• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.955-968
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• 2021

A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1105-1114
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• 2022

A study on a method to overcome the limitations of the topographical and hydrological observation environment for estimating the QPE with high consistency with the ground rainfall by utilizing the spatiotemporal observation advantages of the rainfall radar for use in flood forecasting, and quantitative observations of localized rainfall due to these limiting conditions Uncertainty should be identified in terms of flood analysis. Against this background, in this study, 22 major heavy rain events in 2016 were analyzed for each of Mt. Biseul (BSL), Mt. Sobaek (SBS), Mt. Gari (GRS), Mt. Mohu (MHS), and Mt. Seodae (SDS) to determine the observation distance and altitude. The uncertainty of observation was quantified and an error map was derived. As a result of the analysis, it was found that, on average, the rainfall radar exceeded 10% up to 100 km and 30% over 150 km. Based on the average radar operating altitude angle, it was found that the error for the altitude was approximately 10% or less up to the second altitude angle, 20% at the third or higher altitude angle, and more than 50% at the fourth altitude angle or higher.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.11-21
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• 2022

Drought occurs extensively over a long period and causes great socio-economic damage. Since drought risk consists of social, environmental, physical, and economic factors along with meteorological and hydrological factors, it is important to quantitatively identify their impacts on drought risk. This study investigated the relationship among drought hazard, vulnerability, response capacity, and risk in Chungcheongbuk-do using a structural equation model and evaluated their impacts on drought risk using Bayesian networks. We also performed sensitivity analysis to investigate how the factors change drought risk. Overall results showed that Chungju-si had the highest risk of drought. The risk was calculated as the largest even when the hazard and response capacity were changed. However, when the vulnerability was changed, Eumseong-gun had the greatest risk. The sensitivity analysis showed that Jeungpyeong-gun had the highest sensitivity, and Jecheon-si, Eumseong-gun, and Okcheon-gun had highest individual sensitivities with hazard, vulnerability, and response capacity, respectively. This study concluded that it is possible to identify impact factors on drought risk using regional characteristics, and to prepare appropriate drought countermeasures considering regional drought risk.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.340-351
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• 2023

Landslides are major natural geological hazards that cause enormous property damage and human casualties annually. The vulnerability of mountainous areas to landslides is further exacerbated by the impacts of climate change. Soil depth is a crucial parameter in landslide and debris flow analysis, and plays an important role in the evaluation of watershed hydrological processes that affect slope stability. An accurate method of estimating soil depth is to directly investigate the soil strata in the field. However, this requires significant amounts of time and money; thus, numerous models for predicting soil depth have been proposed. However, they still have limitations in terms of practicality and accuracy. In this study, 71 seismic survey results were collected from domestic mountainous areas to estimate soil depth on hill slopes. Soil depth was estimated on the basis of a shear wave velocity of 700 m/s, and a database was established for slope angle, elevation, and soil depth. Consequently, the statistical characteristics of soil depth were analyzed, and the correlations between slope angle and soil depth, and between elevation and soil depth were investigated. Moreover, various soil depth prediction models based on slope angle were investigated, and corrected linear and exponential soil depth prediction models were proposed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.309-319
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• 2023

Recently, the frequency and intensity of meteorological disasters have increased due to climate change. In South Korea, there are regional differences in vulnerability and response capability to cope with climate change because of regional climate characteristics. In particular, drought results from various factors and is linked to extensive meteorological, hydrological, and agricultural impacts. Therefore, in order to effectively cope with drought, it is necessary to use a composite drought index that can take into account various factors, and to evaluate future droughts comprehensively considering climate change. This study evaluated hydrologic risk(${\bar{R}}$) of future drought in the Nakdong River basin based on the Dynamic Naive Bayesian Classification (DNBC)-based composite drought index, which was calculated by applying Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), Evaporate Stress Index (ESI) and Water Supply Capacity Index (WSCI) to the DNBC. The indices used in the DNBC were calculated using observation data and climate scenario data. A bivariate frequency analysis was performed for the severity and duration of the composite drought. Then using the estimated bivariate return periods, hydrologic risks of drought were calculated for observation and future periods. The overall results indicated that there were the highest risks during the future period (2021-2040) (${\bar{R}}$=0.572), and Miryang River (#2021) had the highest risk (${\bar{R}}$=0.940) on average. The hydrologic risk of the Nakdong River basin will increase highly in the near future (2021-2040). During the far future (2041-2099), the hydrologic risk decreased in the northern basins, and increased in the southern basins.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.137-147
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• 2010

