• Journal of Korea Water Resources Association
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• v.38 no.6 s.155
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• pp.471-483
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• 2005

A monthly Ensemble Streamflow Prediction (ESP) system was developed by applying a daily rainfall-runoff model known as the Streamflow Synthesis and Reservoir Regulation (SSARR) model to the Han, Nakdong, and Seomjin River basins in Korea. This study first assesses the accuracy of the averaged monthly runoffs simulated by SSARR for the 3 basins and proposes some improvements. The study found that the SSARR modeling of the Han and Nakdong River basins tended to significantly underestimate the actual runoff levels and the modeling of the Seomjin River basinshowed a large error variance. However, by implementing optimal linear correction (OLC), the accuracy of the SSARR model was considerably improved in predicting averaged monthly runoffs of the Han and Nakdong River basins. This improvement was not seen in the modeling of the Seomjin River basin. In addition, the ESP system was applied to forecast probabilistic runoff forecasts one month in advance for the 3 river basins from 1998 to 2003. Considerably improvement was also achieved with OLC in probabilistic forecasting accuracy for the Han and Nakdong River basins, but not in that of the Seomjin River basin.

• Journal of Korean Society on Water Environment
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• v.34 no.4
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• pp.382-390
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• 2018

In this study, the LIDMOD3 was developed to design and evaluate low impact development (LIDMOD). In the same fashion, the LIDMOD3 employs a curve number (NRCS-CN) method to estimate the surface runoff, infiltration and event mean concentration as applicable to pollutant loads which are based on a daily time step. In these terms, the LIDMOD3 can consider a hydrologic soil group for each land use type LID-BMP, and the applied removal efficiency of the surface runoff and pollutant loads by virtue of the stored capacity, which was calculated by analyzing the recorded water balance. As a result of Model development, the LIDMOD3 is based on an Excel spread sheet and consists of 8 sheets of information data, including: General information, Annual precipitation, Land use, Drainage area, LID-BMPs, Cals-cap, Parameters, and the Results. In addition, the LIDMOD3 can estimate the annual hydrology and annual pollutant loads including surface runoff and infiltration, the LID efficiency of the estimated surface runoff for a design rainfall event, and an analysis of the peak flow and time to peak using a unit hydrolograph for pre-development, post-development without LID, and as calculated with LID. As a result of the model application as applied to an apartment, the LIDMOD3 can estimate LID-BMPs considering a well spatical distributed hydroloic soil group as realized on land use and with the LID-BMPs. Essentially, the LIDMOD3 is a screen level and simple model which is easy to use because it is an Excel based model, as are most parameters in the database. This system can be expected to be widely used at the LID site to collect data within various programmable model parameters for the processing of a detail LID model simulation.

• Smart Media Journal
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• v.6 no.2
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• pp.50-56
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• 2017

Due to new social environment, expenditure on eating out has increased over the last few year, thereafter the food-tech industries have steadily grown as well. We have studied what variable would affect customer's choices when they plan to eat out or order in. There are two variables are taken into account to prove it. Firstly, it is climate changes, such as an amount of rainfall, snowfall and clouds. Secondly, it is days, such as seasons and holidays. Based on this, we looked up the SikSin user's behaviors patterns, then did analysis of the daily data provided by the Meteorological office. By the end of the study, it turned out that two variables, climate changes and days, both have a strong influence on customer's choices. It is considered that this research outcome will make contributions to small businesses founders who want to take the initiative, marketing managers and people who are engaged in the food-tech industry.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.158-158
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• 2018

