• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 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 The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.1-6
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• 2012

The objective of this study is to analyze the flood inundation in a low-lying rural area. The study watershed selected for this study includes the Il-Pae and Ahn-Gok watersheds. It is located in the Namyangju, Korea and encompasses $3.64km^2$. A major flood event that occurred in July 2011 was chosen as the case for the flood inundation analysis. The Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) and River Analysis System (HEC-RAS) were used to simulate flood runoff and water surface elevation at each cross-section, respectively. The watershed topographic, soil, and land use data were processed using the GIS (Geographic Information System) tool for the models. The contribution to the total flood volume was estimated based on the results simulated by HEC-HMS and HEC-RAS. The results showed that the overflow discharge from the Il-Pae stream constituted 80% of the total flood volume. The contributions of rainfall falling directly on the inundation area and overflow discharge from the Ahn-Gok stream were 15 % and 5 %, respectively. The simulation results in different levee scenarios for the Ahn-Gok stream were also compared. The results indicated that the levee could reduce the flood volume a little bit.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.738-743
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• 2008

최근 기상이변으로 인한 돌발홍수의 빈번한 발생으로 인해 신속하고 정량적인 강우예측의 필요성이 대두되고 있으며 강우의 거동을 실시간으로 관측하여 예측이 가능한 강우레이더의 활용성이 높아지고 있다. 또한, 1Km 해상도의 격자형으로 제공되는 강우레이더를 효과적으로 활용하기 위해 격자단위의 분석이 가능한 분포형 수문모형의 활용이 증가하고 있다. 본 연구를 위한 선행연구로 배영혜 등(2007)은 레이더 강우와 물리적 기반의 분포형 모형인 $Vflo^{TM}$을 이용하여 임진강 유역에 대한 강우-유출 모의를 실시하였으며 분포형 모형의 입력 자료로 활용된 임진강 유역의 공간자료는 임진강 유역조사 성과 및 GIS/RS를 자료를 이용하여 구축하였다. 배영혜 등(2007)이 모의한 임진강 유역의 홍수 유출 모의 결과 모의치와 관측치 사이의 첨두값은 일치하나 지체 시간의 차이가 발생하는 것으로 나타났다. 이러한 오차의 원인을 파악하기 위해 북한의 하천과 연결되지 않은 임진강 영중지점을 대상으로 홍수 유출 모의를 실시한 결과 지상 강우계를 이용한 레이더 강우의 보정 유무보다는 GIS 수문매개변수의 불확실성이 오차에 큰 영향을 주는 것으로 나타났으며 특히 토양분류 체계가 상이하고 현시성이 결여된 토양도의 활용이 수리전도도를 비롯한 토양 매개변수에 불확실성을 초래하여 첨두 유량과 지체시간 등에 영향을 준 것으로 파악되었다. 본 연구에서는 유역면적의 약 2/3가 미계측 지역인 임진강 유역의 지리적 특성과 현지조사가 필수적인 토양도의 재구축이 현실적으로 어렵다는 점을 고려하여 상대적으로 단순한 가 분포형(Quasi-distributed) 수문 모형인 ModClark 모형을 이용하여 2006년 7월 사상에 대하여 홍수 유출 모의를 실시하였으며 그 결과를 선행연구를 통해 모의한 $Vflo^{TM}$ 모형의 유출 모의 결과와 비교하였다.

• Journal of Korean Society on Water Environment
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• v.36 no.4
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• pp.300-313
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• 2020

The Bayesian approach can be used to estimate hydrologic model parameters from the prior expert knowledge about the parameter values and the observed data. The purpose of this study was to compare the performance of the two Bayesian methods, the Metropolis-Hastings (MH) algorithm and the Generalized Likelihood Uncertainty Estimation (GLUE) method. These two methods were applied to the TANK model, a hydrological model comprising 13 parameters, to examine the uncertainty of the parameters of the model. The TANK model comprises a combination of multiple reservoir-type virtual vessels with orifice-type outlets and implements a common major hydrological process using the runoff calculations that convert the rainfall to the flow. As a result of the application to the Nam River A watershed, the two Bayesian methods yielded similar flow simulation results even though the parameter estimates obtained by the two methods were of somewhat different values. Both methods ensure the model's prediction accuracy even when the observed flow data available for parameter estimation is limited. However, the prediction accuracy of the model using the MH algorithm yielded slightly better results than that of the GLUE method. The flow duration curve calculated using the limited observed flow data showed that the marginal reliability is secured from the perspective of practical application.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.405-422
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• 2020

