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• 11. [Article] Hydrodynamic and Water Quality Modeling of the Chehalis River Using CE-QUAL-W2

  The Chehalis River Basin is located in the southwest region of Washington State, originating in the Olympic Mountains and flowing to Grays Harbor and the Pacific Ocean. The Chehalis River is over 125 miles, ...

  Citation × Citation Citation Abstract Copy Title: Hydrodynamic and Water Quality Modeling of the Chehalis River Using CE-QUAL-W2 Author: Van Glubt, Sarah Year: 2017 The Chehalis River Basin is located in the southwest region of Washington State, originating in the Olympic Mountains and flowing to Grays Harbor and the Pacific Ocean. The Chehalis River is over 125 miles, exists within five counties, and flows through agricultural, residential, industrial, and forest land areas. Four major rivers discharge to the Chehalis River, as well as many smaller creeks, five wastewater treatment plants, and groundwater flows. Flooding is a major problem in the relatively flat areas surrounding the cities of Chehalis and Centralia, with severe consequences for property, safety and transportation. As a result, construction of a flood-control dam in the upper basin has been proposed. One major concern of constructing a dam is the potentially severe impacts to fish health and habitat. The Chehalis River has routinely violated water quality standards for primarily temperature and dissolved oxygen, and has had multiple water quality and Total Maximum Daily Load studies beginning in 1990. CE-QUAL-W2, a two-dimensional (longitudinal and vertical) hydrodynamic and water quality model, was used to simulate the Chehalis River, including free flowing river stretches and stratified (in summer) lake-like stretches. The goals of this research were to assess the flood retention structure's impacts to water quality, as well as river responses to potential climate change scenarios. In order to use the model to achieve these goals, calibration to field data for flow, temperature, and water quality constituents was performed. This involved developing meteorological data, riparian shading data, and flow, temperature, water quality records for all tributaries during the calibration period of January 1, 2013 to December 31, 2014. System cross-sectional geometry data were also required for the model grid. Because of the short travel time in the river, the model was sensitive to boundary condition data, wind speed, bathymetry, nutrient kinetics, and algae, epiphyton, and zooplankton kinetics. Future conditions showed predictions of warmer water temperatures and slight changes to water quality conditions on the river. As fish in the area prefer cooler water temperatures, this could pose a threat to fish health and habitat. Flood retention structures also showed impacts to river temperature and water quality. Structures with the purpose of flood retention only (only operating during times of flooding) gave model predictions for daily maximum temperature higher than structures that employed flood retention and flow augmentation (operating during all times of the year). This suggested the management of flow passage or retention by the dam is important for water quality on the river. As this research continues improvements will be made, particularly to temperature and water quality constituents. Additional data for the system would be beneficial to this process. Model predictions of temperature were sensitive to meteorological data, including cloud cover, which were largely estimated based on solar radiation. Additional meteorological data throughout the basin would be useful to temperature results. Temperature results were also sensitive to the model bathymetry, and additional investigations into segments widths and water depths may improve temperature predictions. Water quality constituent data were largely lacking for the system. Many estimation techniques and approximations were used for input water quality constituents for the model upstream boundary and tributaries when little or no data were available, introducing uncertainty to the model. It was not possible to calibrate pH to field data because alkalinity data were essentially unavailable. However, other constituents had good agreement between model predictions and field data, including dissolved oxygen, nitrates, total phosphorus, and total suspended solids. Title: Hydrodynamic and Water Quality Modeling of the Chehalis River Using CE-QUAL-W2 Author: Van Glubt, Sarah Year: 2017 The Chehalis River Basin is located in the southwest region of Washington State, originating in the Olympic Mountains and flowing to Grays Harbor and the Pacific Ocean. The Chehalis River is over 125 miles, exists within five counties, and flows through agricultural, residential, industrial, and forest land areas. Four major rivers discharge to the Chehalis River, as well as many smaller creeks, five wastewater treatment plants, and groundwater flows. Flooding is a major problem in the relatively flat areas surrounding the cities of Chehalis and Centralia, with severe consequences for property, safety and transportation. As a result, construction of a flood-control dam in the upper basin has been proposed. One major concern of constructing a dam is the potentially severe impacts to fish health and habitat. The Chehalis River has routinely violated water quality standards for primarily temperature and dissolved oxygen, and has had multiple water quality and Total Maximum Daily Load studies beginning in 1990. CE-QUAL-W2, a two-dimensional (longitudinal and vertical) hydrodynamic and water quality model, was used to simulate the Chehalis River, including free flowing river stretches and stratified (in summer) lake-like stretches. The goals of this research were to assess the flood retention structure's impacts to water quality, as well as river responses to potential climate change scenarios. In order to use the model to achieve these goals, calibration to field data for flow, temperature, and water quality constituents was performed. This involved developing meteorological data, riparian shading data, and flow, temperature, water quality records for all tributaries during the calibration period of January 1, 2013 to December 31, 2014. System cross-sectional geometry data were also required for the model grid. Because of the short travel time in the river, the model was sensitive to boundary condition data, wind speed, bathymetry, nutrient kinetics, and algae, epiphyton, and zooplankton kinetics. Future conditions showed predictions of warmer water temperatures and slight changes to water quality conditions on the river. As fish in the area prefer cooler water temperatures, this could pose a threat to fish health and habitat. Flood retention structures also showed impacts to river temperature and water quality. Structures with the purpose of flood retention only (only operating during times of flooding) gave model predictions for daily maximum temperature higher than structures that employed flood retention and flow augmentation (operating during all times of the year). This suggested the management of flow passage or retention by the dam is important for water quality on the river. As this research continues improvements will be made, particularly to temperature and water quality constituents. Additional data for the system would be beneficial to this process. Model predictions of temperature were sensitive to meteorological data, including cloud cover, which were largely estimated based on solar radiation. Additional meteorological data throughout the basin would be useful to temperature results. Temperature results were also sensitive to the model bathymetry, and additional investigations into segments widths and water depths may improve temperature predictions. Water quality constituent data were largely lacking for the system. Many estimation techniques and approximations were used for input water quality constituents for the model upstream boundary and tributaries when little or no data were available, introducing uncertainty to the model. It was not possible to calibrate pH to field data because alkalinity data were essentially unavailable. However, other constituents had good agreement between model predictions and field data, including dissolved oxygen, nitrates, total phosphorus, and total suspended solids. Close

