• Title/Summary/Keyword: river flow estimation

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Estimation of Instream Flow for Fish Habitat using Instream Flow Incremental Methodology(IFIM) for Major Tributaries in Han River Basin (유지유량 증분 방법론(IFIM)에 의한 한강수계 주요 지류에서의 어류서식 필요유량 산정)

  • Lee, Joo Heon;Jeong, Sang Man;Lee, Myung Ho;Lee, Yong Su
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.2B
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    • pp.153-160
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    • 2006
  • To recommend ecological flow for major tributaries in Han River basin, the Instream Flow Incremental Methodology (IFIM) have been applied. In particular physical habitat simulation using PHABSIM have been selected for microhabitat variables and QUAL2E model have been used to implement macrohabitat simulation. Habitat Suitability Criteria (HSC) for different life stages in accordance with different hydraulic variables (depth and velocity) have been presented by the field surveying data. We review IFIM procedures and discuss limitations of habitat simulation with specific reference to Han River basin. The results of this research can be used as reference flow for estimation of instream flow in Han River.

Evaluation of LOADEST Model Applicability for NPS Pollutant loads Estimation from Agricultural Watershed (농촌유역의 비점원오염부하 산정을 위한 LOADEST 모델의 적용성 평가)

  • Shin, Min hwan;Seo, Ji yeon;Choi, Yong hun;Kim, Jonggun;Shin, Dongsuk;Lee, Yeoul-Jae;Jung, Myung-Sook;Lim, Kyoung Jae;Choi, Joongdae
    • Journal of Korean Society on Water Environment
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    • v.25 no.2
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    • pp.212-220
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    • 2009
  • In many studies, the Numeric Integration (NI) method has been widely used to calculate pollutant loads from the watershed because it is easy to apply. However, there have been many needs for more accurate pollutant loads estimation method with the restricted number of water quality samples. However, the ESTIMATOR model does not allow the users to define the regression model to explain the measured flow and water quality relationship, indicating the ESTIMATOR model is not flexible. The LOADEST model allows the user to choose the model type from 11 predefined general forms of regression equations. Annual loads of T-N and T-P with the LOADEST model were 0.70 times and 0.84 times of those by NI method, respectively. The coefficient of determination ($R^2$) of the LOADEST regression for the T-N and T-P were 0.92 and 0.72, respectively. This indicates that the load estimation regression model with the LOADEST for the study watershed explains the relationship between the observed flow and water quality data well reasonably well. Based on these findings, we suggest that the LOADEST model estimated regression equation could be used to estimate pollutant loads using the measured flow data for the study watershed.

Examination of Topographical Shape Change in River using Time-series Aerial Photo (시계열 영상정보를 이용한 하천 지형태 변화 검토)

  • Lee, Geun-Sang;Lee, Hyun-Seok;Hwang, Eui-Ho;Lee, Eul-Rae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.2136-2140
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    • 2008
  • Recently environmental and ecological river management have been held in high repute, therefore it needs to river restoration and management works considering topographical shape of river. This study estimated the change of topographical shape in Gab- and Yudeung-River using time-series aerial photos. Especially, we selected location points of river facilities as weir and bridge that were built and removed and the confluence of Gab- and Yudeung-River. And we investigated the change of time-series flux and flow-direction. Also, through the estimation of sediment by river flow together, it is possible to supply decision making data that is very important to instream flow and environmental and ecological river restoration in urban stream.

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Probability Funetion of Best Fit to Distribution of Extremal Minimum Flow and Estimation of Probable Drought Flow (극소치유량에 대한 적정분포형의 설정과 확률갈수량의 산정)

  • 김지학;이순탁
    • Water for future
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    • v.8 no.1
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    • pp.80-88
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    • 1975
  • In this paper the authors established the best fit distribution function by applying the concept of probabiaity to the annual minimum flow of nine areas along the Nakdong river basin which is one of the largest Korean rivers and calculated the probable minimum flow suitable to those distribution function. Lastly, the authors tried to establish the best method to estimate the probable minimun flow by comparing some frequency analysis methods. The results obtained are as follows (1) It was considered that the extremal distribution type III was the most suitable one in the distributional types as a result of the comparision with Exponential distribution, Log-Normal distribution, Extremal distribution type-III and so on. (2) It was found that the formula of extremal distribution type-II for the estimation of probable minimum flow gave the best result in deciding the probable minimum flow of the Nakdong river basin. Therfore, it is recommended that the probable minimum flow should be estimated by using the extremal distribution type-III method. (3) It could be understood that in the probable minimum flow the average non-excessive probability appeared to be $Po{\fallingdotseq}1-\frac{1}{2T}$ and gave the same values of the probable variable without any difference in the various methods of plotting technique.

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Estimation Instream Flow Incremental Methodology (IFIM)

  • Lee, Joo-Heon;Jeong, Sang-Man;Lee, Myung-Ho;Lee, Soo-Yong;Lee, Eun-Tae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.52-59
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    • 2005
  • The goal of this project is to estimate the instream flow of the Han River Basin to ensure the adequate supply of suitable quality water for preservation and enhancement of aquatic ecosystems. A applied model is Physical Habitant Simulation System(PHABSIM) of Instream Flow Incremental Methodology(IFIM). The parameters which are needed to simulation by PHABSIM such as flow depth, velocity distribution and channel cover with cross section data are obtained by field survey. The Habitat Suitability Criteria with the application of univariate curve on Zacco platypus as a target species was able to be established by conducting the field investigation. The estimated results of ecological recommended instream flow by this study has important meanings that the future river management have to seriously take into account for the natural environment and functions of river system.

