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• 1. [Article] Modeling the Bull Run River-Reservoir System

  The City of Portland, Water Bureau currently operates 2 Bull Run reservoirs, Reservoir #2 and Reservoir #1 as a water supply source in the Bull Run watershed shown in Figure 1 and Figure 2. The Water Bureau ...

  Citation × Citation Citation Abstract Copy Title: Modeling the Bull Run River-Reservoir System Author: Wells, Scott A. Year: 2000 The City of Portland, Water Bureau currently operates 2 Bull Run reservoirs, Reservoir #2 and Reservoir #1 as a water supply source in the Bull Run watershed shown in Figure 1 and Figure 2. The Water Bureau wants to operate their water supply system in order to meet both water supply objectives and fish habitat objectives downstream of the Bull Run reservoirs in Bull Run River. In addition, a third Bull Run reservoir has been proposed as an additional water supply source. This reservoir also may be used to meet water supply and fish habitat objectives in Bull Run River. This proposal addresses performing the following tasks to evaluate these objectives: Gather data to construct a computer simulation model of the Bull Run system including Bull Run River, Bull Run Reservoirs #1 through #3 and the river basin without reservoirs. Ensure that the model accurately represents the system physics, chemistry and biology. Use the model to evaluate how to meet water supply and fish habitat objectives by implementation of management scenarios. Title: Modeling the Bull Run River-Reservoir System Author: Wells, Scott A. Year: 2000 The City of Portland, Water Bureau currently operates 2 Bull Run reservoirs, Reservoir #2 and Reservoir #1 as a water supply source in the Bull Run watershed shown in Figure 1 and Figure 2. The Water Bureau wants to operate their water supply system in order to meet both water supply objectives and fish habitat objectives downstream of the Bull Run reservoirs in Bull Run River. In addition, a third Bull Run reservoir has been proposed as an additional water supply source. This reservoir also may be used to meet water supply and fish habitat objectives in Bull Run River. This proposal addresses performing the following tasks to evaluate these objectives: Gather data to construct a computer simulation model of the Bull Run system including Bull Run River, Bull Run Reservoirs #1 through #3 and the river basin without reservoirs. Ensure that the model accurately represents the system physics, chemistry and biology. Use the model to evaluate how to meet water supply and fish habitat objectives by implementation of management scenarios. Close

• 2. [Article] Spokane River in Idaho and Washington TMDL Water Quality and Hydrodynamic Modeling Quality Assurance Project Plan -- DRAFT

  The focus of this present study is to perform the following tasks: • Converting the Upper Spokane River CE‐QUAL‐W2 models (Washington and Idaho) to version 3.6 • Combining the Washington and Idaho models • ...

  Citation × Citation Citation Abstract Copy Title: Spokane River in Idaho and Washington TMDL Water Quality and Hydrodynamic Modeling Quality Assurance Project Plan -- DRAFT Author: Wells, Scott A., Berger, Chris Year: 2009 The focus of this present study is to perform the following tasks: • Converting the Upper Spokane River CE‐QUAL‐W2 models (Washington and Idaho) to version 3.6 • Combining the Washington and Idaho models • Reviewing and updating model boundary conditions • Check model calibration • Meet with stakeholders • Develop and Run Modeling Scenarios • Create reports on calibration and scenario runs Title: Spokane River in Idaho and Washington TMDL Water Quality and Hydrodynamic Modeling Quality Assurance Project Plan -- DRAFT Author: Wells, Scott A., Berger, Chris Year: 2009 The focus of this present study is to perform the following tasks: • Converting the Upper Spokane River CE‐QUAL‐W2 models (Washington and Idaho) to version 3.6 • Combining the Washington and Idaho models • Reviewing and updating model boundary conditions • Check model calibration • Meet with stakeholders • Develop and Run Modeling Scenarios • Create reports on calibration and scenario runs Close

• 3. [Article] Willamette River and Columbia River Waste Load Allocation Model

  A hydrodynamic and water quality model of the Lower Willamette River was developed to evaluate management alternatives designed to improve water quality. The Lower Willamette River is located in Oregon ...

