• Water Engineering Research
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• v.7 no.1
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• pp.9-20
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• 2006

The watersheds are functional geographical areas that integrate a variety of environmental and ecological processes and human impacts on landscapes. Geographical assessments using GIS recognize the relationship between interdependence of resources and ecological/environmental components in watersheds. They are useful methodology for viable long term natural resource management. This paper performs through the using hydrological analyses, landscape ecological analyses, remote sensing, and GIS. Indicators are items or measures that represent key components of the small watersheds, and they are developed to be evaluated. Some indicators are described that they represent watershed condition and trend as well as focus on physical, biological and chemical properties of small watershed. Also, ecological functions such as stability, resilience, and sensitivity are inferred from them. The model implemented in GIS allows to reflect the ecological and hydrological functioning of watershed. Methodology from image analysis, landscape ecological analysis, spatial interpolation, and numerical process modeling are integrated within GIS to provide assessment for eco-logical/environmental condition. Results are described from the small watershed of Gwynns Falls in Baltimore County and Baltimore City, Maryland, an area of about 66.5 square miles. The small watershed within Gwynns Falls watershed are subject to a number of land-use. But it is predominantly urban, with significantly lesser amounts of forest and agriculture. The increasing urbanization is ass-coiated with ecological/environmental impacts and citizen conflicts.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.141-141
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• 2021

This study proposed an equation for Rainfall Threshold for Flood Warning (RTFW) for urban areas based on computer simulations. First, a coupled 1D-2D dual-drainage model was developed for nine watersheds in Seoul, Korea. Next, the model simulation was repeated for a total of 540 combinations of the synthetic rainfall events and watershed imperviousness (9 watersheds × 4 NRCS Curve Number (CN) values × 15 rainfall events). Then, the results of the 101 simulations with the critical flooded depth (0.25m-0.35m) were used to develop the equation that relates the value of RTFW to the rainfall event temporal variability (represented as coefficient of variation) and the watershed Curve Number. The results suggest that 1) the rainfall with greater temporal variability causes critical floods with less amount of total rainfall; and that 2) the greater imperviousness requires less rainfall to have critical floods. For validation, the proposed equation was applied for the flood warning system with two storm events occurred in 2010 and 2011 over 239 watersheds in Seoul. The results of the application showed high performance of the warning system in issuing the flood warning, with the hit, false and missed alarm rates at 68%, 32% and 7.4% respectively for the 2010 event and 49%, 51% and 10.7% for the event in 2011.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.658-659
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• 2015

GCM and scenario uncertainties are first investigated for 5 major watersheds (Han River, Paldang dam, Namhan River, Bukhan River and Imjin River watersheds). As a result of this study, it is found that CCSM3-based annual precipitation increases linearly with respect to the 10-year moving average values while CSIRO-based precipitation does not show much of trend. The results from annual DJF mean precipitation show a similar trend with respect to their 10-year moving average values. Both CCSM3- and CSIRO-based annual JJA mean precipitation do not show much of trend toward 21^st century. In general, CCSM3-based precipitation values are slightly higher than CSIRO-based values with respect to their annual and annual JJA mean precipitation values, but CSIRO-based annual DJF mean precipitation values are slightly higher than CCSM3-based values. In case of mean air temperature between CCSM3 and CSIRO during 21^st century, all of results show a clear trend in warming with the passage of time for 5 watersheds. However the upward trends from CCSM3-based values slow down toward end of 21^stcentury while CSRIO-based values increases almost linearly.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1183-1195
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• 2023

In this study, we collected and analyzed domestic and international studies related to watersheds in the forest sector. Keyword co-occurrence analysis was conducted using the VOSviewer program to identify the research areas of domestic and international studies and the network structure to compare research trends. As a result, the number of research articles in international watershed-related studies showed an overall increasing trend, and the research areas were diverse and located close to each other, indicating that many convergence studies were conducted. On the other hand, the number of papers in domestic watershed-related studies seems to have stagnated overall from the past to the present, and the research areas are mainly focused on forest disasters and hydrology, with limited interdisciplinary convergence studies. In addition, in both domestic and international studies, watersheds are currently mentioned as research sites rather than management or analysis units in the forest sector. It is important to actively promote interdisciplinary research in Korea to provide a scientific and balanced basis for watershed-level forest management planning.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.801-806
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• 2015

The incidence of flood damage by global climate change has increased recently. Because of the increased frequency of flooding in Korea, the technology of flood prediction and prevalence has developed mainly for large river watersheds. On the other hand, there is a limit on predicting flooding through the most present flood forecasting systems because local floods in small watersheds rise quite quickly with little or no advance warning. Therefore, this study estimated the flood warning rainfall using a flood forecasting model at the two alarm trigger points in the Suamcheon basin, which is an urban basin with backwater effects. The flood warning rainfall was estimated to be 25.4mm/120min ~ 78.8mm/120min for the low water alarm, and 68.5mm/120min ~ 140.7mm/120min for the high water alarm. The frequency of the flood warning rainfall is 3-years for the low water alarm, and 80-years for the high water alarm. The results of this analysis are expected to provide a basic database in forecasting local floods in urban watersheds. Nevertheless, more tests and implementations using a large number of watersheds will be needed for a practical flood warning or alert system in the future.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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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.