• 12. [Article] Estimation of Columbia River Virgin Flow: 1879 to 1928

  The Columbia River has historically been a major source of economic activity for the Pacific Northwest, and is one of the more heavily modified rivers in the United States today. Understanding human and ...

  Citation × Citation Citation Abstract Copy Title: Estimation of Columbia River Virgin Flow: 1879 to 1928 Author: Naik, Pradeep K., Jay, David A. Year: 2005 The Columbia River has historically been a major source of economic activity for the Pacific Northwest, and is one of the more heavily modified rivers in the United States today. Understanding human and climate-induced changes in its hydrologic properties is, therefore, a topic of considerable interest. Long streamflow records are essential to determining how runoff has changed over time. Daily streamflow records of the Columbia River at The Dalles dates back to June 1978. However, the observed daily flow does not alone provide enough information to understand or separate anthropogenic and climate effects. It is necessary also to have an estimate of virgin flow of the river to provide a historical perspective of water resources development, separate anthropogenic and climate effects, and compare present water use scenarios with those of the past decades. The United State Geological Survey (USGS) has calculated a monthly averaged adjusted river flow at The Dalles for 1879-1999 that accounts for the effects of flow regulation. The Bonneville Power Administration (BPA) has estimated the monthly averaged virgin (or naturalized) flow at The Dalles, i.e., the flow in the absence of both flow regulation and irrigation depletion for 1929-89. We have estimated the monthly virgin flow of the Columbia River at The Dalles from records of irrigated area for the missing years, i.e., for the period 1879-1928. In addition, a filtered version of the daily observed flows were combined with monthly virgin flow corrections to obtain estimates of daily virgin flows with realistic higher moments and spectral properties. Examination of the virgin flow record shows that climate change since late 19th century has caused a decrease of >7% in its annual average flow volume. The decrease in flow due to irrigation diversion during the same period is also ~7%. Broadly speaking, there are three periods of Columbia River flow management. Before 1900, mainstem dams were absent and flow diversions relatively small. Numerous dams were constructed between 1900 and 1970, and irrigation depletion increased 500%. Since about 1970, river flows have been managed on a system-wide basin, effecting significant interannual transfers of flows for the first time. Title: Estimation of Columbia River Virgin Flow: 1879 to 1928 Author: Naik, Pradeep K., Jay, David A. Year: 2005 The Columbia River has historically been a major source of economic activity for the Pacific Northwest, and is one of the more heavily modified rivers in the United States today. Understanding human and climate-induced changes in its hydrologic properties is, therefore, a topic of considerable interest. Long streamflow records are essential to determining how runoff has changed over time. Daily streamflow records of the Columbia River at The Dalles dates back to June 1978. However, the observed daily flow does not alone provide enough information to understand or separate anthropogenic and climate effects. It is necessary also to have an estimate of virgin flow of the river to provide a historical perspective of water resources development, separate anthropogenic and climate effects, and compare present water use scenarios with those of the past decades. The United State Geological Survey (USGS) has calculated a monthly averaged adjusted river flow at The Dalles for 1879-1999 that accounts for the effects of flow regulation. The Bonneville Power Administration (BPA) has estimated the monthly averaged virgin (or naturalized) flow at The Dalles, i.e., the flow in the absence of both flow regulation and irrigation depletion for 1929-89. We have estimated the monthly virgin flow of the Columbia River at The Dalles from records of irrigated area for the missing years, i.e., for the period 1879-1928. In addition, a filtered version of the daily observed flows were combined with monthly virgin flow corrections to obtain estimates of daily virgin flows with realistic higher moments and spectral properties. Examination of the virgin flow record shows that climate change since late 19th century has caused a decrease of >7% in its annual average flow volume. The decrease in flow due to irrigation diversion during the same period is also ~7%. Broadly speaking, there are three periods of Columbia River flow management. Before 1900, mainstem dams were absent and flow diversions relatively small. Numerous dams were constructed between 1900 and 1970, and irrigation depletion increased 500%. Since about 1970, river flows have been managed on a system-wide basin, effecting significant interannual transfers of flows for the first time. Close

