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• 1. [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

• 2. [Article] Climate Change Assessment in Columbia River Basin (CRB) Using Copula Based on Coupling of Temperature and Precipitation

  The multi downscaled-scenario products allow us to better assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions ...

  Citation × Citation Citation Abstract Copy Title: Climate Change Assessment in Columbia River Basin (CRB) Using Copula Based on Coupling of Temperature and Precipitation Author: Qin, Yueyue Year: 2015 The multi downscaled-scenario products allow us to better assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. In the present study, we have used multi-modelled statistically downscaled ensemble of precipitation and temperature variables. The dataset used is multi-model ensemble of 10 Global Climate Models (GCMs) downscaled product from CMIP5 daily dataset, using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble PDFs of both precipitation and temperature is evaluated for summer (dry) and winter (wet) periods for 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables on multi-model ensemble data. Results have indicated that the probabilistic distribution helps remove the limitations on marginal distributions of variables in question and helps in better prediction. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends are varied, but certainly positive, for summer and winter time scales based on sub-basins. Dry season, generally, is indicating towards higher positive changes in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated by the joint precipitation and temperature, also indicates varied degree and forms during dry season whereas the wet season is rather constant across all the sub-basins. Title: Climate Change Assessment in Columbia River Basin (CRB) Using Copula Based on Coupling of Temperature and Precipitation Author: Qin, Yueyue Year: 2015 The multi downscaled-scenario products allow us to better assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. In the present study, we have used multi-modelled statistically downscaled ensemble of precipitation and temperature variables. The dataset used is multi-model ensemble of 10 Global Climate Models (GCMs) downscaled product from CMIP5 daily dataset, using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble PDFs of both precipitation and temperature is evaluated for summer (dry) and winter (wet) periods for 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables on multi-model ensemble data. Results have indicated that the probabilistic distribution helps remove the limitations on marginal distributions of variables in question and helps in better prediction. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends are varied, but certainly positive, for summer and winter time scales based on sub-basins. Dry season, generally, is indicating towards higher positive changes in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated by the joint precipitation and temperature, also indicates varied degree and forms during dry season whereas the wet season is rather constant across all the sub-basins. Close

• 3. [Article] A Statistical Investigation of Lower Columbia River Water Temperature, 1915-2003

  The Columbia River is home to anadromous salmon populations that migrate upriver every year to spawn. These fish require cool water temperatures (Tw) to survive. In recent years, high summer Tw in the ...

  Citation × Citation Citation Abstract Copy Title: A Statistical Investigation of Lower Columbia River Water Temperature, 1915-2003 Author: Overman, Corina Christina Mae Year: 2017 The Columbia River is home to anadromous salmon populations that migrate upriver every year to spawn. These fish require cool water temperatures (Tw) to survive. In recent years, high summer Tw in the Columbia River has caused increased mortality of salmon. Different possible explanations for increased Tw include climate change, deforestation, and decreased summertime streamflow (Q) due to dams. In this study, robust linear regression models of Tw based on air temperature (Ta) and Q were developed to examine the change in Tw over time. The data was separated into an historical period (1938-1956) and a modern period (1977-2003). Seasonal regression models were used for May through October (summer) and November through April (winter) for each period. Comparison of these models showed that Tw has become less sensitive to recent atmospheric heating and cooling. By contrast, analysis suggested that Tw has become more sensitive to variations in Q. Of the 1.5ºC increase in maximum summertime Tw, approximately 1.3ºC was due to dams and reservoir management based on changes in regression coefficients and average Q. A smaller, 0.2ºC change was estimated to be caused by increasing Ta since the mid-20th century. While average maximum Tw has increased, both the statistical model and data suggest that the variability in Tw from its climatological average has decreased, probably due to reservoir management. Title: A Statistical Investigation of Lower Columbia River Water Temperature, 1915-2003 Author: Overman, Corina Christina Mae Year: 2017 The Columbia River is home to anadromous salmon populations that migrate upriver every year to spawn. These fish require cool water temperatures (Tw) to survive. In recent years, high summer Tw in the Columbia River has caused increased mortality of salmon. Different possible explanations for increased Tw include climate change, deforestation, and decreased summertime streamflow (Q) due to dams. In this study, robust linear regression models of Tw based on air temperature (Ta) and Q were developed to examine the change in Tw over time. The data was separated into an historical period (1938-1956) and a modern period (1977-2003). Seasonal regression models were used for May through October (summer) and November through April (winter) for each period. Comparison of these models showed that Tw has become less sensitive to recent atmospheric heating and cooling. By contrast, analysis suggested that Tw has become more sensitive to variations in Q. Of the 1.5ºC increase in maximum summertime Tw, approximately 1.3ºC was due to dams and reservoir management based on changes in regression coefficients and average Q. A smaller, 0.2ºC change was estimated to be caused by increasing Ta since the mid-20th century. While average maximum Tw has increased, both the statistical model and data suggest that the variability in Tw from its climatological average has decreased, probably due to reservoir management. Close

