• Title/Summary/Keyword: distributed storm runoff model

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Evaluation of the Applicability of a Distributed Model at the Downstream of Dam (댐 하류 지점에 대한 분포형 모형의 적용성 평가)

  • Choi, Yun-Seok;Kim, Kyung-Tak;Shim, Myung-Pil
    • Journal of Korea Water Resources Association
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    • v.42 no.9
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    • pp.703-713
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    • 2009
  • Dam has very important roles in both water use and flood control. Dam release and runoff from rainfall affect directly to the flood control at the downstream of dam during heavy storm especially. This study evaluates the applicability of a distributed model by applying the GRM (Grid based Rainfall-runoff Model) based on HyGIS (Hydro Geographic Information System) environment to runoff modeling at the downstream of dam where the discharge from dam and rainfall affect simultaneously. In order to do this, Yeoju watershed in Han River basin is selected. Rainfall data and discharge from Chungju regulation dam and Hoengseong dam are applied to runoff simulation. The modeling results are verified with Yeoju water level station, and they show good agreement with observed hydrographs. And this study shows that GRM is able to simulate appropriately the effect of dam discharge and rainfall on watershed runoff.

Estimation of Storm Hydrographs in a Small Forest Watershed Using a Distributed Hydrological Model (분포형 수문모형을 이용한 산림소유역의 홍수수문곡선의 추정)

  • Lee, Sang-Ho;Woo, Bo-Myeong;Im, Sang-Jun
    • Korean Journal of Ecology and Environment
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    • v.41 no.1
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    • pp.43-53
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    • 2008
  • This study was conducted to simulate storm hydrographs on a small forested watershed using TOPMODEL, which is a distributed hydrological model. The Myeongseong watershed, which is 58.3 ha in size, was selected to monitor rainfall and runoff data. The Monte Carlo simulation was also used to calibrate parameters of TOPMODEL. Six rainfall-runoff pairs collected at the watershed in the year 1997 were used for parameter calibration, and eight rainfall-runoff pairs collected during the period of $1998\sim1999$ were used for validation effort. The errors of runoff volume ranged from -2.74% to 1.81%, and an average value of model efficiency in terms of runoff volume was 0.92 for the calibration period. The average value of observed peak discharge was $0.324m^3\;s^{-1}$ for six rainfall-runoff pairs, while the prediction value was $0.295m^3\;s^{-1}$. The simulation errors of peak discharge varied according to rainfall characteristics and antecedent condition, within ranges of -27.65% to -1.13%. The model efficiency for the validation period was 0.92. For the validation period, observed peak discharges have an average value of $0.087m^3\;s^{-1}$ and average value of simulated peak discharge was $0.090m^3\;s^{-1}$. Observed and simulated values of time to peak for the calibration period were 18.3 hrs and 11.0 hrs, respectively, and 16.6 hrs and 13.5 hrs, respectively, for the validation period.

Hydrograph Separation using Geochemical tracers by Three-Component Mixing Model for the Coniferous Forested Catchment in Gwangneung Gyeonggido, Republic of Korea

  • Kim, Kyongha;Yoo, Jae-Yun
    • Journal of Korean Society of Forest Science
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    • v.96 no.5
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    • pp.561-566
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    • 2007
  • This study was conducted to clarify runoff production processes in forested catchment through hydrograph separation using three-component mixing model based on the End Member Mixing Analysis (EMMA) model. The study area is located in the coniferous-forested experimental catchment, Gwangneung Gyeonggido near Seoul, Korea (N 37 45', E 127 09'). This catchment is covered by Pinus Korainensis and Abies holophylla planted at stocking rate of 3,000 trees $ha^{-1}$ in 1976. Thinning and pruning were carried out two times in the spring of 1996 and 2004 respectively. We monitored 8 successive events during the periods from June 15 to September 15, 2005. Throughfall, soil water and groundwater were sampled by the bulk sampler. Stream water was sampled every 2-hour through ISCO automatic sampler for 48 hours. The geochemical tracers were determined in the result of principal components analysis. The concentrations of $SO_4{^{2-}$ and $Na^+$ for stream water almost were distributed within the bivariate plot of the end members; throughfall, soil water and groundwater. Average contributions of throughfall, soil water and groundwater on producing stream flow for 8 events were 17%, 25% and 58% respectively. The amount of antecedent precipitation (AAP) plays an important role in determining which end members prevail during the event. It was found that ground water contributed more to produce storm runoff in the event of a small AAP compared with the event of a large AAP. On the other hand, rain water showed opposite tendency to ground water. Rain water in storm runoff may be produced by saturation overland flow occurring in the areas where soil moisture content is near saturation. AAP controls the producing mechanism for storm runoff whether surface or subsurface flow prevails.