• 13. [Article] Cohstrex: Coherent Structures in Rivers and Estuaries Experiment

  COHSTREX, the Coherent Structures in Rivers and Estuaries Experiment, was a five-year project to exploit the remotely sensed signatures of coherent flow structures in rivers and estuaries. The purpose ...

  Citation × Citation Citation Abstract Copy Title: Cohstrex: Coherent Structures in Rivers and Estuaries Experiment Author: Jessup, Andrew, Chickadel, C., Talke, Stefan, Horner-Devine, Alexander Year: 2013 COHSTREX, the Coherent Structures in Rivers and Estuaries Experiment, was a five-year project to exploit the remotely sensed signatures of coherent flow structures in rivers and estuaries. The purpose of the study was to use remote-sensing measurements of coherent structures at a river surface to characterize and quantify the flow. Two major field experiments were undertaken on the Snohomish River near Everett, WA, United States. The first experiment took place near the mouth of the river where stratification was strong due to a tidally driven salt wedge. Flow over a rocky sill generated a field of boils (bottom-generated fluid upwellings) on the flow surface that propagated downstream and provided insight into mixing layer dynamics. The second experiment took place approximately 15[t#]km upstream from the mouth of the river where the tide still affected the river level and velocity, but stratification was minimal. The focus of the unstratified flow experiment was the study of boils generated by flow over flat beds and beds with a bottom roughness. Herein, we provide an overview of infrared measurements of thermal variability on the surface and in-situ measurements of turbulent velocities beneath the surface. A major finding of COHSTREX is that infrared imagery of the thermal signature of coherent flow structures in estuarine rivers is a powerful tool for visualizing and quantifying the flow. Thermal signatures include mixing of water masses with different temperatures, and disruptions of the flow surface by coherent flow structures generated by bottom roughness. Through use of particle image velocimetry (PIV) techniques applied to infrared imagery of the river surface, we are able to estimate mean and turbulent properties of the flow. Title: Cohstrex: Coherent Structures in Rivers and Estuaries Experiment Author: Jessup, Andrew, Chickadel, C., Talke, Stefan, Horner-Devine, Alexander Year: 2013 COHSTREX, the Coherent Structures in Rivers and Estuaries Experiment, was a five-year project to exploit the remotely sensed signatures of coherent flow structures in rivers and estuaries. The purpose of the study was to use remote-sensing measurements of coherent structures at a river surface to characterize and quantify the flow. Two major field experiments were undertaken on the Snohomish River near Everett, WA, United States. The first experiment took place near the mouth of the river where stratification was strong due to a tidally driven salt wedge. Flow over a rocky sill generated a field of boils (bottom-generated fluid upwellings) on the flow surface that propagated downstream and provided insight into mixing layer dynamics. The second experiment took place approximately 15[t#]km upstream from the mouth of the river where the tide still affected the river level and velocity, but stratification was minimal. The focus of the unstratified flow experiment was the study of boils generated by flow over flat beds and beds with a bottom roughness. Herein, we provide an overview of infrared measurements of thermal variability on the surface and in-situ measurements of turbulent velocities beneath the surface. A major finding of COHSTREX is that infrared imagery of the thermal signature of coherent flow structures in estuarine rivers is a powerful tool for visualizing and quantifying the flow. Thermal signatures include mixing of water masses with different temperatures, and disruptions of the flow surface by coherent flow structures generated by bottom roughness. Through use of particle image velocimetry (PIV) techniques applied to infrared imagery of the river surface, we are able to estimate mean and turbulent properties of the flow. Close

• 14. [Article] Identification of Appropriate Lags and Temporal Resolutions for Low Flow Indicators in the River Rhine to Forecast Low Flows with Different Lead Times

  The aim of this paper is to assess the relative importance of low flow indicators for the River Rhine and to identify their appropriate temporal lag and resolution. This is done in the context of low flow ...