  Citation × Citation Citation Abstract Copy Title: Willamette River and Columbia River Waste Load Allocation Model Author: Berger, Chris, Annear, Robert Leslie, Wells, Scott A. Year: 2002 A hydrodynamic and water quality model of the Lower Willamette River was developed to evaluate management alternatives designed to improve water quality. The Lower Willamette River is located in Oregon and drains a watershed covering 11500 square miles consisting of forested, agricultural, and urban lands. Inflows include treated municipal wastes and industrial effluents along with non-point sources from agricultural, silvicultural and urbanized land. The model was designed to address temperature, dissolved oxygen, algae, pH and bacteria concerns. The Corps of Engineers two-dimensional, laterally averaged, hydrodynamic and water quality model CE-QUAL-W2, Version 3 was applied. CE-QUAL-W2 consists of directly coupled hydrodynamic and water quality transport models and simulates parameters such as temperature, algae concentration, dissolved oxygen concentration, pH, nutrient concentrations and residence time. The model domain covers a total of about 126 river miles, including the Lower Willamette River from its intersection with the Columbia River upstream to Canby Ferry (RM 35.0) and the Columbia River from Bonneville Dam (RM 144.5) to Beaver Army Terminal (River Mile 53.8). Modeling of the Columbia River was necessary to simulate tidal fluctuations and influxes of Columbia River water into the Lower Willamette. Major tributaries and major NPDES point sources were point inflows to the system model. The ability to model multiple water bodies was a feature of CE-QUAL-W2 Version 3 and allows the simulation of river, reservoir or estuary sections with varying bottom slopes separated by dams and other hydraulic structures. The model was calibrated for the summers of 1993, 1994, 1997, 1998, and 1999. Hydrodynamics were calibrated first followed by temperature and water quality. Root mean square error of model water level predictions was generally less than 0.05 m. Because of the short residence time within the model domain, the development of accurate boundary conditions was essential for good model calibration. Title: Willamette River and Columbia River Waste Load Allocation Model Author: Berger, Chris, Annear, Robert Leslie, Wells, Scott A. Year: 2002 A hydrodynamic and water quality model of the Lower Willamette River was developed to evaluate management alternatives designed to improve water quality. The Lower Willamette River is located in Oregon and drains a watershed covering 11500 square miles consisting of forested, agricultural, and urban lands. Inflows include treated municipal wastes and industrial effluents along with non-point sources from agricultural, silvicultural and urbanized land. The model was designed to address temperature, dissolved oxygen, algae, pH and bacteria concerns. The Corps of Engineers two-dimensional, laterally averaged, hydrodynamic and water quality model CE-QUAL-W2, Version 3 was applied. CE-QUAL-W2 consists of directly coupled hydrodynamic and water quality transport models and simulates parameters such as temperature, algae concentration, dissolved oxygen concentration, pH, nutrient concentrations and residence time. The model domain covers a total of about 126 river miles, including the Lower Willamette River from its intersection with the Columbia River upstream to Canby Ferry (RM 35.0) and the Columbia River from Bonneville Dam (RM 144.5) to Beaver Army Terminal (River Mile 53.8). Modeling of the Columbia River was necessary to simulate tidal fluctuations and influxes of Columbia River water into the Lower Willamette. Major tributaries and major NPDES point sources were point inflows to the system model. The ability to model multiple water bodies was a feature of CE-QUAL-W2 Version 3 and allows the simulation of river, reservoir or estuary sections with varying bottom slopes separated by dams and other hydraulic structures. The model was calibrated for the summers of 1993, 1994, 1997, 1998, and 1999. Hydrodynamics were calibrated first followed by temperature and water quality. Root mean square error of model water level predictions was generally less than 0.05 m. Because of the short residence time within the model domain, the development of accurate boundary conditions was essential for good model calibration. Close

• 4. [Article] Lake Whatcom Water Quality Model

  A water quality model of Lake Whatcom, Washington was developed as part of a Total Maximum Daily Load Study for the Washington Department of Ecology. Lake Whatcom is a large natural lake which is listed ...

