• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.341-347
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• 2017

From 2014 to 2016 water quality survey results according to the location and depth of Youngrang Lake are as follows: Distribution of dissolved oxygen in the water depth was investigated by the middle section and the downstream 1st, 3rd, 5th, when investigating bottem 1m interval anoxic layer. In organic matter and nutrient concentration distribution COD upstream 2.8 mg/L, middle section 4.2 mg/L downstream 4.1 mg/L, more than two times higher in bottem layer and TP concentrations showed a similar trend with COD, upstream of 0.047 mg/L, middle section was 0.051 mg/L, downstream of 0.059 mg/L. There was a difference in salinity every survey period the average salinity is lowest with 28.5‰ when the second survey. And the highest with 32.1‰ in the fourth investigation. Korean trophic state index($TSI_{KO}$) were showed eutrophic conditions in the middle section and downstream else showed mesotrophic state in the entire period. In order to evaluate the cause of water pollution Youngrang lake, regression analysis of the relationship between salinity and DO, COD, TN, TP, Chl-a results, $R^2$ is from 0.63 to 0.95 Youngrang lake water quality was found to have a close relationship with salinity due to inflow of seawater. As a result, in order to improve the quality of Youngrang lake efficient incorporation of the amount of water through the seawater influent as it is considered the key.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.326-333
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• 2017

The lakes and reservoirs have been reported as important sources of carbon emissions to the atmosphere in many countries. Although field experiments and theoretical investigations based on the fundamental gas exchange theory have proposed the quantitative amounts of Net Atmospheric Flux (NAF) in various climate regions, there are still large uncertainties at the global scale estimation. Mechanistic models can be used for understanding and estimating the temporal and spatial variations of the NAFs considering complicated hydrodynamic and biogeochemical processes in a reservoir, but these models require extensive and expensive datasets and model parameters. On the other hand, data driven machine learning (ML) algorithms are likely to be alternative tools to estimate the NAFs in responding to independent environmental variables. The objective of this study was to develop random forest (RF) and multi-layer artificial neural network (ANN) models for the estimation of the daily $CO_2$ NAFs in Daecheong Reservoir located in Geum River of Korea, and compare the models performance against the multiple linear regression (MLR) model that proposed in the previous study (Chung et al., 2016). As a result, the RF and ANN models showed much enhanced performance in the estimation of the high NAF values, while MLR model significantly under estimated them. Across validation with 10-fold random samplings was applied to evaluate the performance of three models, and indicated that the ANN model is best, and followed by RF and MLR models.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.97-104
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• 2010

The purpose of this study is to evaluate sediment yield reduction under various field slope conditions with rice straw mat. The Vegetative Filter Strip Model-W (VFSMOD-W) and Soil and Water Assessment Tool (SWAT) were used for simulation of sediment yield reduction effect of rice straw mat. The Universe Soil Loss Equation Practice factor (USLE P factor), being able to reflect simulation of rice straw mat in the agricultural field, were estimated for each slope with VFSMOD-W and measured soil erosion values under 5, 10, and 20 % slopes. Then with the regression equation for slopes, USLE P factor was derived and used as input data for each Hydrological Response Unit (HRU) in the SWAT model. The SWAT Spatially Distributed-HRU (SD-HRU) pre-processor module was utilized, moreover, in order to consider spatial location and topographic features (measured topographic features by field survey) of all HRU within each subwatershed in the study watershed. Result of monthly sediment yield without rice straw mat (Jan. 2000 - Aug. 2007) was 814.72 ton/month, and with rice straw mat (Jan. 2000 - Aug. 2007) was 526.75 ton/month, which was reduced as 35.35 % compared without it. Also, during the rainy season (from Jun. to Sep. 2000 - 2007), when without vs. with rice straw mat, monthly sediment indicated 2,109.54 ton and 1,358.61 ton respectively. It showed about 35.60 % was reduced depending on rice straw mat. As shown in this study, if rice straw mat is used as a Best Management Practice (BMP) in the sloping fields, rainfall-driven sediment yield will be reduced effectively.

