• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.156-156
• /
• 2019

In this study, a gated recurrent unit (GRU) network is constructed based on a deep neural network (DNN) with the aim of restoring the missing daily flow data in river basins. Lai Chau hydrological station is located upstream of the Da river basin (Vietnam) is selected as the target station for this study. Input data of the model are data on observed daily flow for 24 years from 1961 to 1984 (before Hoa Binh dam was built) at 5 hydrological stations, in which 4 gauge stations in the basin downstream and restoring - target station (Lai Chau). The total available data is divided into sections for different purposes. The data set of 23 years (1961-1983) was employed for training and validation purposes, with corresponding rates of 80% for training and 20% for validation respectively. Another data set of one year (1984) was used for the testing purpose to objectively verify the performance and accuracy of the model. Though only a modest amount of input data is required and furthermore the Lai Chau hydrological station is located upstream of the Da River, the calculated results based on the suggested model are in satisfactory agreement with observed data, the Nash - Sutcliffe efficiency (NSE) is higher than 95%. The finding of this study illustrated the outstanding performance of the GRU network model in recovering the missing flow data at Lai Chau station. As a result, DNN models, as well as GRU network models, have great potential for application within the field of hydrology and hydraulics.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.38 no.2
• /
• pp.108-122
• /
• 1996

This study was to introduced estimation model for optimum probabilistic rainfall intensity on hydrological area. Originally, probabilistic rainfall intensity formula have been characterized different coefficient of formula and model following watersheds. But recently in korea rainfall intensity formula does not use unionize applyment standard between administration and district. And mingle use planning formula with not assumption model. Following the number of year hydrological duration adjust areal index. But, with adjusting formula applyment was without systematic conduct. This study perceive the point as following : 1) Use method of excess probability of Iwai to calculate survey rainfall intensity value. 2) And, use method of least squares to calculate areal coefficient for a unit of 157 rain gauge station. And, use areal coefficient was introduced new probabilistic rainfall intensity formula for each rain gauge station. 3) And, use new probabilistic rainfall intensity formula to adjust a unit of fourteen duration-a unit of fifteen year probabilistic rainfall intensity. 4) The above survey value compared with adjustment value. And use three theory of error(absolute mean error, squares mean error, relative error ratio) to choice optimum probabilistic rainfall intensity formula for a unit of 157 rain gauge station.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.48 no.2
• /
• pp.37-43
• /
• 2006

A hydrological drought index, MSWSI (Modified Surface Water Supply Index) was suggested based on SWSI (Surface Water Supply Index). With the available data of spatially distributed observation station of precipitation, dam storage, stream water level and natural groundwater level, South Korea was divided into 32 regions. This was conducted to represent the calculated index as a spatially distributed information. Monthly MSWSI was evaluated for the period of 1974 and 2001. It is necessary to compare this result with PDSI (Palmer Drought Severity Index) and SPI (Standard Precipitation Index), and check the applicability of the suggested index in our hydrological drought situation.

• Water Engineering Research
• /
• v.6 no.4
• /
• pp.179-187
• /
• 2005

This paper introduces the Cheonggye-cheon restoration project. The restoration project aims to revive the 600-year-old city of Seoul by recovering the historical heritage, guaranteeing safety from the deteriorated covering structures, creating the environment-friendly space, and revitalizing the neglected city centers. In order to understand the current hydrological cycle of the Chenggye-cheon watershed, the annual water balance of the region was calculated using the observed data including precipitation, runoff, water supply and sewage, and the changes in the groundwater level. The $2001{\sim}2002$ data were used to calibrate the WEP, and the $2003{\sim}2004$ data were used to verify the WEP. The calibration and validation results for the flood hydrograph how a reasonable value (at Majanggyo station, the R2 for the calibration period was 0.9, and that for the validation period was 0.7). According to the annual water balance of the Cheonggye-cheon watershed for 2004, the amount of surface runoff, infiltration, and evapotranspiration was 1,097mm, 216mm and 382mm, respectively, for an annual precipitation of 1,499mm. The application results from WEP, a distributed hydrological model, provide more detailed information of the watershed, and the model will be useful for improving the hydrological cycle in urban watershed.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.271-271
• /
• 2023

