• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.156-156
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• 2018

The subbasin spatial scale can affect a hydrological simulation result. The objective of this study was to investigate an appropriate subbasin spatial scale for reproducing the different flow phases with the Soil and Water Assessment Tool (SWAT). Moreover, this study addressed the total hydrologic model uncertainty using the Generalized Likelihood Uncertainty Estimation (GLUE) method. The hydrologic modelling uncertainty analysis revealed that the courser subbasin spatial scale provided a relatively better coverage of most of the observations by the 95PPU. On the other hand, the finer subbasin spatial scale produced the best single simulation output closer to the observation. Moreover, most of the observed high flows were enveloped by the 95PPU while this did not happen for the low flows. The overall average performance improvement through an appropriate subbasin spatial scale for reproducing the different flow phases in the Yongdam and Gilgelabay watersheds were found to be 36% and 53%, respectively. It is, therefore, a worth that to put more effort in reproducing the different flow phases by investigating an appropriate subbasin spatial scale to improve our understanding about the frequency and magnitude of the different flow phases.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• Journal of Korean Society on Water Environment
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• v.35 no.2
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• pp.131-144
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• 2019

Climate Change affects the hydrological cycle in agricultural watersheds through rising air temperature and changing rainfall patterns. Agricultural watersheds in Korea are characterized by extensive paddy fields and intensive water use, a resource that is under stress from the changing climate. This study analyzed the effects of climate change on river flows for Geum Cheon and Eun-San Choen watershed using STREAM, a semi-distributed watershed model. In order to evaluate the performance and improve the reliability of the model, calibration and validation of the model was done for one flow observation point and three reservoir water storage ratio points. Climate change scenarios were based on RCP data provided by the Korea Meteorological Administration (KMA) and bias corrections were done using the Quantile Mapping method to minimize the uncertainties in the results produced by the climate model to the local scale. Because of water mass-balance, evapotranspiration tended to increase steadily with an increase in air temperature, while the increase in RCP 8.5 scenario resulted in higher RCP 4.5 scenario. The increase in evapotranspiration led to a decrease in the river flow, particularly the decrease in the surface runoff. In the paddy agricultural watershed, irrigation water demand is expected to increase despite an increase in rainfall owing to the high evapotranspiration rates occasioned by climate change.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.51-60
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• 2019

The major purpose of this study is to construct an in-situ soil moisture verification network employing Frequency Domain Reflectometry (FDR) sensors for Cosmic-ray soil moisture observation system operation as well as long-term field-scale soil moisture monitoring. The test bed of Cosmic-ray and FDR verification network system was established at the Sulma Catchment, in connection with the existing instrumentations for integrated data provision of various hydrologic variables. This test bed includes one Cosmic-ray Neutron Probe (CRNP) and ten FDR stations with four different measurement depths (10 cm, 20 cm, 30 cm, and 40 cm) at each station, and has been operating since July 2018. Furthermore, to assess the reliability of the in-situ verification network, the volumetric water content data measured by FDR sensors were compared to those calculated through the core sampling method. The evaluation results of FDR sensors- measured soil moisture against sampling method during the study period indicated a reasonable agreement, with average values of $bias=-0.03m^3/m^3$ and RMSE $0.03m^3/m^3$, revealing that this FDR network is adequate to provide long-term reliable field-scale soil moisture monitoring at Sulmacheon basin. In addition, soil moisture time series observed at all FDR stations during the study period generally respond well to the rainfall events; and at some locations, the characteristics of rainfall water intercepted by canopy were also identified. The Temporal Stability Analysis (TSA) was performed for all FDR stations located within the CRNP footprint at each measurement depth to determine the representative locations for field-average soil moisture at different soil profiles of the verification network. The TSA results showed that superior performances were obtained at FDR 5 for 10 cm depth, FDR 8 for 20 cm depth, FDR2 for 30 cm depth, and FDR1 for 40 cm depth, respectively; demonstrating that those aforementioned stations can be regarded as temporal stable locations to represent field mean soil moisture measurements at their corresponding measurement depths. Although the limit on study duration has been presented, the analysis results of this study can provide useful knowledge on soil moisture variability and stability at the test bed, as well as supporting the utilization of the Cosmic-ray observation system for long-term field-scale soil moisture monitoring.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1077-1089
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• 2022

With the construction of Seoul National University (SNU), the Mt. Gwanak watershed has undergone some urbanization. As with other campus catchments, data related to the water cycle is extremely limited. Therefore, this study began by collecting hydrological and meteorological data using Atmos-41, a complex meteorological observation instrument. The observation results of Atmos-41 were validated by analyzing the statistical characteristics and confidence intervals based on the monthly variability of data from the Korea Meteorological Administration. Results of the previous research were used to validate the simulated surface runoff and infiltration using the Storm Water Management Model (SWMM). The potential evapotranspiration (PET) simulated by the SWMM was rectified by comparing it to the Atmos-41 observation data. Multiple regression analysis was employed to adjust for the fluctuations in precipitation, relative humidity, and wind speed because the calculated SWMM PET tends to be underestimated during periods of low temperatures. R² increased from 0.54 to 0.80 when compared to the Atmos-41 PET. The rate of change in the water cycle as a consequence of the SNU's construction resulted in a 15.7% increase in surface runoff, a 14.2% decrease in infiltration rate, and a 1.6% decrease in evaporation.

