• Journal of Korea Water Resources Association
• /
• v.44 no.11
• /
• pp.875-887
• /
• 2011

The objective of this study is to develop and evaluate a Korean threshold runoff computation method. The selected study area is the Han-River basin and the stream channels in the study area are divided into 3 parts; natural channel and artificial manmade channel for small mountainous catchments, and main channel for master stream. The threshold runoff criteria for small streams is decided to 0.5 m water level increase from the channel bottom, which is the level that mountain climbers and campers successfully escape from natural flood damage. Threshold runoff values in natural channel of small mountainous area are computed by the results from the regional regression analysis between parameters of basin and stream channel, while those in artificial channel of small mountainous area are obtained from the data of basin and channel characteristics parameter. On the other hand, the threshold runoff values for master channel are used the warning flood level that is useful information for escaping guideline for riverside users. For verification of the threshold runoff computation method proposed in this study, three flash flood cases are selected and compared with observed values, which is obtained from SCS effective rainfall computation. The 1, 3, 6-hour effective rainfall values are greater than the corresponding threshold runoff values represents that the proposed computation results are reasonable.

• Proceedings of the Korea Water Resources Association Conference
• /
• 1995.05a
• /
• pp.260-265
• /
• 1995

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.4B
• /
• pp.221-232
• /
• 2012

In this study, the model enhancing the safety of reservoirs and reducing the downstream flood damage by reservoirs system operation during abnormal flood was developed. Linear programming was used for the optimal reservoirs system operation during an abnormal flood and fuzzy inference system was introduced to solve the uncertainty problem which is included in hydrological factors like inflow, water level and inflow variation of reservoir operation. The linear programming model determined the optimal reservoir system operation rules and could be used in situation where water demands varies rapidly during the abnormal flood events using fuzzy control technique. In this study, the optimal reservoirs system operation for Andong and Imha reservoirs located in the upper basin of Nakdong river was performed in order that the design flood discharge at Andong city would not be exceeded for the design flood of 100 year and PMF(Probable Maximum Flood). And the model that determines the release according to the downstream flow discharge, the reservoir storage, the inflow and the inflow variation of each reservoir was developed using the optimal system operation result and fuzzy control technique. The developed model consisted of 224 fuzzy rules according to the conditions of Andong reservoir, Imha reservoir and Andong city. And the release from each reservoir could be determined when the current data are used as input data through the developed GUI.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.10 no.6
• /
• pp.155-163
• /
• 2010

The past researches on flood inundation simulation mainly focused on development of numerical models based on unstructured mesh networks to improve model performances. However, despite the accurate simulation results, such models are not suitable for real-time flood inundation forecasting due to a huge computational burden in terms of geographic data processing. In addition, even though various types of vector and raster data are available to be compatible with flood inundation models for post-processes such as flood hazard mapping and flood inundation risk analysis, the unstructured mesh-based models are not effective to fully use such information due to data incommensurability. Therefore, this study aims to develop a raster-based two-dimensional inundation model; it guarantees computational efficiency because of direct application of DEM for flood inundation modeling and also has a good compatibility with various types of raster data, compared to a commercial model such as FLUMEN. We applied the model to simulate the BaekSan levee break in the Nam river during a flood period from August 10 to 13, 2002. The simulation results showed a good agreement with the field-surveyed inundation area and were also very similar with results from the FLUMEN. Moreover, the model provided physically-acceptable velocity vectors with respect to inundating and returning flows due to the difference of water level between channel and lowland.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.2
• /
• pp.36-52
• /
• 2020

This study performed 2-D(two-dimensional) hydrodynamic analysis using EFDC in the Nakdong River. For the simulation of the flood season and non-flood season, the measured data including water level, weir outflow and tributary inflow were used, and the accuracy and applicability of the model were verified by comparing the measured water level and computed one. In addition, statistical quantitative assessment of the model performance was performed by estimating PBIAS, RSR, and RMSE for the computed water level. Then, the average velocity for each section between weirs was calculated by applying constant discharge conditions, and it was compared and verified with the measured velocity by Hydrological Survey Center. In this study, a simple method for estimating the arrival time was proposed, and it is expected that it will be practically applicable in field practices such as flood forecasting and warning.

