• Journal of Environmental Science International
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• v.14 no.8
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• pp.739-748
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• 2005

The purpose of this study is to analyze seasonal changes in structure and landscape of Gongji stream corridor in Chuncheon, and to suggest some guidelines to contribute to creating a desirable close-to- nature stream. The study seasonally surveyed floodplain and revetment conditions, channel micro-topography, streamflow level and velocity, and vegetational cover. Flooding, water level, and vegetation were major factors of affecting seasonal changes in streambed structure and stream landscape. Small sand bars and islands were considerably disturbed by flooding and water level change. However, large islands and sand bars in the upper and middle section of the study stream remained or reappeared even after flooding. Flooding also tended to repeat channel sedimentation at the same spot. Controlling water volume of the Euiam Lake, which is adjacent to the study stream, caused higher water level downstream in the dry seasons. The majority of vegetation in sand bars and islands was washed away by the floods. Vehicle passing, crop cultivation, and ball game were other elements which disturbed vegetation in the floodplain. Creating a close-to-nature stream should reflect micro-topographical changes of channel by flooding, prevent improper vehicle entry and human use, and remove concrete material in the revetment and floodplain.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.6
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• pp.129-137
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• 2014

This research presents an streamflow modeling approach in a data-scarce estuary reservoir watershed which has been suffered from high salinity irrigation water problem after completion of land reclamation project in South Korea. Since limited hydrology data was available on the Iwon estuary reservoir watershed, water balance relation of the reservoir was used to estimate runoff from upstream of the reservoir. Water balance components in the reservoir consists precipitation, inflow from upstream, discharge through sluice, and evaporation. Estimated daily inflow data, which is stream discharge from upstream, shows a good consistency with the observed water level data in the reservoir in terms of EI (0.93) and $R^2$ (0.94), and were used as observed flow data for the streamflow modeling. HSPF (Hydrological Simulation Program - Fortran) was used to simulate hydrologic response of upstream of the reservoir. The model was calibrated and validated for the periods of 2006 to 2007 and 2008 to 2009, respectively, showing that values of EI and $R^2$ were 0.89 and 0.91 for calibration period, 0.71 and 0.84 for validation period.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.169-169
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• 2020

According to the IPCC analysis, severe climate changes are projected to occur in Korea as the temperature is expected to rise by 3.2 ℃, the precipitation by 15.6% and the sea level by 27cm by 2050. It is predicted that the occurrence of abnormal climate phenomena - especially those such as increase of concentrated precipitation and extreme heat in the summer season and severe drought in the winter season - that have happened in Korea in the past 30 years (1981-2010) will continuously be intensified and accelerated. As a result, the impact on and vulnerability of the water management sector is expected to be exacerbated. This research aims to predict the climate change impacts on streamflow of Daecheong Lake area of Geum River in South Korea during the summer and winter seasons, which show extreme meteorological events, and ultimately develop an integrated policy model in response. We projected and compared the streamflow changes of Daecheong Lake area of Geum River in South Korea in the near future period (2020-2040) and the far future period (2041-2060) with the reference period (1991-2010) using the HEC-HMS model. The data from a global climate model HadGEM2-AO, which is the fully-coupled atmosphere-ocean version of the Hadley Centre Global Environment Model 2, and RCP scenarios (RCP4.5 and RCP8.5) were used as inputs for the HEC-HMS model to identify the river basins where cases of extreme flooding or drought are likely to occur in the near and far future. The projections were made for the summer season (July-September) and the winter season(November-January) in order to reflect the summer monsoon and the dry winter. The results are anticipated to be used by policy makers for preparation of adaptation plans to secure water resources in the nation.

• Journal of Korean Society on Water Environment
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• v.28 no.6
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• pp.819-832
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• 2012

HSPF model based on BASINS was applied for the Hwaseong Reservoir watershed (HRW) to evaluate the feasibility of water quality management. The watershed was divided into 45 sub-basins considering various watershed environment. Streamflow was calibrated based on the measured meteorological data, discharge data of treatment plants and observed streamflow data for 2010 year. Then the model was calibrated against the field measurements of water qualities, including BOD, T-N and T-P. In most cases, there were reasonable agreements between observed and predicted data. The validated model was used to analyze the characterization of pollutant load from study area. As a result, Non-point source pollutant loads during the rainy season was about 66~78% of total loads. In rainy-season, water quality parameters depended on precipitation and pollutant loads patterns, but their concentration were not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. As another result of evaluation for load duration curves, in order to improve water qualities to the satisfactory level, the watershed managements considering both time-variant and pollution sources must be required in the HRW. Overall, it was found that the model could be used conveniently to assess watershed characteristics and pollutant loads in watershed scale.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.165-170
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• 2011

