• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.670-691
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• 2018

This study presents the research results of the BMT(Benchmark Model Test) simulations of the DECOVALEX-2019 project Task B. Task B named 'Fault slip modelling' is aiming at developing a numerical method to predict fault reactivation and the coupled hydro-mechanical behavior of fault. BMT scenario simulations of Task B were conducted to improve each numerical model of participating group by demonstrating the feasibility of reproducing the fault behavior induced by water injection. The BMT simulations consist of seven different conditions depending on injection pressure, fault properties and the hydro-mechanical coupling relations. TOUGH-FLAC simulator was used to reproduce the coupled hydro-mechanical process of fault slip. A coupling module to update the changes in hydrological properties and geometric features of the numerical mesh in the present study. We made modifications to the numerical model developed in Task B Step 1 to consider the changes in compressibility, Permeability and geometric features with hydraulic aperture of fault due to mechanical deformation. The effects of the storativity and transmissivity of the fault on the hydro-mechanical behavior such as the pressure distribution, injection rate, displacement and stress of the fault were examined, and the results of the previous step 1 simulation were updated using the modified numerical model. The simulation results indicate that the developed model can provide a reasonable prediction of the hydro-mechanical behavior related to fault reactivation. The numerical model will be enhanced by continuing interaction and collaboration with other research teams of DECOVALEX-2019 Task B and validated using the field experiment data in a further study.

• Korean Journal of Agricultural Science
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• v.7 no.2
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• pp.131-144
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• 1980

The Linear Regression Model to extend the monthly runoff data in the short-recorded river was proposed by the author in 1979. Here in this study generalization precedure is made to apply that model to any given river basin and to any given station. Lengthier monthly runoff data generated by this generalized model would be useful for water resources assessment and waterworks planning. The results are as follows. 1. This Linear Regression Model which is a transformed water-balance equation attempts to represent the physical properties of the parameters and the time and space varient system in catchment response lumpedly, qualitatively and deductively through the regression coefficients as component grey box, whereas deterministic model deals the foregoings distributedly, quantitatively and inductively through all the integrated processes in the catchment response. This Linear Regression Model would be termed "Statistically deterministic model". 2. Linear regression equations are obtained at four hydrostation in Geum-river basin. Significance test of equations is carried out according to the statistical criterion and shows "Highly" It is recognized th at the regression coefficients of each parameter vary regularly with catchment area increase. Those are: The larger the catchment area, the bigger the loss of precipitation due to interception and detention storage in crease. The larger the catchment area, the bigger the release of baseflow due to catchment slope decrease and storage capacity increase. The larger the catchment area, the bigger the loss of evapotranspiration due to more naked coverage and soil properties. These facts coincide well with hydrological commonsenses. 3. Generalized diagram of regression coefficients is made to follow those commonsenses. By this diagram, Linear Regression Model would be set up for a given river basin and for a given station (Fig.10).

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1069-1077
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• 2009

Lately, it is an important concern in water resources research to maintain a stable water supply according to a future climate change and an increase in water use. In Han-River basin, approximately 10 % of water resources that is provided the capital region (Gyeonggi, Seoul etc.) has been reduced as a consequence of the construction of Imnam Dam (storage volume: 27 billion $m^3$) located in the upper Hwacheon Dam upstream area. Therefore, streamflows have decreased in Bukhangang basin, but it could not be evaluated quantitatively. In this study, SWAT-K which is the physically based long-term runoff simulation model, was used in order to evaluate the effect of Imnam Dam on the reduced inflow to Hwacheon Dam according to the change of hydrological condition in the upstream area of Hwacheon Dam. For the model input data of North Korea area, meteorological data of GTS (Global Telecommunication System) were used, and soil maps by FAO/UNESCO (2003) were applied. Temporal variations of water resources is investigated with comparison of observed and simulated inflows at Hawcheon Dam site. Also, annual, monthly, seasonal decreases in water resources were evaluated using the flow duration analysis of simulated streamflows with or without Imnam dam.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.725-733
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• 2019

Sand dams are structures that can be used as auxiliary water resources in case of drought as sand accumulates due to barriers crossing valley rivers and valley water is stored in the voids, increasing the water level. This structure, which is mainly used in arid regions such as Africa, has not been installed in Korea. In Korea, there are only a few cases where water is taken from debris barriers that prevent debris flow. The purpose of this study is to evaluate the effect of water supply when the sand dam is installed downstream of the existing intake barrier in Seosang-ri valley, Chuncheon. For this purpose, modeling was performed by linking the basin hydrologic model and reservoir routing model. Changes in the water level, storage and discharge in the sand dam reservoir according to the size and intake of the sand dam are presented on a case-by-case basis. As a result of application, it was found that the water supply capacity due to the sand dam installation was improved at 95% reliability. Especially, when the size is L × B × H_o = 25 m × 15 m × 1 m and the pumping rates from intake barrier and sand dam are (Q₁, Q₂) = (30, 20), (35, 15) ㎥/day, the efficiency was the best for water supply of 50 ㎥/day.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.28-38
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• 2019

