Streamflow Synthesis And Reservoir Regulation Research Articles

Using Data-Driven Prediction of Downstream 1D River Flow to Overcome the Challenges of Hydrologic River Modeling

Methods for downstream river flow prediction can be categorized into physics-based and empirical approaches. Although based on well-studied physical relationships, physics-based models rely on numerous hydrologic variables characteristic of the specific river system that can be costly to acquire. Moreover, simulation is often computationally intensive. Conversely, empirical models require less information about the system being modeled and can capture a system’s interactions based on a smaller set of observed data. This article introduces two empirical methods to predict downstream hydraulic variables based on observed stream data: a linear programming (LP) model, and a convolutional neural network (CNN). We apply both empirical models within the Colorado River system to a site located on the Green River, downstream of the Yampa River confluence and Flaming Gorge Dam, and compare it to the physics-based model Streamflow Synthesis and Reservoir Regulation (SSARR) currently used by federal agencies. Results show that both proposed models significantly outperform the SSARR model. Moreover, the CNN model outperforms the LP model for hourly predictions whereas both perform similarly for daily predictions. Although less accurate than the CNN model at finer temporal resolution, the LP model is ideal for linear water scheduling tools.

Assessing environmental flows of coordinated operation of dams and weirs in the Geum River basin under climate change scenarios

The International Panel on Climate Change (IPCC) has predicted frequent and severe droughts and floods caused by irregular climatic conditions in the future, making water resources management difficult. Within the field of integrated watershed management, the concept of ‘environmental flow’ is being increasingly studied. In Korea, the Four Major Rivers Restoration Project was carried out as part of the plan to manage future water resources, particularly in response to climate change. In order to improve comprehensive water resources management, there is an interest in integrating into the operation of the existing dams the multi-functional weirs constructed under the said project. To date, there is an absence of studies comprehensively considering climate change, run-off volume, reservoir operations, and environmental flow, with most of the existing studies focusing only on one or the other of these factors. In this study, we presented a method to evaluate the river environment that considers all the said factors. To evaluate how environmental flow is influenced by the changes in river flow due to climate change and hydraulic structure operation, the Streamflow Synthesis and Reservoir Regulation (SSARR) was used as the hydrological model, HEC-ResSim was used as the hydraulic structures operational model, and the Global Environmental Flow Calculator (GEFC) was used as the method to evaluate environmental flows. RCP climate change scenarios, provided by the Climate Change Information Center (CCIC), a branch of the Korea Meteorological Administration, were applied to analyze the future watershed runoff characteristics of the Geum River Basin under different hydraulic structure operation modes. This study concludes that efficient use of water resources can be achieved through the integrated operation of the dams and multi-functional weirs in times of water shortage. Comparing the results of modelling under a no‑carbon reduction scenario on one hand, and a scenario in which emissions were reduced on the other hand, differences were found in flows during floods, in the mean annual runoff ratio in accordance with the environment management class, and in the environmental flow rating. It appears that a new water resources management plan is required to respond to climate change as indicated by the shift of the flow duration curve to a lower environmental management class (EMC) under climate change scenarios.

Hydrologic Modeling for Simulation of Rainfall-Runoff at Major Control Points of Geum River Watershed

With the recent increase in frequency of extreme hydrological events and climate change, the number of natural disasters increased dramatically in Korea. In this study daily rainfall and discharge data was extracted from Daecheong dam, Yongdam dam, Gongju, Gyuam and Ganggyeong, the major control points of Geum river watershed. The rainfall data from 83 rainfall stations was spatially distributed and utilized as input data in Streamflow Synthesis and Reservoir Regulation (SSARR) rainfall-runoff model. The major input parameters are Soil Moisture Index (SMI), Baseflow Infiltration Index (BII), Surface ¬Subsurface Separation (S-SS) and Lag time (Ts). For the calibration of parameters of SSARR model, the rainfall and discharge data 2006∼2007 year was prepared using the stage-discharge rating curve at the major control point of Geum river watershed. The hydrologic parameters of the SSARR model were verified utilizing 2004 year data. Model calibration results showed that the average relative error during 2006∼2007 year decreased significantly after the calibration. Verification of the model also showed reduction in relative error. Overall model results showed that the quantity of designed flood during 2007 year at all major control points of the Geum river watershed is relatively more as compared to 2006 year. The results of this study can be useful for hydraulic structures designing; landscape planning and can serve as basic data to cope with the flood risk at Geum river watershed in future.

