• Water Engineering Research
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• v.4 no.4
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• pp.187-192
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• 2003

The rainfall observation systems have largely been improved in Japan. The Japan Meteorological Agency, prefecture governments, and other administrative bodies have also increased the number of rain gauges thru out the country. The density of observatories is now one per several $\km^2$. Heavy rainfall information systems have been improved. Besides it, the Internet was popularized in the late 1990s, and has been used to transmit data of heavy rainfall. Internet accessible cellular phones have been popular in Japan since 1999. Such phones are expected to be useful in the field of disaster warning announcements, because they can automatically notify users bye-mail of pending disasters. The use of the Internet during natural disasters is groundbreaking in Japan today. However, in order to use disaster information effectively on Internet it is necessary to investigate how to use the information during the rainfall disaster. Therefore in our study we suggest methods on the effective construction and their use of information technology on Internet.

• Environmental Engineering Research
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• v.17 no.1
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• pp.47-56
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• 2012

A long-term nationwide nonpoint-source pollution monitoring program was initiated by the Ministry of Environment Republic of Korea (ME) in 2007. Monitoring devices including rain gauges, flow meters, and automatic samplers were installed in monitoring sites to collect dynamic runoff data in 2008-2009. More than 10 rainfall events with three or more antecedent dry days were monitored per year. More than 10 samples were collected and analyzed per event. So far, five land use types (single family, apartments, education facilities, power plants, and other public facilities) have been monitored 23 to 24 times each. Characterization of the runoff from different land use types will aid unit load estimation in Korea and hopefully in other countries with similar land use. The monitoring results will be reported regularly at national and international levels.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.302-303
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• 2007

수문관측용으로 사용되는 강우량계는 측정의 편의성과 강인성의 장점 때문에 대부분 전도형 우량계를 사용하고 있다. 한국수자원공사에서는 약 160여개의 우량국을 관리하고 있으며, 2006년도 교정주기가 도래한 우량계 16개 및 특성 분석이 필요한 우량계 4개 등 총 20개에 대하여 한국수자원공사 수자원연구원에서 개발한 전도형 우량계 표준교정시스템을 이용하여 교정을 실시하였다. 우량계의 교정결과 버켓의 평균값이 기준값 1 mm에 대하여 0.95$\sim$1.04mm까지 다양하게 측정되었으나, 모두 기준인 $\pm$5 %를 만족하는 것으로 나타났으며, 전도형 우량계는 강우강도가 강할수록 측정되는 강우량이 많아지는 특성을 확인할 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.595-597
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• 2018

Precipitation has a wide range of applications, such as the management and operation of dams and rivers, supply of dranking water for urban and industrial complex, farming and fishing, forest greening, and safety management. In order to prepare for disasters and to obtain economical effects in case of flood damage, it is necessary to measure accurate precipitation. In this study, we carried out the characteristics tests for various types of rainfall gauge using integrated verification system, which can analyze the performance of collective type rainfall gauge. The uncertainty for tipping bucket rain gauge was 0.2887 mm. Therefore, it can be seen that the uncertainty is calculated differently depending on the characteristics of the rainfall gauges. The uncertainty is also influenced greatly by the resolution.

• Environmental Engineering Research
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• v.21 no.3
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• pp.226-232
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• 2016

Rainfall is one of crucial factors that impact on our environment. Rainfall data is important in water resources management, flood forecasting, and designing hydraulic structures. However, it is not available in some rural watersheds without rain gauges. Thus, effective ways of interpolating the available records are needed. Despite many widely used spatial interpolation methods, few studies have investigated rainfall center characteristics. Based on the theory that the spatial distribution of convective rainfall event has a definite center with maximum rainfall, we present a mathematical interpolation method to estimate convective rainfall distribution and indicate the rainfall center location and the center rainfall volume. We apply the method to estimate three convective rainfall events in Santa Catalina Island where reliable hydrological data is available. A cross-validation technique is used to evaluate the method. The result shows that the method will suffer from high relative error in two situations: 1) when estimating the minimum rainfall and 2) when estimating an external site. For all other situations, the method's performance is reasonable and acceptable. Since the method is based on a continuous function, it can provide distributed rainfall data for distributed hydrological model sand indicate statistical characteristics of given areas via mathematical calculation.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.112-121
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• 2017