수문학적 기준지점(HRS, Reference Hydrological Station)은 유량의 변동성의 장기적인 추세를 파악하기 위해 고품질의 자료를 생산하는 관측소를 의미한다. 선진외국의 경우 운영목적과 수문학적 기준지점의 정의는 조금씩 다르지만 유사한 개념의 관측소를 운영하고 있다. 호주의 경우 기후변화에 따른 장기간의 수자원 부존량의 변화를 예측하기 위한 모니터링 지점으로 정의하며, 미국의 경우 시간에 따른 수문학적 특성의 자연적인 변화 및 인간의 활동에 따른 수문환경의 변화에 대한 연구를 위한 기준값을 제공하기 위해 참조지점(HBN, Hydrological Benchmark Network)의 자료를 제공하기 위해 운영한다. 영국은 기후변화에 따른 유역의 수문학적 응답을 조사할 목적으로 참조지점(RHN, Reference Hydrological Network)을 운영하고 있으며, 주로 자연유역에 설치하여 운영하고 있다. WMO는 2006년 '기후연구를 위한 적절한 유량관측소'를 선정해 줄 것을 회원국에 요청하고, 관련 자료의 데이터베이스를 독일의 GRDC(Global Runoff Data Centre)에 수집하고 있다. 국외의 경우 '자연에 가까운 유역특성을 갖는 하천 유량관측망 중 양질의 자료를 보유하고 있는 관측소'를 고려하여 수문학적 기준지점을 선정한다. 하지만 우리나라의 경우 장기간의 유량자료를 보유하고 있는 관측소가 상대적으로 부족하고, 장기간의 유량자료를 보유한 지점 또한 홍수예보, 댐 운영 등 물관리 업무에 직접 활용하기 위해 대하천의 본류 중심으로 자료를 생산하고 있다. 따라서 현재를 기준으로 국제적으로 통용되는 기준에 부합하는 기준관측소를 선정하는 것은 곤란한 상황으로 미래에 수문학적 기준지점이 될 수 있는 관측소를 선정하여 장기간 모니터링을 통해 기준관측소를 확대해 나갈 필요가 있다. 본 연구에서는 국외의 수문학적 기준관측소 선정기준을 비교 검토하여 우리나라 실정에 맞는 기준관측소 선정기준을 개발하였다. 선정 기준은 ① 유역의 개발정도, ② 댐·저수지 등 인위적인 조절 정도, ③ 취수량 또는 방류량 등 유역간의 물 이동, ④ 유량자료의 보유기간 및 정확도 등을 고려하여 기준을 설정하였다. 또한 기준지점의 선정을 위한 절차를 ① 수위관측소 사전목록의 작성, ② 관측소 정보 분석(유역특성, 시계열자료 등), ③ 수문학적 기준관측소 후보 선정, ④ 유관기관 및 전문가 검토를 통한 우선순위 선정 등 4단계로 구분하여 제시하였다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.179-179
• /
• 2015

Citarum River is one of the important river in West Java, Indonesia. During the rainy season, flood happens almost every year in Upper Citarum Watershed, hence, it is necessary to establish the countermeasure in order to prevent and mitigate flood damages. Since the lack of hydrological data for the modelling is common problem in this area, it is difficult to prepare the countermeasures. Therefore, we used Rainfall-Runoff-Inundation (RRI) Model developed by Sayama et al. (2010) as the hydrological and inundation modelling for evaluating the inundation case happened in Upper Citarum Watershed, West Java, Indonesia and the satellite based information such as rainfall (GSMaP), landuse and so on instead of the limited hydrological data. In addition, 3 arc-second HydroSHEDS Digital Elevation Model (DEM) is used. To verify the model, the observed data of Nanjung water stage gauging station and the daily observation data are used. Simulated inundation areas are compared with the flood extent figure from Upper Citarum Basin Flood Management Project (UCBFM).

