Mountain Scholar :: Browsing by Author "Arabi, Mazdak, advisor"

Browsing by Author "Arabi, Mazdak, advisor"

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Embargo
A data-driven characterization of municipal water uses in the contiguous United States of America
(Colorado State University. Libraries, 2024) Chinnasamy, Cibi Vishnu, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, committee member; Warziniack, Travis, committee member; Goemans, Christopher, committee member
Municipal water systems in the United States (U.S.) are facing increasing challenges due to changing urban population dynamics and socio-economic conditions as well as from the impacts of weather extremities on water availability and quality. These challenges pose a serious risk to the municipal water providers by hindering their ability to continue providing safe drinking water to residents while also securing adequate supply for economic growth. A data-driven approach has been developed in this study to characterize the trends, patterns, and urban scaling relationships in municipal water consumption across the Contiguous United States. Then using sophisticated and robust statistical methods, water consumption patterns are modeled, identifying key climatic, socio-economic, and regional factors. The first chapter of this data-driven study looked at municipal water uses of 126 cities and towns across the U.S. from 2005 to 2017, analyzing the temporal trends and spatial patterns in water consumption and identifying the influencing factors. Water usage in gallons per person per day, ratio of commercial, industrial, and institutional (CII) to Residential water use, and percent outdoor water consumption were statistically calculated using aggregated monthly and annual water use data. The end goal was to statistically relate the variations in CII to Residential water use ratio across the municipalities with their local climatic, socio-economic, and regional factors. The results indicate an overall decreasing trend in municipal water use, 2.6 gallons per person annually, with greater reductions achieved in the residential sector. Both Residential and CII water use exhibit significant seasonality over an average year. Large cities, particularly in the southern and western parts of the U.S. with arid climates, had the highest demand for water but also showed the largest annual reductions in their per capita water consumption. This study also revealed that outdoor water use varied significantly from 3 to 64 percent of the Total water consumption across the U.S., and it was highest in smaller cities in the western and arid regions. Factors such as April precipitation, annual vapor pressure deficit, number of employees in the manufacturing sector, total percentage of houses built before 1950, and total percentage of single-family houses explain much of the variation in CII to Residential water use ratio across the CONUS. The second chapter leverages high-resolution, smart-metered water use data from over 900 single-family households in Arizona for the water year 2021. This part of the study characterizes the determinants or drivers of water consumption patterns, specifically in single-family households, and presents a framework of statistical methods for analyzing smart-metered water consumption data in future research. A novel approach was developed to characterize household appliance efficiency levels using clustering techniques on 5-second interval data. Integrating water consumption data with detailed spatial information of the household and building characteristics, along with local climatic factors, yielded a robust mixed-effects model that captured the variations in household water uses with high accuracy at a monthly time-step. Local air temperature, household occupancy level, presence of a swimming pool, the year the household was built, and the efficiency of indoor appliances and irrigation systems were exhibited to be the key factors influencing variations in household water use. The third and fourth chapter of this study reanalyzed the water consumption data of those 126 municipalities. The third chapter dwelled into the estimation of the state of water consumption efficiencies or economics of scale in the municipal water systems using an econometrics framework called urban scaling theory. A parsimonious mixed-effects model that combined the effects of socio-economic, built environment, and regional factors, such as climate zones and water use type, was developed to model annual water uses. The results confirm efficiencies in water systems as cities grow and become denser, with CII water use category showing the highest efficiency gains followed by the Residential and Total water use categories. A key finding is the estimation of the unique variations in water use efficiency patterns across the U.S. These variations are influenced by factors such as population, housing characteristics, the combined effects of climate type and geographical location of the cities, and the type of water use category (Residential or CII) that dominates in each city. The fourth or the final chapter synthesizes the lessons learned previously about the drivers of municipal water uses and explores the development of a model for predicting monthly water consumption patterns using machine learning algorithms. These algorithms demonstrated improved capabilities in predicting the Total monthly water use more accurately than the previous modeling efforts, also controlling for factors with multi-collinearity. Climatic variables (like precipitation and vapor pressure deficit), socio-economic and built environment variables (such as income level and housing characteristics), and regional factors (including climate type and water use type dominance in a city), were confirmed by the machine learning algorithms to strongly influence and cause variations in the municipal water consumption patterns. Overall, this study showcases the power of data-driven approaches to effectively understand the nuances in municipal water uses. Integration of the lessons learned and the statistical frameworks used in this study can empower water utilities and city planners to manage municipal water demands with greater resiliency and efficiency.
Open Access
A multi criteria decision support system for watershed management under uncertain conditions
(Colorado State University. Libraries, 2012) Ahmadi, Mahdi, author; Arabi, Mazdak, advisor; Ascough, James C., II, committee member; Fontane, Darrell G., committee member; Hoag, Dana L., committee member
Nonpoint source (NPS) pollution is the primary cause of impaired water bodies in the United States and around the world. Elevated nutrient, sediment, and pesticide loads to waterways may negatively impact human health and aquatic ecosystems, increasing costs of pollutant mitigation and water treatment. Control of nonpoint source pollution is achievable through implementation of conservation practices, also known as Best Management Practices (BMPs). Watershed-scale NPS pollution control plans aim at minimizing the potential for water pollution and environmental degradation at minimum cost. Simulation models of the environment play a central role in successful implementation of watershed management programs by providing the means to assess the relative contribution of different sources to the impairment and water quality impact of conservation practices. While significant shifts in climatic patterns are evident worldwide, many natural processes, including precipitation and temperature, are affected. With projected changes in climatic conditions, significant changes in diffusive transport of nonpoint source pollutants, assimilative capacity of water bodies, and landscape positions of critical areas that should be targeted for implementation of conservation practices are also expected. The amount of investment on NPS pollution control programs makes it all but vital to assure the conservation benefits of practices will be sustained under the shifting climatic paradigms and challenges for adoption of the plans. Coupling of watershed models with regional climate projections can potentially provide answers to a variety of questions on the dynamic linkage between climate and ecologic health of water resources. The overarching goal of this dissertation is to develop a new analysis framework for the development of optimal NPS pollution control strategy at the regional scale under projected future climate conditions. Proposed frameworks were applied to a 24,800 ha watershed in the Eagle Creek Watershed in central Indiana. First, a computational framework was developed for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. This study highlighted the use of multiobjective approaches for proper calibration of watershed models that are used for pollutant source identification and watershed management. Second, an integrated simulation-optimization approach for targeted implementation of agricultural conservation practices was presented. A multiobjective genetic algorithm (NSGA-II) with mixed discrete-continuous decision variables was used to identify optimal types and locations of conservation practices for nutrient and pesticide control. This study showed that mixed discrete-continuous optimization method identifies better solutions than commonly used binary optimization methods. Third, the conclusion from application of NSGA-II optimization followed by development of a multi criteria decision analysis framework to identify near-optimal NPS pollution control plan using a priori knowledge about the system. The results suggested that the multi criteria decision analysis framework can be an effective and efficient substitute for optimization frameworks. Fourth, the hydrologic and water quality simulations driven by an extensive ensemble of climate projections were analyzed for their respective changes in basin average temperature and precipitation. The results revealed that the water yield and pollutants transport are likely to change substantially under different climatic paradigms. And finally, impact of projected climate change on performance of conservation practice and shifts in their optimal types and locations were analyzed. The results showed that performance of NPS control plans under different climatic projections will alter substantially; however, the optimal types and locations of conservation practices remained relatively unchanged.
