• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1B
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• pp.11-22
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• 2009

Long-term rainfall-runoff modeling is a key element in the Earth's hydrological cycle, and associated with many different aspects such as dam design, drought management, river management flow, reservoir management for water supply, water right permission or coordinate, water quality prediction. In this regard, hydrologists have used the hydrologic models for design criteria, water resources assessment, planning and management as a main tool. Most of rainfall-runoff studies, however, were not carefully performed in terms of considering reservoir effects. In particular, the downstream where is severely affected by reservoir was poorly dealt in modeling rainfall-runoff process. Moreover, the effects can considerably affect overall the rainfallrunoff process. An objective of this study, thus, is to evaluate the impact of reservoir operation on rainfall-runoff process. The proposed approach is applied to Anseong watershed, where is in a mixed rural/urban setting of the area and in Korea, and has been experienced by flood damage due to heavy rainfall. It has been greatly paid attention to the agricultural reservoirs in terms of flood protection in Korea. To further investigate the reservoir effects, a comprehensive assessment for the results are discussed. Results of simulations that included reservoir in the model showed the effect of storage appeared in spring and autumn when rainfall was not concentrated. In periods of heavy rainfall, however, downstream runoff increased in simulations that do not consider reservoir factor. Flow duration curve showed that changes in streamflow depending upon the presence or absence of reservoir factor were particularly noticeable in ninety-five day flow and low flow.

• Ecology and Resilient Infrastructure
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• v.6 no.1
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• pp.34-48
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• 2019

Naeseong Stream is a natural sand-bed river that flows through mountainous and cultivated area in northern part of Gyeongbuk province. It had maintained its inherent landscape characterized by white sandbars before 2010s. However, since then changes occurred, which include construction of Yeongju Dam and the extensive vegetation development around 2015. In this study, long-term monitoring was carried out on Naeseong Stream to analyze these changes objectively. This paper aims to provide a dataset of the investigation on channel morphology and vegetation for the period 2012-2018. Methods of investigation include drone/terrestrial photography, LiDAR aerial survey and on-site fieldwork. The main findings are as follows. Vegetation development in the channel of Naeseong Stream began around 1987. Before 2013 it occurred along the downstream reach and since then in the entire reach. Some of the sites where riverbed is covered with vegetation during 2014~2015 were rejuvenated to bare bars due to the floods afterwards, but woody vegetation was established in many sites. Bed changes occurred due to deposition of sediment on the vegetated surfaces. Though Naeseong Stream has maintained its substantial sand-bed characteristics, there has been a slight tendency in bed material coarsening. Riverbed degradation at the thalweg was observed in the surveyed cross sections. Considering all the results together with the hydrological characteristics mentioned in the precedent paper (I), it is thought that the change in vegetation and landscape along Naeseong Stream was mainly due to decrease of flow. The effect of Yeongju Dam on the change of the riverbed degradation was briefly discussed as well.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.470-478
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• 2017

This study was classified into two groups, normal season group and drought season group, by the cluster analysis using the weather and water quality data from 2012 to 2015, using SPSS 18 version. Also each cluster was classified into three spaces, Gangcheon, Yeoju and Ipoh weir. We performed the multiple regression analysis with each monthly data that concentration of Chl-a was more than algae warming level. 6 groups classified in time and space were analyzed by the correlation analysis between concentration of Chl-a and 3 weather, 11 water quality and discharge factors. We developed Chl-a prediction equations of each group with independent variables of the multiple regression analysis applying to the correlation result. The result of cluster analysis was that the period was divided into two groups, normal group(2012-2013) that total annual precipitation rate was normal and drought group(2014-2015) that total annual precipitation rate was less than 1,000 mm/hr, in time. The months that concentration of Chl-a was more than algae warming level in each group classified by cluster analysis were that the normal group was 3~8 and drought group was 3 and 6~10. The correlation result between Chl-a and weather, water quality and discharge factors for each 6 group was that relationships between Chl-a and water, discharge factors were high in the drought group more than in normal group at all weirs. This was influenced by velocity reduction and increasing HRT according to the intense drought. Weather, water quality and discharge factors that were high correlation with Chl-a were applied to independent variables of Chl-a prediction equations and each equations were developed. Among them, Each adjusted R square of Prediction equations for Chl-a in each group at Ipoh weir where is located in Namhan river downstream and is directly connected to Paldang dam were normal group = 0.920 and drought group = 0.818. It's showed the high linear.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.