• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.305-314
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• 2016

In this study, a quantitative assessment was carried out in order to identify the agricultural drought in time and space using the Terra MODIS remote sensing data for the agricultural drought. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were selected by MOD13A3 image which shows the changes in vegetation conditions. The land cover classification was made to show only vegetation excluding water and urbanized areas in order to collect the land information efficiently by Type1 of MCD12Q1 images. NDVI and EVI index calculated using land cover classification indicates the strong seasonal tendency. Therefore, standardized Vegetation Stress Index Anomaly (VSIA) of EVI were used to estimated the medium-scale regions in Korea during the extreme drought year 2001. In addition, the agricultural drought damages were investigated in the country's past, and it was calculated based on the Standardized Precipitation Index (SPI) using the data of the ground stations. The VSIA were compared with SPI based on historical drought in Korea and application for drought assessment was made by temporal and spatial correlation analysis to diagnose the properties of agricultural droughts in Korea.

• Journal of Korea Water Resources Association
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• v.51 no.4
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• pp.347-354
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• 2018

In urban areas, runoff flow is drained through sewer networks as well as surface areas. Therefore, it is very important to consider sewer networks as a component of hydrological drainage processes when conducting urban inundation modelling. However, most researchers who have implemented urban inundation/flood modelling, instinctively simplified the sewer networks without the appropriate criteria. In this research, a 1D-2D fully coupled urban inundation model is applied to estimate the influence of sewer network simplification on urban inundation modelling based on the dendritic network classification. The one-dimensional (1D) sewerage system analysis model, which was introduced by Lee et al. (2017), is used to simulate inlet and overflow phenomena by interacting with surface flow. Two-dimensional (2D) unstructured meshes are also applied to simulate surface flow and are combined with the 1D sewerage analysis model. Sewer network pipes are simplified based on the dendritic network classification method, namely the second and third order, and all cases of pipes are conducted as a control group. Each classified network case, including a control group, is evaluated through their application to the 27 July 2011 extreme rainfall event, which caused severe inundation damages in the Sadang area in Seoul, South Korea. All cases are compared together regarding inundation area, inflow discharge and overflow discharge. Finally, relevant criterion for the simplification method is recommended.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.163-174
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• 2015

Urbanization caused various environmental problems like destruction of natural water cycle and increased urban flood. To solve these problems, LID(Low Impact Development) deserves attention. The main objective of LID is to restore the water circulation to the state before the development. In the previous studies about the LID, the runoff reduction effect is mainly discussed and the effects of each techniques of LID depending on rainfall types have not fully investigated. The objective of this research is to evaluate the effect of LID using the quantitative simulation of rainwater runoff as well as an amount of infiltration according to the rainfall and LID techniques. To evaluate the water circulation of LID on the development area, new land development areas of Hanam in South Korea is decided as the study site. In this research, hydrological model named STORM is used for the simulation of water balance associated with LID. Rainfall types are separated into two categories based on the rainfall intensity. And simulated LID techniques are green roof, permeable pavement and swale. Results of this research indicate that LID is effective on improvement of water balance in case of the low intensity rainfall event rather than the extreme event. The most effective LID technique is permeable pavement in case of the low intensity rainfall event and swale is effective in case of the high intensity rainfall event. The results of this study could be used as a reference when the spatial plan is made considering the water circulation.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1061-1069
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• 2021

Recently, the magnitude and frequency of extreme heavy rains and localized heavy rains have increased due to abnormal climate, which caused increased flood damage in river basin. As a result, the nonlinearity of the hydrological system of rivers or basins is increasing, and there is a limitation in that the lead time is insufficient to predict the water level using the existing physical-based hydrological model. This study predicted the water level at Ulsan (Taehwagyo) with a lead time of 0, 1, 2, 3, 6, 12 hours by applying deep learning techniques based on Deep Neural Network (DNN) and Long Short-Term Memory (LSTM) and evaluated the prediction accuracy. As a result, DNN model using the sliding window concept showed the highest accuracy with a correlation coefficient of 0.97 and RMSE of 0.82 m. If deep learning-based water level prediction using a DNN model is performed in the future, high prediction accuracy and sufficient lead time can be secured than water level prediction using existing physical-based hydrological models.