Open Access
Assessing nutrient management scenarios at the system level
(Colorado State University. Libraries, 2017) Jobin, Olivia, author; Arabi, Mazdak, advisor; Hoag, Dana, committee member; Sharvelle, Sybil, committee member
The exponential increase in urbanization and population has led to water quality degradation throughout the country. This can be linked to the increase in impervious surfaces from urban expansion, most wastewater treatment plants (WWTPs) not being equipped to handle higher nutrient inflows, and the exponential demand for food that has led to more intensive farming practices that erode and degrade the soil, further enhancing runoff. The overall goal of this study was to assess nutrient management scenarios at the system level. The objectives included: 1) determine a methodology that could be used to quantify nutrient load contributions from each sector at the watershed scale; 2): determining delivery ratios for each sector based on the ambient nutrient loads at the outlet of the watershed; 3): and assess the cost, equity, and water quality effects of conservation management practices, BMPs, wastewater treatment technologies, and water conservation practices. Assessing the effectiveness of agricultural management practices is often jeopardized by lack of comprehensive monitoring data and computational burden at larger scales. The Soil and Water Assessment Tool (SWAT) within the eRAMS platform was used to assess the benefits of different agricultural management practices at field and watershed scale for the South Platte River Basin (SPRB), a moderately large semi-arid watershed located in northeastern Colorado. The model was calibrated using measured field observations from a study site in the watershed where the target management practices were implemented and monitored for their effectiveness. The agricultural management practices studied included fertilizer application rate and timing, tillage practices (i.e. conventional, reduced, strip, and no-tillage), and center pivot versus surface irrigation for roughly 21,000 irrigated agricultural fields (740,000 acres) in the SPRB. Center pivot irrigation showed the highest potential for nutrient reduction while tillage practices had an intermediate effect. Due to interim warm water instream total nitrogen (TN) and total phosphorus (TP) levels being exceeded over the period of 2002-2015, nutrient management scenarios were assessed at the system level for the Cache la Poudre (CLP) watershed in Colorado. The CLP watershed consists of 13 WWTPs, as well as irrigated agricultural fields, forested land, rangeland and urban areas making it an ideal candidate for this analysis. The scenarios created involved a combination of different practices and technologies for each sector and their associated costs to determine cost effective solutions for the issue at hand. A Gini Index coefficient was also determined in order to determine how equitable each scenario was. Models were used to determine the nutrient load contributions over the 14 year time frame with and without the implementation of the different practices and technologies tested, and were validated based on previous research and monitoring data. It was found that TN reductions needed for regulations could be achieved through the adoption of carbon addition, WWTP effluent reuse, 10% adoption of strip tillage, and a 25% adoption of bio-retention basins for a total of roughly $6,000,000. Whereas the TP reduction needed for regulations for all hydrologic conditions could not be achieved with any combination of the practices looked into, however 2 out of the 3 reductions could be achieved from the adoption of Chem-P, WWTP effluent reuse, 10% adoption of strip tillage, and 25% adoption of bio-retention basins for roughly $11,000,000. Further research would be needed to determine a scenario that could achieve a 70% TP reduction and 40% TN reduction simultaneously at the outlet, which was needed at the system level to be in compliance with regulatory standards.
Open Access
Assessing of performance of stormwater control measures under varying maintenance regimes
(Colorado State University. Libraries, 2020) Joseph George, Alfy, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, committee member; Ronayne, Michael, committee member
Stormwater control measures (SCMs) are being installed worldwide to curb urbanization impacts such as flooding, stream degradation, nutrient pollution, and contaminant loading in receiving water bodies. Regular inspection and maintenance are important to ensure long term effective performance of SCMs over their design life. This study investigates the performance, reliability, and time to failure of permeable pavement, a filtration based SCM, as a function of the design life and different maintenance strategies. The Stormwater Management Model (SWMM) is used to simulate performance of infiltration based SCMs under different climate and operational conditions including different maintenance regimes. A probabilistic approach is developed to characterize the risk, reliability and vulnerability of the system. Performance data including the effects of clogging and maintenance was obtained from comprehensive literature review of numerous international studies on performance of SCMs under different maintenance activities and strategies. The method of Sobol' global sensitivity analysis is used to evaluate the predictive uncertainty in the estimated surface overflow/bypass flow, runoff, and infiltration to characterize uncertainty in the input parameters of SWMM. Risk-based evaluation metrics are defined and characterized to assess the performance and probability of failure of the systems. A hazard function approach is used to characterize the time to failure of the systems under full, partial, and no maintenance regimes. Results indicate that maintenance plays a significant role in the simulated flow budgets and the performance of infiltration based SCMs. The time to failure of the systems is substantially increased by partial maintenance, while full maintenance marginally increases the time to failure compared to the partial maintenance regime. The analysis can be used to develop effective maintenance strategies for SCMs to ensure longevity and reliability of SCMs over their design life.
Open Access
Assessing the impact of EQIP-funded agricultural conservation practices on water quality in Colorado: the Republican, South Platte, Arkansas, and Rio Grande watersheds
(Colorado State University. Libraries, 2021) Trotter, Brianna, author; Arabi, Mazdak, advisor; Bhaskar, Aditi, committee member; Paustian, Keith, committee member
Water quality degradation is one of the world's most pressing environmental concerns. The implementation of Colorado Regulation 85 (5 CCR 1002-85) in 2012 has led to increased awareness of the potential water quality impacts of agricultural and other nonpoint sources of pollution. The use of agricultural conservation practices is widely accepted as a means of reducing nonpoint source pollution from agricultural runoff. The Natural Resources Conservation Service (NRCS) implemented the Environmental Quality Incentives Program (EQIP) under the 1996 Farm Bill to assist producers with applying sustainable on-farm conservation practices. However, there has been limited research to quantify the progress on water quality protection resulting from the application of EQIP-funded practices in Colorado. Water quality models have become increasingly relevant in determining watershed-level characteristics related to environmental concerns. The Soil and Water Assessment Tool (SWAT) model has been a prevailing water quality model in many studies researching the effects of agricultural nutrient runoff. SWAT simulates surface, subsurface, and shallow groundwater hydrologic processes and simulates specific farming practices and their corresponding effects, including erosion, runoff, and edge-of-field losses. In this analysis, SWAT simulation quantified the effects of specific EQIP-funded agricultural conservation practices on field runoff in the Republican, South Platte, Arkansas, and iii Rio Grande watersheds of Colorado. Practices included in this analysis were varying levels of tillage, irrigation systems, and establishment of a conservation buffer. Edge-of-field discharges of Total Nitrogen (TN) and Total Phosphorus (TP) were modeled before and after EQIP conservation practices were implemented. The modeling included EQIP conservation practices applied between 2008 and 2018 and incorporated existing Colorado State University (CSU) edge-of-field water quality data, providing a means of calibrating the model to realistic and attainable results. Results showed the most significant county-level average annual percent reductions in TN came from counties with high adoption of EQIP-funded irrigation practices, such as sprinkler or drip irrigation. On average, these counties yielded a 7.1% reduction in TN per county, which equates to 6.8 tons of TN reduced across all four watersheds. The combined reductions in TN from all EQIP-funded practices averaged 8.2% per county, which totaled approximately 19.5 tons reduced across all four watersheds over the full ten-year period of analysis. The greatest reductions in TP were observed in counties with high adoption rates of irrigation system upgrades, which yielded an average 33.5% reduction in TP per county. The implementation of all EQIP-funded practices produced a 27.7% average reduction in TP per county across all counties considered. This was equivalent to a TP reduction of 263.3 tons across all four watersheds throughout the full ten-year period of analysis. The findings indicate the modeled EQIP conservation practices are significantly reducing nutrient losses from irrigated agricultural lands.
