Matching Items (43)
Description
Accidental wetlands have been created on the bed of the Salt River and are fed by storm-water outfalls discharging at various sections of the Phoenix Metropolitan Area. Water discharges from these outfalls throughout the year, during both dry conditions (base flow) and during rain events (storm flow). In this study, DOC content and composition was studied during these two flow conditions, in the outfalls and along the wetland flow path. The importance of DOC lies in its role in transporting carbon via water movement, between different parts of a landscape, and therefore between pools in the ecosystem. Urbanization has influenced content and composition of DOC entering the accidental urban wetland via outfalls as they represent watersheds from different areas in Phoenix. First, DOC load exhibited higher quantities during stormflow compared to baseflow conditions. Second, DOC load and fluorescence analysis outcomes concluded the outfalls are different from each other. The inputs of water on the north side of the channel represent City of Phoenix watersheds were similar to each other and had high DOC load. The northern outfalls are both different in load and composition from the outfall pipe on the southern bank of the wetland as it represents South Mountain watershed. Fluorescence analysis results also concluded compositional changes occurred along the wetland flow path during both stormflow and baseflow conditions. In this study, it was explored how urbanization and the associated changes in hydrology and geomorphology have affected a desert wetland's carbon content.
ContributorsBone, Stephanie Rosalia (Author) / Hartnett, Hilairy (Thesis director) / Palta, Monica (Committee member) / Mascaro, Giuseppe (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Agriculture is the second largest water consumer in the Phoenix Metropolitan region, after the municipal sector. A significant portion of the cultivated land and agricultural water demand is from the production of animal feed, including alfalfa (~69% of total cropland area), corn (~8), and sorghum (-3%), which are both exported and needed to support local dairy industry. The goal of this thesis is to evaluate the impacts on water demand and crop production of four different crop portfolios using alfalfa, corn, sorghum, and feed barley. For this aim, the Water Evaluation And Planning (WEAP) platform and the embedded MABIA agronomic module are applied to the Phoenix Active Management Area (AMA), a political/hydrological region including most of Phoenix Metro. The simulations indicate that the most efficient solution is a portfolio where all study crop production is made up by sorghum, with an increase of 153% in crop yield and a reduction of 60% of water consumption compared to current conditions. In contrast, a portfolio where all study crop production is made up by alfalfa, which is primary crop grown in current conditions, decreased crop yield by 77% and increases water demand by 105%. Solutions where all study crop production is achieved with corn or feed barley lead to a reduction of 77% and 65% of each respective water demand, with a portfolio of all corn for study crop production increasing crop yield by 245% and a portfolio of all feed barley for study crop production reducing crop yield by 29%.
ContributorsRees, Kendall Marcella (Author) / Mascaro, Giuseppe (Thesis director) / Muenich, Rebecca (Committee member) / Chhetri, Netra (Committee member) / Civil, Environmental and Sustainable Eng Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
There has been much work done predicting the effects of climate change on transportation systems, this research parallels that past work and focuses on the effect of changes in precipitation on roadway drainage systems. On a macro level, this work addresses the process that should be taken to make predictions about the vulnerability of this system due to changes in precipitation. This work also addresses the mechanisms of failure of these drainage systems and how they may be affected by changes in precipitation due to climate change. These changes may entail more frequent failure by certain mechanisms, or a shift in the mechanisms for particular infrastructure. A sample water basin in the urban environment of Phoenix, Arizona is given as a case study. This study looks at the mechanisms of failure of the infrastructure therein, as well as provides a process of analyzing the effects of increases in precipitation to the vulnerability of this infrastructure. It was found that drainage structures at roadways being currently designed will see increases from 20-30% in peak discharge, which will lead to increased frequency of failure.
