• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.97-97
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• 2020

Flooding in urban areas is caused by heavy rains for a short period of time and drains within 1 to 2 hours. It is also characterized by a small flooding area. In addition, flooding is often caused by various and complex causes such as land use, basin slope, pipe, street inlet, drainage pumping station, making it difficult to predict flooding. Therefore, this study analyzes the effect of each basin characteristic on the occurrence of flooding in urban areas by correlating various basin characteristics, whether or not flooding occurred, and rainfall(Limit Rainfall), and intends to use the data for urban flood prediction. As a result of analyzing the relationship between the imperviousness and the urban slope, pipe, threshold rainfall and limit rainfall, the pipe showed a correlation coefficient of 0.32, and the remaining factors showed low correlation. However, the multiple correlation analysis showed the correlation coefficient about 0.81 - 0.96 depending on the combination, indicating that the correlation was relatively high. In the future, I will further analyze various urban characteristics data, such as area by land use, average watershed elevation, river and coastal proximity, and further analyze the relationship between flooding occurrence and urban characteristics. The relationship between the urban characteristics, the occurrence of flooding and the limiting rainfall amount suggested in this study is expected to be used as basic data for the study to predict urban flooding in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.2
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• pp.25-34
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• 2024

The long-term monitoring of the Soyang Lake's water quality, covering 25% of the North Han River watershed, is crucial for effective management of both lake water quality and pollution sources in the broader region. This study utilized continuous monitoring data from the front of the Soyang Dam spanning 2003 to 2022, aiming to analyze trends and provide foundational insights for water quality management. Results revealed a slightly poor grade (IV) for total nitrogen (T-N) in both surface and mid-depth layers, indicating a need for concentrated T-N management. Trend analyses using the Mann-Kendall test and Sen's Slope depicted a decreasing trend in total phosphorus (T-P) for both layers, attributed to non-point source pollution reduction projects initiated after the Soyang Lake's designation as a pollution control area in 2007. The LOWESS analysis showed a T-P increase until 2006, followed by a decrease, influenced by the impact of Typhoon Ewiniar in that year. This 20-year overview establishes a comprehensive understanding of the Soyang Lake's water quality and trends, allowing for a seasonal and periodical analysis of water quality changes. The findings underscore the importance of continued monitoring and management strategies to address evolving water quality issues in the Soyang Lake over time.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.863-874
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• 2018

The purpose of this study is to evaluate the future climate change impact on stream aquatic ecology health of Han River watershed ($34,148km^2$) using SWAT (Soil and Water Assessment Tool) and random forest. The 8 years (2008~2015) spring (April to June) Aquatic ecology Health Indices (AHI) such as Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI) and Fish Assessment Index (FAI) scored (0~100) and graded (A~E) by NIER (National Institute of Environmental Research) were used. The 8 years NIER indices with the water quality (T-N, $NH_4$, $NO_3$, T-P, $PO_4$) showed that the deviation of AHI score is large when the concentration of water quality is low, and AHI score had negative correlation when the concentration is high. By using random forest, one of the Machine Learning techniques for classification analysis, the classification results for the 3 indices grade showed that all of precision, recall, and f1-score were above 0.81. The future SWAT hydrology and water quality results under HadGEM3-RA RCP 4.5 and 8.5 scenarios of Korea Meteorological Administration (KMA) showed that the future nitrogen-related water quality in watershed average increased up to 43.2% by the baseflow increase effect and the phosphorus-related water quality decreased up to 18.9% by the surface runoff decrease effect. The future FAI and BMI showed a little better Index grade while the future TDI showed a little worse index grade. We can infer that the future TDI is more sensitive to nitrogen-related water quality and the future FAI and BMI are responded to phosphorus-related water quality.

