• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.104-118
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• 2018

This study is to evaluate the accuracy improvement of the model using SWAT(Soil and Water Assessment Tool) model and multi - point hydrological observation data. The watershed is located in the Yongdam Dam($930.4km^2$), the Donghyang($165.5km^2$), the Chuncheon($290.9km^2$), the Juchun($57.8km^2$) and the Seokjeong($80.5km^2$). The watershed covers 70.0 % forest. In order to improve the accuracy of the model, precipitation data were used from two weather stations(Jangsu, Geumsan) and 16 AWS stations daily precipitation data(2003~2011) managed by KMA, MLIT, and K-water. Based on the reliable data of the Yongam test basin in 2003~2011, the runoff of single point (Yongdam dam) and multi-point (Donghyang, Chuncheon, Jucheon, Seokjeong). Simulation results show that the $R^2$ of the single subwatershed (Donghyang, Chuncheon, Jucheon, Seokjeong) is single point(0.84) and multipoint(0.88). For model efficiency coefficient of Nash-Sutcliffe at single point(0.45) and multipoint(0.70).

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.155-166
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• 2020

In this study, we applied the Radar-AWS Rainrates (RAR), weather radar-based quantitative precipitation estimations (QPEs), to the Yongdam study watershed in order to perform the flood runoff simulation and calculate the inflow of the dam during flood events using hydrologic model. Since the Yongdam study watershed is a representative area of the mountainous terrain in South Korea and has a relatively large number of monitoring stations (water level/flow) and data compared to other dam watershed, an accurate analysis of the time and space variability of radar rainfall in the mountainous dam watershed can be examined in the flood modeling. HEC-HMS, which is a relatively simple model for adopting spatially distributed rainfall, was applied to the hydrological simulations using HEC-GeoHMS and ModClark method with a total of eight independent flood events that occurred during the last five years (2014 to 2018). In addition, two NCL and Python script programs are developed to process the radar-based precipitation data for the use of hydrological modeling. The results demonstrate that the RAR QPEs shows rather underestimate trends in larger values for validation against gauged observations (R² 0.86), but is an adequate input to apply flood runoff simulation efficiently for a dam watershed, showing relatively good model performance (E_NS 0.86, R² 0.87, and PBIAS 7.49%) with less requirements for the calibration of transform and routing parameters than the spatially averaged model simulations in HEC-HMS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.783-791
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• 2018

The biased estimation of low density rainfall network and radar rainfall has limited application to extreme rainfall in a small area. To improve this, more rainfall information needs to be produced. In this study, we analyzed the applicability of the vehicle rainfall sensor developed and used recently. The developed rainfall sensor was attached to the vehicle to observe the rainfall according to the movement of the vehicle. The analytical method used time series and average rainfall values for observations of rainfall sensors and nearby rainfall stations. The results show that the trend of observed values according to rainfall events shows a certain pattern. It is analyzed that it is caused by various causes such as the difference between the observation position of the rainfall sensor and the nearby rainfall station, the moving speed of the vehicle, and the rainfall observation method. This result shows the possibility of rainfall observation using a rainfall sensor for a vehicle, and it is possible to observe rainfall more precisely through experiments and improvement of rainfall sensors in various conditions in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.617-626
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• 2022

In Korea, annual precipitation and its variability have gradually increased since modern meteorological observations began, and the risk of disasters has also been increasing due to significant regional variations and recent abnormal climate conditions. Given that damage from storms and floods mainly occurs around rivers, it is crucial to determine the appropriate design frequency for river-related projects. This study examined existing design practices used to determine hydrological design frequencies and suggested a new method to determine appropriate design frequencies. The study collected available data pertaining to seven evaluation factors, specifically the basin areas, shape parameters, channel slopes, stream orders, backwater effect reaches, extreme rainfall frequencies, and urbanized flood inundation areasfor 413 local rivers in Chungcheongnam-do in Korea. The estimated weights for areas of extreme rainfall frequencies and urbanized flood inundation were found to be 18, having a great effect on determining the design frequency. Compared with the established design frequency in previous government reports, the estimated design frequency increased for 255 rivers and decreased for 158 rivers.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.759-767
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• 2017

Two main parameters of NRCS-CN method are curve numbers and intial loss ratio. They are generally selected according to the guideline of US National Engineering Handbook, however, they might cause errors on estimated runoff in Korea because there are differences between soil types and hydrological characteristics of Korean watersheds and those of United States. In this study, applying asymptotic CN regression method, we suggested eight modified NRCS-CN models to decide optimum runoff estimation model for Korean watersheds. RSR (RMSE-observations standard deviation ratio) and NSE (Nash-Sutcliffe efficiency) were used to evaluate model performance, consequently M6 for gauged basins (Avg. RSR was 0.76, Avg. NSE was 0.39) and M7 for ungauged basins (Avg. RSR was 0.82, Avg. NSE was 0.31) were selected. Furthermore it was observed that initial loss ratios ranging from 0.01 to 0.10 were more adequate than the fixed ${\lambda}=0.20$ in most of basins.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.191-201
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• 2018