Embargo
Assessing the triple bottom line co-benefits and life cycle cost tradeoffs of cloudburst infrastructure in New York City
(Colorado State University. Libraries, 2024) Fenn, Abby M., author; Arabi, Mazdak, advisor; Grigg, Neil, committee member; Sharvelle, Sybil, committee member; Conrad, Steve, committee member
Urbanization and climate change have increased the risk of urban flooding. Specifically, more frequent cloudburst events are on the rise in cities across the globe. Cloudbursts are characterized by high intensity rainfall over a short duration, causing unpredictable, localized flooding. Effective stormwater management is essential to manage extreme precipitation and runoff induced by cloudbursts. Stormwater control measures have evolved over time shifting from gray infrastructure to nature-based and green solutions. Recently, cloudburst specific infrastructure has emerged as a stormwater intervention strategy designed to handle larger volumes of water by capturing, storing, or conveying excess water in highly impervious areas. Cloudburst infrastructure systems are inextricably linked with land use in cities and thus, their implementation should incorporate life cycle costs, and social and ecological co-benefits. This study assesses the Triple Bottom Line co-benefits and environmental effects of cloudburst systems for flood control in New York City. Specifically, we explore the tradeoffs between the costs and co-benefits of alternative surface vegetation including grass, diverse vegetation, and trees. The study identifies the Pareto optimal set of solutions and quantifies effects of incorporating vegetation into the urban landscape via cloudburst systems. The results indicate that surface vegetation plays a key role in altering the co-benefits and life cycle costs of cloudburst infrastructure. Trees were the most frequent non-dominated solution and were linearly related to Triple Bottom Line score and exponentially related to Life Cycle Cost. The framework and results of this study provide valuable insight to support informed decision-making.
Open Access
Assessing tradeoffs of urban water demand reduction strategies
(Colorado State University. Libraries, 2019) Neale, Michael R., author; Arabi, Mazdak, advisor; Sharvelle, Sybil, advisor; Goemans, Christopher, committee member
In many cities across the World, traditional sources of potable water supply can become susceptible to shortage due to increased water demands from rapid urbanization and more frequent and extreme drought conditions. Understanding impacts of city-scale conservation and water reuse is important for water managers to implement cost effective water saving strategies and develop resilient municipal water systems. Innovative water reuse systems are becoming more cost effective, technologically viable and socially accepted. However, there is still a need for comparative assessment of alternative sources; graywater, stormwater and wastewater use along with indoor and outdoor conservation, implemented at the municipal scale. This study applies the Integrated Urban Water Model (IUWM) to three U.S. cities; Denver, CO; Miami, FL; and Tucson, AZ. We assess the tradeoffs between cost and water savings for a range of solutions composed of up to three strategies; to understand interactions between strategies and their performance under the influence of local precipitation, population density and land cover. A global sensitivity analysis method was used to fit and test model parameters to historical water use in each city. Alternative source and conservation strategies available in IUWM were simulated to quantify annual water savings. Alternative source strategies simulate collection of graywater, stormwater and wastewater to supplement demands for toilet flushing, landscape irrigation and potable supply. A non-dominated sorting function was applied that minimizes annual demand and total annualized cost to identify optimal strategies. Results show discrete strategy performance in demand reduction between cities influenced by local climate conditions, land cover and population density. Strategies that include use of stormwater can achieve highest demand reduction in Miami, where precipitation and impervious area is large resulting in larger generation of stormwater compared to other study cities. Indoor conservation was frequently part of optimal solutions in Tucson, where indoor water use is higher per capita compared to other study cities. The top performing strategies overall in terms of water savings and total cost were found to be efficient irrigation systems and stormwater for irrigation. While use of stormwater achieves large demand reduction relative to other strategies, it only occurred in non-dominated solutions that were characterized by higher cost. This strategy can be very effective for demand reduction, but is also costly. On the contrary, efficient irrigation systems are frequently part of low-cost solutions across all three study cities. Overall, this study introduces a framework for assessing cost and efficacy of water conservation and reuse strategies across regions. Results identify optimal strategies that can meet a range of demand reduction targets and stay within financial constraints.
Open Access
Assessment of the CLASIC urban hydrology model, in the Spring Creek Watershed, northern Colorado
(Colorado State University. Libraries, 2021) Mohammad Zadeh, Mahshid, author; Arabi, Mazdak, advisor; Bhaskar, Aditi, committee member; Ronayne, Michael, committee member
Urban development influences the quantity and quality of water at local to watershed scales. Urban hydrology models are commonly used to plan, design, and implement stormwater infrastructure systems to minimize water quality and flooding consequences of urban development. However, the applicability of existing models at municipal scales is hampered by extensive data and computational requirements. The Community-enabled Life-cycle Analysis of Stormwater Infrastructure Costs (CLASIC) tool is a cloud-computing web application that facilitates the simulation of hydrological and water quality responses at municipal scales. The tool also provides modules to assess the lifecycle costs of green stormwater infrastructure systems. CLASIC is a modified version of the EPA's SWMM model with direct linkages to disperse land use, climate, soils, and other data resources. This study aims to assess the performance validity of the CLASIC tool for the characterization of urban hydrologic processes and responses. Specifically, the objectives of the study are to: i) evaluate the performance of the model compared to the SWMM model and observed stream discharge at various spatial and temporal scales; and ii) identify the most influential model parameters to inform model parameterization. The study is conducted in the Spring Creek catchment within the Cache la Poudre River watershed in Colorado. Streamflow in Spring Creek is influenced by urban activities in the City of Fort Collins. Model evaluation is conducted at hourly, daily, and monthly time steps at two USGS gaging stations along the stream. Comparison of observed and simulated flow duration curves along with several goodness-of-fit measures, including Nash-Sutcliff coefficient of efficiency and percent bias are used to evaluate the model performance. The Sobol' Global Sensitivity Analysis method is used to assess the importance of model parameters for different model responses, including mean and peak stream discharge. The first and total order sensitivity indices are computed to evaluate the effects of parameters individually and in combination. Overall, hydrological budgets are simulated similarly between CLASIC and SWMM. The results indicate the performance validity of CLASIC stream discharge simulations at computational time steps greater than the time of concentration of the catchment. However, SWMM peak discharge simulations at smaller time steps are closer to the observed behavior of the system. Sensitivity analysis results underline the importance of the Horton infiltration parameters and the percent of imperviousness of the catchment.
