• Title/Summary/Keyword: Water level estimation

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Prediction of Water Level at Downstream Site by Using Water Level Data at Upstream Gaging Station (상류 수위관측소 자료를 활용한 하류 지점 수위 예측)

  • Hong, Won Pyo;Song, Chang Geun
    • Journal of the Korean Society of Safety
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    • v.35 no.2
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    • pp.28-33
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    • 2020
  • Recently, the overseas construction market has been actively promoted for about 10 years, and overseas dam construction has been continuously performed. For the economic and safe construction of the dam, it is important to prepare the main dam construction plan considering the design frequency of the diversion tunnel and the cofferdam. In this respect, the prediction of river level during the rainy season is significant. Since most of the overseas dam construction sites are located in areas with poor infrastructure, the most efficient and economic method to predict the water level in dam construction is to use the upstream water level. In this study, a linear regression model, which is one of the simplest statistical methods, was proposed and examined to predict the downstream level from the upstream level. The Pyeongchang River basin, which has the characteristics of the upper stream (mountain stream), was selected as the target site and the observed water level in Pyeongchang and Panwoon gaging station were used. A regression equation was developed using the water level data set from August 22th to 27th, 2017, and its applicability was tested using the water level data set from August 28th to September 1st, 2018. The dependent variable was selected as the "level difference between two stations," and the independent variable was selected as "the level of water level in Pyeongchang station two hours ago" and the "water level change rate in Pyeongchang station (m/hr)". In addition, the accuracy of the developed equation was checked by using the regression statistics of Root Mean Square Error (RMSE), Adjusted Coefficient of Determination (ACD), and Nach Sutcliffe efficiency Coefficient (NSEC). As a result, the statistical value of the linear regression model was very high, so the downstream water level prediction using the upstream water level was examined in a highly reliable way. In addition, the results of the application of the water level change rate (m/hr) to the regression equation show that although the increase of the statistical value is not large, it is effective to reduce the water level error in the rapid level rise section. Accordingly, this is a significant advantage in estimating the evacuation water level during main dam construction to secure safety in construction site.

Development of groundwater level monitoring and forecasting technique for drought analysis (I) - Groundwater drought monitoring using standardized groundwater level index (SGI) (가뭄 분석을 위한 지하수위 모니터링 및 예측기법 개발(I) - 표준지하수지수(SGI)를 이용한 지하수 가뭄 모니터링)

  • Lee, Jeongju;Kang, Shinuk;Jeong, Jihye;Chun, Gunil
    • Journal of Korea Water Resources Association
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    • v.51 no.11
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    • pp.1011-1020
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    • 2018
  • This study aims to develop a drought monitoring scheme based on groundwater which can be exploit for water supply under drought stress. In this context, groundwater level can be used as a proxy for better understanding the temporal evolution of drought state. First, kernel density estimator is presented in the monthly groundwater level over the entire national groundwater stations. The estimated cumulative distribution function is then utilized to map the monthly groundwater level into the standardized groundwater level index (SGI). The SGI for each station was eventually converted into the index for major cities through the Thiessen polygon approach. We provide a drought classification for a given SGI to better characterize the degree of drought condition. Ultimately, we conclude that the proposed monitoring framework enables a more reliable estimation of the drought stress, especially for a limited water supply area.

Satellite-based Rainfall for Water Resources Application

  • Supattra, Visessri;Piyatida, Ruangrassamee;Teerawat, Ramindra
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.188-188
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    • 2017
  • Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

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A Study on the Analysis of Water Waves and Harbor Oscillations due to the Development of Pusan Harbor (부산권개발에 따른 파괴분석과 해면부진동에 관한 연구)

  • 이중우;김지연
    • Journal of Ocean Engineering and Technology
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    • v.5 no.1
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    • pp.25-34
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    • 1991
  • An accurate estimation of water level variation when thewaves propagate to the coastal regionis very important for the port and harbor development plan. This study describes the application of a hybrid element model to harbor oscillation problem due to the construction of shore structure and implementation of shore boundary. The site selected is Pusan Harbor area with the third development and the Artificial Island plan. The observed water level changes at the site are compared with the result of the numerical experiment. The model gives a very important prediction of water level changes for navigation and harbor design.

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Impacts of Reforestation on Stabilization of Riverine Water Levels in South Korea

  • JAEHYUN, YOON;SAANG JOON, BAAK;MIN YOUNG, SEO;TAEJONG, KIM
    • KDI Journal of Economic Policy
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    • v.44 no.4
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    • pp.1-24
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    • 2022
  • We investigate how reforestation contributed to stabilization of riverine water levels in South Korea. For the purpose, we estimate an equation capturing dynamic relationships among rainfall, upstream-area tree stock, and downstream water levels in three river systems of Hongcheon, Mangyeong, and Hyeongsan, using daily observations of precipitation and water levels for the period from 1985 to 2005. Simulation based on estimation results shows that increase in the tree stock in a river basin leads to a significantly suppressed peaking in riverine water levels in response to an abrupt and concentrated rain in the upstream area. For instance, an hour-long concentration of 100mm rain results in 0.7m rise in water level if the volume of growing stock is 1 million m3, whereas the rise in water level stays below 0.27m with 5 million m3 in the growing-stock volume.

