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• 1. [Article] Implementation of a Sediment Transport Model for CE-QUAL-W2

  The CE-QUAL-W2 model, developed by Portland State University, simulates water quality and flow. Recommendations to expand on this model and have it include sediment transport are implemented in this report. ...

  Citation × Citation Citation Abstract Copy Title: Implementation of a Sediment Transport Model for CE-QUAL-W2 Author: Hanna, Rachel Year: 2014 The CE-QUAL-W2 model, developed by Portland State University, simulates water quality and flow. Recommendations to expand on this model and have it include sediment transport are implemented in this report. Existing one-, two-, and three-dimensional models are reviewed and assessed for their sediment transport methodology. A laterally (width) averaged sediment concentration model is developed as an Upwind Center Space Scheme using CE-QUAL-W2 data. The scheme includes a method to calculate scour for sediment concentration and results of the model are shown for a simulated branch of the Spokane River. Title: Implementation of a Sediment Transport Model for CE-QUAL-W2 Author: Hanna, Rachel Year: 2014 The CE-QUAL-W2 model, developed by Portland State University, simulates water quality and flow. Recommendations to expand on this model and have it include sediment transport are implemented in this report. Existing one-, two-, and three-dimensional models are reviewed and assessed for their sediment transport methodology. A laterally (width) averaged sediment concentration model is developed as an Upwind Center Space Scheme using CE-QUAL-W2 data. The scheme includes a method to calculate scour for sediment concentration and results of the model are shown for a simulated branch of the Spokane River. Close

• 2. [Article] puddl: Gamifying Water Conservation

  As the global population surges, the demand for fresh water will only increase. With no technological breakthrough on the horizon, it is more important than ever to conserve water and not waste this precious ...

  Citation × Citation Citation Abstract Copy Title: puddl: Gamifying Water Conservation Author: Assenberg, Quince, Chen, Jack, Glenn, Denny, Lam, Jessica Year: 2016 As the global population surges, the demand for fresh water will only increase. With no technological breakthrough on the horizon, it is more important than ever to conserve water and not waste this precious resource. Water conservation is a serious issue, and will only become more severe as global warming worsens. As the global temperature increases, and rainfall becomes more sporadic, it will be important for communities to find new ways to save water. This push has already been made in certain areas in the united states, California, where they were forced to reduce their water consumption by 25%. Through our fieldwork and other research, we discovered three important factors that would shape our project. The first was all about flow! The flow in a sewage system is integral to its ability to function. If the flow of a sewage system gets too low, you encounter a number of logistical problems. Additionally, if you use too much water, you could adversely affect the ecosystems from which you took the water. Salmon, and their food chain, are affected the most by the overuse of water. When talking with Catherine Howells, we also learned about water conservation. Certain areas in the world, like Perth, Australia, are very good at conserving water, whereas other areas, like Phoenix, Arizona are not.. However, no matter where you are, it is very hard to conserve more than thirty percent of water usage. The average American family of four uses 400 gallons of water per day. On average, approximately 70 percent of that water is used indoors, with the bathroom being the largest consumer. This leaves a large amount of water to be conserve, especially when you consider the average Australian family of the same size uses on 238 gallons of water per day! Also, certain applications use a huge portion of a person’s daily water usage, for instance the toilet and washer equal forty‐eight percent of a household' water consumption, and by learning new ways to reduce this, families could save a lot of water! Title: puddl: Gamifying Water Conservation Author: Assenberg, Quince, Chen, Jack, Glenn, Denny, Lam, Jessica Year: 2016 As the global population surges, the demand for fresh water will only increase. With no technological breakthrough on the horizon, it is more important than ever to conserve water and not waste this precious resource. Water conservation is a serious issue, and will only become more severe as global warming worsens. As the global temperature increases, and rainfall becomes more sporadic, it will be important for communities to find new ways to save water. This push has already been made in certain areas in the united states, California, where they were forced to reduce their water consumption by 25%. Through our fieldwork and other research, we discovered three important factors that would shape our project. The first was all about flow! The flow in a sewage system is integral to its ability to function. If the flow of a sewage system gets too low, you encounter a number of logistical problems. Additionally, if you use too much water, you could adversely affect the ecosystems from which you took the water. Salmon, and their food chain, are affected the most by the overuse of water. When talking with Catherine Howells, we also learned about water conservation. Certain areas in the world, like Perth, Australia, are very good at conserving water, whereas other areas, like Phoenix, Arizona are not.. However, no matter where you are, it is very hard to conserve more than thirty percent of water usage. The average American family of four uses 400 gallons of water per day. On average, approximately 70 percent of that water is used indoors, with the bathroom being the largest consumer. This leaves a large amount of water to be conserve, especially when you consider the average Australian family of the same size uses on 238 gallons of water per day! Also, certain applications use a huge portion of a person’s daily water usage, for instance the toilet and washer equal forty‐eight percent of a household' water consumption, and by learning new ways to reduce this, families could save a lot of water! Close