A Modified grid-based KIneMatic wave STOrm Runoff Model (ModKIMSTORM) (I) - Theory and Model - (격자기반 운동파 강우유출모형 KIMSTORM의 개선(I) - 이론 및 모형 -)

  • Jung, In Kyun;Lee, Mi Seon;Park, Jong Yoon;Kim, Seong Joon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6B
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    • pp.697-707
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    • 2008
  • The grid-based KIneMatic wave STOrm Runoff Model (KIMSTORM) by Kim (1998) predicts the temporal variation and spatial distribution of overland flow, subsurface flow and stream flow in a watershed. The model programmed with C++ language on Unix operating system adopts single flowpath algorithm for water balance simulation of flow at each grid element. In this study, we attempted to improve the model by converting the code into FORTRAN 90 on MS Windows operating system and named as ModKIMSTORM. The improved functions are the addition of GAML (Green-Ampt & Mein-Larson) infiltration model, control of paddy runoff rate by flow depth and Manning's roughness coefficient, addition of baseflow layer, treatment of both spatial and point rainfall data, development of the pre- and post-processor, and development of automatic model evaluation function using five evaluation criteria (Pearson's coefficient of determination, Nash and Sutcliffe model efficiency, the deviation of runoff volume, relative error of the peak runoff rate, and absolute error of the time to peak runoff). The modified model adopts Shell Sort algorithm to enhance the computational performance. Input data formats are accepted as raster and MS Excel, and model outputs viz. soil moisture, discharge, flow depth and velocity are generated as BSQ, ASCII grid, binary grid and raster formats.

Modified grid-based KIneMatic wave STOrm Runoff Model (ModKIMSTORM) (격자기반의 운동파 강우유출모형 KIMSTORM의 개선)

  • Jung, In-Kyun;Shin, Hyung-Jin;Park, Jin-Hyeog;Kim, Seong-Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.254-258
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    • 2008
  • 본 연구는 격자기반 운동파 강우유출모형 KIMSTORM(grid-based KIneMatic wave STOrm Runoff Model)의 기능을 개선하고 적용성을 평가하는 것이다. KIMSTORM은 김성준(1998)이 개발한 분포형 강우유출모형으로 포화상태의 지표흐름 및 토양수분상태의 시공간적인 분포를 파악할 수 있다. UNIX C++ 언어로 개발되었으며, GRASS 형태의 ASCII Grid를 입출력하도록 구성되어 있는 모형으로 UNIX 운영체제에서 구동이 가능하다. 그러나 UNIX와 GRASS는 최근에 많이 이용되지 않는 추세로 KIMSTORM 모형을 이용한 홍수유출해석이 적극적으로 활용되는데 주요 제약사항이 되어 왔다. 본 연구에서는 KIMSTORM을 윈도우즈 환경에서 운영될 수 있도록 FORTRAN 90을 이용하여 재개발하였으며 주요개선 사항으로, ESRI ASCII Grid 형태의 GIS(geographic information system) 자료 입력, 물리적 침투모의 방법인 GAML (Green-Ampt and Mein- Larson) 적용, 공간강우 입력가능, 정렬 알고리즘을 이용한 계산속도의 개선, 모형 자료입력 등 전처리 기능개선, 계산결과의 자동평가 및 분포도출력 등 후처리 방식개선으로 요약할 수 있다. 개선된 모형 GAML에 의한 침투방법을 적용하여, 남강댐유역($2,293\;km^2$)의 6개 강우사상을 대상으로 결정계수, Nash & Sutcliffe 모형효율계수, 용적편차, 첨두유량의 상대오차, 첨두시간의 절대오차를 이용하여 적용성을 평가하였으며, 민감도분석결과 초기토양수분조건과 하천조도계수가 가장 큰 민감도를 나타내었다.

