Search

Search Results

• 1. [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