2011) of observed daily streamflow, suspended solid (SS), total nitrogen (T-N), and total phosphorus (T-P) data at three locations of the catchment. The SWAT was calibrated with average 0.74 Nash and Sutcliffe model efficiency for streamflow, and 0.78, 0.63, and 0.79 determination coefficient ($R^2$) for SS, T-N, and T-P respectively. Under the HadGEM-RA RCP (Representative Concentration Pathway) 4.5 and 8.5 scenarios, the future precipitation and maximum temperature showed maximum increases of 8.3 % and $4.2^{\circ}C$ respectively based on the baseline (1981~2005). The future 2040s and 2080s hydrological components of evapotranspiration, soil moisture, and streamflow showed changes of +3.2~+17.2 %, -0.1~-0.7 %, and -9.1~+8.1 % respectively. The future stream water quality of suspended solid (SS), total nitrogen (T-N), and total phosphorus (T-P) showed changes of -5.8~+29.0 %, -4.5~+2.3 %, and +3.7~+17.4 % respectively. The future SS showed wide range according to streamflow from minus to plus range. We can infer that this was from the increase of long-term rainfall variability in 2040s less rainfalls and 2080s much rainfalls. However, the results showed that the T-P was the future target to manage stream water quality even in 2040s period.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.17-26
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• 2021

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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.23-33
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• 2020

Recently, high-resolution images can be easily acquired using UAV (Unmanned Aerial Vehicle), so that it is possible to produce small area observation and spatial information at low cost. In particular, research on the generation of cover maps in crop production areas is being actively conducted for monitoring the agricultural environment. As a result of comparing classification performance by applying RF(Random Forest), SVM(Support Vector Machine) and CNN(Convolutional Neural Network), deep learning classification method has many advantages in image classification. In particular, land cover classification using satellite images has the advantage of accuracy and time of classification using satellite image data set and pre-trained parameters. However, UAV images have different characteristics such as satellite images and spatial resolution, which makes it difficult to apply them. In order to solve this problem, we conducted a study on the application of deep learning algorithms that can be used for analyzing agricultural lands where UAV data sets and small-scale composite cover exist in Korea. In this study, we applied DeepLab V3 +, FC-DenseNet (Fully Convolutional DenseNets) and FRRN-B (Full-Resolution Residual Networks), the semantic image classification of the state-of-art algorithm, to UAV data set. As a result, DeepLab V3 + and FC-DenseNet have an overall accuracy of 97% and a Kappa coefficient of 0.92, which is higher than the conventional classification. The applicability of the cover classification using UAV images of small areas is shown.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.839-852
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• 2018

The purpose of this study is to predict monthly agricultural reservoir storage by developing weather data-based Multiple Linear Regression Model (MLRM) with precipitation, maximum temperature, minimum temperature, average temperature, and average wind speed. Using Naïve-Bayes classification, total 1,559 nationwide reservoirs were classified into 30 clusters based on geomorphological specification (effective storage volume, irrigation area, watershed area, latitude, longitude and frequency of drought). For each cluster, the monthly MLRM was derived using 13 years (2002~2014) meteorological data by KMA (Korea Meteorological Administration) and reservoir storage rate data by KRC (Korea Rural Community). The MLRM for reservoir storage rate showed the determination coefficient ($R^2$) of 0.76, Nash-Sutcliffe efficiency (NSE) of 0.73, and root mean square error (RMSE) of 8.33% respectively. The MLRM was evaluated for 2 years (2015~2016) using 3 months weather forecast data of GloSea5 (GS5) by KMA. The Reservoir Drought Index (RDI) that was represented by present and normal year reservoir storage rate showed that the ROC (Receiver Operating Characteristics) average hit rate was 0.80 using observed data and 0.73 using GS5 data in the MLRM. Using the results of this study, future reservoir storage rates can be predicted and used as decision-making data on stable future agricultural water supply.

• Journal of the Korean Geosynthetics Society
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• v.20 no.4
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• pp.133-140
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• 2021

There are few attempts to estimate the strength and stiffness of controlled low strength material (CLSM) using existing field-testing methods. The objective of this study is to evaluate the resilient modulus of CLSM by using the Light Weight Deflectometer (LWD) and investigate the relationships between the resilient modulus from LWD and the unconfined compressive strength (UCS) and secant modulus of elasticity from unconfined compressive test. Five CLSMs with different mix designs are used to evaluate the flowability and the stiffening of the CLSM in the flow and Vicat needle tests, respectively. To evaluate the early strength and stiffness characteristics, unconfined compressive tests are performed using the CLSM specimens cured for 1 and 7 days. LWD tests are carried out to estimate the resilient modulus of the CLSM specimens. The experimental results show that for the curing time of 1 day, the UCS and secant modulus of elasticity generally increase with the fast setting mortar content (FC). The CLSM specimen with the highest FC shows the significant increase in the UCS and secant modulus of elasticity along the curing time. Overall, the resilient modulus for the curing time of 1 day increases with the FC, while that for the curing time of 7days decreases with an increase in the FC. From the results, the linear relationships between the resilient modulus and UCS and secant modulus of elasticity are established.

• Environmental Engineering Research
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• v.15 no.4
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• pp.197-205
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• 2010

Recent years have witnessed increasing interest in wetland constructions in Korea as a flood control measure during the flood season and for consideration of the ecology during the non-flood season. In this study, hydraulic and hydrologic analyses were performed on a wetland construction plan for use as an alternative sustainable flood defense during the flood season, as well as a wetland that can protect the ecosystem during the non-flood season. The study area was the basin of the Topyeong-cheon stream, which is a tributary of the Nakdong River, including the Upo wetland, which is registered in the Ramsar Convention and the largest inland wetland in Korea. Wetlands were to be constructed at upstream and downstream of the Upo wetland by considering and analyzing seven scenarios for their constructions to investigate the effect of flood control during the flood season; it was found the best scenario reduced the flood level by 0.56 m. To evaluate the usefulness of the constructed wetlands during the non flood season, the water balance in the wetlands was analyzed, with the best scenario found to maintain a minimum water level of 1.3 m throughout the year. Therefore, the constructed wetlands could provide an alternative measure for flood prevention as well as an ecosystem for biodiversity.

• Water Engineering Research
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• v.2 no.3
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• pp.161-169
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• 2001

Present study deals with the development of a numerical model for the estimation of net annual recharge by coupling the Galerkin's finite element flow simulationl model with the Gauss-Newton-Marquardt optimization technique. The developed coupled numerical model is applied for estimating net annual recharge for Mahi Right Bank Canal (MRBC) project the norms of Groundwater Resources Estimation committee (1984, 1997) and Indian Agricultural research Institute(1983). It is observed that the estimated net recharge by inverse modeling is closer to the net recharge estimated using the water balance approach. Further it is observed that the computed head distribution from the estimated recharge agree closely with the observed head distribution. The study concludes that the developed model for inverse modeling can be successfully applied to large groundwater system involving regional aquifers where reliable recharge estimation always requires considerable time and financial resources.