• Proceedings of the Korea Water Resources Association Conference
• /
• 2012.05a
• /
• pp.944-944
• /
• 2012

Urbanization leads to a change of hydrologic responses because impervious area is increased by urbanization. Decrease of groundwater recharge and increase of overland flow are general hydrologic characteristics caused by urbanization. This can be a source of damages such as increased flooding and reduced groundwater levels. Daily streamflow in Gabcheon watershed, South Korea is simulated by ARCSWAT model, an extension of SWAT2005. After calibration and validation of model, the simulated daily streamflow from 1997 to 2001 are statistically analyzed. The phenomenon that $T_{Qmean}$ is inversly proportional to coefficient of variation for the simulated daily streamflow is demonstrated. Also, hydrologic response was more influenced by weather than land use for high flow. This study also examines the effect of land use change on daily streamflow with spatially and quantitatively different land use maps. The simulated stream flow is tested by Mann-Whitney method. The median between stream flows simulated for 1990 and 2000 land use maps is significantly different, but the simulated streamflow for spatially different land use maps is almost unchanged.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.379-379
• /
• 2017

과거에는 하천 범람으로 인한 홍수피해가 많았으나 최근에는 도시화로 인한 불투수면적의 증가로 홍수도달시간의 단축 및 노면수의 배수불량으로 인한 내수 홍수피해가 많아졌다. 이러한 변화는 도시하천의 홍수예보에 밀접한 관련이 있으며 관련된 분석 모형 및 연계방안 또한 매우 중요하게 되었다. 일반적으로 하천에 대한 유출해석 모형으로 HEC-RAS((Hydrologic Engineering Center-River Analysis System)가 주로 사용되고 있으나 현재와 같이 도심지 하천에서는 내배수의 특성을 고려한 SWMM(Storm Water Management Model)을 사용한다. 또는 이 두모형의 연계를 통해 유출해석을 진행하기도 한다. 최근 HEC-RAS와 SWMM모형이 최신 버전을 공개하였다. HEC-RAS의 경우 2016년 9월 5.0.3버전을 출시하며 1D뿐만 아닌 2D의 모의도 가능하도록 기능을 개선하였으며 SWMM의 경우 2016년 09월 07일 5.1.011버젼이 공개되었다. 본 연구에서는 공개된 최신 모형을 도림천 지역에 적용하여 도림천 지역에 적합한 모형 및 연계 방법을 찾아보려 한다. 이를 통해 최적의 도시홍수예보 시스템을 구성하기 위한 모형 및 연계방안의 조사와 가장 합리적인 도시홍수 시스템의 구성방안을 제시하고자 한다.

• Journal of Korea Water Resources Association
• /
• v.53 no.12
• /
• pp.1193-1201
• /
• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.54 no.2
• /
• pp.137-145
• /
• 2012

본 연구에서는 2005년부터 2006년까지 충청남도 공주시 반포면에 위치한 봉곡천 유역의 경사지 밭을 포함하고 있는 산지하천에서 유출량, 총인, 총질소를 측정하였고 측정된 자료는 SWAT 모형을 통하여 장기간의 배출부하량 산정을 위해 모형의 보정 및 검정자료로 사용하였다. SWAT 모형의 보정 및 검정결과는 유출량은 일별자료를 이용하여 보정 및 검정을 실시하였다. 그 결과 결정계수 ($R^2$)가 0.80~0.83의 값을 보였으며 일별 T-N, T-P 부하량에 대한 보정 및 검정결과는 결정계수 ($R^2$)가 0.62~0.86의 값을 보였다. 모형의 보정 및 검정을 통해 결정된 최적매개변수를 적용하여 1997년부터 2006년까지 관측된 강우자료로 장기간의 유출량, T-N, T-P 배출부하량에 대한 SWAT 모형 시뮬레이션을 수행하였다. 또한 이를 바탕으로 하여 산지와 밭에 대한 원단위를 산정하였으며, 그 결과 산지에 대한 T-N의 원단위는 3.29 $kg/km^2/day$이었고 T-P에 대한 원단위는 0.15 $kg/km^2/day$로 나타났다. 또한 밭에서의 T-N에 대한 원단위는 11.15 $kg/km^2/day$이었고 T-P에 대한 원단위는 0.70 $kg/km^2/day$로 나타났으며 강우의 시간 및 공간적 변화에 따른 유출량을 고려한 산지와 밭에서의 영양염류 배출부하량을 산정하는데 SWAT모형을 적용하는 것이 타당성이 있는 것으로 판단되었다.