ContributorsHolt, Nathan Thomas (Author) / Chester, Mikhail V (Thesis director) / Mascaro, Giuseppe (Committee member) / Underwood, Benjamin S. (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
There is a considerable need for improved understanding of the outcome and amounts of water used to manage urban landscapes in arid and semiarid cities. Outdoor irrigation in urban parks consists of a large fraction of water demands in Phoenix, Arizona. Hence, ecohydrological processes need to be considered to improve outdoor irrigation management. With the goal of reducing outdoor water use and advancing the general knowledge of water fluxes in urban parks, this study explores water conservation opportunities in an arid city through observations and modeling.Most urban parks in Phoenix consist of a mosaic of turfgrass and trees which receive scheduled maintenance, fertilization and watering through sprinkler or flood irrigation. In this study, the effects that different watering practices, turfgrass management and soil conditions have on soil moisture observations in urban parks are evaluated. Soil moisture stations were deployed at three parks with stations at control plots with no compost application and compost treated sites with either a once or twice per year application instead of traditional fertilizer. An eddy covariance system was installed at a park to help quantify water losses and water, energy and carbon fluxes between the turfgrass and atmosphere. Additional meteorological observations are provided through a network of weather stations. The assessment covers over one year of observations, including the period of turfgrass growth in the warm season, and a period of dormancy during the cool season. The observations were used to setup and test a plot-scale soil water balance model to simulate changes in daily soil moisture in response to irrigation, precipitation and evapotranspiration demand for each park.
Combining modeling and observations of climate-soil-vegetation processes, I provide guidance on irrigation schedules and management that could help minimize water losses while supporting turfgrass health in desert urban parks. The irrigation scenarios suggest that water savings of at least 18% can be achieved at the three sites. While the application of compost treatment to study plots did not show clear improvements in soil water retention when compared to the control plots, this study shows that water conservation can be promoted while maintaining low plant water stress.
ContributorsKindler, Mercedes (Author) / Vivoni, Enrique R (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Garcia, Margaret (Committee member) / Arizona State University (Publisher)
Created2021
Description
Observational evidence is mounting on the reduction of winter precipitation and an earlier snowmelt in the southwestern United States. It is unclear, however, how these changes, along with forest thinning, will impact water supplies due to complexities in the precipitation-streamflow transformation. In this study, I use the Triangulated Irregular Network-based Real-time Integrated Basin Simulator (tRIBS) to provide insight into the independent and combined effects of climate change and forest cover reduction on the hydrologic response in the Beaver Creek (~1100 km2) of central Arizona. Prior to these experiments, confidence in the hydrologic model is established using snow observations at two stations, two nested streamflow gauges, and estimates of spatially-distributed snow water equivalent over a long-term period (water years 2003-2018). Model forcings were prepared using station observations and radar rainfall estimates in combination with downscaling and bias correction techniques that account for the orographic controls on air temperature and precipitation. Model confidence building showed that tRIBS is able to capture well the variation in snow cover and streamflow during wet and dry years in the 16 year simulation period. The results from this study show that the climate change experiments increased average annual streamflow by 1.5% at +1°C of warming. However, a 28% decrease in streamflow occurs by +6°C of warming as evapotranspiration (ET) increases by 10%. Forest thinning shifted the warming threshold where ET increases reduce streamflow yield until +4°C of warming as compared to no forest thinning when this threshold occurs at +2°C. An average increase in streamflow of 12% occurs after forest thinning across all climate scenarios. While the snow covered area is unaffected by thinning, the volume of snowmelt increases and is linked to the higher water yield. These findings indicate that water managers can expect decreases in streamflow due to climate change but may be able to offset these impacts up to a warming threshold by thinning forested areas within the Beaver Creek.
ContributorsCederstrom, Charles Joshua (Author) / Vivoni, Enrique R (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Svoma, Bohumil (Committee member) / Arizona State University (Publisher)
Created2021
Description
Accelerated climate and land use land cover (LULC) changes are anticipated to significantly impact water resources in the Colorado River Basin (CRB), a major freshwater source in the southwestern U.S. The need for actionable information from hydrologic research is growing rapidly, given considerable uncertainties. For instance, it is unclear if the predicted high degree of interannual precipitation variability across the basin could overwhelm the impacts of future warming and how this might vary in space. Climate change will also intensify forest disturbances (wildfire, mortality, thinning), which can significantly impact water resources. These impacts are not constrained, given findings of mixed post-disturbance hydrologic responses. Process-based models like the Variable Infiltration Capacity (VIC) platform can quantitatively predict hydrologic behaviors of these complex systems. However, barriers limit their effectiveness to inform decision making: (1) simulations generate enormous data volumes, (2) outputs are inaccessible to managers, and (3) modeling is not transparent. I designed a stakeholder engagement and VIC modeling process to overcome these challenges, and developed a web-based tool, VIC-Explorer, to “open the black box” of my efforts. Meteorological data was from downscaled historical (1950-2005) and future projections (2006-2099) of eight climate models that best represent climatology under low- and high- emissions. I used two modeling methods: (1) a “top-down” approach to assess an “envelope of hydrologic possibility” under the 16 climate futures; and (2) a “bottom-up” evaluation of hydrology in two climates from the ensemble representing “Hot/Dry” and “Warm/Wet” futures. For the latter assessment, I modified land cover using projections of a LULC model and applied more drastic forest disturbances. I consulted water managers to expand the legitimacy of the research. Results showed Far-Future (2066-2095) basin-wide mean annual streamflow decline (relative to 1976-2005; ensemble median trends of -5% to -25%), attributed to warming that diminished spring snowfall and melt and year-round increased soil evaporation from the Upper Basin, and overall precipitation declines in the Lower Basin. Forest disturbances partially offset warming effects (basin-wide mean annual streamflow up to 12% larger than without disturbance). Results are available via VIC-Explorer, which includes documentation and guided analyses to ensure findings are interpreted appropriately for decision-making.