• Korean Journal of Environmental Agriculture
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• v.20 no.3
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• pp.192-200
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• 2001

The event-based agricultural non-point source(AGNPS) pollution model was applied to estimate the loads of nitrogen and phosphorus in a stream draining small agricultural watersheds. Calibration and verification of the model were performed using observed data collected from rainfall events in the Imgo watersheds during 1997-1998. Parameter calibrations were made for the runoff curve number. The peak flow volumes in the watersheds were well reproduced by the modified model. Average deviation between observed and simulated values was 10%, and this match was confirmed by the coefficient of efficiency value of 0.97. The deviations tended to increase as the peak flows increased. The simulated total N concentrations in the stream water were fairly close to the measured values, and the coefficient of efficiency in the estimation was 0.93. However, there were relatively large variations between calculated and observed values of total P concentration, and the coefficient of efficiency in the estimation was 0.74. Any inaccuracies that arise in estimating runoff flow and nutrient loading can not be explained exactly and further adjustment and refinements may be needed for application of AGNPS in agricultural watersheds. With this restrictions in mind, it can be concluded that AGNPS can provide realistic estimates of nonpoint source nutrient yields.

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.691-703
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• 2003

In this paper, a new and integrated approach easily used to calculate the pollutant loads from agricultural watersheds is suggested. Basic concepts of this empirical tool are based on the hypotheses that variations in event mean concentrations(EMCs) of the pollutants from a given agricultural watershed during rainstorms are only due to the rainfall pattern. This assumption would be feasible to agricultural watersheds whose land uses does not change during the cultivation period overlapped by rainy season and also in which point-sources of the pollutants are rare. Therefore, if EMC data sets through extensive sampling from various rural areas are available, it is possible to establish relationships between EMCs, shapes and land uses of the watersheds, and rainfall events. For this purpose, fifty one sets of EMC values were obtained from nine different watersheds, and those data were used to develop predictive tools for the EMCs of 55, COD, TN and TP in rainfall runoff. The results of the statistical tests for those formulas show that they are not only fairly good in predicting actual EMC values of some parameters, but also useful in terms of calculating pollutant loads on any time-spans such as the day of rainfall event or weekly, monthly, and yearly. Their applicability was briefly demonstrated and discussed. Also, the unit loads calculated from EMCs based on different land uses and real rainfall data over one of the watershed used for this study. were provided, and they are compared with other well-known unit loads.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.769-777
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• 2021

This study investigated the change of the achievement rate of the target water quality conditioned on the occurrence of severe drought, to assess the effects of meteorological drought on the water quality management in the Nakdong River basin. Using three drought indices with difference time scales such as 30-, 60-, 90-day, i.e., SPI30, SPI60, SPI90, and three water quality indicators such as biochemical oxygen demand (BOD), total organic carbon (TOC), and total phosphorus (T-P), we first analyzed the relationship between severe drought occurrence water quality change in mid-sized watersheds, and identified the watersheds in which water quality was highly affected by severe drought. The Bayesian network models were constructed for the watersheds to probabilistically assess the relationship between severe drought and water quality management. Among 22 mid-sized watersheds in the Nakdong River basin, four watersheds, such as #2005, #2018, #2021, and #2022, had high environmental vulnerability to severe drought. In addition, severe drought affected spring and fall water quality in the watershed #2021, summer water quality in the #2005, and winter water quality in the #2022. The causal relationship between drought and water quality management is usufaul in proactive drought management.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.2
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• pp.125-133
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• 1984

To obtain the basic date for the improvement of cultural and managemental problems caused by soil characteristics and soil productivity in rice cultivation of Honam area, morphological characteristics of rice soils were investigated in Mangeng-Dongjin and Yeongsan Water-sheds, and compaired differences between two major Watersheds. The results obtained are summarized as follows: 1. According to U.S.D.A. Soil Taxonomy Classification System, eight great groups are distributed in rice soils of two major Watersheds. More than 50% of rice paddy soils are classified as Haplaquepts. 2. Two Watersheds are quite different in soil parent materials. In Mangeong-Dongjin Watershed, most soils (55.1%) are derived from fluvic-marine deposits. Remainders are derived from local alluvium (24.7%) and alluvium (14.2%). But in Yeongsan Watershed, the order is local alluvium>alluvium>fluvio-marine deposits. 3. Rice soils occur mostly in coastal and inland flat-site with the slope of less than 2% (57.8%) in Mangeong-Dongjin Watersheds. However, in Yeongsan Watershed, flat-site and low undulating terrace are mostly distributed (52.9%). 4. About 81.9, 61.4 and 53.3% of rice soils are classified as fine textured in Yeongsan, Dongjin, and Mangeong Watersheds, respectively. 5. More normal paddy soils and less sandy paddy soils are distributed in Yeongsan Watershed. The results indicate that more rice soils are classified as productivity classes of I and II in Yeongsan Watershed than in Mangeong-Dongjin Watersheds.