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Evaluation of GPM satellite and S-band radar rain data for flood simulation using conditional merging method and KIMSTORM2 distributed model (조건부합성 기법과 KIMSTORM2 분포형 수문모형을 이용한 GPM 위성 강우자료 및 Radar 강우자료의 홍수모의 평가)

  • Kim, Se Hoon;Jung, Chung Gil;Jang, Won Jin;Kim, Seong Joon
    • Journal of Korea Water Resources Association
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    • v.52 no.1
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    • pp.21-33
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    • 2019
  • This study performed to simulate the watershed storm runoff using data of S-band dual-polarization radar rain, GPM (Global Precipitation Mission) satellite rain, and observed rainfall at 21 ground stations operated by KMA (Korea Meteorological Administration) respectively. For the 3 water level gauge stations (Sancheong, Changchon, and Namgang) of NamgangDam watershed ($2,293km^2$), the KIMSTORM2 (KIneMatic wave STOrm Runoff Model2) was applied and calibrated with parameters of initial soil moisture contents, Manning's roughness of overland and stream to the event of typhoon CHABA (82 mm in watershed aveprage) in $5^{th}$ October 2016. The radar and GPM data was corrected with CM (Conditional Merging) method such as CM-corrected Radar and CM-corrected GPM. The CM has been used for accurate rainfall estimation in water resources and meteorological field and the method combined measured ground rainfall and spatial data such as radar and satellite images by the kriging interpolation technique. For the CM-corrected Radar and CM-corrected GPM data application, the determination coefficient ($R^2$) was 0.96 respectively. The Nash-Sutcliffe efficiency (NSE) was 0.96 and the Volume Conservation Index (VCI) was 1.03 respectively. The CM-corrected data of Radar and GPM showed good results for the CHABA peak runoff and runoff volume simulation and improved all of $R^2$, NSE, and VCI comparing with the original data application. Thus, we need to use and apply the radar and satellite data to monitor the flood within the watershed.

Runoff Analysis using ModClark Model (ModClark 모형을 이용한 유출 해석)

  • Ahn, Sang-Jin;Yoon, Seok-Hwan
    • Journal of Korea Water Resources Association
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    • v.38 no.3 s.152
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    • pp.245-257
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    • 2005
  • The purpose of the present study is examining the changes of runoff characteristics and extracting hydrologic parameters by applying ModClark model on grid divided watershed. Bocheong stream basin in Geum River system, one of the representative watersheds of IHP projects, is selected. Hydrology-based topographical informations are calculated using GIS data in the HEC-GeoHMS V1.1 extension in Arcview 3.2. The ModClark model requires precipitation data in a gridded format. The gridded data must be recorded in the HEC Data Storage System file format. Therefore, kriging method was used to interpolate the point values to create a grid that gives each cell over the entire watershed a precipitation value. Hec-DSSVue program was used to create DSS file for the rain gage data. The completed HEC-HMS model was calibrated for use in simulating three measured storm events and cell size of 10000m, 5000m, 2000m, 1000m was chosen for the application. As the result of applying distributed rainfall-runoff model to analyze relatively good agreement for peak discharge, runoff volume and peak time.

Yongdam Dam Watershed Flood Simulation Using GPM Satellite Data and KIMSTORM2 Distributed Storm Runoff Model (GPM위성 강우자료와 KIMSTORM2 분포형 유출모형을 이용한 용담댐 유역 홍수모의)

  • KIM, Se-Hoon;KIM, Jin-Uk;CHUNG, Jee-Hun;KIM, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.4
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    • pp.39-58
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    • 2019
  • This study performed the dam watershed storm runoff modeling using GPM(Global Precipitation Measurement) satellite rain and KIMSTORM2(KIneMatic wave STOrm Runoff Model 2) distributed model. For YongdamDam watershed(930㎢), three heavy rain events of 25th August 2014, 11th September 2017, and 26th June 2018 were selected and tested for 4 cases of spatial rainfalls such as (a) Kriging interpolated data using ground observed data at 7 stations, (b) original GPM data, (c) GPM corrected by CM(Conditional Merging), and GPM corrected by GDA(Geographical Differential Analysis). For the 4 kinds of data(Kriging, GPM, CM-GPM, and GDA-GPM), the KIMSTORM2 was calibrated respectively using the observed flood discharges at 3 water level gauge stations(Cheoncheon, Donghyang, and Yongdam) with parameters of initial soil moisture contents, stream Manning's roughness coefficient, and effective hydraulic conductivity. The total average Nash-Sutcliffe efficiency(NSE) for the 3 events and 3 stations was 0.94, 0.90, 0.94, and 0.94, determination coefficient(R2) was 0.96, 0.92, 0.97 and 0.96, the volume conservation index(VCI) was 1.03, 1.01, 1.03 and 1.02 for Kriging, GPM, CM-GPM, and GDA-GPM applications respectively. The CM-GPM and GDA-GPM showed better results than the original GPM application for peak runoff and runoff volume simulations, and they improved NSE, R2, and VCI results.