• Korean Journal of Ecology and Environment
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• v.34 no.1 s.93
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• pp.30-44
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• 2001

In this study limnological characteristics of Lake Juam was surveyed from June 1993 to May 1994 in order to provides important information regarding water resources. Secchi disc transparency, epilimnetic chlorophyll a (chi-a), total nitrogen (TN), total phosphorus (TP) concentration and primary productivity were in the range of $2.0{\sim}4.5\;m$, $0.9{\sim}13.6\;mgChl/m^3$, 0.78$\{sim}$2.32 mgN/l, $11{\sim}56\;mgP/m^3$, $270{\sim}2.160\;mgCm^{-2}\;day^{-1}$, respectively. On the basis of TP, Chl-a and Secchi disc depth, the trophic state of Lake Juam can be classied as mesotrophic lake. The phosphorus inputs from non-point sources are concentrated in heavy rain episodes during the monsoon season. As a result, phosphorus concentration are higher in summer than in winter. TP loading from the watershed were estimated to be $0.9\;gPm^{-2}yr^{-1}$, which correspond to a boundary of the critical loading ($1.0\;gPm^{-2}yr^{-1}$) for eutrophication. From the results of the algal assay, both phosphous and nitrogen act as limiting nutrients in algal growth. The seasonal succession of phytoplankton community structure in Lake Juam was similar to that observed in other temperate lakes. Diatoms (Asterionella formosa and Aulacoseira granulate var. angustissima)fujacofeira BraHuJafa uar. aHgusHrsiaia) weredominant in spring and winter, cyanobacteria) were dominant in warm season. The organic carbon, nitrogen and phosphorus content of lake sediment were $9.5{\sim}14.0\;mgC/g$, $1.01{\sim}1.82\;mgN/g$ and $0.51{\sim}0.65\;mgP/g$, respectively. The allochthonous organic carbon loading from the watershed and autochthonous organic carbon loading by primary production of phytoplankton were determined to be 1,122 tC/yr and 6,718 tC/yr, respectively. To prevent eutrophication of Lake Juam, nutrient management of watershed should be focus on reduction of fertilizer application, proper treatment of manure, and conservation of topsoil as well as point source.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.4
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• pp.398-404
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• 1999

Factor analysis technique was employed to screen the principal indicators influencing soil and water qualities in the intensively cultivated areas of the Han River Basin. Soil chemical parameters were analyzed for the soil samples collected at intensive farming area in Pyungchang-Gun, and water quality monitoring data were obtained from the agricultural small catchments of Han River Basin during 1996 and 1997. Among the $11{\times}11$ cross correlation matrix, 29 correlations were significant out of 55 soil quality indicator pairs. The overall Kaiser's measure of sampling adequacy(KMS) value was acceptable with 0.60. Most indicators except iron were acceptable. Among soil indicators, the first factors showing high factor loadings were pH, Ca and Mg. The factor loading was the highest for Ca. The second factor could be characterized as phosphate and micronutrient. The third factor was organic matter and EC, and the fourth factor was potassium and Fe. Out of 190 water quality indicators, 86 correlations were significant. Overall KMS value was 0.74, but the KMS values for pH, TSS, Cd, Cu and Fe were lower than 50. The first factor of EC accounts 27.1 percents of the total variance, and showed high factor loadings with Na, Ca, $SO_4$, Mg, K, Cl, $NO_3$, and T-N. The second factor showed high loadings with Zn, Fe, Mn and Cd. The third to seventh factors could be characterized as $PO_4$, TSS, inorganic nitrogen, pH and T-P, and Cu factors, respectively. The factor score for EC was the highest in Kuri, followed by Chunchon, Dunnae and Daegwanryng. The factor score for heavy metals were the highest in the Daegwanryng. The results demonstrated that the factor analysis could be useful to select the most principal factor influencing soil and water qualities in the agricultural watershed.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.203-222
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• 2011

