• 한국농공학회논문집
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• 제52권5호
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• pp.87-95
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• 2010

The optimum volume of sediment settling pond is determined by the maximum rainfall and surface peak rate runoff from crop field. Based on analysis of measured rainfall and runoff data, it was found that rainfall intensity of 2 mm/min would result in peak rate runoff from the agricultural field of study area. Optimum pond volume under various slope scenarios were determined using the WEPP model calibrated with measured flow and sediment data for the study watershed. For the agricultural field with the slope of 7 % and area of $2,600\;m^2$ at the study area, at least $6.4\;m^3$ of sediment settling pond is needed as shown in this study. The results presented in this study could be used as a guide in designing appropriate volume of sediment settling pond at highland agricultural areas because both very detailed field measurement and calibrated WEPP model results are used in the analysis.

• 한국환경농학회지
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• 제28권2호
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• pp.113-124
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• 2009

Severe sediment-laden problem has been the hot issue in Korea. It was assumed that agricultural activities and landslides were the primary causes of these problems in watersheds. The USLE-based systems have been widely used in soil erosion studies. However the GIS-based USLE modeling system has limitation in USLE L factors. In this study, the SATEEC L module was developed to reflect the slope length segmentations in the fields. The SATEEC L module was applied to the study watershed to analyze the effects of using the SATEEC L module on estimated sediment. As shown in the comparisons between SATEEC estimated sediment with SWAT values, the SATEEC GA-SDR module derives the SDR with reasonably acceptable accuracies. However, it is worthy to note that the soil erosion using the SATEEC L module for the study watershed was lower than that without using the SATEEC L module by 25%, although the SATEEC estimated sediment values with and without using L module match the SWAT sediment values with similar accuracies. This is because the SATEEC GA-SDR module estimates lower SDR in case of greater soil erosion estimation without the L module and greater SDR in case of lower soil erosion estimation with the L module. This indicates that the SATEEC input parameters, especially L factor, need to be prepared with care for accurate estimation of SDR at a watershed scale and for accurate evaluation of BMPs in the watershed.

• 한국물환경학회지
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• 제31권5호
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• pp.543-555
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• 2015

The existing standard for soil erosion risk assessment has limitations in sustainable topsoil management since the fixed criteria are applied to determination of soil erosion risk areas regardless of land use types. It may not be necessary to apply soil erosion best management practices to agricultural areas with high potential of soil erosion because human or economic damage derived from soil erosion might be tiny in that region. Furthermore, the fixed criterion with absolute values can select too many hot spots of soil erosion to conduct efficient soil erosion management. Thus, objective of this study was to suggest the relative criteria using statistical analysis for efficient soil erosion management. In future, the relative indices for soil erosion prevention should be improved to provide a priority of soil erosion management considering economic damage from soil erosion or functional values of soil with quantitative soil erosion. Additional researches will be needed to reflect a regional characteristics and to consider various land use types and different criteria.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2005년도 학술발표논문집
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• pp.139-155
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• 2005

All these days, we achieved the result of our efforts on agricultural facilities by a huge budget for stable agricultural infrastructure development. But it is anticipated that the cost of maintenance is increased from now on since we've focused on installing facilities(agricultural infrastructures) in quantity more than in quality. Furthermore we are short of efficient management system(S/W) because of active and overall support for facilities expansion(H/W). This study is focus on how to improve our agricultural infrastructure for not only to maintain eco-friendly facilities but also to prepare water shortage era.

• 한국농공학회논문집
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• 제59권4호
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• pp.97-107
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• 2017

This study is to determine the coefficients of regression equations and to select the optimal regression equation in the LOADEST model after classifying the whole study period into 5 flow conditions for 16 watersheds located in the Nakdonggang waterbody. The optimized coefficients of regression equations were derived using the gradient descent method as a learning method in Tensorflow which is the engine of machine-learning method. In South Korea, the variability of streamflow is relatively high, and rainfall is concentrated in summer that can significantly affect the characteristic analysis of pollutant loads. Thus, unlike the previous application of the LOADEST model (adjusting whole study period), the study period was classified into 5 flow conditions to estimate the optimized coefficients and regression equations in the LOADEST model. As shown in the results, the equation #9 which has 7 coefficients related to flow and seasonal characteristics was selected for each flow condition in the study watersheds. When compared the simulated load (SS) to observed load, the simulation showed a similar pattern to the observation for the high flow condition due to the flow parameters related to precipitation directly. On the other hand, although the simulated load showed a similar pattern to observation in several watersheds, most of study watersheds showed large differences for the low flow conditions. This is because the pollutant load during low flow conditions might be significantly affected by baseflow or point-source pollutant load. Thus, based on the results of this study, it can be found that to estimate the continuous pollutant load properly the regression equations need to be determined with proper coefficients based on various flow conditions in watersheds. Furthermore, the machine-learning method can be useful to estimate the coefficients of regression equations in the LOADEST model.

