• Water for future
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• v.28 no.1
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• pp.81-90
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• 1995

This study attempts to develop a stochastic system model for extension and prediction of monthly runoff series in river basins where the observed runoff data are insufficient although there are long-term hydrometeorological records. For this purpose, univariate models of a seasonal ARIMA type are derived from the time series analysis of monthly runoff, monthly precipitation and monthly evaporation data with trend and periodicity. Also, a causual model of multiple input-single output relationship that take monthly precipitation and monthly evaporation as input variables-monthly runoff as output variable is built by the cross-correlation analysis of each series. The performance of the univariate model and the multiple input-output model were examined through comparisons between the historical and the generated monthly runoff series. The results reveals that the multiple input-output model leads to the improved accuracy and wide range of applicability when extension and prediction of monthly runoff series is required.

• Water for future
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• v.24 no.3
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• pp.95-104
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• 1991

The study was focused on developing a new model to estimate annual runoff. This model can be used to estimate the available water resources for ungaged catchments for long-term water resources development planning. Data used in the model development were daily rainfall and daily runoff of the sample basin with record length from 1945 to 1988 years in Korea. The sample basin selected by consideration whether the flow is virgin and quality of discharge data is good. As a result, 46 stage gaging station were selected. Annual runoff was determined by sum of daily runoff calculated by daily stage data of the sample basin. Also, the annual mean precipitation by using daily rainfall data was estimated and the annual runoff ratio for each sample basin was calculated, and the annual mean runoff ratio was estimated. The linear regression model was proposed and calibrated using auunal mean precipitation values and geomorphological characteristics of the basins. To verify reasonableness of this model, the regression model was applied to the gaging stations which have historical data.

• KIEAE Journal
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• v.6 no.3
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• pp.27-34
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• 2006

The recent emphasis on ecological urban development has led to the need to maintain a hydrologic cycle in urban areas. As such, this study proposes decentralized rainwater management, a concept of onsite rainwater management that involves the utilization, infiltration, detention, and retention of rainwater. The main objective of this research is to estimate the proportion of decentralized rainwater management that is needed. From the research that was conducted in this study, it was found that the total runoff quantity increases by 10-20% after district lands are developed, when the probable rate of precipitation every 10 years is within this range. Thus, the runoff rate can be reduced by 10~20% of the total runoff quantity through decentralization. On the other hand, in the scale of housing complex development, the total runoff quantity increases by as much as 10~40% due to the changes in the rate of the impervious surface area. If 10-40% of the total runoff quantity was processed through decentralized rainwater management, the rate of infiltration, detention, retention, and runoff in precipitation prior to development could be recovered.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.429-437
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• 2020

In this study we quantified the long-term change in discharge against precipitation in a forested watershed and investigated how the growth of forest trees influences these changes. We found a proportional relationship between precipitation and discharge for each year, and discharge decreased gradually with time. Precipitation and discharge were highest in July and August, and the changes in precipitation, discharge, and runoff rate did not always coincide, given that high runoff rate was shown in August and September. The monthly coefficient of variation (CV) for discharge was larger than that for precipitation, and the deviation between precipitation and discharge increased gradually. From 2011 to 2017, the gradient of the trend line for the change of total discharge and direct runoff against precipitation decreased, whereas the gradient of the base flow increased in this same time period. A possible explanation is that the water holding capacity of soil deposits increased as the forest soil of the Palgong Mountain watershed developed and the increase of base flow rose with groundwater level together with that of outflow quantity. The coefficient of flood recession was lower in the period 2011 to 2017 than in 2003 to 2010; thus, the reduction of discharge was mitigated and remained steady as time progressed. We conclude from these results that the discharge of surface runoff decreased as tree growth and base flow increased; however, the water yield function of the forest increased gradually.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.657-665
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• 1998

New diagnosing method o flood possibility was proposed. The method can be processed by following steps: first, decide if current available water resources are above normal or not; second, compute a consecutive period above normal; third, precipitation is accumulate through the period; fourth, daily depletion (runoff and evapotranspiration) amount is subtracted from the accumulated precipitation and remains are translated to one day's precipitation, which is called effective precipitation; and finally, effective precipitation index. the larger effective precipitation index means the higher flood possibility. This method has been applied to the flood event occurred in the central region of Korea at late July 1996 and compared with the study by Korea Water resources Association (1996). The new method is proven to be much faster in computation, and therefore much better in practical use for emergency situation than current rainfall-runoff models. It is because the new method simplifies some steps of currently used method such as parameter estimation and water level observation. It is also known that new method is more scientific than any other methods that use accumulated precipitation only as it considers the runoff depletion in time

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.201-212
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• 2009

The Tank model and the PRMS(Precipitation Runoff Modeling-modular System) model have been adopted to simulate runoff data from 1981 to 2001 year in the Seomgin-dam basin. However, the simulated runoff by each single model showed some deviations compared with the observed runoff, respectively. In this study a genetic algorithm combination runoff model has been proposed to minimize deviations between simulated runoff and observed runoff that should yield from single model such as Tank model or PRMS model. The proposed combination runoff model combining the simulated respective output of the Tank model and the PRMS model is to produce the optimum combination ratio of each single model applying to the genetic algorithm which may yield the minimum deviations between simulated runoff and observed one. The proposed combination runoff model has been applied to the Seomgin-dam basin. It has also been shown that the combination model by introducing optimal combination ratio should yield less deviations than single model such as the Tank model or the PRMS model.

• Journal of Korea Soil Environment Society
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• v.2 no.2
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• pp.35-51
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• 1997

To clarify the effect of forest environmental changes (forest type difference and clearcut) on water storage capacity in soil and stream flow, watershed had been investigated in Pyungchang, Kangwon-Do during 1983∼1993. Hydrological datas such as runoff, monthly ratio of runoff to precipitation, runoff-duration, monthly runoff(by plenty, ordinary, low and scanty duration), total runoff, direct runoff by runoff components, bulk density, porosity, coarse pore, fine pore, permeability and effective water storage were obtained from Backokpo and Yimokjong watersheds. The monthly ratio of runoff to precipitation, runoff and runoff-duration were higher in Yimokiong than in Backokpo due to forest type difference. On compararing pre-treatment with trement period in two experimental watersheds, pre-treatment period was lower than treatment period. Physical properties of soil such as bulk density, porosity, permeability, and effective water storage capacity conditions were better during the pre-trement period than treatment period in the two experiment plots.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.3
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• pp.1-11
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• 2014

Recently, major cities in Korea are suffering from frequent urban flooding caused by heavy rainfall. Such urban flooding mainly occurs due to the limited design capacity of the current drainage network, which increases the vulnerability of the cities to cope with intense precipitation events brought about by climate change. In other words, it can be interpreted that runoff exceeding the design capacity of the drainage network and increased impervious surfaces in the urban cities can overburden the current drainage system and cause floods. The study presents the green roof as a sustainable solution for this issue, and suggests the pre-design using the LID controls model in SWMM to establish more specific flood prevention system. In order to conduct the computer simulation in connection with Korean climate, the study used the measured precipitation data from Cheonan Station of Korea Meteorological Administration (KMA) and the forecasted precipitation data from RCP 8.5 scenario. As a result, Extensive Green Roof System reduced the peak runoff by 53.5% with the past storm events and by 54.9% with the future storm events. The runoff efficiency was decreased to 4% and 7%. This results can be understood that Extensive Green Roof System works effectively in reducing the peak runoff instead of reducing the total stormwater runoff.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.