Recently natural disasters such as the frequency and intensity of drought have been increasing as a result of climate change. This study suggests a drought index, WADI (Water Availability Drought Index), that considers water availability using 6 components (water intake, groundwater level, agricultural reservoir water level, dam inflow, streamflow, and precipitation) using the Z score and data monitoring on a nationwide level. SPI (Standardized Precipitation Index) was applied in coastal area. For the severe droughts of 2001 spring and 2008 autumn, the index was evaluated by comparison with reported damage areas. suggested to combine The spatial concordance rate of WADI in 2001 and 2008 for estimation of the degree of drought severity was 50 % and 24 % compared to the actual recorded data respectively.

• Journal of Korea Water Resources Association
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• v.49 no.10
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• pp.835-849
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• 2016

Accurate drought outlook and drought monitoring have been preceded recently to mitigate drought damages that further deepen. This study improved the limitations of the previous MSWSI (Modified Surface Water Supply Index) used in Korea and carried out probabilistic drought forecasts based on ensemble technique with the improved MSWSI. This study investigated available hydrometeorological components in Geum river basin and supplemented appropriate components (dam water level, dam release discharge) in addition to the four components (streamflow, groundwater, precipitation, dam inflow) usedin the previous MSWSI to each sub-basin. Although normal distribution was fitted in the previous MSWSI, the most suitable probabilistic distributions to each meteorological component were estimated in this study, including Gumbel distribution for precipitation and streamflow data; 2-parameter log-normal distribution for dam inflow, water level, and release discharge data; 3-parameter log-normal distribution for groundwater. To verify the improved MSWSI results using historical precipitation and streamflow, simulated drought situations were used. Results revealed that the improved MSWSI results were closer to actual drought than previous MSWSI results. The probabilistic forecasts based on ensemble technique with improved MSWSI were performed and evaluated in 2006 and 2014. The accuracy of the improved MSWSI was better than the previous MSWSI. Moreover, the drought index of actual drought was included in ranges of drought forecasts using the improved MSWSI.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.605-616
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• 2020

The purpose of this study is to assess the future hydrological and water quality change of Man-gyeong river basin (1,602 ㎢) based on future extreme climate change scenarios and reduction of inter-basin water transfer amount using SWAT (Soil and Water Assessment Tool). The SWAT was calibrated (2012~2014) and validated (2016~2018) at 2 water level observation stations (DC, JJ) and 2 water quality observation stations (SR, GJ) considering inter-basin water transfer amount, stream water withdrawal, and point source data. For the streamflow, the coefficient of determination (R²) was 0.70 and the average Nash-Sutcliffe efficiency (NSE) was 0.51 respectively. For the water quality of SS, T-N, and T-P, the R² was 0.72, 0.80 and 0.72 respectively. The future average streamflow under climate change scenarios increased up to 459 mm/yr, and average SS, T-N and T-P yields also increased up to 19,548 ton/yr, 68,748 kg/yr, and 13,728 kg/yr respectively. When the amount of inter basin water transfer decreased, the streamflow especially decreased in spring and winter periods, and the future water quality yields increased under the influence of precipitation. In order to solve the deterioration of water quality due to decrease in the flow rate and an increase in the load, the amount of inter basin water transfer should be maintained to a certain level.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.525-536
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• 2014

In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.138-138
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• 2022

Understanding a stream's or river's discharge is essential for a variety of hydrological and geomorphological applications at various sizes. However, depending on the stream environment and flow conditions, it is crucial to use the appropriate techniques and instruments. This will ensure that discharge estimations are as reliable as possible. This study presents developed smart system for continuous measurement of open channel discharge and evaluate streamflow measurement over various techniques. This includes developed smart flow meter as flow point measurements, smart water level sensor (installed on Hydraulic Structure ? Weir) and current meters. Advantages and disadvantages of each equipment are presented to ensure that the most appropriate method can be selected. we found that smart water level sensor is more prominent once used during flood event as compared to smart flow meter and current meters, while current meters seems to show better accuracy once applied for open channel.