Open Access
Characterization of co-benefits of green stormwater infrastructure across ecohydrologic regions in the United States
(Colorado State University. Libraries, 2020) Rainey, William, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, committee member; McHale, Melissa, committee member
Green stormwater infrastructure (GSI) systems such as rain gardens, permeable pavement and bioswales are commonly used in municipalities to reduce urban flooding and water pollution. In conjunction with these direct benefits, GSI systems provide additional social and ecological "co-benefits". Our goal was to investigate the co-benefits of commonly used GSI systems in five cities in the United States, including Baltimore, Denver, New York City, Philadelphia, and Portland. Specifically, carbon storage, carbon sequestration, air pollution removal, UV reduction, and cooling effects of the trees used in GSI in the study cities were quantified. The i-Tree Eco urban forestry model was used to predict various co-benefits for individual tree species and total SGI tree inventories across the five study cities based on observed tree characteristic data. Aspects of SGI design, environmental factors, and model inputs were evaluated to find what influences the assessment of SGI co-benefits. SGI design types and utilization levels of those designs played a big role in determining the number of trees used in SGI projects, however there is more nuance to the evaluation of co-benefits of different cities' SGI trees than just the tree population. Climate was a large influence on co-benefits' estimation, with similar co-benefit responses for cities with similar climates, like the eastern seaboard. The inputs that influence co-benefit predictions the most were evaluated using global sensitivity analysis. We also found that the inputs that represent the tree growth and environmental factors heavily influenced the computation of co-benefits in i-Tree Eco. Our research supports current literature in developing SGI programs that provide the most amount of co-benefits for specific climates. This study aims to reveal more about the mechanisms and prevailing equations within i-Tree Eco by providing modelled datasets and assessment approaches to estimate the co-benefits of GSI at unit and city levels.
Open Access
Characterization of the vulnerability of urban streams to nutrient pollution under varying flow regimes
(Colorado State University. Libraries, 2019) Heiden, Chelsey, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, committee member; Covino, Tim, committee member
Nutrient pollution is a primary cause of water quality impairment in streams in the United States and throughout the world. Regulatory approaches under the Clean Water Act, such as water quality standards and the Total Maximum Daily Load program, aim to improve water quality. In this study, novel probabilistic methods are developed to characterize vulnerability to nutrient pollution along urban streams and to assess risk of water quality impairment under varying hydrologic conditions. Vulnerability is defined as the probability that ambient conditions exceed desired water quality standards. Both EPA ecoregional and state-level targets are included in the analysis. Specifically, the study i) explores relationships between urban influences and risk to nutrient pollution; and ii) expands on the load duration curve framework to quantify vulnerability to nutrient pollution as a function of flow exceedance probability. The study objectives are examined at 20 stream locations in four ecohydrologically different regions across the United States, including Denver, CO; Phoenix, AZ; Portland, OR; and Baltimore, MD. Total phosphorus (TP) and total nitrogen (TN) water quality data collected between 1990 and 2018 with daily discharge measurements are utilized in the analysis. Indicators of urban influence include wastewater treatment capacity, urban land cover, impervious surfaces, and population density. In general, study locations exhibit vulnerability (greater than 5%) to nutrient impairment across urban gradients, including some relatively undisturbed monitoring locations. Nearly 30% of TP sites and 45% of TN sites are impaired under state level regulation. Results indicate that incorporation of more stringent EPA ecoregional targets lead to higher vulnerability estimates than those corresponding to the state-level targets. Over 70% of TP sites and 55% of TN sites with state level standards are characterized as vulnerable (greater than 5%) when EPA goals are considered. Patterns of impairment through urban gradients are more evident in arid regions with wastewater-dominated river flows, specifically in Denver and Phoenix, than humid regions. Multiple linear regressions between indicators of urban influence and vulnerability provide strong (R2 > 0.7) relationships for most monitoring locations. Inverse distance weighted annual wastewater treatment facility flow capacity and urban land cover are the most significant predictors. However, the most important nonpoint source exploratory variable differ from site to site. More monitoring locations are required to determine model significance. In addition, assessment of nutrient pollution vulnerability using the enhanced load duration approach show that higher vulnerability to impairment tends to occur under consistent hydrologic conditions within each city. For example, high vulnerability to TN and TP impairments are observed under low flow conditions at sites within and around the Denver incorporated area. Conversely, nutrient levels during high flow conditions are more likely to exceed the TN and TP standards in Phoenix, Baltimore, and Portland. Many locations are vulnerable to nutrient pollution (greater than 5%) under all possible flow scenarios, especially at downstream monitoring locations. Approximately 85% of TP sites and 70% of TN sites are vulnerable under all flow conditions assuming EPA water quality goals. The methodology developed in this study can be used to probabilistically quantify the vulnerability to water quality impairments in streams and to identify hydrologic conditions under which higher vulnerabilities prevail.
Open Access
Characterization of urban water use and performance evaluation of conservation practices using the Integrated Urban Water Model in São Paulo, Brazil
(Colorado State University. Libraries, 2018) Batista, Giovana das Gracas, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, advisor; Dozier, Andre, committee member; Goemans, Christopher, committee member
Increasing urban population around the globe has intensified the need for water, food and energy. The residential sector is responsible for the highest water use in urban settings. Understanding the factors affecting water use helps to improve management strategies, incentivize conservation practices, develop public educational events, feed demand forecasting models and support policy creation. Modelling urban water demand in the long-term is a complex process because of incorporation of multiple dynamic components in the urban-environment system. The Integrated Urban Water Model – IUWM – offers capabilities of long-term modelling by using a mass-balance approach for urban water demand predictions and potential demand reductions assessment. A combination of climate anomalies, water resources management practices over the years and watershed conservation contributed to the water shortage in Southeastern Brazil in 2014-2015. In the city of São Paulo, the shortage was worsened by drops in reservoir levels, rise in water use patterns and in number of inhabitants, and the historical tendency to neglect local water sources. Residential water demand, which accounts for 84% of the total water use, faced compulsory reductions through behavioral changes and reuse of graywater and roof runoff harvesting. The goals of this study are to apply IUWM to the city of São Paulo to quantify savings produced by graywater and roof runoff use and to evaluate the potential of conservation practices for demand reduction. The first part of the study focuses on exploring differences in water demand patterns under shortage conditions using a water use time-series from 2013-2017. In this part, IWUM is trained to estimate indoor and outdoor demand through calibration procedures. Determinants of water demand are also investigated through a multiple linear regression, which identified household size and socioeconomic variables as having a significant effect in water use. The second portion focuses on applying IUWM to evaluate reductions during the shortage and performance of graywater, stormwater, roof runoff harvesting and effluent reuse for potable and non-potable purposes. Climate change was added to assess shifts in performances of conservation practices due to future reductions in precipitation. Lastly, a comparison of maximum potential and benefits of fit-for-purpose technology adoption is done using a cost-benefit matrix. The matrix was adapted for required treatment representing cost and percentage reductions in water demand as benefit. The results of this work support decision-making with respect to conservation practices adoption by enhancing the list of options to manage water demand, especially during shortage conditions. Ultimately, these results can encourage development of water reuse policies in Brazil.