• 4. [Article] Modeling Density Currents in a Typical Tributary of the Three Gorges Reservoir, China

  The initial filling of the Three Gorges Reservoir (TGR), China, has caused serious phytoplankton blooms in its tributary bays. A two-dimensional, laterally averaged, hydrodynamic and water quality CE-QUAL-W2 ...

  Citation × Citation Citation Abstract Copy Title: Modeling Density Currents in a Typical Tributary of the Three Gorges Reservoir, China Author: Ma, Jun, Liu, Defu, Wells, Scott A., Tang, Hongwu, Ji, Daobin, Yang, Zhengjian Year: 2015 The initial filling of the Three Gorges Reservoir (TGR), China, has caused serious phytoplankton blooms in its tributary bays. A two-dimensional, laterally averaged, hydrodynamic and water quality CE-QUAL-W2 model was used to simulate the hydrodynamics and water temperature of a typical tributary (Xiangxi Bay XXB) of the TGR to study the relationship between phytoplankton and density currents. The CE-QUAL-W2 model was calibrated to data collected in XXB (depth profiles of velocity and water temperature at three locations) from January 2008 through December 2008. The model performed well in simulating (1) flow velocity profiles, (2) unusual water temperature profiles, (3) the plunge point location of the intrusion layer, (4) propagation speed, and (5) the travel distance of the density currents. The model was then used to examine potential factors that affect the density currents, such as water level fluctuations in the mainstem of the TGR, water temperature differences between the mainstem and XXB, and inflow rates to XXB. Therefore, a better understanding of the hydrodynamics of tributaries in the TGR can be used to understand the aquatic ecosystem dynamics of these tributaries. Title: Modeling Density Currents in a Typical Tributary of the Three Gorges Reservoir, China Author: Ma, Jun, Liu, Defu, Wells, Scott A., Tang, Hongwu, Ji, Daobin, Yang, Zhengjian Year: 2015 The initial filling of the Three Gorges Reservoir (TGR), China, has caused serious phytoplankton blooms in its tributary bays. A two-dimensional, laterally averaged, hydrodynamic and water quality CE-QUAL-W2 model was used to simulate the hydrodynamics and water temperature of a typical tributary (Xiangxi Bay XXB) of the TGR to study the relationship between phytoplankton and density currents. The CE-QUAL-W2 model was calibrated to data collected in XXB (depth profiles of velocity and water temperature at three locations) from January 2008 through December 2008. The model performed well in simulating (1) flow velocity profiles, (2) unusual water temperature profiles, (3) the plunge point location of the intrusion layer, (4) propagation speed, and (5) the travel distance of the density currents. The model was then used to examine potential factors that affect the density currents, such as water level fluctuations in the mainstem of the TGR, water temperature differences between the mainstem and XXB, and inflow rates to XXB. Therefore, a better understanding of the hydrodynamics of tributaries in the TGR can be used to understand the aquatic ecosystem dynamics of these tributaries. Close

• 5. [Article] Spatial, Temporal and Frequency Based Climate change Assessment in Columbia River Basin Using Multi Downscaled-Scenarios

  Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have ...

  Citation × Citation Citation Abstract Copy Title: Spatial, Temporal and Frequency Based Climate change Assessment in Columbia River Basin Using Multi Downscaled-Scenarios Author: Rana, Arun, Moradkhani, Hamid Year: 2016 Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070–2099 with respect to historical period of 1970–2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation. Title: Spatial, Temporal and Frequency Based Climate change Assessment in Columbia River Basin Using Multi Downscaled-Scenarios Author: Rana, Arun, Moradkhani, Hamid Year: 2016 Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070–2099 with respect to historical period of 1970–2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation. Close

• 6. [Article] Comparisons of Linear Regression Models for Properties of Alkaliactivated Binder Concrete

  Concrete with alkali-activated binder (AAB) is increasingly considered as a better alternative to conventional portland cement (PC) concrete due to its superior sustainable and green properties. In order ...