Climate change on the Korean peninsula is progressing faster than the global average. For example, typhoons, extreme rainfall, heavy snow, cold, and heatwave that are occurring frequently. North Korea is particularly vulnerable to climate change-related natural disasters such as flooding and flooding due to long-term food shortages, energy shortages, and reckless deforestation and development. In addition, North Korea is classified as an unmeasured area due to political and social influences, making it difficult to obtain sufficient hydrologic data for hydrological analysis. Also, as interest in climate change has increased, studies on climate change have been actively conducted on the Korean Peninsula in various repair facilities and disaster countermeasures, but there are no cases of research on North Korea. Therefore, this study selects watershed characteristic variables that are easy to acquire in order to apply localization model to North Korea where it is difficult to obtain observed hydrologic data and estimates parameters based on meteorological and topographical characteristics of 16 dam basins in South Korea. Was calculated. In addition, as a result of reviewing the applicability of the parameter estimation equations calculated for the fifty thousand, Gangneungnamdaecheon, Namgang dam, and Yeonggang basins, the applicability of the parameter estimation equations to North Korea was very high.

• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1107-1119
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• 2012

The objectives of this study are to develop the flow nomograph for real-time flood forecasting and to assess its applicability in restored Cheonggye stream. The Cheonggye stream basin has the high impermeability and short concentration time and complicated hydrological characteristics. Therefore, the flood prediction method using runoff model is ineffective due to the limit of forecast. Flow nomograph which is able to forecast flood only with rainfall information. To set the forecast criteria of flow nomograph at selected flood forecast points and calculated criterion flood water level for each point, and in order to reflect various flood events set up simulated rainfall scenario and calculated rainfall intensity and rainfall duration time for each condition of rainfall. Besides, using a rating curve, determined scope of flood discharge following criterion flood water level and using SWMM model calculated flood discharge for each forecasting point. Using rainfall information following rainfall scenario calculated above and flood discharge following criterion flood water level developed flow nomograph and evaluated it by applying it to real flood event. As a result of performing this study, the applicability of flow nomograph to the basin of Cheonggye stream appeared to be high. In the future, it is reckoned to have high applicability as a method of prediction of flood of urban stream basin like Cheonggye stream.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1057-1066
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• 2019

The storage function method is used as a flood prediction model for four flood control offices in Korea as a method to analyze the actual rainfall-runoff relationship with non-linearity. It is essential to accurately estimate the parameters of the storage function method for accurate runoff analysis. However, the parameters of the storage function method currently in use are estimated by the empirical formula developed by the limited hydrological analysis in 2012; therefore, they are somewhat inaccurate. The kinematic wave method is a method based on physical variables of watershed and channel and is widely used for rainfall-runoff analysis. By adopting the two-term storage function method by the conversion of the kinematic wave method, parameters can be estimated based on physical variables, which can increase the accuracy of runoff calculation. In this research, the reproducibility of the kinematic wave method by the two-term storage function method was investigated. It is very easy to estimate the parameters because equivalent roughness, which is an important physical variable in watershed runoff, can be easily obtained by using land use and land cover, and the physical variable of channel runoff can be easily obtained from the basic river planning report or topographic map. In addition, this research examined the applicability of the two-term storage function method to runoff simulation of Naechon Stream, a tributary of the Hongcheon River in the Han River basin. As a result, it is considered that more accurate runoff calculation results could be obtained than the existing one-term storage function method. It is expected that the utilization of the storage function method can be increased because the parameters can be easily estimated using physical variables even in unmeasured watersheds and channels.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.495-513
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• 2004

The shape of land surface work as a cradle for various environmental processes and human activities. As spatially distributed process modelings become increasing important in current research communities, a classification system that delineates land surface into characteristic geomorphological units is a pre-requisite for sustainable land use planning and management. Existing classification systems are either morphometric or generic, which have limitations to characterize continuous ecological processes over the landscape. A new classification system was developed to delineate the land surface into different geomorphological units from Digital Elevation Models(DEMs). This model assumes that there are pedo-geomorphological units in which distinct sets of hydrological, pedological, and consequent ecological processes occur. The classification system first divides the whole landsurface into eight soil-landscape units. Possible energy and material nows over the land surface were interpreted using a continuity equation of mass flow along the hillslope, and subsequently implemented in terrain analysis procedures. The developed models were tested at a 12$\textrm{km}^2$ area in Yangpyeong-gun, Kyeongi-do, Korea. The method proposed effectively delineates land surface into distinct pedo-geomorphological units, which identify the geomorphological characteristics over a large area at a low cost. The delineated landscape units mal provide a basic information for natural resource survey and environmental modeling practices.