Development of water quality forecasting system with ensemble stream prediction method in the Geum River Basin, Korea

The accurate prediction of the water quality of a river is very important in identifying instream flow and water supply requirements and solving relevant environmental problems. The purpose of the study is to develop a water quality forecasting system for the Geum River in Korea. The water quality forecasting system was composed with the Streamflow Synthesis and Reservoir Regulation (SSARR) for watershed runoff simulation and Qual2E for calculation of river quality. The SSARR model was improved by applying the Optimal Linear Correction method and was also used to predict probabilistic streamflow with the ensemble stream prediction. The water quality forecasting system was validated with data measured at the Geum River Basin in 2007 and 2008. As the results, it was found that the proposed model simulated the values of BOD, T-N, and T-P within acceptable reliability. The developed system will contribute to various prediction of water, and improvement of current water quality management practice.

Evaluation of dams and weirs operating for water resource management of the Geum River

As part of the Four Major Rivers Restoration Project, 16 multi-functional weirs have recently been constructed in each river system in Korea. The Project has pursued ecological approaches through constructing artificial weirs in waterways to ensure sufficient flow even in the dry seasons, improving agricultural reservoirs to supply environmental flow for the rivers, and thereby enhancing the water quality of the rivers. However, these anthropogenic activities have been accompanying a significant change in the riverine environment. In this study, the SSARR (Streamflow Synthesis and Reservoir Regulation) model was used to estimate natural flow in the 14 sub-basins of the Geum River. The natural flow determined by the SSARR model was used in estimation of environmental flow and input data of reservoir operation model. Hec-ResSim was used to assess runoff variations, water supply and energy generation based on the protocols for the associated operation of dams and multi-functional weirs. In addition to this, a method developed by the IWMI (International Water Management Institute) was also used to analyze the environmental flow, considering channels, water fronts and flow variations, and thereby assess the environmental management class of changing the riverine environment and to take countermeasures to mitigate the resulting adverse environmental impacts. It is hoped that the results of this study will provide basic data to establish policies for the effective operation and management of the existing dams and the newly constructed multi-functional weirs, and the effective monitoring and preservation of aquatic ecosystems in the Geum River basin.

Evaluating the SWAT's snow hydrology over a Northern Quebec watershed

AbstractThe snow treatment becomes an important component of Soil and Water Assessment Tool (SWAT)’s hydrology when spring flows are dominated by snow melting. However, little is known about SWAT's snow hydrology performance because most studies using SWAT were conducted in rainfall‐driven catchments. To fill this gap, the present study aims to evaluate the ability of SWAT in simulating snow‐melting‐dominated streamflow in the Outardes Basin in Northern Quebec. SWAT performance in simulating snowmelt is evaluated against observed streamflow data and compared to simulations from the operationally used Streamflow Synthesis and Reservoir Regulation (SSARR) model over that catchment. The SWAT 5‐year calibration showed a satisfactory performance at the daily and seasonal time scales with low volume biases. The SWAT validation was conducted over two (17‐year and 15‐year) periods. Performances were similar to the calibration period in simulating the daily and seasonal streamflows again with low model biases. The spring‐snowmelt‐generated peak flow was accurately simulated by SWAT both in magnitude and timing. When SWAT's results are compared to SSARR, similar performances in simulating the daily discharges were observed. SSARR simulates more accurately streamflow generated at the snowmelt onset whereas SWAT better predicts streamflow in summer, fall and winter. SWAT provided reasonable streamflow simulations for our snow‐covered catchment, but refinement of the process‐driven baseflow during the snowmelt onset could improve spring performances. Therefore, SWAT becomes an attractive tool for evaluating water resources management in Nordic environments when a distributed model is preferred or when water quality information (e.g. temperature) is required. Copyright © 2013 John Wiley & Sons, Ltd.

