• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1295-1299
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• 2008

Soil erosion is a natural process and has been occurring in most areas in the watershed. However, accelerated soil erosion rates have been causing numerous environmental impacts in recent years. To reduce soil erosion and sediment inflow into the water bodies, site-specific soil erosion best management practices (BMPs) need to be established and implemented. The most commonly used soil erosion model is the Universal Soil Loss Equation (USLE), which have been used in many countries over 30 years. The Sediment Assessment Tool for Effective Erosion Control (SATEEC) ArcView GIS system has been developed and enhanced to estimate the soil erosion and sediment yield from the watershed using the USLE input data. In the last decade, the Soil and Water Assessment Tool (SWAT) model also has been widely used to estimate soil erosion and sediment yield at a watershed scale. The SATEEC system estimates the LS factor using the equation suggested by Moore and Burch, while the SWAT model estimates the LS factor based on the relationship between sub watershed average slope and slope length. Thus the SATEEC and SWAT estimated soil erosion values were compared in this study. The differences in LS factor estimation methods in the SATEEC and SWAT caused significant difference in estimated soil erosion. In this study, the difference was -51.9%(default threshold)$\sim$-54.5%(min. threshold) between SATEEC and non-patched SWAT, and -7.8%(default threshold)$\sim$+3.8%(min. threshold) between SATEEC and patched SWAT estimated soil erosion.

• Economic and Environmental Geology
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• v.29 no.5
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• pp.575-587
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• 1996

The purpose of this study is to develop geostatistical methods for selection of prospective areas of polymetallic nodule deposits in KODOS (Korea Deep Ocean Study) area of the North-East Pacific Ocean. In this study $110{\times}165$ grid system was used, and each node represents the center of an estimated block of $1km{\times}1km$. The ordinary kriging was applied to SeaBeam2000 data in order to evaluate the bathymetry. A structural analysis (variogram) of the bathymetry data was carried out for constructing digital terrain model (DTM) and the maximum slopes of the bathymetry were calculated by DTM data. The above method can be used to solve the problem that is resulted from the lack of theory of a change of support model for the maximum slope of the bathymetry. The ordinary kriging and the indicator kriging were used to evaluate the nodule abundance, and the different two kriging methods were compared to evaluate the accuracy for the estimation of the nodule abundance. It has been shown that indicator kriging was better estimation tool than the ordinary kriging. The overlay map is presented for the selection of potentially minable sites by combining the two indicator maps of the nodule abundance and the maximum slope of bathymetry. This overlay map could be utilized to establish follow-up survey and to investigate the potentially minable sites in the KODOS area.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.1
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• pp.3-12
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• 2008

Soil erosion is a natural process and has been occurring in most areas in the watershed. However, accelerated soil erosion rates have been causing numerous environmental impacts in recent years. To reduce soil erosion and sediment inflow into the water bodies, site-specific soil erosion best management practices(BMPs) need to be established and implemented. The most commonly used soil erosion model is the Universal Soil Loss Equation(USLE), which have been used in many countries over 30 years. The Sediment Assessment Tool for Effective Erosion Control(SATEEC) ArcView GIS system has been developed and enhanced to estimate the soil erosion and sediment yield trom the watershed using the USLE input data. In the last decade, the Soil and Water Assessment Tool(SWAT) model also has been widely used to estimate soil erosion and sediment yield at a watershed scale. The SATEEC system estimates the LS factor using the equation suggested by Moore and Burch, while the SWAT model estimates the LS factor based on the relationship between sub watershed average slope and slope length. Thus the SATEEC and SWAT estimated soil erosion values were compared in this study. The differences in LS factor estimation methods in the SATEEC and SWAT caused significant difference in estimated soil erosion. In this study, the difference was -51.9%(default threshold)${\sim}-54.5%$(min. threshold) between SATEEC and non-patched SWAT, and -7.8%(default threshold)${\sim}+3.8%$(min. threshold) between SATEEC and patched SWAT estimated soil erosion.

