• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.1
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• pp.27-38
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• 2012

This study is to analyse the hydrological behavior of agricultural reservoir using CAT (Catchment hydrologic cycle Assessment Tool). The CAT is a water cycle analysis model in order to quantitatively assess the characteristics of the short/long-term changes in watershed. It supports the effective design of water cycle improvement facilities by supplementing the strengths and weaknesses of existing conceptual parameter-based lumped hydrologic models and physical parameter-based distributed hydrologic models. The CAT especially supports the analysis of runoff processes in paddy fields and reservoirs. To evaluate the impact of agricultural reservoir operation and irrigation water supply on long-term rainfall-runoff process, the CAT was applied to Idong experimental catchment, operated for research on the rural catchment characteristics and accumulated long term data by hydrological observation equipments since 2000. From the results of the main control points, Idong, Yongdeok and Misan reservoirs, the daily water levels of those points are consistent well with observed water levels, and the Nash-Sutcliffe model efficiencies were 0.32~0.89 (2001~2007) and correlation coefficients were 0.73~0.98.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.6
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• pp.3-10
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• 2004

The fundamental study of hydrologic redesign of Donghwa area located in a sccond tributary of Seomjin river was performed. The amounts of hydrologic design were estimated using the available cumulated hydrology data provided by Korea Agricultural and Rural Infrastructure Corporation (KARICO). The management status of The water resources in Donghwa area was also widely surveyed. The probability rainfalls, probable maximum precipitation (PMP) and probability floods were estimated and subsequently their changes analyzed. The amount of 200 year frequency rainfall with l day duration was 351.1 mm, 2.5 % increased from the original design value, and The PMP was 780.2 mm. The concentration time was reestimated as 2.5 hours from existing 2.4 hours. Soil Conservation Service(SCS) method was used to estimate effective rainfall- The runoff curve number was changed from 90 to 78, therefore the maximum potential retention was 71.6 mm, 154 % increased from the original value. The Hood estimates using SCS unit hydrograph showed 8 % increase from original value 623 $m^3$/s to 674 $m^3$/s and The probable maximum Hood was 1,637 $m^3$/s. Although the Row rate at the dam site was increased, the Hood risk at the downstream river was decreased by the Hood control of the Donghwa dam.

• Journal of Korea Water Resources Association
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• v.34 no.5
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• pp.511-519
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• 2001

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$is thought to be the main cause for glogal warming, its impact on global climate has not been revealed clearly in rather quantitative manners. The objective of this research is to predict the hydrological environment changes in the Daechung Dam basin due to the global warming. A mesoscale atmospheric/hydrologic model (IRSHAM96 model) is used to predict the possible changes in precipitation and temperature in the Daechun Dam basin. The simulation results of IRSHAM96 model and a conceptual water balance model are used to analyze the changes in soil moisture, evapotranspiration and runoff in the Daechung Dam basin. From the simulation results using the water balance model for 1x$CO_2$and 2x$CO_2$situations, it has been found that the runoff would be decreased in dry season, but increased in wet season due to the global warming. Therefore, it is predicted that the frequency of drought and flood occurrences in the Daechung Dam basin would be increased in 2x$CO_2$condition.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.501-506
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• 2001

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.509-522
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• 2021

In many countries, including Korea, it has been challenging to understand flood-related social dynamics due to urbanization and climate change. In this regard, socio-hydrology has been proposed to consider the interaction between hydrologic systems, land-use change, and human activities. However, there is a general lack of understanding of the interactions of socio-hydrologicsystems. This study examines the interactions between human activities and hydrologic systems from a sociological perspective using a dynamic system model. In other words, this study aims to present a conceptualization model that considers the mutual interaction of flood and community from a socio-hydrologic perspective. Depending on the construction cost of the levee for the Yangjae River, this study considered three scenarios to simulate the interaction of socio-hydrologic systems. Socio-hydrologic interactions can effectively reproduce the changes in the Yangjae River. Moreover, It is expected that the proposed model can be further used to understand possible hydrologic changes and interaction with social systems in the future as a decision-making tool in water resources management.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.121-121
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• 2020

Varying dominant processes, including Tropical Cyclone (TC) and non-TC rainfall events, have been known to drive the occurrence of precipitation in South Korea. With the changes in the pattern of the Earth's climate due to anthropogenic activities, nonstationarity or changes in the magnitude and frequency of these dominant processes have been separately observed for the past decades and are expected to continue in the coming years. These changes often cause unprecedented hydrologic events such as extreme flooding which pose a greater risk to the society. This study aims to take into account a more reliable future climate condition with two dominant processes. Diverse statistical models including the hidden markov chain, K-nearest neighbor algorithm, and quantile mappings are utilized to mimic future rainfall events based on the recorded historical data with the consideration of the varying effects of TC and non-TC events. The data generated is then utilized to the hydrologic model to conduct a flood frequency analysis. Results in this study emphasize the need to consider the nonstationarity of design rainfalls to fully grasp the degree of future flooding events when designing urban water infrastructures.

• 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.57 no.2
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• pp.15-26
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• 2015

The purpose of this paper is to develop a software tool, PGA-CC (Projection of hydrology via Grid-based Assessment for Climate Change) to evaluate the present hydrologic cycle and the future watershed hydrology by climate change. PGA-CC is composed of grid-based input data pre-processing module, hydrologic cycle calculation module, output analysis module, and output data post-processing module. The grid-based hydrological model was coded by Fortran and compiled using Compaq Fortran 6.6c, and the Graphic User Interface was developed by using Visual C#. Other most elements viz. Table and Graph, and GIS functions were implemented by MapWindow. The applicability of PGA-CC was tested by assessing the future hydrology of South Korea by HadCM3 SRES B1 and A2 climate change scenarios. For the whole country, the tool successfully assessed the future hydrological components including input data and evapotranspiration, soil moisture, surface runoff, lateral flow, base flow etc. From the spatial outputs, we could understand the hydrological changes both seasonally and regionally.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.50-52
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• 2003

The purpose of this study is to evaluate the hydrological impact due to temporal land cover changes by gradual urbanization of a watershed. WMS HEC-1 was adopted, and DEM with 200m resolution and hydrologic soil group from 1:50,000 soil map were prepared. Land covers of 1986, 1990, 1994 and 1999 Landsat TM images were classified by maximum likelihood method. By applying the model, watershed average CN value was affected in the order of paddy, forest and urban/residential, respectively.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.25-33
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• 2008

To investigate the hydrologic impacts of climate changes on dam inflow for Soyanggangdam watershed $(2694.4km^2)$ of northeastern South Korea, SLURP (Semi-distributed Land Use-based Runoff Process) model and the climate change results of CCCma CGCM2 based on SRES A2 and B2 were adopted. By the CA-Markov technique, future land use changes were estimated using the three land cover maps (1985, 1990, 2000) classified by Landsat TM satellite images. NDVI values for 2050 and 2100 land uses were estimated from the relationship of NDVI-Temperature linear regression derived from the observed data (1998-2002). Before the assessment, the SLURP model was calibrated and verified using 4 years (1998-2001) dam inflow data with the Nash-Sutcliffe efficiencies of 0.61 to 0.77. In case of A2 scenario, the dam inflows of 2050 and 2100 decreased 49.7 % and 25.0 % comparing with the dam inflow of 2000, and in case of B2 scenario, the dam inflows of 2050 and 2100 decreased 45.3 % and 53.0 %, respectively. The results showed that the impact of land use change covered 2.3 % to 4.9 % for the dam inflow change.