Open Access
Characterization of water quality pollution in mixed land use watersheds
(Colorado State University. Libraries, 2020) Ludwig, Madeline, author; Arabi, Mazdak, advisor; De Long, Susan, committee member; Wilkins, Michael, committee member
Anthropogenic sources of pollution often lead to degraded surface water quality in urban and agricultural streams. The Clean Water Act was developed to mitigate the negative effects of urbanization on water quality through the development of water quality targets and the Total Maximum Daily Load program. In this study, a probabilistic framework was developed to quantitatively assess how indicators of human influence impact vulnerability to E. coli impairment and nutrient concentrations in mixed land use watersheds across the state of Colorado. The models derived using this method can be used to predict instream pollutant concentrations and help regulatory agencies create sampling programs for at risk waterbodies. Specifically, the first part of this study explores vulnerability to E. coli impairment under varying levels of upstream anthropogenic influences and develops a probabilistic method for assessing E. coli pollution based on the regulatory monitoring program. In this study, vulnerability is defined as the probability that ambient instream pollutant concentrations exceed numeric water quality standards. The study objective was examined for 28 sites along the Cache la Poudre River and its tributaries including: Boxelder Creek, Fossil Creek, and Spring Creek in northern Colorado. Indicators of urban influence include land use, wastewater treatment plant discharge capacity, combined animal feeding operation capacity, and population. Multiple linear regressions analysis between anthropogenic indicators, E. coli concentrations and vulnerability provide significant (p < 0.05) and strong (R2 > 0.7) relationships. In general, land use predictor variables were able to accurately predict E. coli load, however the most important indicator of human influence differed between E. coli concentration response variables. Additionally, the second part of this study expands upon the multiple linear regression framework to develop regression models that can predict base level nutrient concentrations for stream segments in three regions of Colorado. Regression models were developed using data from 89 sampling locations upstream of wastewater treatment plants and 84 sampling locations downstream of wastewater treatment plants. An initial analysis of gaged sampling locations showed that flow was a significantly influenced instream nutrient concentrations. Area and slope of the contributing sub watershed were then analyzed in a regression analysis and were found to be a surrogate for streamflow. Strong (R2 > 0.7) and significant (p < 0.05) regression models for upstream and downstream locations were developed using area and slope, hydrologic, point, and non-point source predictor variables. The models showed that agricultural and urban activity significantly impacted instream baseline nutrient concentrations. The methodology developed in this study can be used to predict instream pollutant concentration and assist in the development of monitoring programs for at risk waterbodies.
Open Access
Comparison of regionalization methods for a process based hydrologic model in major river basins of Colorado
(Colorado State University. Libraries, 2010) Sanadhya, Pranay, author; Arabi, Mazdak, advisor; Fassnacht, Steven R., committee member; Salas, Jose D., committee member
Distributed watershed models are increasingly used for management of scarce water resources around the world. However, the utility of these models in ungaged or poorly gaged basins is a major issue in the field of hydrological sciences. Performance of watershed models cannot be evaluated for regions with paucity or unavailability of observed streamflow records; thus, a challenge is posed for the effective management of water resources in a region. Regionalization methods that relate watershed characteristics to model parameters are considered as a potential approach to overcome this challenge. The aim of this research is to analyze different regionalization methods and categorize the ones performing efficiently for the regionalization of the Soil and water assessment tool (SWAT) in five major river basins of Colorado. These River basins include: the Arkansas River basin at Canon City, the Cache la Poudre River basin at mouth of canyon, the Gunnison River basin above Blue Mesa dam, the San Juan River basin near Archuleta, and the Yampa River basin near Maybell. SWAT models were prepared for the study watersheds and their performance was evaluated corresponding to naturalized monthly streamflow available for these watersheds. Initially, these prepared models were reconciled with a global sensitivity analysis method known as Fourier Amplitude Sensitivity Test (FAST) to identify sensitive model parameters and the corresponding hydrologic processes they represent. Sensitivity analysis was performed for the two objective functions; mean monthly streamflow and the corresponding root mean square error (RMSE). Results of the sensitivity analysis showed that the majority of sensitive parameters were similar between the watersheds, resulting in a common parameter set selection for Colorado watersheds. Interestingly, sensitivity of parameters was observed to be varying depending upon the objective function. Through this part of the study, the significance of association between snowmelt and sub-surface hydrologic processes for generation of streamflow in mountainous watersheds was realized. Secondly, regionalization methods based on different approaches were used to compute the values of parameters identified as sensitive in the previous step. Later, performances of SWAT models developed for the study watersheds were evaluated by using the parameter values obtained from diverse regionalization methods. These methods included: arithmetic mean approach, approaches based on similarity indices (SI) related to watershed attributes, spatial proximity, Bayesian statistical analysis, and multisite calibration. In order to perform regionalization, a watershed was considered as ungaged and the parameter values for the watershed were obtained by using regionalization methods. Performances of these methods were evaluated by using the jack-knife cross validation technique and computing a performance measure ‘E’. The method based on the weighted arithmetic mean approach using SI and the multi-site calibration approach were observed as the most favorable regionalization methods for Colorado watersheds. Likewise, regionalization methods with average and rather poor performances were also identified. This research analyze the applicability of SWAT in mountainous regions and shows that the distributed hydrologic models like SWAT are capable of flow simulations and hydrologic modeling in mountainous regions like Colorado. Observed interactions between the SWAT parameters related to sub-surface processes and snow related processes helps in understanding the role of these hydrologic processes in magnitude and timing of streamflow generation in mountainous watersheds. This study shows that a great extent of similarity in terms of critical hydrologic processes exists between the major river basins of Colorado and thus helps in selecting a common SWAT parameter set for snow dominated mountainous regions. Performance of regionalization methods as analyzed in this study shows the importance of methods based on weighted arithmetic mean approach and the multi-site calibration approach for performing regionalization of SWAT in snow dominated mountainous regions.