The characteristics of flood damages have been increasingly strengthened and take the form of unpredictable and unusual weather phenomena caused by climate change and climate anomalies. To prevent inundation damage caused by breach of hydraulic structure such as dam or levee, and trouble of drainage of inner basin, the prediction necessity of flood inundation area, flood risk analysis, and drawing flood risk maps have been on the rise, and the national flood risk maps have been produced. In this study, the quantitative flood vulnerability analysis was performed, which represents population living within flood-affected areas, types of economic activities, facilities affected by flood, in order to extend flood risk mapping from simple hazard concept into risk based idea. By applying it to Nakdong River basin, the flood vulnerability indices were estimated to draw flood risk maps subdivided into administrative districts. The result of this study can be applied to establish the disaster prevention measures and priority decision of disaster prevention project.

• Journal of Wetlands Research
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• v.11 no.3
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• pp.161-169
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• 2009

Rainfall-runoff procedures of urban area are more complicated than agricultural procedures. Extension and development of town leads to shift of the basin characteristics and it makes more difficult to use runoff models. In this study, the changes of hydrologic circumstances and the shape of hydrograph due to the urbanization in Cho-kyung river basin has been assessed which is the representative urban stream in Jeonju city. The urbanization can be classified as four typical year. The natural basin period(1924) that is before the urban development, the period of construction of Chonbuk National University campus (1963), the period of construction of residential area(1986), and urbanization process has been finally completed in 1995. The rainfall-runoff analysis has been carried out by Storm Water Management Model(SWMM) under condition of the basin characteristics and impervious area of each period. It was found that hydrologic characteristics such as river length, roughness coefficient, and coefficient of surface storage has been decreased. According to the land use change, the pervious area was decreased from 97.7% to 42%, while the impervious area was increased from 0.6% to 34%. The time of concentration was shorten from 90 minutes to 37 minutes. Along with decreasing the time of concentration, the peak discharge was increased from $4.37m^3/s$ to $111.13m^3/s$, and the runoff rate was also increased from 0.8% to 68%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.169-177
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• 2010

Recently due to the typhoon and extreme rainfall induced by abnormal weather and climate change, the probability of severe damage to human life and property is rapidly increasing. Thus it is necessary to create adequate and reliable flood risk map in preparation for those natural disasters. The study area is Seo-gu in Daegu which is located near Geumho river, one of the tributaries of Nakdong river. Inundation depth and velocity at each time were calculated by applying FLUMEN model to the target area of interest, Seo-gu in Daegu. And the research of creating flood risk map was conducted according to the Downstream Hazard Classification Guidelines of USBR. The 2-dimensional inundation analysis for channels and protected lowland with FLUMEN model was carried out with the basic assumption that there's no levee failure against 100 year precipatation and inflow comes only through the overflowing to the protected lowland. The occurrence of overflowing was identified at the levee of Bisan-dong located in Geumho watershed. The level of risk was displayed for house/building residents, drivers and pedestrians using information about depth and velocity of each node computed from the inundation analysis. Once inundation depth map and flood risk map for each region is created with this research method, emergency action guidelines for residents can be systemized and it would be very useful in establishing specified emergency evacuation plans in case of levee failure and overflowing resulting from a flood.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.471-479
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• 2024

Flood damage is becoming more serious due to the heavy rainfall caused by climate change. Physically based hydrological models have been utilized to predict stream water level variability and provide flood forecasting. Recently, hydrological simulations using machine learning and deep learning algorithms based on nonlinear relationships between hydrological data have been getting attention. In this study, the Long Short-Term Memory (LSTM) algorithm is used to predict the water level of the Seomjin River watershed. In addition, Climate Prediction Center morphing method (CMORPH)-based gridded precipitation data is applied as input data for the algorithm to overcome for the limitations of ground data. The water level prediction results of the LSTM algorithm coupling with the CMORPH data showed that the mean CC was 0.98, RMSE was 0.07 m, and NSE was 0.97. It is expected that deep learning and remote data can be used together to overcome for the shortcomings of ground observation data and to obtain reliable prediction results.