Recently, the frequency of heavy rainfall is increasing due to the effects of climate change, and heavy rainfall in urban areas has an unexpected and local characteristic. Floods caused by localized heavy rains in urban areas occur rapidly and frequently, so that life and property damage is also increasing. It is crucial how fast and precise observations can be made on successful flood management in urban areas. Local heavy rainfall is predominant in low-level storms, and the present large-scale radars are vulnerable to low-level rainfall detection and observations. Therefore, it is necessary to introduce a new urban flood forecasting system to minimize urban flood damage by upgrading the urban flood response system and improving observation and forecasting accuracy by quickly observing and predicting the local storm in urban areas. Currently, the WHAP (Water Hazard Information Platform) Project is promoting the goal of securing new concept water disaster response technology by linking high resolution hydrological information with rainfall prediction and urban flood model. In the WHAP Project, local rainfall detection and prediction, urban flood prediction and operation technology are being developed based on high-resolution small radar for observing the local rainfall. This study is expected to provide more accurate and detailed urban flood warning system by enabling high-resolution observation of urban areas.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1143-1157
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• 2020

In this study, a criteria for the SWAT model calibration method in SWAT-CUP which considers multi-site and multi-variable observations was presented. For its application, the SWAT model was simulated using long-term observed flow, soil moisture, and evapotranspiration data in Yongdam study watershed, investigating the hydrological runoff characteristics and water balance in the water cycle analysis. The model was calibrated with different parameter values for each sub-watershed in order to reflect the characteristics of multiple observations through one-by-one calibration, appropriate settings of model simulation run/iteration number (1,000 simulation runs in the first iteration and then 500 simulation runs for the following iterations), and executions of partial and all run in SWAT-CUP. The flow simulation results of watershed outlet point, ENS 0.85, R2 0.87, and PBIAS -7.6%, were compared with the analysis results (ENS 0.52, R2 0.54, and PBIAS -22.4%) applied in the other batch (i.e., non one-by-one) calibration approach and showed better performances of proposed method. From the simulation results of a total of 15 years, it was found that the total runoff (streamflow) and evapotranspiration rates from precipitation are 53 and 39%, and the ratio of surface runoff and baseflow (i.e., sum of lateral and return flow, and recharge deep aquifer) are 35 and 65%, respectively, in Yongdam watershed. In addition, the analytical amount of available water (i.e., water yield), including the total annual streamflow (daily average 21.8 m3/sec) is 6.96 billion m3 per year (about 540 to 900 mm for sub-watersheds).

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1145-1149
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• 2006

The typhoon Rusa passed through the Korean peninsula from the west-southern part to the east-northern part in the summer season of 2002. The flash flood due to the Rusa was occurred over the Korean peninsula and especially the damage was concentrated in Kangnung, Yangyang, Kosung, and Jeongsun areas of Kangwon-Do. Since the latter half of the 1990s the flash flood has became one of the frequently occurred natural disasters in Korea. Flash floods are a significant threat to lives and properties. The government has prepared against the flood disaster with the structural and nonstructural measures such as dams, levees, and flood forecasting systems. However, since the flood forecasting system requires the rainfall observations as the input data of a rainfall-runoff model, it is not a realistic system for the flash flood which is occurred in the small basins with the short travel time of flood flow. Therefore, the flash flood forecasting system should be constructed for providing the realistic alternative plan for the flash flood. To do so, firstly, Flash Flood Monitoring and Prediction (FFMP) Model must be developed suitable to Korea terrain. In this paper, We develop the FFMP model which is based on GIS, Radar techniques and hydro-geomorphologic approaches. We call it the F2MAP model. F2MAP model has three main components (1) radar rainfall estimation module for the Quantitative Precipitation Forecasts (QPF), (2) GIS Module for the Digital terrain analysis, called TOPAZ(Topographic PArametiZation), (3) hydrological module for the estimation of threshold runoff and Flash Flood Guidance(FFG). For the performance test of the model developed in this paper, F2MAP model applied to the Kangwon-Do, Korea, where had a severe damage by the Typhoon Rusa in August, 2002. The result shown that F2MAP model is suitable for the monitoring and the prediction of flash flood.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.1035-1046
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• 2003

In order to evaluate the TOPMODEL's prediction ability for spatial distribution of water table depths, two major assumptions and governing equation of water table depth are tested. For the test, data of hydrological observations are used and a soil survey is made in the steep hillslope with thin soils. Responses of water table and hydraulic properties of soil are coincident with two major assumptions of the TOPMODEL's such as water table gradient parallel to the local topographical slope and exponential decline in transmissivity with depths. Soil texture and the decline rate of transmissivity(f) we homogeneous in space at the 0∼0.3m depths of the soil of the hillslope, but they are heterogeneous in space below its 0.3m depths due to the vertical change of soil texture and the ‘f’. It is shown that the TOPMODEL's equation can be used for simulating distribution of water table depth at the depths with uniform values of the 'f'.