Land use change by urbanization has significantly affected the hydrological process including the runoff characteristics. Due to this situation, it has been becoming more complicated to manage non-point source pollutions caused by rainfall. In order to effectively control non-point sources, it is necessary to identify the reduction efficiency of the various management method based on land use characteristics. Thus, the purpose of this study is to analyze the reduction efficiency of non-point source pollution management practices targeting three different watersheds with the different land use characteristics using the Soil and Water Assessment Tool (SWAT). To do this, the vulnerable subwatersheds to non-point source pollution occurrence within each watershed were selected based on the streamflow and water quality simulation results. Then, considering the land use, low impact development (LID) or best management practices (BMPs) were applied to the selected subwatersheds and the efficiency of each management was analyzed. As a result of analysis of the non-point source pollution reduction efficiency, when LID was applied to urban areas, the average reduction efficiencies of SS, NO₃-N, and TP were 5.92%, 4.62%, and 10.35%, respectively. When BMPs were applied to rural areas, the average reduction efficiencies of SS, TN and TP were 35.45%, 4.37%, and 10.16%, respectively. The results of this study can be used as a reference for determining appropriate management methods for non-point source pollution in urban, rural, and complex watersheds.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.1037-1049
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• 2015

The most of natural disasters that occur in North Korea are flood, typhoon and damage from heavy rain. The damage caused by those disasters since the mid-1990s is aggravating North Korea's economic difficulties every year. By recognizing the seriousness of the damages from the floods, the North Korean government has carried out the river maintenance, farmland restoration, land readjustment and afforestation projects since the last-1990s, but it has failed preventing the damages. In order to estimate the degree of flood risk regarding damage from chronic floods that occur inveterately in North Korea, this research conducted an additional simulation for rainfall-runoff analysis to reflect the characteristics of the ungauged area that make foreign countries hard to obtain the hydrological data and do not open the topographical data to public. In addition, this research estimates the degree of flood risk by selecting the factors of the hazard, exposure and vulnerability by following the standards of the Intergovernmental Panel on Climate Change (IPCC).

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1211-1218
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• 2008

This study is for design of the detention system distributed in a watershed by the Multi-Objective Genetic Algorithms(MOGAs). A new model is developed to determine optimal size and location of detention. The developed model has two primary interfaced components such as a rainfall runoff model to simulate water surface elevation(or flowrate) and MOGAs to get the optimal solution. The objective functions used in this model depend on the peak flow and storage of detention. With various constraints such as structural limitations, capacities of storage and operational targets. The developed model is applied at Gwanyang basin within Anyang watershed. The simulation results show the maximum outlet reduction is occurred at detention facilities located in upper reach of watershed in the peak discharge rates. It is also reviewed the simultaneous construction of an off-line detention and an on-line detention. The methodologies obtained from this study will be used to control the flood discharges and to reduce flood damage in urbanized watershed.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.365-365
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• 2012