Analysis of runoff in the Han River basin by SSARR model considering agricultural water

This study begins to address the need for a runoff model that is able to simulate runoffs at control points in a dam’s upper and lower stream during the seasons of high and low water levels. We need to establish a synthetic management plan on water resources considering the runoff at the upper and lower streams to effectively manage the limited water resources in Korea. For this reason, we classified the Han River Basin into 24 sub-basins and arranged a great amount of rainfall data using 151 rainfall observation stations so as to prepare for the spatial distribution of precipitation. We chose several dams as subjects for this study, which includes the Chungju Regulating Reservoir, Soyang, Chungju, Hoengseong, Hwacheon, Chuncheon, Euiam, Cheongpyeong, and Paldang Dams as main controlling points. Also, we made up input data of this model, selecting the Streamflow Synthesis and Reservoir Regulation (SSARR) model as a runoff model in the Han River Basin. We performed a sensitivity analysis of parameters using hydrological data from the year 2002. And as a result, the findings of this study showed that, among many parameters related to the basin runoff, the following have revealed greater sensitivity than any other parameters: soil moisture index-runoff percent, baseflow infiltration index-baseflow percent, and surface-subsurface separation. On the basis of the above sensitivity analysis, we have used hydrological data between 2001 and 2002 when drafts and floods broke out in Korea to verify and calibrate the parameters of the SSARR model. Furthermore, we verified and calibrated the 2000 data using corrected parameters and performed an analysis of annual water balance in the Han River Basin from 1996 to 2005 considering agricultural water.

한강수계의 고수 및 저수기 유출모형 매개변수 민감도 분석

본 연구는 수계별 한정된 수자원의 효율적 관리를 위한 기존댐의 연계운영과 병행하여 댐 상·하류 유출을 고려한 종합적인 수자원관리방안 수립의 필요성이 대두됨에 따라, 고수기 및 저수기 댐 상 하류의 수계주요지점에 대한 하천유출상황을 모의할 수 있는 유출모형을 구성하는데 목적이 있다. 또한 장 단기적으로는 기존 모형을 검토하여 한국수자원공사의 "한강수계 댐 통합운영계획 수립" 업무에 활용될 수 있도록 하는데 있다. 본 연구에서는 한강수계의 소유역을 24개로 분할하였고 강우의 공간 분포를 작성하기 위해 151개의 강우관측소를 이용하여 강우자료를 정리하였다. 한강수계의 주요 제어지점으로 소양강댐, 충주댐, 충주 조정지댐, 횡성댐, 화천댐, 춘천댐, 의암댐, 청평댐, 팔당댐을 선정하였다. SSARR(Streamflow Synthesis and Reservoir Regulation) 모형을 기반모형으로 선정하여 모형의 입력자료를 작성하고 2002년의 수문자료를 이용하여 매개변수의 민감도 분석을 수행하였다. 민감도 분석 결과, 유역유출과 관련된 매개변수 중 토양습윤상태별 유출율, 침투량별 지하수유입률 및 지표수와 복류수를 분리하는 매개변수가 비교적 큰 민감도를 나타내었다. Growing needs for efficient management of water resources urge the joint operation of dams and integrated management of whole basin. As one of the tools for supporting above tasks, this study aims to constitute a hydrologic model that can simulate the streamflow discharges at some control points located both upper and down stream of dams. One of the currently available models is being studied to be applied with a least effort in order to support the ongoing project of KWATER (Korea Water Resources Corporation), "Establishment of integrated operation scheme for the dams in Han River Basin". On this study, following works have been carried out : division of Han River Basin into 24 sub-basins, use of rainfall data of 151 stations to make spatial distribution of rainfall, selection of control points such as Soyanggang Dam, Chungju Dam, Chungju Release Control Dam, Heongseong Dam, Hwachun Dam, Chuncheon Dam, Uiam Dam, Cheongpyung Dam and Paldang Dam, selection of SSARR (Streamflow Synthesis and Reservoir Regulation) model as a hydrologic model, preparation of input data of SSARR model, sensitivity analysis of parameter using hydrologic data of 2002. The sensitivity analysis showed that soil moisture index versus runoff percent (SMI-ROP), baseflow infiltration index versus baseflow percent (BII-BFP) and surface-subsurface separation (S-SS) parameters are higher sensitive parameters to the simulation result.