ContributorsWhitney, Kristen Marie (Author) / Vivoni, Enrique R (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Whipple, Kelin X (Committee member) / White, Dave D (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Weather radars provide quantitative precipitation estimates (QPEs) with seamless spatial coverage that can complement limitations of sparse rain gage measurements, including those affecting intensity-duration-frequency (IDF) relations used for infrastructure design. The goal of this M.S. thesis is to assess the ability of 4-km, 1-h QPEs from the Stage IV analysis of the Next-Generation Radar (NEXRAD) network to reproduce the statistics of extreme precipitation (P) in central Arizona, USA, using a dense network of 257 rain gages as reference. The generalized extreme value (GEV) distribution is used to model the frequency of annual P maximum series observed at gages and radar pixels for durations, d, from 1 to 24 h. Estimates of P quantiles from radar QPEs are negatively biased (-20% – -30%) for d = 1 h. The bias tends to 0 and errors are small for d ≥ 6 h, independently of the return period. The presence of scaling for the GEV location and scale parameters, needed to apply IDF scaling models, was found for both radar and gage products. Regional frequency analysis methods combined with bias correction of the GEV shape parameter allow reducing the statistical uncertainty and providing seamless spatial distribution of P quantiles at daily and subdaily durations that address limitations of current IDF relations in southwestern U.S. based on NOAA Atlas 14.
ContributorsSrivastava, Nehal Ansh (Author) / Mascaro, Giuseppe (Thesis advisor) / Chester, Mikhail (Committee member) / Garcia, Margaret (Committee member) / Papalexiou, Simon Michael (Committee member) / Arizona State University (Publisher)
Created2022
Description
Cities are facing complex problems in urban water management due to unprecedented changes in climate, natural and built environment. The shift in urban hydrology from pre-development to post-development continues to accelerate the challenges of managing excess stormwater runoff, mitigating urban flood hazards and flood damages. Physically based hydrologic-hydraulic stormwater models are a useful tool for broad subset of urban flood management including risk and hazard assessment, flood forecasting, and infrastructure adaptation decision making and planning. The existing limitations in data availability, gaps in data, and uncertainty in data preclude reliable model construction, testing, deployment, knowledge generation, effective communication of flood risks, and adaptation decision making. These challenges that affect both the science and practice motivate three chapters of this dissertation. The first study conducts diagnostic analysis of the effects of stormwater infrastructure data completeness on model’s ability to simulate flood duration, flooding flow rate; and assesses the combined effects of data gaps and model resolution to simulate flood depth, extent and volume (chapter 2). The analysis showed the significance of complete stormwater infrastructure data and high model resolution to reduce error, bias and uncertainty; this study also presented an approach for filling infrastructure data gaps using available data and design standards. The second study addresses the lack of long-term hydrological observation in urban catchment by investigating the process and benefits of leveraging novel data sources in urban flood model construction and testing (chapter 3). A proof-of-concept demonstrated the application and benefits of leveraging novel data sources for urban flood monitoring and modeling. Furthermore, it highlights the need for developing and streamlining novel data collection infrastructure. The third study applies the hydrologic-hydraulic model as an adaptation planning tool and assess the effects of uncertainty in design precipitation estimates and land use change on the optimal configuration of green infrastructure (chapter 4). Several uncertainties affect infrastructure decision making as showed by variation in optimal green infrastructure configuration under precipitation estimates and land use change. Thus, the study further highlights the need of flexible planning process in infrastructure decision making.