Open Access
Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences
(Colorado State University. Libraries, 2012) Yen, Haw, author; Arabi, Mazdak, advisor; Fontane, Darrell G., committee member; Hoag, Dana L., committee member; Loftis, Jim C., committee member
Simulation modeling is arguably one of the most powerful scientific tools available to address questions, assess alternatives, and support decision making for environmental management. Watershed models are used to describe and understand hydrologic and water quality responses of land and water systems under prevailing and projected conditions. Since the promulgation of the Clean Water Act of 1972 in the United States, models are increasingly used to evaluate potential impacts of mitigation strategies and support policy instruments for pollution control such as the Total Maximum Daily Load (TMDL) program. Generation, fate, and transport of water and contaminants within watershed systems comprise a highly complex network of interactions. It is difficult, if not impossible, to capture all important processes within a modeling framework. Although critical natural processes and management actions can be resolved at varying spatial and temporal scales, simulation models will always remain an approximation of the real system. As a result, the use of models with limited knowledge of the system and model structure is fraught with uncertainty. Wresting environmental decisions from model applications must consider factors that could conspire against credible model outcomes. The main goal of this study is to develop a novel Bayesian-based computational framework for characterization and incorporation of uncertainties from forcing inputs, model parameters, model structures, and measured responses in the parameter estimation process for multisite multiple-response watershed modeling. Specifically, the following objectives are defined: (i) to evaluate the effectiveness and efficiency of different computational strategies in sampling the model parameter space; (ii) to examine the role of measured responses at various locations in the stream network as well as intra-watershed processes in enhancing the model performance credibility; (iii) to facilitate combining predictions from competing model structures; and (iv) to develop a statistically rigorous procedure for incorporation of errors from input, parameter, structural and measurement sources in the parameter estimation process. The proposed framework was applied for simulating streamflow and total nitrogen at multiple locations within a 248 square kilometer watershed in the Midwestern United States using the Soil and Water Assessment Tool (SWAT). Results underlined the importance of simultaneous treatment of all sources of uncertainty for parameter estimation. In particular, it became evident that incorporation of input uncertainties was critical for determination of model structure for runoff generation and also representation of intra-watershed processes such as denitrification rate and dominant pathways for transport of nitrate within the system. The computational framework developed in this study can be implemented to establish credibility for modeling watershed processes. More importantly, the framework can reveal how collection of data from different responses at different locations within a watershed system of interest would enhance the predictive capability of watershed models by reducing input, parametric, structural, and measurement uncertainties.
Open Access
Confronting the natural variability and modeling uncertainty of nonpoint source pollution in water quality management
(Colorado State University. Libraries, 2017) Tasdighi, Ali, author; Arabi, Mazdak, advisor; Bledsoe, Brian, committee member; Bailey, Ryan, committee member; Hoag, Dana, committee member
Nonpoint source pollution is the primary cause of impaired water bodies in the United States and around the world. Hence, managing the water quality is hinged mainly on controlling this type of pollution. However, characterization of nonpoint source pollution is extremely difficult due to high inherent natural variability and uncertainty. Nonpoint source pollution loads depend on climate, land use, and other environmental conditions that are highly variable by nature. On the other hand, since it is often infeasible to measure pollutant loads from nonpoint sources within a watershed using monitoring campaigns, models are increasingly used to estimate these loads. Models are simplified representations of reality. Consequently, they are subject to various sources of uncertainty including: model parameters, input data (climate, land use, etc.), model structure (conceptualization), and measurement data (streamflow, nutrient concentrations or loads, etc.).
Open Access
Enhanced watershed modeling and data analysis with a fully coupled hydrologic model and cloud-based flow analysis
(Colorado State University. Libraries, 2014) Wible, Tyler, author; Arabi, Mazdak, advisor; Bailey, Ryan, advisor; Baù, Domenico, committee member; Ronayne, Michael, committee member
In today's world of increased water demand in the face of population growth and climate change, there are no simple answers. For this reason many municipalities, water resource engineers, and federal analyses turn to modeling watersheds for a better understanding of the possible outcomes of their water management actions. The physical processes that govern movement and transport of water and constituents are typically highly nonlinear. Therefore, improper characterization of a complex, integrated, processes like surface-subsurface water interaction can substantially impact water management decisions that are made based on existing models. Historically there have been numerous tools and watershed models developed to analyze watersheds or their constituent components of rainfall, run-off, irrigation, nutrients, and stream flow. However, due to the complexity of real watershed systems, many models have specialized at analyzing only a portion of watershed processes like surface flow, subsurface flow, or simply analyzing local monitoring data rather than modeling the system. As a result many models are unable to accurately represent complex systems in which surface and subsurface processes are both important. Two popular watershed models have been used extensively to represent surface processes, SWAT (Arnold et al, 1998), and subsurface processes, MODFLOW (Harbaugh, 2005). The lack of comprehensive watershed simulation has led to a rise in uncertainty for managing water resources in complex surface-subsurface driven watersheds. For this reason, there have been multiple attempts to couple the SWAT and MODFLOW models for a more comprehensive watershed simulation (Perkins and Sophocleous, 1999; Menking, 2003; Galbiati et al., 2006; Kim et al., 2008); however, the previous couplings are typically monthly couplings with spatial restrictions for the two models. Additionally, most of these coupled SWAT-MODFLOW models are unavailable to the general public, unlike the constituent SWAT and MODFLOW models which are available. Furthermore, many of these couplings depend on a forced equal spatial discretization for computational units. This requires that one MODFLOW grid cell is the same size and location of one SWAT hydrologic response unit (HRU). Additionally, many of the previous couplings are based on a loose monthly average coupling which might be insufficient in natural spring and irrigated agricultural driven groundwater systems which can fluctuate on a sub-monthly time scale. The primary goal of this work is to enhance the capacity for modeling watershed processes by fully coupling surface and subsurface hydrologic processes at a daily time step. The specific objectives of this work are 1) to examine and create a general spatial linkage between SWAT and MODFLOW allowing the use of spatially-different existing models for coupling; 2) to examine existing practices and address current weaknesses for coupling of the SWAT and MODFLOW models to develop an integrated modeling system; 3) to demonstrate the capacity of the enhanced model compared to the original SWAT and MODFLOW models on the North Fork of the Sprague River in the Upper Klamath Basin in Oregon. The resulting generalized daily coupling between a spatially dis-similar SWAT and MODFLOW model on the North Fork of the Sprague River has resulted in a slightly more lower representation of monthly stream flow (monthly R2 = 0.66, NS = 0.38) than the original SWAT model (monthly R2 = 0.60, NS = 0.57) with no additional calibration. The Log10 results of stream flow illustrate an even greater improvement between SWAT-MODFLOW correlation (R2) but not the overall simulation (NS) (monthly R2 = 0.74, NS = -0.29) compared to the original SWAT (monthly R2 = 0.63, NS = 0.63) correlation (R2). With an improved water table representation, these SWAT-MODFLOW simulation results illustrate a more in depth representation of overall stream flows on a groundwater influenced tributary of the Sprague River than the original SWAT model. Additionally, with the increased complexity of environmental models there is a need to design and implement tools that are more accessible and computationally scalable; otherwise their use will remain limited to those that developed them. In light of advancements in cloud-computing technology a better implementation of modern desktop software packages would be the use of scalable cloud-based cyberinfrastructure, or cloud-based environmental modeling services. Cloud-based deployment of water data and modeling tools assist in a scalable as well as platform independent analysis; meaning a desktop, laptop, tablet, or smart phone can perform the same analyses. To utilize recent advancements in computer technology, a further focus of this work is to develop and demonstrate a scalable cloud-computing web-tool that facilitates access and analysis of stream flow data. The specific objectives are to 1) unify the various stream flow analysis topics into a single tool; 2) to assist in the access to data and inputs for current flow analysis methods; 3) to examine the scalability benefits of a cloud-based flow analysis tool. Furthermore, the new Comprehensive Flow Analysis tool successfully combined time-series statistics, flood analysis, base-flow separation, drought analysis, duration curve analysis, and load estimation into a single web-based tool. Preliminary and secondary scalability testing has revealed that the CFA analyses are scalable in a cloud-based cyberinfrastructure environment to a request rate that is likely unrealistic for web tools.