• Journal of Korea Water Resources Association
• /
• v.53 no.2
• /
• pp.89-96
• /
• 2020

Water management agencies under the Ministry of Environment produce and accumulate qualified basic data for major rivers. However, the integrated management of the river water has been weak since the artificial water circulation process, such as the intaking and drainage of agricultural water, has not been examined in the basin, which includes many agricultural land. In this study, a study was conducted on how the power usage method (operating time method) based on the running time can be applied and improved among indirect flow rate measurement methods used to investigate flow rates collected by the riverside for agricultural water purposes, and thus the resultant data of high reliability can be obtained at low cost. The operation time method is suitable for small-scale water pumping stations where it is difficult to secure real-time power supply data. The reliability of the data was verified through the correlation analysis with the actual flow rate, and it was found that the flow rate calculated by the operation time method reflecting the level of the stream to which the inlet of the pumping station is connected can be reasonably matched with the actual flow rate. In addition, it was confirmed that the investment cost at the time of initial installation of the facility was highly efficient by generating qualified flow data at low cost through comparison with direct flow rate measurement methods. If flow data is secured by applying the operation time method to large and small water farms located along the riverside, it is expected that more quantitative and integrated stream water management will be possible.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.2
• /
• pp.39-52
• /
• 2020

A high quality, long-term, high-resolution precipitation dataset is an essential in climate analyses and global water cycles. Rainfall data from station observations are inadequate over many parts of the world, especially North Korea, due to non-existent observation networks, or limited reporting of gauge observations. As a result, satellite-based rainfall estimates have been used as an alternative as a supplement to station observations. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and global coverage. CHIRPS is a global precipitation product and is made available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. In this study, we analyze the applicability of CHIRPS data on the Korean Peninsula by supplementing the lack of precipitation data of North Korea. We compared the daily precipitation estimates from CHIRPS with 81 rain gauges across Korea using several statistical metrics in the long-term period of 1981-2017. To summarize the results, the CHIRPS product for the Korean Peninsula was shown an acceptable performance when it is used for hydrological applications based on monthly rainfall amounts. Overall, this study concludes that CHIRPS can be a valuable complement to gauge precipitation data for estimating precipitation and climate, hydrological application, for example, drought monitoring in this region.

• Journal of Korea Water Resources Association
• /
• v.53 no.12
• /
• pp.1049-1057
• /
• 2020

This study aimed to develop a flow measurement method using drone in flood season. Measuring flow in all branches is difficult to conduct annually due to budget and labor limitation, safety and river works. Especially when heavy rain like storm comes, changes in stage-discharge relationship should be reviewed; however, it is usually impeded by the aforementioned issues. To solve the problem, it developed a simple measuring method with a minimum of labor and time. A numeric map and numeric orthophoto coordinate of South Korea are mostly based on Transverse Mercator Projection (TM) in accordance with rectangular coordinate system and use World Geodetic Reference System 1980 (GRS80) oval figure for conversion. Applying a concept of aerial photogrammetry, it located four visible Ground Control Points (GCP) near the river at Uijeongbu-si (Singok Bridge) and Yeongdong-gun (Youngdong 2nd Bridge) station and measured the coordinates using VRS DGPS. Hovering at a same level, drones took orthophoto of water surface at an interval of 3 seconds. It defined the pictures with GRS80 TM coordinate system, a rectangular coordinate system and then conducted an orthometric correction using GCP coordinates. According to X and Y coordinate analysis, it estimated the distance between the floating positions at 3 seconds-intervals and calculated the flow through the flow area according to the flow path. This study attested applicability of the flow measurement method using drone in flood season by applying the rectangular coordinate system based on the concept of aerial photogrammetry.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.390-390
• /
• 2019

Application of Hidden Markov Model (HMM) to the hydrological time series would be an innovative way to identify extreme rainfall events in a series. Even though the optimum number of hidden states can be identify based on maximizing the log-likelihood or minimizing Bayesian information criterion. However, occasionally value for the log-likelihood keep increasing with the state which gives false identification of the optimum hidden state. Therefore, this study attempts to identify optimum number of hidden states for Colombo station, Sri Lanka as fundamental approach to identify frequency and percentage of extreme rainfall events for the station. Colombo station consisted of daily rainfall values between 1961 and 2015. The representative station is located at the wet zone of Sri Lanka where the major rainfall season falls on May to September. Therefore, HMM was ran for the season of May to September between 1961 and 2015. Results showed more or less similar log-likelihood which could be identified as maximum for states between 4 to 7. Therefore, measure of central tendency (i.e. mean, median, mode, standard deviation, variance and auto-correlation) for observed and simulated daily rainfall series was carried to each state to identify optimum state which could give statistically compatible results. Further, the method was applied for the second major rainfall season (i.e. October to February) for the same station as a comparison.