  Citation × Citation Citation Abstract Copy Title: Identification of Appropriate Lags and Temporal Resolutions for Low Flow Indicators in the River Rhine to Forecast Low Flows with Different Lead Times Author: Demirel, Mehmet, Booij, Martijn, Hoekstra, Arjen Year: 2012 The aim of this paper is to assess the relative importance of low flow indicators for the River Rhine and to identify their appropriate temporal lag and resolution. This is done in the context of low flow forecasting with lead times of 14 and 90 days. First, the Rhine basin is subdivided into seven sub-basins. By considering the dominant processes in the sub-basins, five low flow indicators were selected: precipitation, potential evapotranspiration, groundwater storage, snow storage and lake storage. Correlation analysis was then carried out to determine the relationship between observed low flows and preselected indicators with varying lags (days) and temporal resolutions (from 1 day to 7 months). The results show that the most important low flow indicators in the Alpine sub-basins for forecasts with a lead time of 14 days are potential evapotranspiration with a large lag and temporal resolution, and lake levels with a small lag and temporal resolution. In the other sub-basins groundwater levels with a small lag and temporal resolution are important in addition to potential evapotranspiration with a large lag and temporal resolution. The picture is slightly different for forecasts with a lead time of 90 days. The snow storage in the Alpine sub-basins and the precipitation in the other sub-basins also become relevant for low flows. Consequently, the most important low flow indicators in the Alpine sub-basins for forecasts with a lead time of 90 days are potential evapotranspiration with a large lag and temporal resolution, lake levels with a small lag and temporal resolution and snow storage with a small lag and large temporal resolution. The resultant correlation maps provide appropriate lags and temporal resolutions for indicators to forecast low flows in the River Rhine with different lead times. Title: Identification of Appropriate Lags and Temporal Resolutions for Low Flow Indicators in the River Rhine to Forecast Low Flows with Different Lead Times Author: Demirel, Mehmet, Booij, Martijn, Hoekstra, Arjen Year: 2012 The aim of this paper is to assess the relative importance of low flow indicators for the River Rhine and to identify their appropriate temporal lag and resolution. This is done in the context of low flow forecasting with lead times of 14 and 90 days. First, the Rhine basin is subdivided into seven sub-basins. By considering the dominant processes in the sub-basins, five low flow indicators were selected: precipitation, potential evapotranspiration, groundwater storage, snow storage and lake storage. Correlation analysis was then carried out to determine the relationship between observed low flows and preselected indicators with varying lags (days) and temporal resolutions (from 1 day to 7 months). The results show that the most important low flow indicators in the Alpine sub-basins for forecasts with a lead time of 14 days are potential evapotranspiration with a large lag and temporal resolution, and lake levels with a small lag and temporal resolution. In the other sub-basins groundwater levels with a small lag and temporal resolution are important in addition to potential evapotranspiration with a large lag and temporal resolution. The picture is slightly different for forecasts with a lead time of 90 days. The snow storage in the Alpine sub-basins and the precipitation in the other sub-basins also become relevant for low flows. Consequently, the most important low flow indicators in the Alpine sub-basins for forecasts with a lead time of 90 days are potential evapotranspiration with a large lag and temporal resolution, lake levels with a small lag and temporal resolution and snow storage with a small lag and large temporal resolution. The resultant correlation maps provide appropriate lags and temporal resolutions for indicators to forecast low flows in the River Rhine with different lead times. Close

• 15. [Article] Flow Forecast by SWAT Model and ANN in Pracana Basin, Portugal

  This study provides a unique opportunity to analyze the issue of flow forecast based on the soil and water assessment tool (SWAT) and artificial neural network (ANN) models. In last two decades, the ANNs ...