Discharge characteristics at the control point for rainfall runoff model application

AbstractTo manage and distribute water resources efficiently, a rainfall runoff model must be selected and established. To determine the appropriations for this rainfall runoff model, however, accurate flow data must first be obtained. Thus, in this study, the simulated flow of Korea's Geum River was compared with the observed flow at Gongju point, a main control point, using the Streamflow Synthesis and Reservoir Regulation (SSARR) model. The results obtained showed a huge difference between the simulated and observed flows during the low flow period. To determine what caused this difference, a confidence analysis of the formula of the stage discharge curve at Gongju point, developed by the Ministry of Construction and Transportation's Geum River Flood Control Office, was conducted. The flow during the low flow period (between 2003 and 2005) was also measured, and the value obtained was compared with the simulated flow. The long‐term flow as low flow was also calculated, through runoff component analysis, to determine the hydraulic characteristics of the control point and to examine the runoff characteristics during the low flow water utilization seasons.The study results show that during the low flow period (between 2003 and 2005), the simulated flow (based on the SSARR model) approximated the long‐term flow (based on the runoff component analysis).The results, however, also show that the observed flow, according to the stage discharge curve formula developed by the Geum River Flood Control Office, was overestimated by about 10% up to 20% both during the normal water level and drought seasons, due to hydraulic factors caused by the spatial characteristics of Gongju point, a main control point. The results of the study reveal that the estimation of the flow must be corrected, and that such flow must be continuously monitored. Copyright © 2008 John Wiley & Sons, Ltd.

A flood risk projection for Yongdam dam against future climate change

A sensitivity analysis of the flood safety of Yongdam Dam using a regional climate change simulation is presented. Based on the output of the CCSM (Community Climate System Model) general circulation model, the SNURCM (Seoul National University Regional Climate Model) computes regional scale output with 60 km spatial resolution and 21 vertical layers. Using the SRES (Special Report Emission Scenario) “B1” climate change scenario when applied to the Geum river basin, where Yongdam Dam is located, SNURCM reduces significantly the bias in Annual Maximum Event total Precipitation (AMEP) & Annual Maximum Daily Precipitation (AMDP) that CCSM shows. The streamflow change scenario is then simulated using SSARR (Streamflow Synthesis and Reservoir Regulation) model. A rainfall-runoff model was implemented using precipitation and temperature projected by CCSM and SNURCM. The model demonstrated that average streamflow would increase 38.7% and the variability would increase 14.3%. This remarkable increase in projected annual maximum flow for the next 20 years (2000-2019) should be a significant negative signal to water resources managers. This streamflow change scenario was then inputted into the G-RiBSS (Geum River Basin Systems Simulator) model to assess the sensitivity of the current river basin system to possible climate change. The result indicates that the number of floods remains almost the same, but that the magnitude of a single flood event and the recovery from it become worse.