  Citation × Citation Citation Abstract Copy Title: Comparisons of Linear Regression Models for Properties of Alkaliactivated Binder Concrete Author: Kar, Arkamitra, Halabe, Udaya B., Ray, Indrajit, Unnikrishnan, Avinash Year: 2015 Concrete with alkali-activated binder (AAB) is increasingly considered as a better alternative to conventional portland cement (PC) concrete due to its superior sustainable and green properties. In order to promote the practical usage of AAB concrete, a previous study by the present authors proposed models on correlations among their mechanical and nondestructive properties. The present study extends the previous knowledge by proposing new improved models using linear regressions to predict compressive strengths and modulus of elasticity from ultrasonic pulse velocities. The models are developed for both unstressed and stressed AAB concrete with different curing temperatures. The accuracies of the models are compared with both sum of squares due to errors (SSE) and R2 depending on the type of equations; and the new models are found to be more accurate compared to the previous models. Title: Comparisons of Linear Regression Models for Properties of Alkaliactivated Binder Concrete Author: Kar, Arkamitra, Halabe, Udaya B., Ray, Indrajit, Unnikrishnan, Avinash Year: 2015 Concrete with alkali-activated binder (AAB) is increasingly considered as a better alternative to conventional portland cement (PC) concrete due to its superior sustainable and green properties. In order to promote the practical usage of AAB concrete, a previous study by the present authors proposed models on correlations among their mechanical and nondestructive properties. The present study extends the previous knowledge by proposing new improved models using linear regressions to predict compressive strengths and modulus of elasticity from ultrasonic pulse velocities. The models are developed for both unstressed and stressed AAB concrete with different curing temperatures. The accuracies of the models are compared with both sum of squares due to errors (SSE) and R2 depending on the type of equations; and the new models are found to be more accurate compared to the previous models. Close

• 7. [Article] Benchtop Minimal-Intervention Anaerobic Digestion of Vegetarian Food Waste for pH and Methane Production: Conceivability and Control Study

  Cities around the world transport large quantities of waste to landfills at a great expense to their residents, infrastructures, and environments. The objective of this study was to run an anaerobic food ...

  Citation × Citation Citation Abstract Copy Title: Benchtop Minimal-Intervention Anaerobic Digestion of Vegetarian Food Waste for pH and Methane Production: Conceivability and Control Study Author: Heleva-Ponaski, Emily J Year: 2014 Cities around the world transport large quantities of waste to landfills at a great expense to their residents, infrastructures, and environments. The objective of this study was to run an anaerobic food waste digester with minimal interference or maintenance. One specific goal of this research was to evaluate the relationship between anaerobic food waste and pH. Two benchop digesters were started with vegetarian food waste collected from the Portland State University campus. Measurements were collected over the course of the digestion process. Due to low pH and lack of biogas production, the digesters were buffered with sodium carbonate and seeded with wastewater digestate. Post recovery, the solids content decreased and methane production began though the process was never fully optimized. The lack of digester performance is thought to be due in part to low operation temperature. Title: Benchtop Minimal-Intervention Anaerobic Digestion of Vegetarian Food Waste for pH and Methane Production: Conceivability and Control Study Author: Heleva-Ponaski, Emily J Year: 2014 Cities around the world transport large quantities of waste to landfills at a great expense to their residents, infrastructures, and environments. The objective of this study was to run an anaerobic food waste digester with minimal interference or maintenance. One specific goal of this research was to evaluate the relationship between anaerobic food waste and pH. Two benchop digesters were started with vegetarian food waste collected from the Portland State University campus. Measurements were collected over the course of the digestion process. Due to low pH and lack of biogas production, the digesters were buffered with sodium carbonate and seeded with wastewater digestate. Post recovery, the solids content decreased and methane production began though the process was never fully optimized. The lack of digester performance is thought to be due in part to low operation temperature. Close

• 8. [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

• 9. [Article] Multi-Criteria Evaluation of CMIP5 GCMs for Climate Change Impact Analysis

  Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. ...

  Citation × Citation Citation Abstract Copy Title: Multi-Criteria Evaluation of CMIP5 GCMs for Climate Change Impact Analysis Author: Ahmadalipour, Ali, Rana, Arun, Moradkhani, Hamid, Sharma, Ashish Year: 2015 Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area. Title: Multi-Criteria Evaluation of CMIP5 GCMs for Climate Change Impact Analysis Author: Ahmadalipour, Ali, Rana, Arun, Moradkhani, Hamid, Sharma, Ashish Year: 2015 Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area. Close