  Citation × Citation Citation Abstract Copy Title: Flow Forecast by SWAT Model and ANN in Pracana Basin, Portugal Author: Demirel, Mehmet, Venancio, Anabela, Kahya, Ercan Year: 2009 This study provides a unique opportunity to analyze the issue of flow forecast based on the soil and water assessment tool (SWAT) and artificial neural network (ANN) models. In last two decades, the ANNs have been extensively applied to various water resources system problems. In this study, the ANNs were applied to the daily flow of the Pracana basin in Portugal. The comparison of ANN models and a process-based model SWAT was established based on their prediction accuracy. The ANN model was found to be more successful than the SWAT in relation to better forecast of peak flow. Nevertheless the SWAT model results revealed a better value of mean squared error. The results of this study, in general, showed that ANNs can be powerful tools in daily flow forecasts. Title: Flow Forecast by SWAT Model and ANN in Pracana Basin, Portugal Author: Demirel, Mehmet, Venancio, Anabela, Kahya, Ercan Year: 2009 This study provides a unique opportunity to analyze the issue of flow forecast based on the soil and water assessment tool (SWAT) and artificial neural network (ANN) models. In last two decades, the ANNs have been extensively applied to various water resources system problems. In this study, the ANNs were applied to the daily flow of the Pracana basin in Portugal. The comparison of ANN models and a process-based model SWAT was established based on their prediction accuracy. The ANN model was found to be more successful than the SWAT in relation to better forecast of peak flow. Nevertheless the SWAT model results revealed a better value of mean squared error. The results of this study, in general, showed that ANNs can be powerful tools in daily flow forecasts. Close

• 16. [Article] Seasonality of Low Flows and Dominant Processes in the Rhine River

  Low flow forecasting is crucial for sustainable cooling water supply and planning of river navigation in the Rhine River. The first step in reliable low flow forecasting is to understand the characteristics ...

  Citation × Citation Citation Abstract Copy Title: Seasonality of Low Flows and Dominant Processes in the Rhine River Author: Tongal, Hakan, Demirel, Mehmet, Booij, Martijn Year: 2013 Low flow forecasting is crucial for sustainable cooling water supply and planning of river navigation in the Rhine River. The first step in reliable low flow forecasting is to understand the characteristics of low flow. In this study, several methods are applied to understand the low flow characteristics of Rhine River basin. In 108 catchments of the Rhine River, winter and summer low flow regions are determined with the seasonality ratio (SR) index. To understand whether different numbers of processes are acting in generating different low flow regimes in seven major sub-basins (namely, East Alpine, West Alpine, Middle Rhine, Neckar, Main, Mosel and Lower Rhine) aggregated from the 108 catchments, the dominant variable concept is adopted from chaos theory. The number of dominant processes within the seven major sub-basins is determined with the correlation dimension analysis. Results of the correlation dimension analysis show that the minimum and maximum required number of variables to represent the low flow dynamics of the seven major sub-basins, except the Middle Rhine and Mosel, is 4 and 9, respectively. For the Mosel and Middle Rhine, the required minimum number of variables is 2 and 6, and the maximum number of variables is 5 and 13, respectively. These results show that the low flow processes of the major sub-basins of the Rhine could be considered as non-stochastic or chaotic processes. To confirm this conclusion, the rescaled range analysis is applied to verify persistency (i.e. non-randomness) in the processes. The estimated rescaled range statistics (i.e. Hurst exponents) are all above 0.5, indicating that persistent long-term memory characteristics exist in the runoff processes. Finally, the mean values of SR indices are compared with the nonlinear analyses results to find significant relationships. The results show that the minimum and maximum numbers of required variables (i.e. processes) to model the dynamic characteristics for five out of the seven major sub-basins are the same, but the observed low flow regimes are different (winter low flow regime and summer low flow regime). These results support the conclusion that a few interrelated nonlinear variables could yield completely different behaviour (i.e. dominant low flow regime). Title: Seasonality of Low Flows and Dominant Processes in the Rhine River Author: Tongal, Hakan, Demirel, Mehmet, Booij, Martijn Year: 2013 Low flow forecasting is crucial for sustainable cooling water supply and planning of river navigation in the Rhine River. The first step in reliable low flow forecasting is to understand the characteristics of low flow. In this study, several methods are applied to understand the low flow characteristics of Rhine River basin. In 108 catchments of the Rhine River, winter and summer low flow regions are determined with the seasonality ratio (SR) index. To understand whether different numbers of processes are acting in generating different low flow regimes in seven major sub-basins (namely, East Alpine, West Alpine, Middle Rhine, Neckar, Main, Mosel and Lower Rhine) aggregated from the 108 catchments, the dominant variable concept is adopted from chaos theory. The number of dominant processes within the seven major sub-basins is determined with the correlation dimension analysis. Results of the correlation dimension analysis show that the minimum and maximum required number of variables to represent the low flow dynamics of the seven major sub-basins, except the Middle Rhine and Mosel, is 4 and 9, respectively. For the Mosel and Middle Rhine, the required minimum number of variables is 2 and 6, and the maximum number of variables is 5 and 13, respectively. These results show that the low flow processes of the major sub-basins of the Rhine could be considered as non-stochastic or chaotic processes. To confirm this conclusion, the rescaled range analysis is applied to verify persistency (i.e. non-randomness) in the processes. The estimated rescaled range statistics (i.e. Hurst exponents) are all above 0.5, indicating that persistent long-term memory characteristics exist in the runoff processes. Finally, the mean values of SR indices are compared with the nonlinear analyses results to find significant relationships. The results show that the minimum and maximum numbers of required variables (i.e. processes) to model the dynamic characteristics for five out of the seven major sub-basins are the same, but the observed low flow regimes are different (winter low flow regime and summer low flow regime). These results support the conclusion that a few interrelated nonlinear variables could yield completely different behaviour (i.e. dominant low flow regime). Close

