• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.830-840
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• 2011

Climate change has been settled as pending issues to consider water resources and environment all over the world, however, scientific and quantitative assessment methods of climate change have never been standardized. When South Korea headed toward water deficiency nation, the study is not only required analysis of atmospheric or hydrologic factors, but also demanded analysis of correlation with water quality environment factors to gain management policies about climate change. Therefore, this study explored appropriate monthly rainfall elasticity in chosen 41 unit watersheds in Nak-dong river which is the biggest river in Korea and applied monitored discharge data in 2004 to 2009 with monthly rainfall using Thiessen method. Each unit watershed drew elasticity between water temperature and water quality factors such as BOD, COD, SS, T-N, and T-P. Moreover, this study performed non-linear correlation analysis with monitored discharge data. Based on results of analysis, this is first steps of climate change analysis using long-term monitoring to develop basic data by Nak-dong river Environmental Research Center (Ministry of Environment) and to draw quantitative results for reliable forecasting. Secondary, the results considered characteristic of air temperature and rainfall in each unit watershed so that the study has significance its various statistical applications. Finally, this study stands for developing comparable data through "The 4 major river restoration" project by Korea government before and after which cause water quality and water environment changes.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.91-106
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• 2014

This study tries to cluster the 795 standard watersheds of Korea Water Resources Unit Map using multivariate statistical analysis technique. The 30 factors of watershed characteristics related to topography, stream, meteorology, soil, land cover and hydrology were selected for comprehensive analysis. From the factor analysis, 16 representative factors were selected. The significant factors in order were the pedological feature, scale and geological location and meteorological and hydrological features of the watershed. As a next step, the 73 gauged watersheds were selected for cluster analysis. They are scattered properly to the whole country and the discharge data were within a confidential level. Based on the 73 watersheds, the other ungaged watersheds were clustered by applying the 16 factors and calculating Euclidian distances. The clustering results showed that the similarity between standard watersheds within the same river basin were 87%, 69%, 41%, 52%, and 27% for Han, Nakdong, Geum, Seomjin, and Yeongsan river basins respectively.

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.351-360
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• 2014

The allocation of margin of safety (MOS) at a uniform rate to all areas of the unit watershed makes it very difficult to keep the load allotment stable in the area for lack of reduction measures like forest land. This study developed an equation to calculate margin of safety differentially according to the regional characteristics. The equation was formulated on the basis of the regional characteristic factors such as a load contribution factor for land use type and a site conversion factor for the unit watershed. The load contribution factor represents a contribution of loads from a particular land use. The site conversion factor was derived from the site conversion ratio of a unit watershed. Margin of safety for the non-point pollution load in the land use sector decreased by 20~25% in three river basins. The margin of safety in the unit watersheds with low site occupation ratios decreased in high rate, while in the unit watersheds with large urban area decreased in low rate. With the application of the differential margin of safety considering regional characteristics, not only the reduction of pollution loads can become lighter but also it can be easier to develop plans for Total Maximum Daily Loads (TMDLs) even where the reduction measures are not available.

• Proceedings of the Korea Water Resources Association Conference
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• 1989.07a
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• pp.17-30
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• 1989

In this study, more exact runoff phenomina of the watersheds were comprehened and the relationships between geographical factors of the selected watershed and the unit hydrograph characteristic variables representing runoff processes, were also established. Moreover, the estimation of the adequate design flood was presented, which is needed for the design of the hydrologic structures in the ungauged watersheds. And owing to these results, it is considered to be possible to execute the effective flood control projects of the river and the efficient water resources management.

• Water for future
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• v.22 no.4
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• pp.423-433
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• 1989

In this study, more exact runoff phenomina of the watersheds were comprehended and the relationships between geographical factors of the selected watershed and the unit hydrograph characteristic variables representing runoff processes, were also established. Moreover, the estimation of the adequate design flood was presented, which is needed for the design of the hydrologic structures in the ungauged watersheds. And owing to these results, it is considered to be possible to execute the effective flood control projects of the river and the efficient water resources management.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.1-13
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• 2010

For the first time, this study identifies Nash model parameters by GIUH theory based on grid of GIS with heterogeneity of drainage path. Identified parameters have advantages to improve accuracy and usefulness with considering hillslpoe-flow, geomorphological dispersion and easily extracting geomorphological factors by GIS in the watershed. Calculated results by identified parameters compare with observation data for verification of this model. The comparison is well correspondence between observed data and calculated results. And the comparison results of changing trends about lag time and the variance as hillslope and channel characteristic velocities sensitively present changes about hillslope characteristic velocity. Thus this model justifies that estimation of hillslope characteristic velocity demands with the great caution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3726-3734
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• 2012

This study evaluated the behavior of pollutants based on the seasonal change by selecting the branch river's factors that influence the outflow of pollutants in Soyang lake basin. The analysis method was the factor analysis that classified the factors of the drainage area influencing the outflow of pollutants, and evaluated selected representative factors. As a result of the study, SS and T-P factors should be classified as similar factors to the storm water runoff, and the improvement of water must be strived through managing source of pollution at the time of no rain. Second, as the result of the influence from the factors, spring and winter seasons usually exert 36% influence and summer and fall exert over 90% significant influence that the improvement of water through managing source of water seems possible. At last, the prediction about delivery pollution load considering the outflow characteristic of pollutants at the drainage area based on seasonal change by regarding selected factors as independent variables is possible.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.1-11
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• 2021

Recently, in Korea, the risk of meteorological disasters is increasing due to climate change, and the damage caused by rainfall is being emphasized continuously. Although the current weather forecast provides quantitative rainfall, there are several difficulties in predicting the extent of damage. Therefore, in order to understand the impact of damage, the threshold rainfall for each watershed is required. The damage caused by rainfall occurs differently by region, and there are limitations in the analysis considering the characteristic factors of each watershed. In addition, whenever rainfall comes, the analysis of rainfall-runoff through the hydrological model consumes a lot of time and is often analyzed using only simple rainfall data. This study used GIS data and calculated the threshold rainfall from the threshold runoff causing flooding by coupling two hydrologic models. The calculation result was verified by comparing it with the actual case, and it was analyzed that damage occurred in the dangerous area in general. In the future, through this study, it will be possible to prepare for flood risk areas in advance, and it is expected that the accuracy will increase if machine learning analysis methods are added.