• 3. [Article] Estimation of Surface Water Temperature of the Tigris River System in Iraq

  Monitoring surface water temperatures (Tw) in lakes, rivers, and reservoirs is a key component of environmental management and influences water quality by affecting bio-geo chemical reaction rates, altering ...

  Citation × Citation Citation Abstract Copy Title: Estimation of Surface Water Temperature of the Tigris River System in Iraq Author: Al-Murib, M., Wells, Scott A., Talke, Stefan A. Year: 2017 Monitoring surface water temperatures (Tw) in lakes, rivers, and reservoirs is a key component of environmental management and influences water quality by affecting bio-geo chemical reaction rates, altering the saturation concentration of dissolved oxygen (DO), and influencing the susceptibility of fish to disease. Temperatures in the Tigris River, one of the largest rivers in the Middle East, are influenced by factors such as heat fluxes at the air-water and human activities such as direct discharge of water to the river. However, modeling and management of water temperature is limited by a paucity of in-situ data, which prevents calibration of models. In this study, we infill data gaps by estimating Tw using the thermal bands of both the Landsat 5 TM and Landsat 7 ETM+ sensors. These satellite-based estimates, typically measured once or twice a month with 60-120m resolution, are then used to develop a regression model that relates daily water temperature to daily air temperature and river flow. These estimates are used to define the Tw boundary conditions for a hydrodynamic and water quality model of the Tigris River based on a 2D implementation of the CE-QUAL-W2 (W2) numerical model. Initial results suggest that there is a significant agreement between modeled and remotely estimated data of Tw. Results suggest that short-wave solar radiation is the most important factor that controls seasonal Tw variations. However, anthropogenic influence is observed as a result of return irrigation flows and flows from Tharthar Lake. Title: Estimation of Surface Water Temperature of the Tigris River System in Iraq Author: Al-Murib, M., Wells, Scott A., Talke, Stefan A. Year: 2017 Monitoring surface water temperatures (Tw) in lakes, rivers, and reservoirs is a key component of environmental management and influences water quality by affecting bio-geo chemical reaction rates, altering the saturation concentration of dissolved oxygen (DO), and influencing the susceptibility of fish to disease. Temperatures in the Tigris River, one of the largest rivers in the Middle East, are influenced by factors such as heat fluxes at the air-water and human activities such as direct discharge of water to the river. However, modeling and management of water temperature is limited by a paucity of in-situ data, which prevents calibration of models. In this study, we infill data gaps by estimating Tw using the thermal bands of both the Landsat 5 TM and Landsat 7 ETM+ sensors. These satellite-based estimates, typically measured once or twice a month with 60-120m resolution, are then used to develop a regression model that relates daily water temperature to daily air temperature and river flow. These estimates are used to define the Tw boundary conditions for a hydrodynamic and water quality model of the Tigris River based on a 2D implementation of the CE-QUAL-W2 (W2) numerical model. Initial results suggest that there is a significant agreement between modeled and remotely estimated data of Tw. Results suggest that short-wave solar radiation is the most important factor that controls seasonal Tw variations. However, anthropogenic influence is observed as a result of return irrigation flows and flows from Tharthar Lake. Close

• 4. [Article] Estimating River Discharge Using Multiple-Tide Gauges Distributed Along a Channel

  Reliable estimation of freshwater inflow to the ocean from large tidal rivers is vital for water resources management and climate analyses. Discharge gauging stations are typically located beyond the tidal ...