• 17. [Article] Low Flow Forecasting with a Lead Time of 14 days for Navigation and Energy Supply in the Rhine River

  Low flow forecasting, days or even months in advance, is particularly important to the efficient operation of power plants and freight shipment. This study presents a low flow forecasting model with a ...

  Citation × Citation Citation Abstract Copy Title: Low Flow Forecasting with a Lead Time of 14 days for Navigation and Energy Supply in the Rhine River Author: Demirel, Mehmet C., Booij, Martijn Year: 2011 Low flow forecasting, days or even months in advance, is particularly important to the efficient operation of power plants and freight shipment. This study presents a low flow forecasting model with a lead time of 14 days for the Rhine River. The forecasts inherit uncertainty sources mainly because of model parameterization. Therefore, a systematic uncertainty analysis is applied to indicate the major uncertainty sources in the results. Firstly, the Rhine basin is divided into 7 major sub-basins. Each sub-basin is modeled separately with a data-driven model and the output discharges are routed to Lobith after German-Dutch border with another data-driven model. Five pre-selected low flow indicators (basin averaged precipitation, basin averaged potential evapotranspiration; basin averaged fresh snow depths, basin averaged groundwater levels and major lake levels in the sub-basins) are used as inputs to the models. The basin discretization and the selection of indicators are based on a literature study and seasonality analysis of the discharge time series from 108 sub-basins. The correlations between indicator and low flows with varying temporal resolution and varying lags between indicator and low flows were used to identify appropriate temporal scales of the model inputs. We assume that a suitable model structure for the Rhine basin has been determined; that is, the sub-system boundaries have been specified, the important state variables and input and output fluxes to be included have been identified and selected for each sub-basin. The results in this study show that the data-driven models used for each sub-basin are capable of representing the essential characteristics of the system based on lagged and temporally averaged low flow indicators and are forecasting low flows adequately. In addition to the forecast results, the uncertainties due to specific model parameters in the calibrated data-driven model corresponding to key processes are also given. Title: Low Flow Forecasting with a Lead Time of 14 days for Navigation and Energy Supply in the Rhine River Author: Demirel, Mehmet C., Booij, Martijn Year: 2011 Low flow forecasting, days or even months in advance, is particularly important to the efficient operation of power plants and freight shipment. This study presents a low flow forecasting model with a lead time of 14 days for the Rhine River. The forecasts inherit uncertainty sources mainly because of model parameterization. Therefore, a systematic uncertainty analysis is applied to indicate the major uncertainty sources in the results. Firstly, the Rhine basin is divided into 7 major sub-basins. Each sub-basin is modeled separately with a data-driven model and the output discharges are routed to Lobith after German-Dutch border with another data-driven model. Five pre-selected low flow indicators (basin averaged precipitation, basin averaged potential evapotranspiration; basin averaged fresh snow depths, basin averaged groundwater levels and major lake levels in the sub-basins) are used as inputs to the models. The basin discretization and the selection of indicators are based on a literature study and seasonality analysis of the discharge time series from 108 sub-basins. The correlations between indicator and low flows with varying temporal resolution and varying lags between indicator and low flows were used to identify appropriate temporal scales of the model inputs. We assume that a suitable model structure for the Rhine basin has been determined; that is, the sub-system boundaries have been specified, the important state variables and input and output fluxes to be included have been identified and selected for each sub-basin. The results in this study show that the data-driven models used for each sub-basin are capable of representing the essential characteristics of the system based on lagged and temporally averaged low flow indicators and are forecasting low flows adequately. In addition to the forecast results, the uncertainties due to specific model parameters in the calibrated data-driven model corresponding to key processes are also given. Close

• 18. [Article] Validation of an ANN Flow Prediction Model Using a Multt-Station Cluster Analysis

  The objective of this study is to validate a flow prediction model for a hydrometric station using a multistation criterion in addition to standard single-station performance criteria. In this contribution ...