• 한국농공학회논문집
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• 제59권1호
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• pp.21-30
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• 2017

Soil erosion has been issued in many countries since it causes negative impacts on ecosystem at the receiving water bodies. Therefore best management practices to resolve the problem in a watershed have been developed and implemented. As a prior process, there is a need to define soil erosion level and to identify the area of concern regarding soil erosion so that the practices are effective as they are designed. Universal Soil Loss Equation (USLE) were developed to estimate potential soil erosion and many Geographic Information System (GIS) models employ USLE to estimate soil erosion. Sediment Assessment Tool for Effective Erosion Control (SATEEC) is one of the models, the model provided several opportunities to consider various watershed peculiarities such as breaking of slope length, monthly variation of rainfall, crop growth at agricultural fields, etc. SATEEC is useful to estimate soil erosion, however the model can be implemented with ArcView software that is no longer used or hard to use currently. Therefore SATEEC based on ArcView was rebuild for the ArcGIS software with all modules provided at the previous version. The rebuilt SATEEC, ArcSATEEC, was programmed in ArcPy and works as ArcGIS Toolset and allows considering monthly variations of rainfall and crop growth at any watershed in South-Korea. ArcSATEEC was applied in Daecheong-dam watershed in this study, monthly soil erosion was estimated with monthly rainfall and crop growth variation. Annual soil erosion was computed by summing monthly soil erosion and was compared to the conventional approach to estimate annual soil erosion. The annual soil erosion estimated by the conventional approach and by summing monthly approach did not display much differences, however, ArcSATEEC was capable to provide monthly variation of soil erosion.

• 한국농공학회논문집
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• 제58권6호
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• pp.23-30
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• 2016

Soil loss is an accompanying phenomenon of hydrologic cycle in watersheds. Both rainfall drops and runoff lead to soil particle detachment, the detached soil particles are transported into streams by runoff. Here, a sediment-laden water problem can be issued if soil particles are severely detached and transported into stream in the watershed. There is a need to estimate or simulate soil erosion in watersheds so that an adequate plan to manage soil erosion can be established. Universal Soil Loss Equation (USLE), therefore, was developed and modified by many researchers for their watersheds, moreover the simple model, USLE, has been employed in many hydrologic models for soil erosion simulations. While the USLE has been applied even in South-Korea, the model is often regarded as being limited in applications for the watersheds in South-Korea since monthly conditions against soil erosion on soil surface are not capable to represent. Thus, the monthly USLE factors against soil erosion, soil erodibility and crop management factors, were established for four major watersheds, which are Daecheong-dam, Soyang-dam, Juam-dam, and Imha-dam watersheds. The monthly factors were established by recent fifteen years from 2000 to 2015. Five crops were selected for the monthly crop management factor establishments. Soil loss estimations with the modified factors were compared to conventional approach that is average annual estimations. The differences ranged from 9.3 % (Juam-dam watershed) to 28.1 % (Daecheong-dam watershed), since the conventional approaches were not capable of seasonally and regionally different conditions.

• 한국농공학회논문집
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• 제60권6호
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• pp.111-119
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• 2018

The air-void is known to be one of the influencing factors for estimating long-term performance of asphalt concrete. Most of all, confirming air void or density of pavement layer is important for quality control of field compaction level of asphalt concrete pavement. In this study, a non-nuclear type non-destructive density gage (NDDG) was used to estimate compacted air-voids of asphalt pavement as a non-destructive test method. Asphalt concrete slab specimens were prepared using 6 types of asphalt mixes in laboratory (lab) for lab NDDG test. Four different base structure materials were used to find out if there were any differences due to the type of base structure materials. The actual air-voids and NDDG air-voids were measured from 6 asphalt concrete slabs. Four sections of field asphalt pavements were tested using the NDDG, and actual air voids were also measured from field cores taken from the site where the NDDG air-void was measured. From lab and field experimental tests, it was found that the air-voids obtained by NDDG were not the same as the actual air-voids measured from the asphalt concrete specimen. However, it was possible to estimate air voids based on the relationship obtained from regression analysis between actual and NDDG air voids. The predicted air-voids based on the NDDG air-voids obtained from 50mm depth were found to be reliable levels with $R^2{\fallingdotseq}0.9$. Therefore, it was concluded that the air-voids obtained from NDDG could be used to estimate actual air-voids in the field asphalt pavement with a relatively high coefficient of determination.

• 한국농공학회논문집
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• 제58권1호
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• pp.27-38
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• 2016

More severe and frequent flood and drought have increased the attentions on the river management. In particular, baseflow is an important element among many streamflow characteristics because streamflow is mainly consisted of direct runoff and baseflow. In this regard, this study attempted to analyze the relationship between streamflow variability and baseflow contributions on Nakdong river basin. For this, two Streamflow Variability Indices (SVI) were used: Coefficient of Variation (CV) and Coefficient of Flow Regime (CFR). Furthermore, baselow separation was individually conducted by three methods (PART, WHAT and BFLOW), and based on this, Baseflow Index (BFI) was calculated. Also, we used the daily streamflow data retrieved from 27 gauge stations in Nakdong river basin for baseflow separation. The results showed that BFI calculated by three models ranges from 0.14 to 0.90 for 27 gauge stations. For SVI, BFI has much higher correlation with CV than with CFR. Also, the inversely proportional relationship between BFI and CV showed that higher baseflow contribution, less streamflow variability.

• 한국농공학회논문집
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• 제59권6호
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• pp.101-108
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• 2017

This study attempted to improve the accuracy of streamflow and baseflow prediction of Soil and Water Assessment Tool (SWAT) by applying baselfow recession constants for each sub-watershed. This study set two different scenarios (S1 and S2) to evaluate the impact of application of baseflow recession constants for each sub-watershed on streamflow prediction. In S1, Only the baseflow recession constant obtained from the streamflow station located in the final outlet of study area was applied for whole sub-watersheds. In S2, baseflow recession constants obtained from six different streamflow stations were applied for each sub-watershed. Then, baseflow was separated form the measured streamflow data and the predicted streamflow of S1 and S2 using Web-based Hydrograph Analysis Tool (WHAT). The results showed Nash-Sutcliff efficiency (NSE) and $R^2$ of S2 were a little higher than these of S1 in both streamflow and baseflow prediction results. However, it is important that S2 reflected physical meaning of baseflow recess. Also, recession part of hydrograph in S2 was calibrated better than that of S1 compared to the measured hydrograph.