• Korean Journal of Ecology and Environment
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• v.34 no.1 s.93
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• pp.1-8
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• 2001

During April 1993 to November 1994, cations, anions, and conductivity were analyzed to examine how summer monsoon influences the ionic content of Taechung Reservoir, Korea. Interannual variability of ionic content reflected hydrological characteristics between the two years(high-flood year in 1993 vs. draught year in 1994). Cations, anions and conductivity were lowest during peak inflow in 1993 and highest during a drought in 1994. Floods in 1993 markedly decreased total salinity as a result of reduced Ca$^{2+}$ and HCO$_{3}\;^{-}$ and produced extreme spatial heterogeneity (i.e., longitudinal, vertical, and horizontal variation) in ionic concentrations. The dominant process modifying the longitudinal (the headwaters-to-downlake) and vertical (top-to-bottom) patterns in salinity was an interflow current during the 1993 monsoon. The interflow water plunged near a 27${\sim}$37 km-location (from the dam) of the mid-lake and passed through the 10${\sim}$30m stratum of the reservoir, resulting in an isolation of epilimnetic high conductivity water (>100 ${\mu}$S/cm) from advected river water with low conductivity (65${\sim}$75 ${\mu}$S/cm), During postmonsoon 1993, the factors regulating salinity differed spatially; salinity of downlake markedly declined as a result of dilution through the mixing of lake water with river water, whereas in the headwaters it increased due to enhanced CaCO$_{3}$ (originated from limestone/metamorphic rock) of groundwaters entering the reservoir. This result suggests an importance of the basin geology on ion compositions with hydrological characteristics. In 1994, salinity was markedly greater (p<0.001) relative to 1993 and ionic dilution did not occur during the monsoon due to reduced inflow. Overall data suggest that the primary factor influencing seasonal ionic concentrations and compositions in this system is the dilution process depending on the intensity of monsoon rainfall.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.475-488
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• 2017

To simulate accurate drought, a drought index is needed to reflect the hydrometeorological phenomenon. Several studies have been conducted in Korea using the Modified Surface Water Supply Index (MSWSI) to simulate hydrological drought. This study analyzed the limitations of MSWSI and quantified the uncertainties of MSWSI. The influence of hydrometeorological components selected as the MSWSI components was analyzed. Although the previous MSWSI dealt with only one observation for each input component such as streamflow, ground water level, precipitation, and dam inflow, this study included dam storage level and dam release as suitable characteristics of the sub-basins, and used the areal-average precipitation obtained from several observations. From the MSWSI simulations of 2001 and 2006 drought events, MSWSI of this study successfully simulated drought because MSWSI of this study followed the trend of observing the hydrometeorological data and then the accuracy of the drought simulation results was affected by the selection of the input component on the MSWSI. The influence of the selection of the probability distributions to input components on the MSWSI was analyzed, including various criteria: the Gumbel and Generalized Extreme Value (GEV) distributions for precipitation data; normal and Gumbel distributions for streamflow data; 2-parameter log-normal and Gumbel distributions for dam inflow, storage level, and release discharge data; and 3-parameter log-normal distribution for groundwater. Then, the maximum 36 MSWSIs were calculated for each sub-basin, and the ranges of MSWSI differed significantly according to the selection of probability distributions. Therefore, it was confirmed that the MSWSI results may differ depending on the probability distribution. The uncertainty occurred due to the selection of MSWSI input components and the probability distributions were quantified using the maximum entropy. The uncertainty thus increased as the number of input components increased and the uncertainty of MSWSI also increased with the application of probability distributions of input components during the flood season.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.