Monthly Joint Operations for the Nakdong Multi-reservoir System in Korea

This study applies a state-of-art optimization technique, SSDP/ESP (Sampling Stochastic Dynamic Programming with Ensemble Streamflow Prediction), to derive a monthly joint operating policy for the Nakdong multi-reservoir system in Korea. A rainfall-runoff model, SSARR (Streamflow Synthesis And Reservoir Regulation), is linked to the SSDP/ESP model to provide ESP scenarios for runoff during the next month in the Nakdong River basin. The primary advantage of the SSDP/ESP is that it updates the derived operating policy as new ESP forecasts become available. Another SSDP model that employs historical runoff scenarios (SSDP/Hist) is also developed. The main difference between the two SSDP models is that SSDP/Hist is an off-line model whereas the SSDP/ESP is on-line. The developed operating policies are tested with a simulation model using an object-oriented simulation software, STELLA. The simulation results show that SSDP/ESP is superior to SSDP/Hist with respect to the water supply criterion, although both models perform similarly with respect to the hydroelectric energy production criterion.

RRFS에 의한 금강수계의 주요지점별 유역유출지표 개발

In this study, we attempted to develop a watershed runoff index subject to main control points by dividing the Geum River basin into 14 sub-basins. The Yongdam multipurpose dam Daecheong multipurpose dam and Gongju gage station were selected to serve as the main control points of the Geum River basin, and the observed flow of each control point was calculated by the discharge rating curve, whereas the simulated flow was estimated using the Rainfall Runoff Forecasting System (RRFS), user-interfaced software developed by the Korea Water Corporation, based on the Streamflow Synthesis and Reservoir Regulation (SSARR) model developed by the US Army Corps of Engineers. This study consisted of the daily unit observed flow and the simulated flow of the accumulated moving average flow by daily, 5-days, 10-days, monthly, quarterly and annually, and normal monthly/annually flow. We also performed flow duration analysis for each of the accumulated moving average and the normal monthly/annually flows by unit period, and abundant flow, ordinary flow, low flow and drought flow estimated by each flow duration analysis were utilized as watershed runoff index by main control points. Further, as we determined the current flow by unit period and the normal monthly/annually flow through the drought and flood flow analysis subject to each flow we were able to develop the watershed runoff index in a system that can be used to determine the abundance and scarcity of the flow at the corresponding point.

최적선형보정을 이용한 앙상블 유량예측 시스템의 개선

일단위 강우-유출모형인 SSARR모형을 이용하여 한강, 낙동강, 섬진강유역에 월 앙상블 유량예측 시스템을 구축하였다. 우선 SSARR모형의 월 평균 유출량에 대한 모의정확성을 평가한 결과 한강과 낙동강유역에서는 과소추정하는 경향이 뚜렷하였으며, 섬진강유역에서는 모의오차의 분산이 커 정확성 개선이 필요하였다. 최적선형 보정기법을 적용하여 SSARR모형의 모의유량을 보정한 결과, 섬진강을 제외한 한강과 낙동강유역의 검증지점에서는 모의 정확성이 크게 개선되었다. 또한 1998년부터 2003년까지 월 앙상블 유량예측을 실시하여 예측 정확성을 평가하였다. 한강과 낙동강유역에서 최적선형 보정기법을 이용할 경우 앙상블 유량예측 정확성이 크게 개선되었으나, 섬진강유역은 개선효과가 미비하였다. A monthly Ensemble Streamflow Prediction (ESP) system was developed by applying a daily rainfall-runoff model known as the Streamflow Synthesis and Reservoir Regulation (SSARR) model to the Han, Nakdong, and Seomjin River basins in Korea. This study first assesses the accuracy of the averaged monthly runoffs simulated by SSARR for the 3 basins and proposes some improvements. The study found that the SSARR modeling of the Han and Nakdong River basins tended to significantly underestimate the actual runoff levels and the modeling of the Seomjin River basinshowed a large error variance. However, by implementing optimal linear correction (OLC), the accuracy of the SSARR model was considerably improved in predicting averaged monthly runoffs of the Han and Nakdong River basins. This improvement was not seen in the modeling of the Seomjin River basin. In addition, the ESP system was applied to forecast probabilistic runoff forecasts one month in advance for the 3 river basins from 1998 to 2003. Considerably improvement was also achieved with OLC in probabilistic forecasting accuracy for the Han and Nakdong River basins, but not in that of the Seomjin River basin.