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Estimation of river discharge using satellite-derived flow signals and artificial neural network model: application to imjin river (Satellite-derived flow 시그널 및 인공신경망 모형을 활용한 임진강 유역 유출량 산정)

  • Li, Li;Kim, Hyunglok;Jun, Kyungsoo;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.49 no.7
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    • pp.589-597
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    • 2016
  • In this study, we investigated the use of satellite-derived flow (SDF) signals and a data-based model for the estimation of outflow for the river reach where in situ measurements are either completely unavailable or are difficult to access for hydraulic and hydrology analysis such as the upper basin of Imjin River. It has been demonstrated by many studies that the SDF signals can be used as the river width estimates and the correlation between SDF signals and river width is related to the shape of cross sections. To extract the nonlinear relationship between SDF signals and river outflow, Artificial Neural Network (ANN) model with SDF signals as its inputs were applied for the computation of flow discharge at Imjin Bridge located in Imjin River. 15 pixels were considered to extract SDF signals and Partial Mutual Information (PMI) algorithm was applied to identify the most relevant input variables among 150 candidate SDF signals (including 0~10 day lagged observations). The estimated discharges by ANN model were compared with the measured ones at Imjin Bridge gauging station and correlation coefficients of the training and validation were 0.86 and 0.72, respectively. It was found that if the 1 day previous discharge at Imjin bridge is considered as an input variable for ANN model, the correlation coefficients were improved to 0.90 and 0.83, respectively. Based on the results in this study, SDF signals along with some local measured data can play an useful role in river flow estimation and especially in flood forecasting for data-scarce regions as it can simulate the peak discharge and peak time of flood events with satisfactory accuracy.

Estimation of Habitat Suitability Index of Fish Species in the Geum River Watershed (금강수계 하천에서의 어류 서식처적합도지수 산정)

  • Kang, Hyeongsik;Im, Dongkyun;Hur, Jun Wook;Kim, Kyu-Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.2B
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    • pp.193-203
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    • 2011
  • With the recent growth of environmental and ecological interests, various river restoration and habitat environment creation projects are being carried out. For this, the estimation of the habitat flow discharge is important. In U.S. and Europe nations, The instream flow incremental methodology (IFIM) has been used to estimate the habitat discharge. IFIM is the method that can be applied to evaluate the flow discharge for the suitable habitat. To use the IFIM in river, a habitat suitability index(HSI) for the target organism is needed. However, HSIs for only two species of Zacco platypus and Zacco temminckii were proposed from the field monitoring. Thus, for the estimation of the ecological flow rate for a group of fish, the development of the HSIs for various fish are necessary. In this study, physical data such as water level and flow rate, chemical data such as acidity and dissolved oxygen, and life data such as fish types and population are collected in Keum river watershed. Based on the 2,736 field data, HSIs for the following 6 fish are developed: Zacco platypus, Zacco temminckii, Microphysogobio yaluensis, Coreoleuciscus splendidus, Pungtungia herzi, Pseudogobio esocinus. Through the comparison with HSIs in the literature, the developed HSIs are modified. Also, the limits of Froude number, pH, and DO for 6 fish are proposed. The HSIs developed in this study can be utilized as a essential data for performing river project evaluations.

Analysis of Korean TMLD Design Flow Variation due to Large Dam Effluents and Water Use Scenarios

  • Shin, Hyun-Suk;Kang, Doo-Kee;Kim, Sang-Dan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.74-83
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    • 2007
  • The goal of this study is to establish an integrated watershed hydrologic model for the whole Nakdong River basin whose area is an approximately 24,000 km2. Including a number of watershed elements such as rainfall, runoff, water use, and so on, the proposed model is based on SWAT model, and is used to improve the flow duration curve estimation of ungauged watersheds for Korean Total Maximum Daily Load (TMDL). The model is also used to recognize quantitatively the river flow variation due to water use elements and large dam effluents in the whole watershed. The established combined watershed hydrologic model, SWAT-Nakdong, is used to evaluate the quantified influences of artificial water balance elements, such as a dam and water use in the watershed. We apply two water balance scenarios in this study: the dam scenario considering effluent conditions of 4 large multi-purpose dams, Andong dam, Imha dam, Namgang dam, and Habcheon dam, and the water use scenario considering a water use for stream line and the effluent from a treatment plant. The two scenarios are used to investigate the impacts on TMDL design flow and flow duration of particular locations in Nakdong River main stream. The results from this study will provide the basic guideline for the natural flow restoration in Nakdong River.

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Stream flow estimation in small to large size streams using Sentinel-1 Synthetic Aperture Radar (SAR) data in Han River Basin, Korea

  • Ahmad, Waqas;Kim, Dongkyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.152-152
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    • 2019
  • This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

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