• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.50-50
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• 2018

As the frequency of drought due to climate change is increasing and the severity of drought becomes severe, it is urgent to prepare measures against extreme drought. Despite the significant impacts of drought on the coupled human-environment system, we have not fully understood the consequences of extreme droughts affecting all parts of the environment and our communities, and there is no system to assess environmental droughts quantitatively. Even if a drought disaster occurs on the same scale, the severity of the drought depends on the vulnerability of the region. Therefore, this study proposes environmental drought assessment based on water quality vulnerability to extreme drought for the resilient proactive response.

• Journal of Korean Society on Water Environment
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• v.37 no.1
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• pp.32-46
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• 2021

South Korea has been divided into quantities and water quality, and due to a revision of the Government Organization law in June 2018, the controversial water management system was integrated into the Ministry of Environment. The total Maximum Daily Loads System has been called the flower of water quality control, and since 2004, all three major river systems which have been introduced into the Han River system, despite its various difficult environments, and subsequently leading to all of the four major rivers undergoing obligatory implementation since 2013. Currently, the target TMDL (Han River Phase 1 and Other Water Systems Phase 3) for the 2020 stage has been implemented. The domestic TMDL established a basic plan for calculating the load which complies with the unit watershed's target water quality, as well as an implementation plan for annual load management, both which have been institutionalized in order to evaluate load compliance on a repeated annual basis. Local governments ask external organizations to conduct investigations every year in order to assess the transition, which thereby requires tens of millions of won every year. Therefore, an assessment and management model that can be easily operated at the TMDL personnel level is required. In this study, when the Han river Water System TMDL was implemented in earnest, we confirmed the the water quality improvement effect when TMDL was introduced to major inflow tributaries (TancheonA, JungnangA, AnyangA) under the Seoul City's jurisdiction through the use of the total amount control unit basin evaluation technique. By presenting customized management measures, we propose the guidelines that are necessary for determining more effective water environmental policies.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05b
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• pp.1334-1339
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• 2002

The objective of this study is to help practicing engineers easily use the Clark model which is used for estimating the magnitude of design flood for small stream. A representative unit hydrograph was derived on the basis of the past rainfall-runoff data and unit hydrographs, and the storage coefficient of Clark model was estimated by using hydrograph recession analysis. Since the storage coefficient(K) is a dominating factor among the parameters of Clark method, a mulitple regression formula, which has the drainage area, main channel length and slope as parameters, is propsed to estimate K value of a basin where measured data are missing. The result of regression analysis showed that there is a correlation between a storage coefficient(K) and aforemetioned three parameters in homogenious basins. A regression formular for K was derived using these correlations in a basin of Han River, Nakdong River, Young River, Kum River and Sumjin River

• Journal of Korea Water Resources Association
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• v.37 no.2
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• pp.145-154
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• 2004

The purpose of this study is to develop a real-time forecasting model in order to predict the flood runoff which has the nature of non-linearity and to verify applicability of neural network model for flood warning system. Developed model based on neural network, NRDFM(Neural River Discharge-Stage Forecasting Model) is applied to predict the flood discharge on Waekwann and Jindong stations in Nakdong river basin. As a result of flood forecasting on these two stations, it can be concluded that NRDFM-II is the best predictive model for real-time operation. In addition, the results of forecasting used on NRDFM-I and NRDFM-II model are not bad and these models showed sufficient probability for real-time flood forecasting. Consequently, it is expected that NRDFM in this study can be utilized as suitable model for real-time flood warning system and this model can perform flood control and management efficiently.

• Journal of the Korean association of regional geographers
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• v.17 no.5
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• pp.505-520
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• 2011

This study is aimed to examine the change on extreme precipitation events in South Korea. The country is divided into six basins, and seven extreme precipitation indices-related to heavy rainfall are analyzed at sixty weather stations. The increasing trend in amount of heavy rainfall is more stable than that in days of heavy rainfall. The increasing trend is the most stable when days of rainfall are more than 50 mm, or rainfall is over the 95th percentile. The precipitation indices-related to heavy rainfall was mostly increasing during analysis period. Especially, basins of the Han river, the upper Nakdong river, and the Eastern coast show significantly increasing trends compared to the other basins. However, the increasing trends of the Geum river and the Seomjin river are not statistically significant. Heavy rainfall events had stably increased in the Han and the Nakdong rivers since the mid-1970s. However, the number of stably increasing regions has decreased since the mid-2000s. It means that the frequency and intensity of the recent heavy rainfall become more irregular.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1505-1515
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• 2023

As extreme weather events caused by climate change are occurring around the world, blue carbon has recently been gaining attention as a carbon sink. Blue carbon has been officially recognized by the Intergovernmental Panel on Climate Change (IPCC) as a means of reducing greenhouse gases, and various studies are underway to discover new blue carbon sources both domestically and internationally. Domestic blue carbon research is centered on carbon absorption and storage in tidal flats, which account for most of the coastal wetlands, but there is a lack of research on spatial information. This study utilized the carbon storage of tidal flats from previous studies and converted it into location and spatial information for each basin of the Geumgang and Nakdong rivers. In addition, a proxy value of carbon storage per area by basin was calculated to compare and analyze the total carbon storage of various tidal flats in Korea and abroad. As a result of the analysis, both the Geumgang and Nakdong River basins showed different amounts of carbon storage depending on the tidal flats data, with the highest amount in the Geumgang basin coming from the National Ocean Survey (469,810.1 Mg C) and the highest amount in the Nakdong River basin coming from the Ministry of Environment (217,145.01 Mg C). The results of this study can be used as a basis for future research on the establishment of domestic blue carbon spatial information.

• 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.

• Journal of Environmental Science International
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• v.9 no.6
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• pp.455-462
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• 2000

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

• Journal of the Korean Society of Industry Convergence
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• v.16 no.3
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• pp.61-68
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• 2013

Long-term runoff model can be used to establish the effective plan of water reources allocation and the determination of the storage capacity of reservoir. So this study aims at the development of monthly runoff model using artificial neural network technique. For this, it was selected multi-layer neural network(MLN) and radial basis function neural network(RFN) model. In this study, it was applied model to analysis monthly runoff process at the Wi stream basin in Nakdong river which is representative experimental river basin of IHP. For this, multi-layer neural network model tried to construct input 3, hidden 7, and output 1 for each number of layer. As the result of analysis of monthly runoff process using models connected with artificial neural network technique, it showed that these models were effective in the simulation of monthly runoff.

• Journal of Environmental Science International
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• v.12 no.10
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• pp.1109-1116
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• 2003

The genetic algorithm is investigated fer parameters estimation of SED (storage - effective drainage) model from the Wi-stream watershed in Nakdong river basin. In the practical application of model, as a number of watershed parameters do not measure directly, it is desirable to make a good estimation from the known rainfall and runoff data. For the estimation of parameters of the SED model using the genetic algorithm, parameters of Green-Ampt equation(SM, K$\_$s/) for the estimation of an effective rainfall and initial storage(y$\_$in/) used in SED model are obtained a regression equation with 5, 10, 20 days antecedent precipitation. And as a consequence of computation, the parameters were obtained to satisfy the proposed objective function. From the comparison of observed and computed hydrographs, it shows a good agreement in the shape and the rising limb, peak, falling limb of hydrograph, so the SED model using the genetic algorithm shows a suitable model for runoff analysis in river basin.