  Citation × Citation Citation Abstract Copy Title: Lake Whatcom Water Quality Model Author: Berger, Chris Year: 2005 A water quality model of Lake Whatcom, Washington was developed as part of a Total Maximum Daily Load Study for the Washington Department of Ecology. Lake Whatcom is a large natural lake which is listed on the 1998 Washington State 303(d) list of waterbodies which do not meet the criterion for dissolved oxygen. Located next to the city of Bellingham, it is approximately 10 miles long and has a surface area of approximately 5000 acres and a maximum depth of over 100 meters. Eutrophication processes in the lake have been accelerated in recent years perhaps by the availability of nutrients from tributary discharges to the basin. Many of these tributaries have accelerated their nutrient loading to the system as a result of development in the watershed. The lake is being modeled using the Corps of Engineer’s model CE-QUAL-W2, which is a two-dimensional, hydrodynamic and water quality model. The project is managed by the Washington Department of Ecology which plans to make recommendations for reduction and allocation of pollutant loads. The objectives of this study were then to develop a hydrodynamic and water quality model of Lake Whatcom, calibrate the model to field data collected from February 2002 through December 2003, and use the model to evaluate strategies for water quality improvement. Title: Lake Whatcom Water Quality Model Author: Berger, Chris Year: 2005 A water quality model of Lake Whatcom, Washington was developed as part of a Total Maximum Daily Load Study for the Washington Department of Ecology. Lake Whatcom is a large natural lake which is listed on the 1998 Washington State 303(d) list of waterbodies which do not meet the criterion for dissolved oxygen. Located next to the city of Bellingham, it is approximately 10 miles long and has a surface area of approximately 5000 acres and a maximum depth of over 100 meters. Eutrophication processes in the lake have been accelerated in recent years perhaps by the availability of nutrients from tributary discharges to the basin. Many of these tributaries have accelerated their nutrient loading to the system as a result of development in the watershed. The lake is being modeled using the Corps of Engineer’s model CE-QUAL-W2, which is a two-dimensional, hydrodynamic and water quality model. The project is managed by the Washington Department of Ecology which plans to make recommendations for reduction and allocation of pollutant loads. The objectives of this study were then to develop a hydrodynamic and water quality model of Lake Whatcom, calibrate the model to field data collected from February 2002 through December 2003, and use the model to evaluate strategies for water quality improvement. Close

• 5. [Article] Towards Improving Drought Forecasts Across Different Spatial and Temporal Scales

  Recent water scarcities across the southwestern U.S. with severe effects on the living environment inspire the development of new methodologies to achieve reliable drought forecasting in seasonal scale. ...