This study proposed the quantitative precipitation estimation method using overlapped area in radar network. For this purpose, the dense rain gauges and radar network are used. As a result, we found a reflectivity bias between two radar located in different area and developed the new quantitative precipitation estimation method using the bias. Estimated radar rainfall from this method showed the apt radar rainfall estimate than the other results from conventional method at overall rainfall field.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.499-499
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• 2018

Hydro-meteorological extremes are trivial in these days. Therefore, it is important to identify extreme hydrological events in advance to mitigate the damage due to the extreme events. In this context, exploring temporal distribution of sub-daily extreme rainfall at multiple rain gauges would informative to identify different states to describe severity of the disaster. This study proposehidden Markov chain model (HMM) based rainfall analysis tool to understand the temporal sub-daily rainfall patterns over South Korea. Hourly and daily rainfall data between 1961 and 2017 for 92 stations were used for the study. HMM was applied to daily rainfall series to identify an observed hidden state associated with rainfall frequency and intensity, and further utilized the estimated hidden states to derive a temporal distribution of daily extreme rainfall. Transition between states over time was clearly identified, because HMM obviously identifies the temporal dependence in the daily rainfall states. The proposed HMM was very useful tool to derive the temporal attributes of the daily rainfall in South Korea. Further, daily rainfall series were disaggregated into sub-daily rainfall sequences based on the temporal distribution of hourly rainfall data.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.24-24
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• 2023

This presentation highlights the IAHR book, recently published last April, of which the author is the editor-in-chief, on the historical water projects and traditional water technologies of international interest in the Asian region, addressing information on past water projects (mostly before the 20th century) in the regions that are technically and culturally of interest and educationally valuable. The book explores historical water projects in these regions, presenting technologies used at the time, including calculation and forecasting methods, measurement, material, labor, methodologies, and even water culture. Through this book, it is expected that the old Asian wisdom of "reviewing the old and learning the new" would be realized to a certain extent in modern planning and practice of water projects. The book comprises a lead article that the presenter authored and five Parts representing China, Japan, Korea, South Asia, and Southeast Asia, respectively, followed by an invited one from Uzbekistan. Throughout the book, it is found that historically the Asian monsoon, affecting the Indian subcontinent and Southeast and East Asian regions, induced rice cultivation. It fundamentally needs proper irrigation systems, including reservoirs (dams) and canals, water wheels, and even rain gauges. Flood risks have been more common in Asia than Europe under this climate condition, as recognized in history. To utilize and sometimes overcome these climate conditions, people built and managed many historical and grandiose water projects and invented and used localized but sophisticated water-related technologies in the Asian region.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.123-123
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• 2020

The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.134-134
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• 2022

Streamflow forecasting plays a crucial role in water resource control, especially in highly urbanized areas that are very vulnerable to flooding during heavy rainfall event. In addition to providing the accurate prediction, the evaluation of effects and importance of the input predictors can contribute to water manager. Recently, machine learning techniques have applied their advantages for modeling complex and nonlinear hydrological processes. However, the techniques have not considered properly the importance and uncertainty of the predictor variables. To address these concerns, we applied the GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting and analyzing input predictors. The Jungrang urban basin was selected as a case study and a database was established based on 39 heavy rainfall events during 2003 and 2020 from the rain gauges and monitoring stations. For the goal of this study, we used a combination of inputs that included the areal rainfall of the subbasins at current time step and previous time steps and water level and streamflow of the stations at time step for multistep-ahead streamflow predictions. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. In addition, the GA-BART model could reasonably determine the relative importance of the input variables. The assessment might help water resource managers improve the accuracy of forecasts and early flood warnings in the basin.