Open Access
Geospatial analysis of water and nutrient transport in two northern Colorado mixed-landuse watersheds
(Colorado State University. Libraries, 2011) Cowley, Cortney A., author; Arabi, Mazdak, advisor; Carlson, Ken, advisor; Bledsoe, Brian, committee member; Stromberger, Mary, committee member
This study examines the effect of different sources, transport pathways, and hydrologic regimes on phosphorus concentrations along a pristine-urban-agricultural gradient. A total of 48 sampling locations were monitored to characterize total phosphorus concentrations in the Cache la Poudre River Watershed in Northern Colorado. The comprehensive design of sampling locations aimed to capture the influence of anthropogenic activities and geospatial heterogeneity. Samples were collected at seven points in time with distinct climatic and hydrologic characteristics from April 2010 to February 2011. A geographic information system (GIS) was used to measure the overland, irrigation ditch, and stream/river distances from the sources to sampling locations. Analysis of variance, non-linear regression, and multiple linear regression models were used in combination to explore the co-variation of phosphorus concentrations with capacities of upstream WWTPs and CAFOs, along with other geospatial factors. It was evident, under all hydrologic conditions, that phosphorus concentrations downstream from WWTPs were significantly higher than the concentrations upstream of the facilities. Transport from WWTPs governed phosphorus concentrations in surface water during dry and low flow conditions, whereas contribution of CAFOs was significant during rainfall events. The total flow distance (a function of overland, irrigation ditch, and stream/river distances) from CAFOs to the sample locations was strongly associated with phosphorus concentrations during precipitation events. The results of this study provide the foundation for creating a decision support system for water quality analysis, monitoring, and management in the Poudre River basin and other similar mixed-land use watersheds. After examining the Poudre River watershed, a thorough investigation of Boxelder Creek basin was executed. The objectives were to gain an understanding of the geospatial heterogeneity and hydrologic complexity of the watershed using available data, aerial photography, and ground truthing and to develop a model that could accurately simulate the hydrology and nutrient routing in the watershed. Modeling the system using a simplified method for irrigation produced simulated results that were inconsistent with observed flow measurements. These results seem to indicate that irrigation ditches play a vital role in the hydrologic cycle of the basin. Previous studies indicate that watersheds in the study region can be accurately modeled; and although stream flow was not adequately simulated, the model did perform better when estimating total phosphorus concentrations. Therefore, future studies attempting to model basins containing irrigation ditches, like Boxelder Creek basin, should incorporate methods for representing the channels and their various interactions with the natural system. Routing irrigation canals through the watershed, along with irrigation and manure application methods described in this study, should improve the feasibility of modeling the heterogeneity of mixed landuse watersheds.
Open Access
Hydrologic and hydraulic response to wildfires in the upper Cache la Poudre watershed using a SWAT and HEC-RAS model cascade
(Colorado State University. Libraries, 2015) Havel, Aaron, author; Arabi, Mazdak, advisor; Baker, Daniel, committee member; Wohl, Ellen, committee member
The enhanced possibility of catastrophic wildfires in the western USA and other regions around the world has increased the need to evaluate the effects of wildfire on the hydrology of watersheds and the hydraulic behavior of rivers. Understanding the effects of wildfires is vital in water-resources management and for public safety especially in regions where communities depend on surface water supply. Similarly, areas adjacent to river systems may be at risk of increased flooding due to wildfires in their upstream watersheds. Effects of wildfires on hydrologic fluxes in watersheds and rivers have been extensively studied; but, characterization of responses to wildfires is difficult due to the spatial variability of post-wildfire conditions. At the watershed scale, hydrologic responses comprise a network of complex nonlinear interactions. Hence, comprehensive watershed models serve as a useful tool to understand these relationships. Watershed models commonly lack the ability to represent channel geometry and channel process with sufficient spatial frequency. Thus, a hydrologic and hydraulic model cascade provides a bridge between the nonlinear interactions of the uplands and the river responses at the channel scale. The overall goal of this study is to examine the spatial variability of the effects of the 2012 High Park and Hewlett wildfires that occurred within the headwaters of the Cache la Poudre River located in northern Colorado, USA. Two commonly used models were calibrated and used in combination. First, the Soil and Water Assessment Tool (SWAT) was used to evaluate the hydrologic responses of the upper Cache la Poudre watershed to the wildfire events. Subsequently, the results from the SWAT model were used as inputs for the hydraulic model Hydrologic Engineering Center River Analysis System (HEC-RAS) to simulate channel hydraulics along 42.5 km of the upper Cache la Poudre River. The baseline SWAT model was established to simulate the hydrology of the study area between the years 2000 and 2014. This model accounts for wildfires by modifying land use/land cover inputs and corresponding parameters during simulations. Daily streamflow data were used for model calibration and testing. Using the calibrated baseline model, no-wildfire and wildfire scenarios were created. The two scenarios were then compared for changes in average annual total runoff volume, water budgets, and full streamflow statistics at the watershed and sub-basin scales. Then a HEC-RAS model was developed to simulate the hydraulic responses of the stream network using streamflows for various floods extracted from the two SWAT scenarios. High resolution DEM data and surveyed water surface elevations are used for model calibration and testing, respectively. Channel hydraulic behavior including flood inundation area, streamflow velocities, and channel shear stress were compared for the two scenarios at the channel scale. At the watershed scale, wildfire conditions have little effect on the hydrologic responses, but at the sub-basin scale a total runoff increase up to 75 percent between scenarios was found. Generally, wildfire affected water budgets showed more surface runoff versus subsurface runoff, suggesting a decrease in infiltration rates under post-wildfire conditions. Flow-duration curves developed using full streamflow statistics for burned sub-basins show that less frequent streamflows become greater in magnitude leading to ecosurplus values up to 0.279. Also, simulations revealed that there is a strong and significant (R2 > 0.8 and p < 0.001) positive correlation between runoff increase and percentage of burned area upstream. Streamflow increases were between 2 and 14 percent depending on the reach’s proximity to the wildfire and the flood. Lastly, along the main stem only slight increases in flood area, average cross section velocity, and shear stress as a result of wildfire were observed in the simulations. The results have important implications on improving post-wildfire water resources management.
