• 한국수자원학회논문집
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• 제35권3호
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• pp.295-306
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• 2002

지표하부에 이중 저류체계를 고려해주는 수정 TOPMODEL을 일반화된 지표하 투수량계수 감소함수와 연결시켰으며, 대공극으로의 수직배수 효과, 지표저류 효과, 토양층 내에서의 상대 저류 부족량에 대한 영향을 검토하기 위해 세가지 형태의 지하수 충전함수를 도입하였다. 이러한 접근은 사면 수문학에 대한 30가지 형태의 모형구조를 제공한다. 개발된 모형들은 설마천 유역의 여러 강우사상에 적용되었다. Monte-carlo 모의를 통한 수행결과는 지수함수적 투수량계수 감소형태가 설마천 유역의 물리적인 수문모의에 적절함을 제시하였고, 대공극 흐름을 표현해 주는 재충전 함수가 일반화시킨 수정 TOPMODEL의 예측적 향상에 기여하였다.

• 한국물환경학회지
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• 제34권6호
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• pp.569-578
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• 2018

To minimize the negative alterations in hydrologic and water quality environment in urban areas due to urbanization, Low Impact Development (LID) techniques are actively applied. In Korea, LID facilities are classified as Non-point Pollution Reduction Facilities (NPRFs), and therefore they are evaluated using the performance evaluation method for NPRFs. However, while LID facilities are generally installed in small, distributed configuration and mainly work with the infiltration process, the existing NPRFs are installed on a large scale and mainly work with the reservoir process. Therefore, some limitations are expected in assessing both facilities using the same method as they differ in properties. To solve these problems, in this study, a new method for performance evaluation was proposed with focus on bio-retention LID facilities. EPA SWMM was used to reproduce the hydrologic and water quality phenomena in study area, and SWMM-LID module used to simulate TP interception performance by installing a bio-retention cell under various conditions through long-term simulations. Finally, an empirical formula for Load Capture Ratio (LCR) was derived based on storm water interception ratio in the same form as the existing method. Using the existing formula in estimating the LCR is likely to overestimate the performance of interception for non-point pollutants in the extremely low design capacity, and also underestimate it in the moderate and high design capacity.

• 한국물환경학회지
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• 제27권3호
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• pp.273-285
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• 2011

This study describes the modeling of climate change impact on runoff across southeast Korea using a conceptual rainfall-runoff model TANK and assesses the results using the concept of environmental flows developed by International Water Management Institute. The future climate time series is obtained by scaling the historical series, informed by 4 global climate models and 3 greenhouse gas emission scenarios, to reflect a $4.0^{\circ}C$ increase at most in average surface air temperature and 31.7% increase at most in annual precipitation, using the spatio-temporal changing factor method that considers changes in the future mean seasonal rainfall and potential evapotranspiration as well as in the daily rainfall distribution. Although the simulation results from different global circulation models and greenhouse emission scenarios indicate different responses in flows to the climate change, the majority of the modeling results show that there will be more runoff in southeast Korea in the future. However, there is substantial uncertainty, with the results ranging from a 5.82% decrease to a 48.15% increase in the mean annual runoff averaged across the study area according to the corresponding climate change scenarios. We then assess the hydrologic perturbations based on the comparison between present and future flow duration curves suggested by IMWI. As a result, the effect of hydrologic perturbation on aquatic ecosystems may be significant at several locations of the Nakdong river main stream in dry season.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.372-372
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• 2021

The agriculture sector plays a vital role in the economy of Pakistan by contributing about 20% of the GDP and 42% of the labor force. Rivers from the top of Himalayas are the major water resources for this agriculture sector. Recent reports have found that Pakistan is one of the most vulnerable country to climate change that can cause water scarcity which is a big challenge to the communities. Previous studies have investigated the impact of climate change on the trend of streamflow, but the understanding of seasonal change in the regional hydrologic regimes remained limited. Therefore, a better understanding of the seasonal hydrologic change will help cope with the future water scarcity issue. In this study, we used the daily stream flow data for four major river basins of Pakistan (Chenab, Indus, Jhelum and Kabul) over 1962 - 2019. Utilizing these daily river discharge data, we calculated the winter-spring center time and the summer-autumn center times. In this study Winter-spring center time (WSCT) is defined as the day of the calendar year during which half of the total six months (Jan-Jun) discharge volume was exceeded. Results show that the four river basins experienced a statistically significant decreasing trend of WSCT, that is the center time keeps coming earlier compared to the past. We further used the Climate Research Unit (CRU) climate data comprising of the average temperature and precipitation for the four basins and found that the increasing average temperature value causes the early melting of the snow covers and glaciers that resulted in the decreasing of 1^st center time value by 4 to 8 days. The findings of this study informs an alarming situation for the agriculture sector specifically.