The use of snow-pillow data for melt rate input to the streamflow synthesis and reservoir regulation watershed model

A split watershed version of the streamflow synthesis and reservoir regulation (SSARR) model was calibrated and verified for Marmot Creek, a small forested research watershed located in the Rocky Mountains west of Calgary, Alberta. The model is used for forecasting runoff rates. Melt-rate data from five snow pillows, located at sites of different elevation and exposure on the basin, were applied to the model. The melt-rate factor expressed in millimetres per degree-day was the only input parameter changed in the model, which was run for the months of April, May, and June over an 8-year period, 1973–1980.An average melt rate from the snow-covered area as determined from the five snow pillows provided the best runoff simulation. Measured melt rates from just one snow pillow, located at the middle elevation of the basin in a heavily forested area, provided a comparable simulation. Snow pillows located at lower elevations in either open or closed areas and snow pillows located at higher elevations in open areas yielded poor simulations. The characteristics and problems associated with the use of snow pillow for modelling snowmelt are also discussed. Key words: snowmelt, snow pillows, watershed models, runoff forecasting.

Great Lake basins (U.S.A.-Canada) runoff modeling

Large-scale watershed models are required in order to estimate basin runoff to the Great Lakes for use in routing determinations and operational hydrology studies. Data limitations, large-basin applicability and economic efficiency preclude the use of existing large-watershed models. This paper describes an interdependent tank-cascade model that uses a mass balance coupled with linear reservoir concepts. It is physically based and uses climatological considerations not possible for small watersheds; it employs analytical solutions to bypass numerical inaccuracies. Snowmelt and net-supply computations are separable from the mass-balance determinations and are based on a simple heat balance. Partial-area concepts are used to determine infiltration and surface runoff. Losses are determined from joint consideration of available energy for evapotranspiration and of available moisture in the soil horizons by using climatologic concepts. Also described are heuristic calibration procedures that give insight into the use of the model. The model is applied, for a 30-day computation interval, to the Genesee River Basin in New York State and compared with past 6-hr. computation interval applications of the Streamflow Synthesis and Reservoir Regulation (SSARR) and National Weather Service Hydrologic (NWSH) models to the same data set.

Prévision des apports hydriques au lac Memphremagog

Within the context of studies concerning water inflow forecasts for some Quebec watersheds, a deterministic hydro-meteorological model, the SSARR (streamflow synthesis and reservoir regulation), was used for Lake Memphremagog near Magog. The low discharge capacity at the outlet of the lake and the obligation to regulate water levels, imposed both by an international agreement and by the wish to protect the environment, had made essential an accurate assessment of runoff during the spring thaw and periods of heavy rain. The results were so conclusive that tests are currently being carried out to prepare forecasts for eight other watersheds in Quebec. [Traduit par la revue]

CALIBRATING AND VERIFYING THE SSARR MODEL ‐MISSOURI RIVER WATERSHEDS STUDY1

ABSTRACTThe Streamflow Synthesis and Reservoir Regulation (SSARR) model was calibrated and verified on the Madison and Gallatin watersheds in the upper Missouri River drainage. The study was performed to determine if the SSARR model could simulate snowmelt‐runoff volumes to effect better operation of six multipurpose reservoirs on the Missouri River. Physical watershed characteristics and parameter sensitivity are incorporated into a procedure which expedites model calibration. Criteria are established to facilitate parameter development and to objectively evaluate calibration and verification results. A ratio of simulated to observed snowmelt‐runoff volumes of the Madison River averaged 1.00 and 1.02 for calibration (N = 8 years) and verification (N = 6 years) with corresponding standard deviations of 0.08 and 0.13. Gallatin volume ratios averaged 0.99 and 0.95 for calibration (N = 7 years) and verification (N = 5 years) with respective standard deviations of 0.08 and 0.28.