• Journal of the Korean GEO-environmental Society
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• v.20 no.2
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• pp.5-18
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• 2019

In this study, it was conducted a broad-area landslide analysis for the entire area of Kyungsangbuk-do Province based on spatially-distributed wetness index and root reinforcement infinity slope stability theory. Specifically, digital map, soil map and forest map were used to extract topological and geological parameters, and to build spatially-distributed database at $10m{\times}10m$ resolution. Infinity flow direction method was used for rain catchment area to produce spatially-distributed wetness index. The safety level that indicates risk of a broad-area landslide was classified into four groups. The result showed that areas with a high estimated risk of a landslide coincided with areas that recently went through an actual landslide, including Bonghwa and Gimcheon, and unstable areas were clustered around mountainous areas. A comparison between the estimation result and the records of actual landslide showed that the analysis model is effective for estimating a risk of a broad-area landslide based on accumulation of reasonable parameters.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.297-303
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• 2014

The effect of solar irradiance has been used to estimate daily maximum temperature, which make it possible to reduce the error inherent to lapse-rate based elevation difference correction in mountainous terrain. Still, recent observations indicated that the effect of solar radiation would need correction for estimation of daily maximum temperature. It was attempted to examine what would cause the variability of solar irradiance effect in determination of daily maximum temperature under natural field conditions and to suggest improved methods for estimation of the temperature distribution over mountainous regions. Temperature at 1500 and the wind speed for 1100 to 1500 were obtained at 10 validation sites with various topographical features including slope and aspect within a mountainous $50km^2$ catchment for 2012-2013. Lapse-rate corrected temperature estimates on clear days were compared with these observations, which would represent the differential irradiance effect among sloped surfaces. Results indicated a negative correlation between the mean wind speed and the estimation error. A simple scheme was derived from relationship between wind speed and estimation error for daily temperature to correct the effect of solar radiation. This scheme was incorporated into an existing model to estimate daily maximum temperature based on the effect of solar radiation. At 10 validation sites on clear days, estimates of 1500 LST temperature with and without the correction scheme were compared. It was found that a substantial improvement was achieved when the correction scheme was applied in terms of bias correction as well as error size reduction at all sites.

• Journal of Wetlands Research
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• v.6 no.3
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• pp.119-126
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• 2004

In recent, the critical rainfall duration concept is widely used but we do not have understandable criteria yet. However, the critical rainfall duration is usually calculated considering concentration time, runoff model using effective rainfall, and unit hydrograph for the estimation of design flood. This study is to derive the regression equations between the critical rainfall duration and hydrologic components such as the basin area, slope, length, CN, and so on. We use a GIS tool which is called the ArcView for the estimation of hydrologic components and the HEC-1 module which is provided in WMS model is used for the runoff computation. As the results, the basin area, basin slope, and basin length had a great influence on the estimations of peak runoff and critical rainfall duration. We also investigated the sensitivities for the peak runoff and critical duration of rainfall from the correlation analysis for the involved components in the runoff estimation.

• Economic and Environmental Geology
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• v.53 no.3
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• pp.245-258
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• 2020

In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.370-379
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• 2015

In recent, the natural disaster like localized heavy rainfall due to the climate change is increasing. Therefore, it is important issue that the precise observation of rainfall and accurate spatial distribution of the rainfall for fast recovery of damaged region. Thus, researches on the use of the radar rainfall data have been performed. But there is a limitation in the estimation of spatial distribution of rainfall using rain gauge. Accordingly, this study uses the Kriging method which is a spatial interpolation method, to measure the rainfall field in Namgang river dam basin. The purpose of this study is to apply KED(Kriging with External Drift) with OK(Ordinary Kriging) and CK(Co-Kriging), generally used in Korea, to estimate rainfall field and compare each method for evaluate the applicability of each method. As a result of the quantitative assessment, the OK method using the raingauge only has 0.978 of correlation coefficient, 0.915 of slope best-fit line, and 0.957 of $R^2$ and shows an excellent result that MAE, RMSE, MSSE, and MRE are the closest to zero. Then KED and CK are in order of their good results. But the quantitative assessment alone has limitations in the evaluation of the methods for the precise estimation of the spatial distribution of rainfall. Thus, it is considered that there is a need to application of more sophisticated methods which can quantify the spatial distribution and this can be used to compare the similarity of rainfall field.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.152-152
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• 2019

This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

• Smart Structures and Systems
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• v.11 no.1
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.