  Citation × Citation Citation Abstract Copy Title: Estimating River Discharge Using Multiple-Tide Gauges Distributed Along a Channel Author: Moftakhari, Hamed R., Jay, David A, Talke, Stefan Year: 2016 Reliable estimation of freshwater inflow to the ocean from large tidal rivers is vital for water resources management and climate analyses. Discharge gauging stations are typically located beyond the tidal intrusion reach, such that inputs and losses occurring closer to the ocean are not included. Here, we develop a method of estimating river discharge using multiple gauges and time-dependent tidal statistics determined via wavelet analysis. The Multiple-gauge Tidal Discharge Estimate (MTDE) method is developed using data from the Columbia River and Fraser River estuaries and calibrated against river discharge. Next, we evaluate the general applicability of MTDE by testing an idealized two-dimensional numerical model, with a convergent cross-sectional profile, for eighty-one cases in which nondimensional numbers for friction, river flow, and convergence length scale are varied. The simulations suggest that MTDE is applicable to a variety of tidal systems. Model results and data analyses together suggest that MTDE works best with at least three gauges: a reference station near the river mouth, and two upstream gauges that respond strongly to distinct portions of the observed range of flow. The balance between tidal damping and amplifying factors determines the favorable location of the gauges. Compared to previous studies, the MTDE method improves the time resolution of estimates (from 2.5 to < 1 week) and is applicable to systems with mixed diurnal/semidiurnal tides. However, model results suggest that tide-induced residual flows such as the Stokes drift may still affect the accuracy of MTDE at seaward locations during periods of low river discharge. Title: Estimating River Discharge Using Multiple-Tide Gauges Distributed Along a Channel Author: Moftakhari, Hamed R., Jay, David A, Talke, Stefan Year: 2016 Reliable estimation of freshwater inflow to the ocean from large tidal rivers is vital for water resources management and climate analyses. Discharge gauging stations are typically located beyond the tidal intrusion reach, such that inputs and losses occurring closer to the ocean are not included. Here, we develop a method of estimating river discharge using multiple gauges and time-dependent tidal statistics determined via wavelet analysis. The Multiple-gauge Tidal Discharge Estimate (MTDE) method is developed using data from the Columbia River and Fraser River estuaries and calibrated against river discharge. Next, we evaluate the general applicability of MTDE by testing an idealized two-dimensional numerical model, with a convergent cross-sectional profile, for eighty-one cases in which nondimensional numbers for friction, river flow, and convergence length scale are varied. The simulations suggest that MTDE is applicable to a variety of tidal systems. Model results and data analyses together suggest that MTDE works best with at least three gauges: a reference station near the river mouth, and two upstream gauges that respond strongly to distinct portions of the observed range of flow. The balance between tidal damping and amplifying factors determines the favorable location of the gauges. Compared to previous studies, the MTDE method improves the time resolution of estimates (from 2.5 to < 1 week) and is applicable to systems with mixed diurnal/semidiurnal tides. However, model results suggest that tide-induced residual flows such as the Stokes drift may still affect the accuracy of MTDE at seaward locations during periods of low river discharge. Close

• 5. [Article] Archival Water-Level Measurements: Recovering Historical Data to Help Design for the Future

  Improving methods of assessing risk and designing structures to withstand extreme events and changing sea levels is a vital component of strategies for reducing risk to coastal resources and assets. An ...