  Citation × Citation Citation Abstract Copy Title: Validation of an ANN Flow Prediction Model Using a Multt-Station Cluster Analysis Author: Demirel, Mehmet, Booij, Martijn, Kahya, Ercan Year: 2012 The objective of this study is to validate a flow prediction model for a hydrometric station using a multistation criterion in addition to standard single-station performance criteria. In this contribution we used cluster analysis to identify the regional flow height, i.e., water-level patterns and validate the output of an artificial neural network (ANN) model of the Alportel River in Portugal. Measurements of precipitation, temperature, and flow height were used as input variables to the ANN model with a lead time of 12 h. The lead time of 12 h is assumed to be appropriate for a short-term hydrological prediction since it is meaningful for physical processes. The ANN model with three inputs, four hidden neurons, and ten epochs was tested using the new model-validation criterion. The high performance of the model (i.e., Nash-Sutcliffe coefficient is equal to 0.922) was confirmed by the cluster-analysis criterion. It can be concluded that a multistation-based approach can be used as an additional validation criterion and might result in a rejection of a model which initially passed a single-station validation criterion. Title: Validation of an ANN Flow Prediction Model Using a Multt-Station Cluster Analysis Author: Demirel, Mehmet, Booij, Martijn, Kahya, Ercan Year: 2012 The objective of this study is to validate a flow prediction model for a hydrometric station using a multistation criterion in addition to standard single-station performance criteria. In this contribution we used cluster analysis to identify the regional flow height, i.e., water-level patterns and validate the output of an artificial neural network (ANN) model of the Alportel River in Portugal. Measurements of precipitation, temperature, and flow height were used as input variables to the ANN model with a lead time of 12 h. The lead time of 12 h is assumed to be appropriate for a short-term hydrological prediction since it is meaningful for physical processes. The ANN model with three inputs, four hidden neurons, and ten epochs was tested using the new model-validation criterion. The high performance of the model (i.e., Nash-Sutcliffe coefficient is equal to 0.922) was confirmed by the cluster-analysis criterion. It can be concluded that a multistation-based approach can be used as an additional validation criterion and might result in a rejection of a model which initially passed a single-station validation criterion. Close

• 19. [Article] Impacts of Columbia River Discharge on Salmonid Habitat: 2. Changes in Shallow-Water Habitat

  This is the second part of an investigation that analyzes human alteration of shallow-water habitat (SWH) available to juvenile salmonids in the tidal Lower Columbia River. Part 2 develops a one-dimensional, ...

  Citation × Citation Citation Abstract Copy Title: Impacts of Columbia River Discharge on Salmonid Habitat: 2. Changes in Shallow-Water Habitat Author: Jay, David A., Kukulka, Tobias Year: 2003 This is the second part of an investigation that analyzes human alteration of shallow-water habitat (SWH) available to juvenile salmonids in the tidal Lower Columbia River. Part 2 develops a one-dimensional, subtidal river stage model that explains ~90% of the stage variance in the tidal river. This model and the tidal model developed in part 1 (Kukulka and Jay, 2003) uncouple the nonlinear interaction of river tides and river stage by referring both to external forcing by river discharge, ocean tides, and atmospheric pressure. Applying the two models, daily high-water levels were predicted for a reach from rkm-50 to rkm-90 during 1974 to 1998, the period of contemporary management. Predicted water levels were related to the bathymetry and topography to determine the changes in shallow-water habitat area (SWHA) caused by flood control dikes and altered flow management. Model results suggest that diking and a >40% reduction of peak flows have reduced SWHA by ~62% during the crucial spring freshet period during which juvenile salmon use of SWHA is maximal. Taken individually, diking and flow cycle alteration reduced spring freshet SWHA by 52% and 29%, respectively. SWHA has been both displaced to lower elevations and modified in its character because tidal range has increased. Our models of these processes are economical for the very long simulations (seasons to centuries) needed to understand historic changes and climate impacts on SWH. Through analysis of the nonlinear processes controlling surface elevation in a tidal river, we have identified some of the mechanisms that link freshwater discharge to SWH and salmonid survival. Title: Impacts of Columbia River Discharge on Salmonid Habitat: 2. Changes in Shallow-Water Habitat Author: Jay, David A., Kukulka, Tobias Year: 2003 This is the second part of an investigation that analyzes human alteration of shallow-water habitat (SWH) available to juvenile salmonids in the tidal Lower Columbia River. Part 2 develops a one-dimensional, subtidal river stage model that explains ~90% of the stage variance in the tidal river. This model and the tidal model developed in part 1 (Kukulka and Jay, 2003) uncouple the nonlinear interaction of river tides and river stage by referring both to external forcing by river discharge, ocean tides, and atmospheric pressure. Applying the two models, daily high-water levels were predicted for a reach from rkm-50 to rkm-90 during 1974 to 1998, the period of contemporary management. Predicted water levels were related to the bathymetry and topography to determine the changes in shallow-water habitat area (SWHA) caused by flood control dikes and altered flow management. Model results suggest that diking and a >40% reduction of peak flows have reduced SWHA by ~62% during the crucial spring freshet period during which juvenile salmon use of SWHA is maximal. Taken individually, diking and flow cycle alteration reduced spring freshet SWHA by 52% and 29%, respectively. SWHA has been both displaced to lower elevations and modified in its character because tidal range has increased. Our models of these processes are economical for the very long simulations (seasons to centuries) needed to understand historic changes and climate impacts on SWH. Through analysis of the nonlinear processes controlling surface elevation in a tidal river, we have identified some of the mechanisms that link freshwater discharge to SWH and salmonid survival. Close