LIDMOD3 Development for Design and Evaluation of Low Impact Development (저영향개발기법 설계 및 평가를 위한 LIDMOD3 개발)

  • Jeon, Ji-Hong;Seo, Seong-Cheol
    • Journal of Korean Society on Water Environment
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    • v.34 no.4
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    • pp.382-390
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    • 2018
  • In this study, the LIDMOD3 was developed to design and evaluate low impact development (LIDMOD). In the same fashion, the LIDMOD3 employs a curve number (NRCS-CN) method to estimate the surface runoff, infiltration and event mean concentration as applicable to pollutant loads which are based on a daily time step. In these terms, the LIDMOD3 can consider a hydrologic soil group for each land use type LID-BMP, and the applied removal efficiency of the surface runoff and pollutant loads by virtue of the stored capacity, which was calculated by analyzing the recorded water balance. As a result of Model development, the LIDMOD3 is based on an Excel spread sheet and consists of 8 sheets of information data, including: General information, Annual precipitation, Land use, Drainage area, LID-BMPs, Cals-cap, Parameters, and the Results. In addition, the LIDMOD3 can estimate the annual hydrology and annual pollutant loads including surface runoff and infiltration, the LID efficiency of the estimated surface runoff for a design rainfall event, and an analysis of the peak flow and time to peak using a unit hydrolograph for pre-development, post-development without LID, and as calculated with LID. As a result of the model application as applied to an apartment, the LIDMOD3 can estimate LID-BMPs considering a well spatical distributed hydroloic soil group as realized on land use and with the LID-BMPs. Essentially, the LIDMOD3 is a screen level and simple model which is easy to use because it is an Excel based model, as are most parameters in the database. This system can be expected to be widely used at the LID site to collect data within various programmable model parameters for the processing of a detail LID model simulation.

Distributed GIS-Based Watershed Rainfall-Runoff Model Development and Its Calibration using Weather Radar (기상레이더와 지형정보시스템을 이용한 분포형 강우-유출 유역모형의 개발과 검정)

  • Skahill, Brian E.;Choi, Woo-Hee;Kim, Min-Hwan;Kim, Sung-Kyun;Johnson, Lynn E.
    • Journal of Korea Water Resources Association
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    • v.36 no.2
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    • pp.285-300
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    • 2003
  • An event-based, kinematic, infiltration-excess, and distributed rainfall-runoff model using weather radar and Geographic Information System(GIS) was developed to acknowledge and account lot the spatial variability and uncertainty of several parameters relevant to storm surface runoff and surface flow The developed model is compatible with raster GIS and spatially and temporally varied rainfall data. To calibrate the model, Monte Carlo simulation and a likelihood measure are utilized; allowing for a range of possible system responses from the calibrated model. Using rain gauge adjusted radar-rainfall estimates, the developed model was applied and evaluated to a limited number of historical events for the Ralston Creek and Goldsmith Gulch basins within the Denver Urban Drainage and Flood Control District (UDFCD) that contain mixed land use classifications. While based on a limited number of Monte Carlo simulations and considered flood events, Nash and Sutcliffe efficiency score ranges of -0.19∼0.95 / -0.75∼0.81 were obtained from the calibrated models for the Ralston Creek and Goldsmith Gulch basins, based on a comparison of observed and simulated hydrographs. For the Ralston Creek and Goldsmith Gulch basins, Nash and Sutcliffe efficiency scores of 0.88/0.10, 0.14/0.71, and 0.99/0.95 for runoff volume, peak discharge, and time to peak, respectively, were obtained from the model.