Open Access
Impacts of climate change on the hydrologic response of headwater basins in Colorado
(Colorado State University. Libraries, 2010) Foy, Caleb R., author; Arabi, Mazdak, advisor; Kampf, Stephanie, committee member; Ramirez, Jorge, committee member
The headwater basins of Colorado are heavily relied upon for freshwater resources on an annual basis. However, knowledge concerning generation of such resources, and implications of climate change on their availability in the future, is not well understood. Thus, this research has been undertaken to develop, calibrate, and test a comprehensive process-based model in four mountainous watersheds of Colorado, and investigate the potential impacts of changing climate on hydrologic response in these basins. Specifically, the four study watersheds considered for analysis include the Cache la Poudre, Gunnison, San Juan and Yampa River basins. Calibration of the model compared several parameter optimization techniques for performance in each of the study basins, which included the more common Shuffled Complex Evolution – University of Arizona (SCE-UA) method and a Markov Chain Monte Carlo (MCMC) method known as the Gibbs Sampler Algorithm (GSA). Fully calibrated and tested models were driven by a suite of 112 climate projections, downscaled both spatially and temporally, and were run on a daily time-step for a period of 90 years from 2010 – 2099. Results from model calibration indicate GSA outperformed SCE-UA in a majority of the study basins, in addition to revealing promising results from a two-stage method that combined the strengths of the two techniques. Error statistics showed very good (Nash-Sutcliffe coefficient of efficiency >0.75 and relative error <+/-10%) performance of monthly streamflow simulations compared to naturalized flows at the outlet of each watershed over a period of 16 years (1990 – 2005). Additionally, the models provided satisfactory results for simulating monthly streamflow at multiple sites nested within each watershed, which increased confidence in model parameterization and representation of dominant hydrologic processes. Results indicate that on an average annual basis, 55% – 65% of precipitation goes to evapotranspiration, and lateral flow contributes to between 64% and 82% of gross water yield. Results from future simulations over the course of the 21st century indicate inconsistent responses in streamflow to increasing temperature and variable precipitation projections. However, results did show consistency in the Yampa River basin, where 71 out of 112 future projections resulted in statistically significant (α<0.1) positive trends of average annual streamflow. Furthermore, all study basins exhibited a decreasing ratio of precipitation to potential evapotranspiration from emissions scenario ensemble averages, which suggest Colorado basins will become more arid over the 21st century. Future forecasting of water availability in Colorado may benefit from this research, as specific climate projections were provided that resulted in consistent responses (increasing and decreasing) in streamflow across all watersheds. Implications of this study are considerable, as management of water resources, both within the state and across the West, will be affected by freshwater availability in headwater basins of Colorado in the future.
Embargo
Integrated assessment of water shortage under climate, land use, and adaptation changes in the contiguous United States
(Colorado State University. Libraries, 2024) Gharib, Ahmed AbdelTawab Fahmy AbdelMeged, author; Arabi, Mazdak, advisor; Goemans, Christopher, committee member; Sharvelle, Sybil, committee member; Warziniack, Travis, committee member
Water scarcity is a critical global challenge. Water managers pursue water supply- and demand-side strategies, including construction or enhancement of water supply systems, conservation, and water reuse, to address water security driven by changes in climate, population, and land use. However, the effects of these strategies to mitigate future water shortages under dynamic climate and socioeconomic conditions at various spatial and temporal scales remain unclear. The overarching goal of this dissertation is to (1) improve understanding of the interconnections and interactions between climate, socioeconomic, hydrological, and institutional factors that influence water shortage at the river basin level, and (2) conduct an integrated assessment of water and land use management strategies. The dissertation is organized into three research studies. The first study explores water shortages in the South Platte River Basin (SPRB) and the potential benefits of investing in storage infrastructure and demand management strategies. The second study develops a methodology to understand the interactions between land use planning, water demands, shortage vulnerability, and effects on associated economic value. The third study expands the integrative assessment framework to assess changes in water demand, supply, and withdrawals, and identify effective mitigation strategies across river basins in the Contiguous United States over a range of climatic and socioeconomic pathways that are forecasted for the coming decades. In the first study, we develop data analysis and modeling tools to project water demands, supply, and shortages in the SPRB by the mid and end of the 21st century, examine the efficacy of adaptation strategies to reduce water shortages, and explore conditions under which reservoir storage and demand management would serve benefits for reduction of the vulnerability of economic sectors to water shortages. We implement two demand modeling tools to simulate the current and future urban and agricultural water demand in the river basin. Water yield is simulated using calibrated and tested Variable Infiltration Capacity (VIC) model. The estimated water demands and supplies are integrated using the Water Evaluation and Planning (WEAP) model to simulate water allocation with a half-monthly timestep to 70 aggregate users in the basin. Population growth, climate change, reservoir operations, and institutional agreements were considered during the modeling. The study reveals that the vulnerability to water shortages across sectors would increase without adaptation strategies. Population growth tends to be the primary driver of water shortages in the river basin. Reservoirs in the basin can relieve the sequences of the earlier seasonal shift of the water supply by capturing water during the high flow to be used in the high-demand seasons. However, additional storage is only beneficial up to a threshold of storage capacity to the water supply mean ratio of 0.64. The second study focuses on integrating the effects of land use planning and water rights institutions into the shortage analysis of the SPRB. The goal is to build a framework to understand the complex interactions between climate change, water rights institutions, urban land use planning, and population growth, and how they collectively impact the water shortage and economic analysis. We apply this framework to the SPRB simulate three water institutions, update the urban demand modeling to be a function of the population density, and test different scenarios of population locations throughout the basin. Results show that changing water rights institutions has a small impact on total shortages compared to climate change, but substantially impacts which users experience shortages. Land use policies influencing population locations have larger impacts on shortage and economic value compared to water rights. Finally, distributing the population more evenly between upstream and downstream regions reduces water shortages and increases associated economic value regardless of water rights institutions and climate conditions. The third study employs an integrative modeling assessment framework to assess water shortage and effective mitigation strategies in river basins across the Contiguous United States. The goals are to improve the methodologies for estimation of water withdrawals, consumptive use, and water shortage, and explore the effectiveness of supply- and demand-side adaptation strategies. The simulated demands are integrated with the water supply components (groundwater, interbasin transfers, water yield, and reservoirs) into a water allocation model for simulating shortage under different scenarios. Results reveal that irrigation has the highest historical and future consumptive use, over 75% of the total consumptive use. Although the consumptive use ratio receives little attention in the literature, it appears to be the most significant parameter for shortage calculations. The allocation model provides comprehensive shortage analysis considering shortage volume, ratio, and frequency across multiple scenarios for the 204 sub-regions –Hydrologic Unit Code 4 watersheds– of the Contiguous United States. Water shortages concentrate between the boundaries of the West Region with both the Midwest and the South regions, in addition to Arizona, Florida, and the center valley of California. Relying only on sustainable groundwater pumping rates is essential to stop the ongoing groundwater depletion, but adds more pressure on demand reduction strategies. The ongoing research examining water demand, supply, and shortage is important and requires further integration of the key influencing variables. This dissertation demonstrates the necessity of an integrated approach to fully understand the relative impacts of the main drivers of water allocation and shortage. We highlight that reservoirs play a vital role in balancing seasonal fluctuations in the water supply. However, their effect on the 30-year mean annual shortage is effective until the storage volume ratio to mean water supply exceeds 64%. Additionally, land use policies carry higher direct significance on water shortages compared to water rights. We find that distributing the population more evenly throughout the river basin provides the lowest shortage. Lastly, the approaches targeting shortage calculation and mitigation should analyze both regional and national scenarios under integrated frameworks comparing demand- and supply-side options.