• Journal of Korea Water Resources Association
• /
• v.53 no.2
• /
• pp.121-129
• /
• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• KIEAE Journal
• /
• v.13 no.5
• /
• pp.89-96
• /
• 2013

Green roofs can reduce surface water runoff, provide a habitat for wildlife moderate the urban heat island effect, improve building insulation and energy efficiency, improve the air quality, create aesthetic and amenity value, and preserve the roof's waterproofing. Green roofs are mainly divided into three types : intensive, simple-intensive, and extensive. Especially, extensive roof environment is a harsh one for plant growth; limited water availability, wide temperature fluctuations, high exposure to wind and solar radiation create highly stressed environment. This study, aimed at extensive green roof, was carried out on the rooftop of the library at Seoul Women's Univ. from October to November, 2012 and from March to August, 2013. To suggest the most effective vegetation model for biodiversity and heat island mitigation, surface temperatures were monitored by each vegetation model. We found that herbaceous plants of Aster sphathulifolius, Aceriphyllum rossii and Belamcanda chinensis, shrub of Syringa patula 'Miss Kim', Thymus quinquecostatus var. japonica, Sedum species can mixing each other. Among them, the vegetation models including Sedum takesimense, Aster sphathulifolius, Thymus quinquecostatus var. japonica was more effective on the surface temperature mitigation, because the species have the tolerance and high ratio of covering, and also in water. Especially, in the treatment of bark mulching, they helped to increase the temperature of vegetation models. In the case of summer, temperature mitigation of vegetation models were no significant difference among vegetation types. Compared to surface temperature of June, July and August were apparent impact of temperature mitigation, it shows that temperature mitigation are strongly influenced by substrate water content.

• Journal of Korea Water Resources Association
• /
• v.38 no.3 s.152
• /
• pp.213-222
• /
• 2005

This study is a sensitivity analysis of the parameters which affect the simulation results under various design rainfall conditions, using the SWMM model, for three selected basins in urban areas. The sensitivity of the peak flow rate is defined by $S_Q$ (=1.0 - (min. ratio of peak flow rate/max. ratio of peak flow rate)), and the rainfall conditions are classified in terms of design rainfall frequency, duration, and distribution. The simulation results show that in most conditions the parameters - the impermeable area ratio, the sewer slope, and the initial infiltration capacity - have more significant effects on the results than other parameters. As the design rainfall frequency increases, the sensitivity of the sewer slope and sewer roughness increases, while the parameters related with the surface runoff decrease. When the rainfall duration increases, the sensitivities of most parameters of surface runoff and sewer flow decrease. Also, at the 1st quarterly Huff rainfall distribution condition, the impermeable area ratio has high sensitivity, but at the 4th quarterly condition the parameters related with sewer flow show higher sensitivities. These tendencies can be explained by considering the procedure for computing the effective rainfall and kinematic wave on the surface and sewer flow.

• Journal of Environmental Impact Assessment
• /
• v.24 no.1
• /
• pp.16-34
• /
• 2015

Impervious covers(IC) are artificial structures, such as driveways, sidewalks, building's roofs, and parking lots, through which water cannot infiltrate into the soil. IC is an environmental concern because the pavement materials seal the soil surface, decreasing rainwater infiltration and natural groundwater recharge, and consequently disturb the hydrological cycle in a watershed. Increase of IC in a watershed can cause more frequent flooding, higher flood peaks, groundwater drawdown, dry river, and decline of water quality and ecosystem health. There has been an increased public interest in the institutional adoption of LID(Low Impact Development) and GI(Green Infrastructure) techniques to address the adverse impact of IC. The objectives of this study were to construct the modeling site for a samll urban watershed with the Storm Water Management Model(SWMM), and to evaluate the effect of various LID techniques on the control of rainfall runoff processes and non-point pollutant load. The model was calibrated and validated using the field data collected during two flood events on July 17 and August 11, 2009, respectively, and applied to a complex area, where is consist of apartments, school, roads, park, etc. The LID techniques applied to the impervious area were decentralized rainwater management measures such as pervious cover and green roof. The results showed that the increase of perviousness land cover through LID applications decreases the runoff volume and pollutants loading during flood events. In particular, applications of pervious pavement for parking lots and sidewalk, green roof, and their combinations reduced the total volume of runoff by 15~61 % and non-point pollutant loads by TSS 22~72 %, BOD 23~71 %, COD 22~71 %, TN 15~79 %, TP 9~64 % in the study site.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.3
• /
• pp.273-283
• /
• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Journal of Korean Society of Disaster and Security
• /
• v.16 no.1
• /
• pp.13-22
• /
• 2023

The importance of preemptive flood preparation is growing as the importance of preparing for climate change increases due to record heavy rains in the Seoul metropolitan area in August 2022. Although it is responding to flood control through reservoirs and sediment sites, the government is preparing excellent spill reduction measures through a preliminary consultation system for Low Impact Development (LID). In this study, the depth of flooding was simulated when LID technologies were applied to the Sillim 2-drain region in Dorimcheon Stream basin, an urban stream, using XP-SWMM, a two-dimensional model. In addition, the analysis and applicability of the effect of reducing rainfall runoff for the largest rainfall in a day were reviewed, and it was judged to be effective as a method of reducing flooding in urban areas. Although there is a limitation in which the reduction effect is overestimated, it is thought that the LID technologies can be a significant countermeasure as a countermeasure for small-scale flooded areas where some flooding occurs after structural flooding measures are established.