• Journal of the Mineralogical Society of Korea
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• v.21 no.2
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• pp.139-159
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• 2008

Geochemical analysis of the various kinds of water including observation borehole groundwater was carried out for the assessment of the hydrological safety of the underground oil storage cavern and the potentiality of mineralogical and microbiological clogging was estimated. Most of water samples belonged to $Ca-HCO_3$ and $Ca-HCO_3-SO_4$ types. There was no distinct chemical difference in the various kinds of water. All kinds of water are undersaturated with the calcite which is the major clogging mineral. Most water samples have low Fe and Mn concentrations. However, they are saturated or oversaturated with the iron-oxide/hydroxide minerals and have high dissolved oxygen contents which suggests the possibility of clogging by the iron-oxide/hydroxide minerals as a long-term aspect. Several water samples from the ground observation borehole also show the high saturation indices far the clay minerals, which can fill up the fractures, indicating the possibility of clogging by the clay minerals. Statistical analysis shows the degree of mineral precipitation or dissolution is mainly controlled by pH, Eh and DO of water samples. According to the microbial analysis, the aerobic microbes and slime forming bacteria are dominant in most water samples and anaerobic microbes including sulfate reducing bacteria are very low or not detected. Although the slime forming bacteria which are known as a main microbial cause of the clogging is lower than $10^5\;CFUs/mL$ in all water samples, because the slime forming bacteria are dominant microbe in several observation boreholes, the clogging can be caused by it as a long-term aspect. In addition, the possibility of clogging can be increased if the microbial effect is combined with the mineralogical effect such as iron oxide/hydroxide minerals for the possibility of clogging. Therefore, the systematic and long-term program for the assessment of clogging is required for the safe operation of underground oil storage cavern.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.52-67
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• 2008

Recently, frequent occurrence of flash floods caused by climactic change has necessitated prompt and quantitative prediction of precipitation. In particular, the usability of rainfall radar that can carry out real-time observation and prediction of precipitation behavior has increased. Moreover, the use of distributed hydrological model that enables grid level analysis has increased for an efficient use of rainfall radar that provides grid data at 1km resolution. The use of distributed hydrologic model necessitates grid-type spatial data about target basins; to enhance reliability of flood runoff simulation, the use of visible and precise data is necessary. In this paper, physically based $Vflo^{TM}$ model and ModClark, a quasi-distributed hydrological model, were used to carry out flood runoff simulation and comparison of simulation results with data from Imjin River Basin, two-third of which is ungauged. The spatial scope of this study was divided into the whole Imjin River basin area, which includes ungauged area, and Imjin River basin area in South Korea for which relatively accurate and visible data are available. Peak flow and lag time outputs from the two simulations of each region were compared to analyze the impact of uncertainty in topographical parameters and soil parameters on flood runoff simulation and to propose effective methods for flood runoff simulation in ungauged regions.

• 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 Wetlands Research
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• v.16 no.1
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• pp.73-83
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• 2014

The government has recently carried out monitoring to attain a better understanding of the current situation and model for prediction of future events pertaining to water quality in the estuarine area of Yeongsan River. But many users have noted difficulties to understand and utilize the results because most monitoring and model data consist of figures and text. The aim of this study is to develop a GIS-based integrated information system to support the understanding of the current situation and prediction of future events about water quality in the estuarine area of Yeongsan River. To achieve this, a monitoring DB is assembled, a linkages model is defined, a GUI is composed, and the system development environment and system composition are defined. The monitoring data consisted of observation data from 2010 ~ 2012 in the estuarine area of Yeongsan River. The models used in the study are HSPF (Hydrological Simulation Program-Fortran) for simulation of the basin and EFDC (Environmental Fluid Dynamics Code) for simulation of the estuary and river. Ultimately, a GIS based system was presented for utilization and expression using monitoring and model data. The system supports prediction of the estuarine area ecological environment quantitatively and displays document type model simulation results in a map-based environment to enhance the user's spatial understanding. In future study, the system will be updated to include a decision making support system that is capable of handling estuary environment issues and support environmental assessment and development of related policies.