Drought is a recurrent natural hazard in Bangladesh. It has significant impacts on agriculture, environment, and society. Well-timed information on the onset, extent, intensity, duration, and impacts of drought can mitigate the potential drought-related losses. Thus, drought characteristics need to be explained in terms of frequency, severity, and duration. This paper aims to characterize the spatial and temporal pattern of meteorological drought using EDI and illustrated drought severity over Bangladesh. Twenty-seven (27) station-based daily rainfall data for the study period of 1981-2015 were used to calculate the EDI values over Bangladesh. The evaluation of EDI is conducted for 4 sub-regions over the country to confirm the historical drought record-developed at the regional scale. The finding shows that on average, the frequency of severe to extreme drought is approximately 0.7 events per year. As a result of the regional analysis, most of the recorded historical drought events were successfully detected during the study period. Additionally, the seasonal analysis showed that the extreme droughts were frequently hit in northwestern, middle portion of the eastern and small portion of central parts of Bangladesh during the Kharif(wet) and Rabi(dry) seasons. The severe drought was affected recurrently in the central and northern regions of the country during all cropping seasons. The study also points out that the northern, south-western and central regions in Bangladesh are comparatively vulnerable to both extreme and severe drought event. The study showed that EDI would be a useful tool to identify the drought-prone area and time and potentially applicable to the climate change-induced drought evolution monitoring at regional to the national level in Bangladesh. The outcome of the present study can be used in taking anticipatory strategies to mitigate the drought damages on agricultural production as well as human sufferings in drought-prone areas of Bangladesh.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.17-17
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• 2019

IPCC (Intergovernmental Panel on Climate Change) 기후변화 전망보고서에 따르면 RCP 4.5 시나리오 기준, 21세기 전 지구 평균기온은 $2.5^{\circ}C$ 상승(한반도 $+3.0^{\circ}C$)하며, 전 지구 평균강수량은 4.1% 증가(한반도 +16.0%)할 것이라 전망하고 있다(기상청, 2012). 최근 기후변화와 기상이변에 따른 도심지 폭우특성이 변화하고 있음을 많은 연구결과에서 말해주고 있으며, 그 발생 빈도와 강도가 점차 증가하고 있는 추세이다. 특히, 서울시의 경우 인구와 재산이 밀집해 있어 폭우 발생에 의한 시민의 인명과 재산 피해 우려가 크다. 따라서 본 연구에서는 서울시를 대상으로 근미래(~2050년) 기후변화 하에서의 재현기간에 따른 확률강우량 변화 특성을 분석하여 비교 평가한 후 설계 강우량 산정에 활용하고자 하였다. 관측자료 기반 강수량의 변동 특성 분석과 Non-stationary GEV방법을 이용한 비정상성 빈도해석을 수행하였으며, 근미래 폭우특성 변화분석을 위하여 CMIP5 (Coupled Model Intercomparison Project 5)에 참여한 GCMs(General Circulation Models)을 활용한 강우빈도해석을 수행하였다. Mann-Kendall Test와 Quantile Regression을 통한 서울지점 여름철 강수량(June to September)과 기준강수량 초과 강수(30, 50, 80, 100mm/hr), 연간 10th 최대 강수량(Annual Top 10th Precipitation) 등을 분석한 결과 최근 증가 경향이 뚜렷하게 나타났으며, 비정상성 빈도해석에 의한 확률강우량 분석의 가능성과 신뢰성을 확인하였다. 또한 19-GCMs을 통하여 모의된 일(Daily) 단위 강수량자료를 비모수통계적 상세화(Nonparametric Temporal Downscaling) 기법을 적용하여 시간(Hourly) 강우로 다운스케일링하였으며, 서울시 미래 확률강우량에 대한 IDF 곡선(Intensity-Duration-Frequency Curve)을 작성하여 비교?분석한 결과 지속시간 1시간 강우에 대하여 재현기간 30년, 100년 조건에서 확률강우량이 약 4%~11% 수준에서 증가하고 있음을 확인하였다. 본 연구의 결과는 도심지 수공구조물의 설계빈도 영향을 진단하고, 근미래 발생가능한 확률강우량 변화에 따른 시간당 목표 강우량설정의 방법론을 제시하였다는데 의의가 있으며, 서울시의 방재성능목표 설정과 침수취약지역 해소를 위한 기후변화에 따른 수공구조물 설계 시 활용이 가능할 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.545-552
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• 2021