이수 및 치수를 위한 수공구조물 설계 및 하천기본계획 수립의 요점은 설계홍수량의 산정에 있으며, 통계적으로 유의성을 가지는 설계홍수량을 산정하기 위해서는 일반적으로 30년 이상 관측된 홍수자료가 요구된다. 우리나라의 경우 대부분의 유역이 미계측 유역이거나 관측년수가 비교적 작은 경우가 많으므로, 상대적으로 자료 연한이 긴 강우자료를 빈도분석한 후 이를 강우-유출 모형에 입력하여 확률홍수량을 추정하는 간접적인 방법이 주로 이용되며 사용된 강우의 빈도가 홍수의 빈도와 동일하다는 가정을 기본으로 한다. 그러나 동일한 강우량이 발생하더라도 강우의 강도, 지속시간, 유역의 선행함수조건 등과 같은 유역 특성에 따라 유출의 특성은 현저히 다르게 나타나며 결국 이러한 특성은 입력자료, 강우-유출 모형, 기후변동성 등과 같은 불확실성 요소로 인식될 수 있다. 따라서 본 연구에서는 이러한 불확실성을 고려할 수 있는 강우-유출 모의기법을 개발하여 이를 통해 홍수빈도곡선을 유도할 수 있는 방법론을 제시하고자 한다. 불확실성 분석을 위해 기존 HEC-1 강우-유출 모형에서 Bayesian MCMC 기법을 적용하여 매개변수들의 사후분포를 추정하여 매개변수들의 최적화 및 불확실성 분석을 수행하였다. 마지막으로 기후변화 영향을 통합한 홍수빈도곡선을 유도하기 위해서 극치강수를 모의하는 것이 필요하며, 본 연구에서는 극치값 재현에 있어서 우수한 성능을 발휘하는 Kernel-Pareto Piecewise분포 기반의 강우모의발생 기법을 적용하여 HEC-1모형과 연동되도록 모형을 개발하였다. 본 연구에서 제안하는 방법론은 기존 홍수빈도곡선 유도 방법에서 불확실성을 분석하기 위해 모든 변수들을 독립사상으로 간주하고 Monte Carlo Simulation을 수행함으로서 매개변수들간의 상호연관성, 상관성, 조건부 확률들을 고려할 수 없었던 점을 Bayesian 모형을 통해 매개변수들간의 조건부 확률을 고려한 매개변수의 사후분포 도출을 가능하게 하여 보다 현실적인 강우-유출 관계 도출이 가능하고 불확실성 구간이 자연적으로 도출됨으로서 향후, 신뢰성 있는 수자원 계획수립에 유용한 자료로 활용이 가능할 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.547-558
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• 2013

Improved methodology of Synthetic Unit Hydrograph (SUH) utilized generally in hydrologic design work was suggested. In this study, regression analysis between peak hydrological data and geospatial data was applied to estimate specific peak flow and peak time for determining shape of SUH. Regression formulas for specific peak flow with respect to shape factors show higher coefficient of determination (0.73~0.81) than the ones with geospatial components only (0.52~0.69). The areal limitation of unit hydrograph application is regarded as 500~700 $km^2$. The validation through rainfall-runoff simulation shows encouraging results that relative error is 1.7~29.0%(Avg. 11.6%) for the case of using SUH developed in this study and 35.0~ 64.9% (Avg. 46.7%) for the SUH in the previous study except for the extraordinary cases.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.231-231
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• 2015

Rapid development in the upper reaches of the Mekong River, in the form of construction of large hydropower dams and reservoirs, large irrigation schemes, and rapid urban development, is putting water resources under stress. Many scientific reports have pointed out that cascade dams along the Mekong River lead to serious problems: not only hydrologically but also a decline of agricultural productivity due to a decrease of sediment supply in the Mekong Delta and a change of fish amount due to drastic change of the water environment. Cambodia and Vietnam, located in the lowest Mekong basin, are gravely affected by radical changes of hydrologic regime due to Mekong River developments. In particular, the Tonle Sap Lake in Cambodia is very sensitive to the flood cycle and flow variation of the Mekong River as well as inflow water quality from the Mekong River. More than 50% of Cambodian GDP depends on the primary industries such as agriculture, fishing, and forestry, and the Tonle Sap Lake plays an important role to support the national economy in Cambodia. In addition, Cambodian people usually take nourishment from the fish of Tonle Sap Lake. This research aims to assess the impacts of the Mekong river flow alternation on the hydrologic regime of the Mekong River - Tonle Sap Lake. We carried out rainfall-runoff-inundation simulation using CAESER-LISFLOOD for integrated water resource management in the Tonle Sap Basin and then analyze flood inundation variation of the Tonle Sap Lake due to the scenarios. Furthermore, the simulated inundation maps were compared to MODIS satellite images for model verification and hydrologic prediction.