• Water Engineering Research
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• 제5권2호
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• pp.81-99
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• 2004

Long term streamflow regime under virtual climate change scenario was examined. Rainfall forecast simulation of the Canadian Global Coupled Model (CGCM2) of the Canadian Climate Center for modeling and analysis for the IPCC SRES B2 scenario was used for analysis. The B2 scenario envisions slower population growth (10.4 billion by 2010) with a more rapidly evolving economy and more emphasis on environmental protection. The relatively large scale of GCM hinders the accurate computation of the important streamflow characteristics such as the peak flow rate and lag time, etc. The GCM rainfall with more than 100km scale was downscaled to 2km-scale using the space-time stochastic random cascade model. The HEC-HMS was used for distributed hydrologic model which can take the grid rainfall as input data. The result illustrates that the annual variation of the total runoff and the peak flow can be much greater than rainfall variation, which means actual impact of rainfall variation for the available water resources can be much greater than the extent of the rainfall variation.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.1008-1013
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• 2007

The objectives of the paper were to identify appropriate best management practices (BMPs) for reducing nonpoint source (NPS) pollutant loadings and to simulate the effects of the application of the several BMP scenarios on the study watershed using Agricultural Nonpoint Source (AGNPS) model. AGNPS model was calibrated and validated for runoff, sediment yield, and nutrient components using the observed hydrologic and water quality data. The simulated runoff, sediment, and nutrient components were well agreed with observed data. The validated AGNPS was applied to estimate the NPS pollution removal efficiency for BMP scenarios which were selected considering the pollutant characteristics of the study watershed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1645-1648
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of recurrent neural networks model (RNNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of RNNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1346-1349
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• 2010

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국환경과학회지
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• 제24권8호
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• pp.1065-1073
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• 2015

Urbanization can be significantly affected the hydrologic cycle by increasing flood discharge and heat flux. In order to mitigate these modifications in urban areas, Low Impact Development (LID) technique has been designed and applied in Korea. In order to estimate runoff reduction rate using SWMM LID model, the characteristics of five LID techniques was firstly analyzed for water balance. Vegetated swale and green roof were not reduce flood discharge nor infiltration amount. On the other hand, porous pavement and infiltration trench were captured by infiltration function. The flood reduction rate with LID is substantially affected by their structures and properties, e.g., the percentage of the area installed with LID components and the percentage of the drainage area of the LID components.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.562-562
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• 2015

하천의 유황특성을 분석하는 것은 하천생태계의 변화를 파악하고 예측하는데 있어 매우 중요하다고 할 수 있다. 최근에는 수문학적인 변화과정을 통계학적 기법을 적용하여 정량적인 지표로 산정하고 분석하는 모델을 개발하여 다양한 연구가 진행되고 있다. 특히 미국 Nature Conservancy에서 개발한 수문변화지표법(IHA)은 일(daily)유출량 자료로부터 수문학적 관점에서의 특성지표와 환경유량 관점에의 변화지표를 분석함으로써 하천 유황변동을 정량화 할 수 있다. 본 연구는 기후변화가 향후 하천유황과 수생태계에 미치는 영향을 분석하기 위해 중규모 하천유역인 만경강을 대상으로 하고 RCP 8.5 기후변화시나리오를 기반으로 준분포형 모형인 SLURP 모형으로부터 일(daily)단위의 유출모의 시나리오를 작성하였다. 그리고 수문변화지표법(IHA)을 이용하여 기후변화에 따른 하천 유황과 수생태계에 미치는 영향을 정량화하였다.