• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.170-175
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• 2001

No Abstract (See Full-text)

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.2
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• pp.71-79
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• 2014

Climate change has been social and environmental issues, it typically indicates the trend changes of not only temperature but also rainfall. There is a need to consider climate changes in a long-term soil erosion estimation since soil loss in a watershed can be varied by the changes of rainfall intensity and frequency of torrential rainfall. The impacts of rainfall trend changes on soil loss, one of climate changes, were estimated using Sediment Assessment Tool for Effective Erosion Control (SATEEC) employing L module with current climate scenario and future climate scenario collected from the Korea Meteorological Administration. A 62 $km^2$ watershed was selected to explore the climate changes on soil loss. SATEEC provided an increasing trend of soil loss with the climate change scenarios, which were 182 ton/ha/year in 2010s, 169 ton/ha/year in 2020s, 192 ton/ha/year in 2030s,182 ton/ha/year in 2040s, and 218 ton/ha/year in 2050s. Moreover, it was found that approximately 90% of agricultural area in the watershed displayed the soil loss of 50 ton/ha/year which is exceeding the allow able soil loss regulation by the Ministry of Environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.2
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• pp.29-38
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• 1982

Nonlinear hydrological model containing the nonlinearity of effective rainfall, lag time and runoff is presented. In the evaluation of rainfall excess, the polynomial fitting method for total rainfall, 5 day antecedant rainfall and direct runoff is developed. In the application to actual watershed, the estimated model parameters of nonlinear lag model reflecting the nonlinearity of lag time are compared with the parameters, by both the fitting method and the correlation, model which are the modified version of the storage function model. The Successive Approximation Method in mathematical solution and Newton-Rhapson method in numerical solution are found to be superior to the conventional numerical graphic method in the analysis of nonlinear processes.

• Journal of Korean Society of Disaster and Security
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• v.8 no.1
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• pp.15-19
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• 2015

In rainfall-runoff models employed in hydrological applications, runoff amount is estimated through temporal delay of effective precipitation based on a linear system. Its amount is resulted from the linearized ratio by analyzing the convolution multiplier. Furthermore, in case of kernel density estimate (KDE) used in probabilistic analysis, the definition of the kernel comes from the convolution multiplier. Individual data values are smoothed through the kernel to derive KDE. In the current study, the roles of the convolution multiplier for KDE and rainfall-runoff models were revisited and their similarity and dissimilarity were investigated to discover the mathematical applicability of the convolution multiplier.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1526-1530
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• 2007

In this study, the chukwookee data were evaluated by applying that for the historical rainfall frequency analysis. To derive a two parameter log-normal distribution by using historical data and modern data, censored data MLE and binomial censored data MLE were applied. As a result, we found that both average and standard deviation were all estimated smaller with chukwookee data then those with only modern data. This indicates that rather big events rarely happens during the period of chukwookee data then during the modern period. The frequency analysis results using the parameters estimated were also similar to those expected. The point to be noticed is that the rainfall quantiles estimated by both methods were similar, especially for the 99% threshold. This result indicates that the historical document records like the annals of Chosun dynasty could be valuable and effective for the frequency analysis. This also means the extension of data available for frequency analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.159-167
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• 2000

The purpose of this study is to estimate the stochastic monthly runoff model for the Kunwi south station of Wi-stream basin in Nakdong river system. This model was based on the theory of Box-Jenkins multiplicative ARlMA and the state-space model to simulate changes of monthly runoff. The forecasting monthly runoff from the pair of estimated effective rainfall and observed value of runoff in the uniform interval was given less standard error then the analysis only by runoff, so this study was more rational forecasting by the use of effective rainfall and runoff. This paper analyzed the records of monthly runoff and effective rainfall, and applied the multiplicative ARlMA model and state-space model. For the P value of V AR(P) model to establish state-space theory, it used Ale value by lag time and VARMA model were established that it was findings to the constituent unit of state-space model using canonical correction coefficients. Therefore this paper confirms that state space model is very significant related with optimization factors of VARMA model.

• Journal of Korea Water Resources Association
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• v.30 no.5
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• pp.423-430
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• 1997

It is one of the most important factors to determine the effective rainfall for estimation of flood hydrograph in design schedule. SCS curve number (CN) method has been frequently used to estimate the effective rainfall of synthesized design flood hydrograph for hydraulic structures. But, it should be cautious to apply SCS-CN originally developed in U.S.A to watersheds in Korea, because characteristics of watersheds in Korea and cropping patterns especially like a paddy land cultivation are quite different from those in USA. New CN method has been introduced. Maximum storage capacity which was herein defined as Umax can be calibrated from the streamflow data and converted to new CN-I of direst condition of soil moisture in the given watershed. Effective rainfall for design flood hydrograph can be estimated by the curve number developed in the watersheds in Korea.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.79-84
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• 2003

This study revealed the differences in runoff processes of granite drainage basins in Korea and Mongolia by hydrological measurements in the field. The experimental drainage basins are chosen in Korea (K-basin) and Mongolia (M-basin). Occurrence of intermittent flow in K-basin possibly implies that very quick discharge dominates. The very high runoff coefficient implies that most of effective rainfall quickly discharge by throughflow or pipeflow. The Hortonian overlandflow is thought to almost not occur because of high infiltration capacity originated by coarse grain sized soils of K- basin. Very little baseflow and high runoff coefficient also suggest that rainfall almost does not infiltrate into bedrocks in K-basin. Flood runoff coefficient in M-basin shows less than 1 %. This means that most of rainfall infiltrates or evaporates in M-basin. Runoff characteristics of constant and gradually increasing discharge imply that most of rainfall infiltrates into joint planes of bedrock and flow out from spring very slowly. The hydrograph peaks are sharp and their recession limbs steep. Very short time flood with less than 1-hour lag time in M-basin means that overland flow occurs only associating with rainfall intensity of more than 10 mm/hr. When peak lag time shows less than 1 hour for the size of drainage area of 1 to 10 km2, Hortonian overland flow causes peak discharge (Jones, 1997). The results of electric conductivity suggest that residence time in soils or weathered mantles of M-basin is longer than that of K-basin. Qucik discharge caused by throughflow and pipeflow occurs dominantly in K-basin, whereas baseflow more dominantly occur than quick discharge in M-basin. Quick discharge caused by Hortonian overlandflow only associating with rainfall intensity of more than 10 mm/hr in M-basin.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.587-595
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• 2008

In order to aid the derivation of the IDF relationship for a station with insufficient duration-rainfall data, an approach to derive a simple and practical IDF formula is presented. The IDF formula is described simply by the term of the two parameters and a design frequency. The model parameters were estimated from a statistical technique based on the normal distribution of transformed rainfall intensities. In order to give the transformed data, both the Kruskal-Wallis statistic and the Manly transformation of duration-rainfall data were adopted. With the methods, the proposed IDF formula becomes a simpler model that compares well with conventional form. In addition, it allows avoiding an exceptional condition of the higher rainfall intensity for longer duration. The performance of the proposed formula was evaluated by using the limited rainfall data for short duration from two gauge stations. The result showed that the IDF formula developed in this work was an effective tool, providing a reliable relationship between the intensity and duration even though insufficient data are only available.