ContributorsShrestha, Ashish (Author) / Garcia, Margaret (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Chester, Mikhail (Committee member) / Fletcher, Sarah (Committee member) / Arizona State University (Publisher)
Created2022
Description
Integrated water resources management for flood control, water distribution, conservation, and food security require understanding hydrological spatial and temporal trends. Proliferation of monitoring and sensor data has boosted data-driven simulation and evaluation. Developing data-driven models for such physical process-related phenomena, and meaningful interpretability therein, necessitates an inventive methodology. In this dissertation, I developed time series and deep learning model that connected rainfall, runoff, and fish species abundances. I also investigated the underlying explainabilty for hydrological processes and impacts on fish species. First, I created a streamflow simulation model using computer vision and natural language processing as an alternative to physical-based routing. I tested it on seven US river network sections and showed it outperformed time series models, deep learning baselines, and novel variants. In addition, my model explained flow routing without physical parameter input or time-consuming calibration. On the basis of this model, I expanded it from accepting dispersed spatial inputs to adopting comprehensive 2D grid data. I constructed a spatial-temporal deep leaning model for rainfall-runoff simulation. I tested it against a semi-distributed hydrological model and found superior results. Furthermore, I investigated the potential interpretability for rainfall-runoff process in both space and time. To understand impacts of flow variation on fish species, I applied a frequency based model framework for long term time series data simulation. First, I discovered that timing of hydrological anomalies was as crucial as their size. Flooding and drought, when properly timed, were both linked with excellent fishing productivity. To identify responses of various fish trait groups, I used this model to assess mitigated hydrological variation by fish attributes. Longitudinal migratory fish species were more impacted by flow variance, whereas migratory strategy species reacted in the same direction but to various degrees. Finally, I investigated future fish population changes under alternative design flow scenarios and showed that a protracted low flow with a powerful, on-time flood pulse would benefit fish. In my dissertation, I constructed three data-driven models that link the hydrological cycle to the stream environment and give insight into the underlying physical process, which is vital for quantitative, efficient, and integrated water resource management.
ContributorsDeng, Qi (Author) / Sabo, John (Thesis advisor) / Grimm, Nancy (Thesis advisor) / Ganguly, Auroop (Committee member) / Li, Wenwen (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2022
Description
Quantifying the interactions among food, energy, and water (FEW) systems is crucial to support integrated policies for the nexus governance. Metropolitan areas are the main consumption and distribution centers of these three resources and, as urbanization continues, their role will become even more central. Despite this, the current understanding of FEW systems in metropolitan regions is limited. In this dissertation, the key factors leading to a more sustainable FEW system are identified in the metropolitan area of Phoenix, Arizona using the integrated WEAP-MABIA-LEAP platform. In this region, the FEW nexus is challenged by dramatic population growth, competition among increasing FEW demand, and limited water availability that could further decrease under climate change. First, it was shown that the WEAP platform allows the reliable simulations of water allocations from supply sources to demand sectors and that agriculture is a key stressor of the nexus, which will require additional groundwater (+83%) and energy (+15%) if cropland area is preserved over the next 50 years. Second, the climate change impacts on the food-water nexus were quantified by applying the WEAP-MABIA model with climate projections up to 2100 from 27 GCMs under different warming levels. It was found that the increases in temperature will lead to higher atmospheric evaporation demand that will, in turn, reduce crop production at a rate of -4.8% per decade. In the last part, the fully integrated WEAP-MABIA-LEAP platform was applied to investigate future scenarios of the FEW nexus in the metropolitan region. Several scenarios targeting each FEW sector were compared through sustainability indicators quantifying availability/consumption, reliability, and productivity of the three resources. Results showed that increasing renewable energy and changing cropping patterns will increase the FEW nexus sustainability compared to business-as-usual conditions. The findings of this dissertation, along with its analytical approach, support policy making towards integrated FEW governance and sustainable development.
ContributorsGuan, Xin (Author) / Mascaro, Giuseppe (Thesis advisor) / White, Dave (Committee member) / Vivoni, Enrique (Committee member) / Muenich, Rebecca (Committee member) / Arizona State University (Publisher)
Created2022