• Journal of Korea Water Resources Association
• /
• v.47 no.2
• /
• pp.107-117
• /
• 2014

Hancheon reservoir, which is located upstream of Jeju city, has been built for flood mitigation after Typhoon Nari, 2007. To verify flood mitigating effect of the this reservoir on the downstream area, runoff analysis based on the measured data (two stream discharge monitoring stations and inflow data to the reservoir) is carried out during torrential rain followed by typhoon Dainmu, 2010. The stream water level was recorded as 3.14 m for the peak at the down gradient station. The stream water level under the assumption of absence of Hancheon reservoir is calculated as 4.16 m using the estimated rating curve, stream water propagation velocity, and the bypassed volume of water to the reservoir. This result shows that clear effect of reservoir operation which is capable of mitigating peak discharge in the downstream area.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.394-398
• /
• 2016

Numerical analysis was conducted using Delft3D developed by Deltares in Netherlands to predict long-term river bed changes in Saemangeum Area. Tidal flow, discharge through the drainage gates and river bed changes in numerical model was verified by comparing to the results of field observation and hydraulic experiments. We calculated long-term river bed changes in Saemangeum area for 10 years from 2031 to 2040 after completion of development in Saemangeum. It is shown that 70 cm and 139 cm of accumulation occur in estuaries of Dongjin River and Mankyong River, respectively. Variation of flood level was also investigated considering long-term river bed changes. There was no change in estuary of Dongjin River but maximum flood level in estuary of Mankyong River increased 81 cm.

• Journal of Korean Society of Rural Planning
• /
• v.21 no.4
• /
• pp.177-186
• /
• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• Ecology and Resilient Infrastructure
• /
• v.7 no.4
• /
• pp.345-352
• /
• 2020

Securing the lead time for evacuation is crucial to minimize flood damage. In this study, downstream water levels for heavy rainfall were predicted using measured water level observation data. Multiple regression analysis and artificial neural networks were applied to the Seom River experimental watershed to predict the water level. Water level observation data for the Seom River experimental watershed from 2002 to 2010 were used to perform the multiple regression analysis and to train the artificial neural networks. The water level was predicted using the trained model. The simulation results for the coefficients of determination of the artificial neural network level prediction ranged from 0.991 to 0.999, while those of the multiple regression analysis ranged from 0.945 to 0.990. The water level prediction model developed using an artificial neural network was better than the multiple-regression analysis model. This technique for forecasting downstream water levels is expected to contribute toward flooding warning systems that secure the lead time for streams.

• Water for future
• /
• v.52 no.8
• /
• pp.56-66
• /
• 2019

Nepal is bestowed with abundant water. With more than 1500 mm average annual rainfall in the country, a vast quantity of underutilized groundwater in the Terai belt, and the water stored in snowcaps in the Himalayas, aquifers in the mountains and glacial lakes, Nepal is potentially in an advantageous position in terms of per capita availability. However, low emphasis in management aspect of water and high emphasis in infrastructural developments related to water resources management has resulted in conversion of water in Nepal from a resource to a burden. The global climate change, reduction in number of rainy days, increase in intensity of rainfall during wet monsoon season, encroachment of river banks for settlement, inadequate release of environmental flows from hydropower plants, and attempt to tame the mighty and high velocity rivers of Nepal have resulted in increasing number of water induced disasters (flood and landslide), rise in conflict between local residents and hydropower developers, higher number of devastating landslides, and in some extreme cases mass migration of residents resulting in climate refugees. There is a ray of hope; the awareness level of the people regarding sustainable use of water resources is increasing, the benefit sharing mechanism is gradually being implemented, the role of interdisciplinary and integrated water resources management is appreciated at a higher level and the level of preparedness against flood and landslides is at a higher degree compared to a couple of decades ago. With the use of renewable energy sources, the possibilities for sustainable and productive use of water are on the rise in Nepal.