• 20. [Article] Green River CE-QUAL-W2 Project: A Hydrodynamic and Water Quality Study of the Green River King County, Washington

  This report describes the data processing and model calibration performed for a hydrodynamic and water quality model of the Green River, located in King County, Washington. Figure 1 shows the location ...

  Citation × Citation Citation Abstract Copy Title: Green River CE-QUAL-W2 Project: A Hydrodynamic and Water Quality Study of the Green River King County, Washington Author: Kraft, Tim, Annear, Robert Leslie, Berger, Chris, Wells, Scott A. Year: 2004 This report describes the data processing and model calibration performed for a hydrodynamic and water quality model of the Green River, located in King County, Washington. Figure 1 shows the location of the river, and the limits of the section of river that was modeled. The Green River flows from its headwaters in the Cascade Mountain foothills through the King County, Washington communities of Auburn, Kent, and Tukwila before discharging into the Duwamish River. Two sections of the river were modeled in this project. The Middle Green River begins in the Cascade Mountain foothills east of Tacoma, and continues downstream to the city of Auburn, WA. The Lower Green River continues from Auburn to the confluence with the Duwamish River, in the town of Tukwila. The Green/Duwamish River system is unique in that it flows through a heavily urbanized and industrialized environment yet supports a large salmon population (Green/Duwamish Ecosystem Restoration Study, 2003). To protect the river and its prime salmon habitat, King County and the US Army Corps of Engineers have joined together on a study to identify and implement strategies for restoring and protecting the Green/Duwamish River System and its tributaries (Green/Duwamish Ecosystem Restoration Study, 2003). As part of the Green-Duwamish Watershed Water Quality Assessment Program, King County contracted with Portland State University to develop a hydrodynamic and water quality model for the Lower and Middle Green River. This model will be used in Total Maximum Daily Load (TMDL) development, in assessing current water quality conditions in the river, and as a planning tool for evaluating the impacts of future development in the basin. Title: Green River CE-QUAL-W2 Project: A Hydrodynamic and Water Quality Study of the Green River King County, Washington Author: Kraft, Tim, Annear, Robert Leslie, Berger, Chris, Wells, Scott A. Year: 2004 This report describes the data processing and model calibration performed for a hydrodynamic and water quality model of the Green River, located in King County, Washington. Figure 1 shows the location of the river, and the limits of the section of river that was modeled. The Green River flows from its headwaters in the Cascade Mountain foothills through the King County, Washington communities of Auburn, Kent, and Tukwila before discharging into the Duwamish River. Two sections of the river were modeled in this project. The Middle Green River begins in the Cascade Mountain foothills east of Tacoma, and continues downstream to the city of Auburn, WA. The Lower Green River continues from Auburn to the confluence with the Duwamish River, in the town of Tukwila. The Green/Duwamish River system is unique in that it flows through a heavily urbanized and industrialized environment yet supports a large salmon population (Green/Duwamish Ecosystem Restoration Study, 2003). To protect the river and its prime salmon habitat, King County and the US Army Corps of Engineers have joined together on a study to identify and implement strategies for restoring and protecting the Green/Duwamish River System and its tributaries (Green/Duwamish Ecosystem Restoration Study, 2003). As part of the Green-Duwamish Watershed Water Quality Assessment Program, King County contracted with Portland State University to develop a hydrodynamic and water quality model for the Lower and Middle Green River. This model will be used in Total Maximum Daily Load (TMDL) development, in assessing current water quality conditions in the river, and as a planning tool for evaluating the impacts of future development in the basin. Close