Estimation Error and Reliability of Measuring Unit Water Content Test Methods for Fresh Concrete Depending on Mix Design Factors at the Laboratory Level (실험실 수준에서 배합변수별 굳지 않은 콘크리트 단위수량 실험방법의 추정오차 및 신뢰성 검토)

  • Park, Min-Yong;Han, Min-Cheol
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.10 no.1
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    • pp.101-110
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    • 2022
  • In this study, water content tests were performed on various fresh concretes subjected to different binder compostions to review the estimation errors and reliability of water content test methods. Micro-oven drying method, air-meter method, capacitance method and microwave penetration method were used to estimate water content of fresh concrete. Errors in water content estimation were analyzed by each test method. Regardless of the test method of water content, the estimation error was less than 5 %, and in the case of the test using mortar, the error in the estimation value was relatively large. In addition, based on the test results of water content of various concrete, the probability density function in which the estimation error for each test method becomes the population was analyzed. Water content test methods of fresh concrete which using concrete samples showed high estimate reliability of 97 % within the estimation error range of ± 10 kg/m3. On the other hand, the reliability of water content test method using mortar samples was lower.

Assessing Irrigation Water Supply from Agricultural Reservoir Using Automatic Water Level Data of Irrigation Canal (관개용수로의 자동수위측정 자료를 활용한 농업용 저수지 공급량 산정 및 분석)

  • Bang, Jehong;Choi, Jin-Yong;Yoon, Pureun;Oh, Chang-Jo;Maeng, Seung-Jin;Bae, Seung-Jong;Jang, Min-Won;Jang, Taeil;Park, Myeong Soo
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.1
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    • pp.27-35
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    • 2021
  • KRC (Korea Rural Community Corporation) is in charge of about 3,400 agricultural reservoirs out of 17,240 agricultural reservoirs, and automatic water level gauges in reservoirs and canals were installed to collect reservoir and canal water level data from 2010. In this study, 10-minute water level data of 173 reservoir irrigation canals from 2016 to 2018 are collected, and discharge during irrigation season was calculated using rating curves. For estimation of water supply, irrigation water requirement was calculated with HOMWRS (Hydrological Operation Model for Water Resources System), and the summation of reservoir water storage decrease was calculated with daily reservoir storage data from RAWRIS (Rural Agricultural Water Resource Information System). From the results, the total yearly amount of irrigation water supply showed less than 10% difference than the irrigation water requirement. The regional analysis revealed that reservoirs in Jeollanam-do and Chungcheongnam-do supply greater irrigation water than average. On the contrary, reservoirs in Gyeongsangnam-do and Chungcheongbuk-do supply less than others. This study was conducted with a limited number of reservoirs compared to total agricultural reservoirs. Nevertheless, it can indicate irrigation water supply from agricultural reservoirs to provide information about agricultural water use for irrigation.

Estimation of water content and strong acideity of ambient particles in Seoul (서울지역 입자의 수분함량 및 강산성도 예측)

  • 김진영;김용표;심상규;문길주;천만영;김희강
    • Journal of Korean Society for Atmospheric Environment
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    • v.11 no.1
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    • pp.69-76
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    • 1995
  • Water content and strong acidity are estimated for ambient particles measured between Fall, 1991 and Summer, 1992 in Seoul using a gas/aerosol equilibrium model, called SCAPE. Particle water content and formation of solid species are closely related to ambient relative humidity and ionic concentrations. Generally, water content of particles is high during the night and summer. Estimated particle strong acidity level of Seoul is similar to that of Los Angeles, U.S.A. Acidity of wet and dry depositions in Seoul is discussed.

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Spatial Distribution of the Levels of Water Pollutants in Han River (수질오염도의 공간적 분포 변화 분석 : 한강 유역을 대상으로)

  • Kim, Kwang-Soo;Kwon, Oh-Sang
    • Environmental and Resource Economics Review
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    • v.18 no.1
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    • pp.105-138
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    • 2009
  • This study investigates the spatial distribution of the degree of water pollutants in Han River using data obtained by the water pollution observation stations. This study estimates a non -parametric kernel density function for each water pollutants, and tests a significant difference between two estimated distribution functions. Next, Generalized Entropy inequality indices are evaluated and this research tests difference of inequality indices between two years using bootstrapping method. Lastly in a dynamic of view, it is analyzed that there are significant changes in the ranking of water pollution level. Estimation results show that the degree of inequality in spatial distribution of water pollution tends to be stable or decreasing for last 15 years in a great part of water pollutants, and ranking of water pollution level hardly changes in Han River.

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A Study on Roughness Coefficient Estimations in Gravel Bed Stream without Water Level-Discharge Data (수위-유량자료가 부재한 자갈하천의 조도계수 산정에 관한 연구)

  • Lee, Sin-Jae;Park, Sang-Woo
    • Journal of Korea Water Resources Association
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    • v.39 no.12 s.173
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    • pp.985-996
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    • 2006
  • This study developed a model that could calculate equivalent roughness using shear stress acting on distributed grains in gravel bed stream. The estimated equivalent roughness by the model developed was used for estimation of water level and roughness coefficient in the stream without water level-discharge data. The model was applied to the Gurey-Songjeong stage station section located in the Sumjin river mid-downstream. The equivalent roughness by the model developed in this study was estimated to be 0.194m at the Gurey stage station. Calculated water level which the estimated equivalent roughness was applied to the flow model was shown ewer of within 6% in comparison with observed water level. Also, roughness coefficient was estimated using observed and calculated water level about each discharge scale by unsteady flow analysis. As a result, error of roughness coefficient estimated by observed and calculated water level was shown error of $0{\sim}0.002$ and could consider variability of roughness coefficient.