The burden of flood control on the dam under frequently flood due to climate change and especially heavy flood in 2020 year are come to the forward and increased. The objective of the study is therefore to establish the method to estimate capacity and target water level for flood control in actual dam management. Frequency matching method was applied to establish a pair of cumulative distribution function (CDF) based on daily dam inflow and discharge records. The relationship between dam storage and discharge volume represented as a percentage of inflow volume was derived and its characteristics was analyzed. As the result, the Soyanggang (45%) and Chungju Dam (39%) contributing to flood control with temporarily storing flood runoff. The method and diagram to estimate flood control capacity and target water level for flood control in the dam were established. The result of the study could be used as a supplementary data for flood control of the dam according to the rainfall prediction on the Korea Meteorological Administration.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.109-123
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• 2017

The effects of recent climate change on hydrological systems could affect the Winter Olympic Games (WOG) because the event is dependent on suitable snow and ice conditions to support elite-level competitions. We investigate the long-term variability and change in winter total precipitation (P), snowfall water equivalent (SFE), and ratios of SFE to P during the period 1973/74~2015/16 in Gangwon province. The climatological percentages of SFE relative to winter total precipitation were 71%, 28%, and 44% in Daegwallyeong, Chuncheon, and Gangneung, respectively. The winter total P, SFE, and SFE/P has decreased (but not significantly), although significant increases of winter maximum and minimum temperature were detected at a 95% confidence level. Notably, a significant negative trend of SFE/P at Daegwallyeong in February, the month of the WOG, was attributable to a larger decrease in SFE related to the increases in maximum and minimum temperature. Winter wet-day minimum temperatures were warmer than climatological minimum temperatures averaged over the study period. The 20-year return values of daily maximum P and SFE decreased in Yongdong area. Since the SFE/P decrease with increasing temperature, the probability of rainfall rather than snowfall can increase if global warming continues.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.83-83
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• 2017

수자원공학에서 일강수량 모의기법은 다양한 목적으로 활용되고 있지만, 일반적으로 홍수와 가뭄의 영향을 고려할 수 있는 수공구조물의 위험도 및 신뢰성 평가 및 수자원 계획을 수립하기 위한 입력 자료생성을 목적으로 활용된다. 유역 단위의 분석시 단일 지점에 대한 강수 모의 기법을 적용할 경우 각각의 지점에서 관측된 강수 자료의 시계열 및 통계치 특성이 효과적으로 재현되지만 공간적으로 발생하는 즉, 지점 간의 종속관계를 재현하지 못하는 문제가 발생한다. 이러한 이유로 공간적인 전이 특성이 있는 가뭄 분석 및 유역내 유출량의 공간적 변동 특성 분석에 단일지점별 모의 결과를 이용할 경우 관측 자료와 상반된 공간적 변동성으로 인하여 잘못된 가뭄 및 유출 분석 결과가 도출되는 문제점이 있다. 따라서, 실제적으로 발생하는 강수 특성을 반영한 유역 단위의 홍수 및 가뭄 등의 수문 분석을 위해서는 지점간의 종속성을 반영할 수 있는 다지점 강수 모의 모형의 적용이 필수적이다. 본 연구에서는 다지점 모의에 있어서, Wilks 모형의 지점별 시변동 특성과 공간상관성 재현 능력, HMM 모형이 갖는 강수 사상별로 분포된 양적 분포 패턴 재현 능력을 복합적으로 나타낼 수 있는 새로운 다지점 일강수량 모의 모형인 기계학습 기반 범주화 기법을 이용한 다지점 일강수량 모의 모형(ML-MRS)을 개발하였다. 또한, 지점별 강수량에 적용되는 확률분포모형은 Gamma 분포로 구성된 혼합모형을 적용하여 단일 확률 분포 모형의 자료 적합 문제를 개선하였다. 모의를 통한 일강수량 시계열 자료는 일 강수자료의 통계량을 효과적으로 모의하였으며, 다지점 모형의 모의 결과를 적용한 가뭄 모의 결과 관측 자료에서 나타나는 공간적 패턴이 재현되었다. 본 모형은 시 공간적 사상을 효과적으로 재현함으로서 지역의 변동특성을 반영한 가뭄, 홍수, 기상 현상 분석 등 활용도가 매우 높을 것으로 판단된다.