• Journal of Biosystems Engineering
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• v.40 no.3
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• pp.165-177
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• 2015

Purpose: Accurate monitoring of soil strength is a key technology applicable to various precision agricultural practices. Soil strength has been traditionally measured using a cone penetrometer, which is time-consuming and expensive, making it difficult to obtain the spatial data required for precision agriculture. To improve the current, inefficient method of measuring soil strength, our objective was to develop and evaluate an in-situ system that could measure horizontal soil strength in real-time, while moving across a soil bin. Methods: Multiple cone-shape penetrometers were horizontally assembled at the front of a vertical plow blade at intervals of 5 cm. Each penetrometer was directly connected to a load cell, which measured loads of 0-2.54 kN. In order to process the digital signals from every individual transducer concurrently, a microcontroller was embedded into the measurement system. Wireless data communication was used between a data storage device and this real-time horizontal soil strength (RHSS) measurement system travelling at 0.5 m/s through an indoor experimental soil bin. The horizontal soil strength index (HSSI) measured by the developed system was compared with the cone index (CI) measured by a traditional cone penetrometer. Results: The coefficient of determination between the CI and the HSSI at depths of 5 cm and 10 cm ($r^2=0.67$ and 0.88, respectively) were relatively less than those measured below 20 cm ($r^2{\geq}0.93$). Additionally, the measured HSSIs were typically greater than the CIs for a given numbers of compactor operations. For an all-depth regression, the coefficient of determination was 0.94, with a RMSE of 0.23. Conclusions: A HSSI measurement system was evaluated in comparison with the conventional soil strength measurement system, CI. Further study is needed, in the form of field tests, on this real-time measurement and control system, which would be applied to precision agriculture.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.6
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• pp.119-130
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• 2011

Land-use changes have made considerable impacts on humans and nature such as biodiversity and ecosystem services. It is recognized as important elements for land use planning and regional natural resources conservation to identify the major causes of land use changes and to predict a process of changes and effects. This study, by using a spatially explicit Dyna-CLUE model, analyzed correlations between driving factors, quantified location characteristics of different land use types using logistic regression analysis and examined future land use changes and its effects in Yangpyeong and Yeoju region. We expected land use changes based on the three scenarios with different future land demands and simulated future changes for spatial variations of land use for the 20 years. The outcomes shows that larger change was found in agricultural areas than forest areas, based on the change in built-up areas. The changes in forest areas, which were mainly occurred in edge area, were expected to affect a large impact on its ecotone. It was found to be the importance of the management of forest edge and the necessity of the environmentally sound and sustainable development in order to conserve natural resources of the region.

• KSBB Journal
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• v.14 no.4
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• pp.414-421
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• 1999

The influenced of light intensity, cell density, and light pathlength on photosynthetic activity of Chlorella vulgaris were investigated. Since the light respon curve varied according to reaction conditions, the parameters estimated from nonlinear regression were proved to be apparent and could not be applied to various situations. The light response model incorporating the light penetration through the microalgal suspension was developed based upon the spatial distribution of the photosynthetic activity. This model showed a good agreement with experimental data at different cell densities and light intensities. Using the model the effects of cell density and light pathlenth were simulated and some dicussions about optimization of operation conditions of photobioreactors were carried out. Concludingly, the developed model can be useful for predicting microalgal photosynthesis and for determining the optimal operating conditions.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1231-1244
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• 2008

The objective of this study is to present a methodology for estimating runoff curve number(CN) using SWAT model which is capable of reflecting watershed heterogeneity such as climate condition, land use, soil type. The proposed CN estimation method is based on the asymptotic CN method and particularly, it uses surface flow data simulated by SWAT. This method has advantages to estimate spatial CN values according to subbasin division and to reflect watershed characteristics because the calibration process has been made by matching the measured and simulated streamflows. Furthermore, the method is not sensitive to rainfall-runoff data since CN estimation is on a daily basis. The SWAT based CN estimation method is applied to Chungju dam watershed. The regression equation of the estimated CN that exponentially decays with the increase of rainfall is presented.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.57-70
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• 2017

In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.13-25
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• 2016

This paper analyses the impacts of the characteristics of policyholder and contract on the lapse of Voluntarily Insured Person in National Pension, using the recent lapse data from National Pension Service. The logistic regression model is used in examining lapse odds with several independent variables. The result demonstrates several hypotheses of the lapse behaviors. First, the lapse odds of men is lower than that of women. Second, the effect of age on lapse odds shows concave shave with the peak at 37. Third, insured period has a negative effect on lapse odds in entrants sample. Fourth, standard monthly income has little effect on lapse in either sample. Fifth, the lapse odds decreases as the expected benefit ratio increases. Sixth, 2013 pension bill resulted in the sharp increase of lapse odds and the effect was greater for entrants. Last but not least, spatial environment such as residence also affects the lapse behavior.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.57-64
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• 2004

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, the forest fire danger rating system was developed to estimate forest fire risk by means of weather, topography, and forest type. Forest fires occurrence prediction needs to improve continually. Logistic regression and spatial analysis was used in developing the forest fire occurrence probability model. The forest fire danger index in accordance to the probability of forest fire occurrence was used in the classification of forest fire occurrence risk regions.