In this study, Chukwooki and modern data were compared using annual maximum rainfall event series. Annual maximum series for specified rainfall duration in modern frequency analysis can not be constructed from Chukwooki data, so the concept of independent rainfall event is introduced to compare Chukwooki and modern data. Annual maximum rainfall event is determined by applying the bivariate exponential distribution and the parameters estimated annually are selected. The results using the annual parameter show that the hydrological meaning of the parameters is related to the variation of annual total rainfall amounts. For the whole independent rainfall events, the total rainfall and the rainfall intensity of Chukwooki data are greater than those of modern data, and rainfall duration of the two periods is similar. However modern annual maximum rainfall events show different characteristics that rainfall duration is much longer, rainfall intensity is similar and the total rainfall is greater than those of Chukwooki period. The increasing trend of rainfall duration and total rainfall of the modern annual rainfall events may be regarded as the one of components of the long-term cycle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.525-533
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• 2008

Global circulation models (GCMs) have been used to study impact of climate change on water resources for hydrologic models as inputs. Recently, regional circulation models (RCMs) have been used widely for climate change study, but the RCMs have been rarely used in the climate change impacts on water resources in Korea. Therefore, this study is intended to use a set of climate scenarios derived by RegCM3 RCM ($27km{\times}27km$), which is operated by Korea Meteorological Administration. To begin with, the RCM precipitation data surrounding major rainfall stations are extracted to assess validation of the scenarios in terms of reproducing low frequency behavior. A comprehensive comparison between observation and precipitation scenario is performed through statistical analysis, wavelet transform analysis and EOF analysis. Overall analysis confirmed that the precipitation data driven by RegCM3 shows capabilities in simulating hydrological low frequency behavior and reproducing spatio-temporal patterns. However, it is found that spatio-temporal patterns are slightly biased and amplitudes (variances) from the RCMs precipitation tend to be lower than the observations. Therefore, a bias correction scheme to correct the systematic bias needs to be considered in case the RCMs are applied to water resources assessment under climate change.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.315-325
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• 2023

This study analyzed the disturbance process of river wetlands based on modern and contemporary maps and aerial photographs, and analyzed land cover and NDVI changes in the hydro-ecological impact zone around the Wangjin District. A stable sandbar was formed near Wangjinnaru and was naturally connected to the agricultural land within inland, but after the sandbar and river wetland were destroyed due to heavy floods, embankment construction, land readjustment, and comprehensive river management, artificial replaced wetlands and ecological parks were created, and sandbars in the form of river island were restored again. The change in land cover in the hydro-ecological impact zone showed that rice paddies and fields in agricultural areas decreased from 36.3% in 2013 to 22.9% in 2022, with the largest change in area to 814,476m². It was confirmed that the land cover was undergoing vegetation over time. Since the vegetation condition is good, a healthy food chain is formed in the waterfront ecosystem, which can be expected to be biodiversity-positive. Summarizing seasonal changes in the vegetation index, the overall change in the vegetation index was the largest in spring (March), followed by summer (June), and the change in autumn (September) was the smallest except for water. By land use, the overall vegetation index (NDVI) increased, including 39.1% improvement in alternative wetlands, 38.2% improvement in load, 44.3% improvement in ecological parks, 35.6% improvement in agricultural areas, and -8.1% decrease in water.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.103-113
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• 2023

The river confluence is a section in which two rivers with different topographical and hyrodynamic characteristics are combined into one, and it is a section in which rapid flow, inflow of sediments, and hydrological topographic changes occur. In the confluence section, the flow of fluid occurs due to the difference in density due to the type of material or temperature difference, which is called a density flow. It is necessary to accurately measure and observe the confluence section including a certain section of the main stream and tributaries in order to understand the mixing behavior of the water body caused by the density difference. A comprehensive analysis of this water mixture can be obtained by obtaining flow field and flow rate information, but there is a limit to understanding the mixing of water bodies with different physical properties and water quality characteristics of rivers flowing with stratigraphic flow. Therefore, this study attempts to grasp the density flow through the water temperature distribution in the confluence section. Among the extensive data of the river, vertical data and water surface data were acquired, and through this, the stratification phenomenon of the confluence was to be confirmed. It was intended to analyze the mixed pattern of the confluence by analyzing the water mixing pattern according to the water temperature difference using the vertical data obtained by measuring the repair volume by installing the ADCP on the side of the boat and measuring the real-time concentration using YSI. This study can supplement the analysis results of the existing water quality measurement in two dimensions. Based on the comparative analysis, it will be used to investigate the current status of stratified sections in the water layer and identify the mixing characteristics of the downstream section of the river.