  Citation × Citation Citation Abstract Copy Title: Towards Improving Drought Forecasts Across Different Spatial and Temporal Scales Author: Madadgar, Shahrbanou Year: 2014 Recent water scarcities across the southwestern U.S. with severe effects on the living environment inspire the development of new methodologies to achieve reliable drought forecasting in seasonal scale. Reliable forecast of hydrologic variables, in general, is a preliminary requirement for appropriate planning of water resources and developing effective allocation policies. This study aims at developing new techniques with specific probabilistic features to improve the reliability of hydrologic forecasts, particularly the drought forecasts. The drought status in the future is determined by certain hydrologic variables that are basically estimated by the hydrologic models with rather simple to complex structures. Since the predictions of hydrologic models are prone to different sources of uncertainties, there have been several techniques examined during past several years which generally attempt to combine the predictions of single (multiple) hydrologic models to generate an ensemble of hydrologic forecasts addressing the inherent uncertainties. However, the imperfect structure of hydrologic models usually lead to systematic bias of hydrologic predictions that further appears in the forecast ensembles. This study proposes a post-processing method that is applied to the raw forecast of hydrologic variables and can develop the entire distribution of forecast around the initial single-value prediction. To establish the probability density function (PDF) of the forecast, a group of multivariate distribution functions, the so-called copula functions, are incorporated in the post-processing procedure. The performance of the new post-processing technique is tested on 2500 hypothetical case studies and the streamflow forecast of Sprague River Basin in southern Oregon. Verified by some deterministic and probabilistic verification measures, the method of Quantile Mapping as a traditional post-processing technique cannot generate the qualified forecasts as comparing with the copula-based method. The post-processing technique is then expanded to exclusively study the drought forecasts across the different spatial and temporal scales. In the proposed drought forecasting model, the drought status in the future is evaluated based on the drought status of the past seasons while the correlations between the drought variables of consecutive seasons are preserved by copula functions. The main benefit of the new forecast model is its probabilistic features in analyzing future droughts. It develops conditional probability of drought status in the forecast season and generates the PDF and cumulative distribution function (CDF) of future droughts given the past status. The conditional PDF can return the highest probable drought in the future along with an assessment of the uncertainty around that value. Using the conditional CDF for forecast season, the model can generate the maps of drought status across the basin with particular chance of occurrence in the future. In a different analysis of the conditional CDF developed for the forecast season, the chance of a particular drought in the forecast period can be approximated given the drought status of earlier seasons. The forecast methodology developed in this study shows promising results in hydrologic forecasts and its particular probabilistic features are inspiring for future studies. Title: Towards Improving Drought Forecasts Across Different Spatial and Temporal Scales Author: Madadgar, Shahrbanou Year: 2014 Recent water scarcities across the southwestern U.S. with severe effects on the living environment inspire the development of new methodologies to achieve reliable drought forecasting in seasonal scale. Reliable forecast of hydrologic variables, in general, is a preliminary requirement for appropriate planning of water resources and developing effective allocation policies. This study aims at developing new techniques with specific probabilistic features to improve the reliability of hydrologic forecasts, particularly the drought forecasts. The drought status in the future is determined by certain hydrologic variables that are basically estimated by the hydrologic models with rather simple to complex structures. Since the predictions of hydrologic models are prone to different sources of uncertainties, there have been several techniques examined during past several years which generally attempt to combine the predictions of single (multiple) hydrologic models to generate an ensemble of hydrologic forecasts addressing the inherent uncertainties. However, the imperfect structure of hydrologic models usually lead to systematic bias of hydrologic predictions that further appears in the forecast ensembles. This study proposes a post-processing method that is applied to the raw forecast of hydrologic variables and can develop the entire distribution of forecast around the initial single-value prediction. To establish the probability density function (PDF) of the forecast, a group of multivariate distribution functions, the so-called copula functions, are incorporated in the post-processing procedure. The performance of the new post-processing technique is tested on 2500 hypothetical case studies and the streamflow forecast of Sprague River Basin in southern Oregon. Verified by some deterministic and probabilistic verification measures, the method of Quantile Mapping as a traditional post-processing technique cannot generate the qualified forecasts as comparing with the copula-based method. The post-processing technique is then expanded to exclusively study the drought forecasts across the different spatial and temporal scales. In the proposed drought forecasting model, the drought status in the future is evaluated based on the drought status of the past seasons while the correlations between the drought variables of consecutive seasons are preserved by copula functions. The main benefit of the new forecast model is its probabilistic features in analyzing future droughts. It develops conditional probability of drought status in the forecast season and generates the PDF and cumulative distribution function (CDF) of future droughts given the past status. The conditional PDF can return the highest probable drought in the future along with an assessment of the uncertainty around that value. Using the conditional CDF for forecast season, the model can generate the maps of drought status across the basin with particular chance of occurrence in the future. In a different analysis of the conditional CDF developed for the forecast season, the chance of a particular drought in the forecast period can be approximated given the drought status of earlier seasons. The forecast methodology developed in this study shows promising results in hydrologic forecasts and its particular probabilistic features are inspiring for future studies. Close