  Citation × Citation Citation Abstract Copy Title: Archival Water-Level Measurements: Recovering Historical Data to Help Design for the Future Author: Talke, Stefan A., Jay, David A. Year: 2017 Improving methods of assessing risk and designing structures to withstand extreme events and changing sea levels is a vital component of strategies for reducing risk to coastal resources and assets. An obvious approach to improving the statistical robustness of risk assessments is to increase the number, time span, and quality of available water-level data sets, and to assess trends and non-stationarity. In this report we discuss efforts to recover, digitize, and analyze hundreds of station-years of lost-and-forgotten tide data and other water-level measurements that extend back to the early 19th century. To date, more than 6,500 station-years of previously lost or forgotten tide data have been identified, of which more than 1,600 station-years have been recovered and more than 550 station-years digitized. An additional 500+ years of once-a-day river-stage measurements in tidal rivers have been recovered and digitized. Approximately 300,000 documents have been recovered. In this report we also demonstrate how data recovery can help engineers better characterize their water-level environment and understand long-term trends, resulting in better risk assessment and ultimately more robust design of new infrastructure and adaptation of existing infrastructure. Long records help improve hazard estimates and can help characterize whether statistics are nonstationarity over climate-relevant time scales. Further, long and more complete records exhibit more natural variability and can be used to validate numerical simulations of historical storms (e.g., the 1893 New York hurricane). Historical tide data can help inform how tidal datums such as High Water and Low Water have changed, can be used to hindcast historical river flow, and provide a much richer view of long-term trends in local sea level. Used with numerical models, historical data help explain how anthropogenic activities have changed tide range and river slope, with the largest effects often observed far inland from the coast. Moreover, numerical models combined with tide data can be used to assess whether local engineering or other long-term changes have influenced storm surge risk. In conclusion, improved assessment of the past can help us better plan for the future. Title: Archival Water-Level Measurements: Recovering Historical Data to Help Design for the Future Author: Talke, Stefan A., Jay, David A. Year: 2017 Improving methods of assessing risk and designing structures to withstand extreme events and changing sea levels is a vital component of strategies for reducing risk to coastal resources and assets. An obvious approach to improving the statistical robustness of risk assessments is to increase the number, time span, and quality of available water-level data sets, and to assess trends and non-stationarity. In this report we discuss efforts to recover, digitize, and analyze hundreds of station-years of lost-and-forgotten tide data and other water-level measurements that extend back to the early 19th century. To date, more than 6,500 station-years of previously lost or forgotten tide data have been identified, of which more than 1,600 station-years have been recovered and more than 550 station-years digitized. An additional 500+ years of once-a-day river-stage measurements in tidal rivers have been recovered and digitized. Approximately 300,000 documents have been recovered. In this report we also demonstrate how data recovery can help engineers better characterize their water-level environment and understand long-term trends, resulting in better risk assessment and ultimately more robust design of new infrastructure and adaptation of existing infrastructure. Long records help improve hazard estimates and can help characterize whether statistics are nonstationarity over climate-relevant time scales. Further, long and more complete records exhibit more natural variability and can be used to validate numerical simulations of historical storms (e.g., the 1893 New York hurricane). Historical tide data can help inform how tidal datums such as High Water and Low Water have changed, can be used to hindcast historical river flow, and provide a much richer view of long-term trends in local sea level. Used with numerical models, historical data help explain how anthropogenic activities have changed tide range and river slope, with the largest effects often observed far inland from the coast. Moreover, numerical models combined with tide data can be used to assess whether local engineering or other long-term changes have influenced storm surge risk. In conclusion, improved assessment of the past can help us better plan for the future. Close

• 6. [Article] Daily Discharge Forecasting Using Least Square Support Vector Regression and Regression Tree

  Prediction of river flow is one of the main issues in the field of water resources management. Because of the complexity of the rainfall-runoff process, data-driven methods have gained increased importance. ...

  Citation × Citation Citation Abstract Copy Title: Daily Discharge Forecasting Using Least Square Support Vector Regression and Regression Tree Author: Sahraei, Shahram, Andalani, Saeed Zare, Zakermoshfegh, Mohammad, Sisakht, Babak Nikeghbal, Talebbeydokhti, Nasser, Moradkhani, Hamid Year: 2015 Prediction of river flow is one of the main issues in the field of water resources management. Because of the complexity of the rainfall-runoff process, data-driven methods have gained increased importance. In the current study, two newly developed models called Least Square Support Vector Regression (LSSVR) and Regression Tree (RT) are used. The LSSVR model is based on the constrained optimization method and applies structural risk minimization in order to yield a general optimized result. Also in the RT, data movement is based on laws discovered in the tree. Both models have been applied to the data in the Kashkan watershed. Variables include (a) recorded precipitation values in the Kashkan watershed stations, and (b) outlet discharge values of one and two previous days. Present discharge is considered as output of the two models. Following that, a sensitivity analysis has been carried out on the input features and less important features has been diminished so that both models have provided better prediction on the data. The final results of both models have been compared. It was found that the LSSVR model has better performance. Finally, the results present these models as a suitable models in river flow forecasting. Title: Daily Discharge Forecasting Using Least Square Support Vector Regression and Regression Tree Author: Sahraei, Shahram, Andalani, Saeed Zare, Zakermoshfegh, Mohammad, Sisakht, Babak Nikeghbal, Talebbeydokhti, Nasser, Moradkhani, Hamid Year: 2015 Prediction of river flow is one of the main issues in the field of water resources management. Because of the complexity of the rainfall-runoff process, data-driven methods have gained increased importance. In the current study, two newly developed models called Least Square Support Vector Regression (LSSVR) and Regression Tree (RT) are used. The LSSVR model is based on the constrained optimization method and applies structural risk minimization in order to yield a general optimized result. Also in the RT, data movement is based on laws discovered in the tree. Both models have been applied to the data in the Kashkan watershed. Variables include (a) recorded precipitation values in the Kashkan watershed stations, and (b) outlet discharge values of one and two previous days. Present discharge is considered as output of the two models. Following that, a sensitivity analysis has been carried out on the input features and less important features has been diminished so that both models have provided better prediction on the data. The final results of both models have been compared. It was found that the LSSVR model has better performance. Finally, the results present these models as a suitable models in river flow forecasting. Close