ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Civil Engineering
Description
The history of outdoor water use in the Phoenix, Arizona metropolitan area has given rise to a general landscape aesthetic and pattern of residential irrigation that seem in discord with the natural desert environment. While xeric landscaping that incorporates native desert ecology has potential for reducing urban irrigation demand, there are societal and environmental factors that make mesic landscaping, including shade trees and grass lawns, a common choice for residential yards. In either case, there is potential for water savings through irrigation schedules based on fluxes affecting soil moisture in the active plant rooting zone. In this thesis, a point-scale model of soil moisture dynamics was applied to two urban sites in the Phoenix area: one with xeric landscaping, and one with mesic. The model was calibrated to observed soil moisture data from irrigated and non-irrigated sensors, with local daily precipitation and potential evapotranspiration records as model forcing. Simulations were then conducted to investigate effects of irrigation scheduling, plant stress parameters, and precipitation variability on soil moisture dynamics, water balance partitioning, and plant water stress. Results indicated a substantial difference in soil water storage capacity at the two sites, which affected sensitivity to irrigation scenarios. Seasonal variation was critical in avoiding unproductive water losses at the xeric site, and allowed for small water savings at the mesic site by maintaining mild levels of plant stress. The model was also used to determine minimum annual irrigation required to achieve specified levels of plant stress at each site using long-term meteorological records. While the xeric site showed greater potential for water savings, a bimodal schedule consisting of low winter and summer irrigation was identified as a means to conserve water at both sites, with moderate levels of plant water stress. For lower stress levels, potential water savings were found by fixing irrigation depth and seasonally varying the irrigation interval, consistent with municipal recommendations in the Phoenix metropolitan area. These results provide a deeper understanding of the ecohydrologic differences between the two types of landscape treatments, and can assist water and landscape managers in identifying opportunities for water savings in desert urban areas.
ContributorsVolo, Thomas J (Author) / Vivoni, Enrique R (Thesis advisor) / Ruddell, Benjamin L (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2013
Description
The Colorado River Basin (CRB) is the primary source of water in the
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
ContributorsGautam, Jenita (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2018
Description
The increasingly recurrent extraordinary flood events in the metropolitan area of Monterrey, Mexico have led to significant stakeholder interest in understanding the hydrologic response of the Santa Catarina watershed to extreme events. This study analyzes a flood mitigation strategy proposed by stakeholders through a participatory workshop and are assessed using two hydrological models: The Hydrological Modeling System (HEC-HMS) and the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS).
The stakeholder-derived flood mitigation strategy consists of placing new hydraulic infrastructure in addition to the current flood controls in the basin. This is done by simulating three scenarios: (1) evaluate the impact of the current structure, (2) implementing a large dam similar to the Rompepicos dam and (3) the inclusion of three small detention dams. These mitigation strategies are assessed in the context of a major flood event caused by the landfall of Hurricane Alex in July 2010 through a consistent application of the two modeling tools. To do so, spatial information on topography, soil, land cover and meteorological forcing were assembled, quality-controlled and input into each model. Calibration was performed for each model based on streamflow observations and maximum observed reservoir levels from the National Water Commission in Mexico.
Simulation analyses focuses on the differential capability of the two models in capturing the spatial variability in rainfall, topographic conditions, soil hydraulic properties and its effect on the flood response in the presence of the different flood mitigation structures. The implementation of new hydraulic infrastructure is shown to have a positive impact on mitigating the flood peak with a more favorable reduction in the peak at the outlet from the larger dam (16.5% in tRIBS and 23% in HEC-HMS) than the collective effect from the small structures (12% in tRIBS and 10% in HEC-HMS). Furthermore, flood peak mitigation depends strongly on the number and locations of the new dam sites in relation to the spatial distribution of rainfall and flood generation. Comparison of the two modeling approaches complements the analysis of available observations for the flood event and provides a framework within which to derive a multi-model approach for stakeholder-driven solutions.
The stakeholder-derived flood mitigation strategy consists of placing new hydraulic infrastructure in addition to the current flood controls in the basin. This is done by simulating three scenarios: (1) evaluate the impact of the current structure, (2) implementing a large dam similar to the Rompepicos dam and (3) the inclusion of three small detention dams. These mitigation strategies are assessed in the context of a major flood event caused by the landfall of Hurricane Alex in July 2010 through a consistent application of the two modeling tools. To do so, spatial information on topography, soil, land cover and meteorological forcing were assembled, quality-controlled and input into each model. Calibration was performed for each model based on streamflow observations and maximum observed reservoir levels from the National Water Commission in Mexico.
Simulation analyses focuses on the differential capability of the two models in capturing the spatial variability in rainfall, topographic conditions, soil hydraulic properties and its effect on the flood response in the presence of the different flood mitigation structures. The implementation of new hydraulic infrastructure is shown to have a positive impact on mitigating the flood peak with a more favorable reduction in the peak at the outlet from the larger dam (16.5% in tRIBS and 23% in HEC-HMS) than the collective effect from the small structures (12% in tRIBS and 10% in HEC-HMS). Furthermore, flood peak mitigation depends strongly on the number and locations of the new dam sites in relation to the spatial distribution of rainfall and flood generation. Comparison of the two modeling approaches complements the analysis of available observations for the flood event and provides a framework within which to derive a multi-model approach for stakeholder-driven solutions.
ContributorsCázares Rodríguez, Jorge E (Author) / Vivoni, Enrique (Thesis advisor) / Wang, Zhihua (Committee member) / Mays, Larry W. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Bioretention basins are a common stormwater best management practice (BMP) used to mitigate the hydrologic consequences of urbanization. Dry wells, also known as vadose-zone wells, have been used extensively in bioretention basins in Maricopa County, Arizona to decrease total drain time and recharge groundwater. A mixed integer nonlinear programming (MINLP) model has been developed for the minimum cost design of bioretention basins with dry wells.
The model developed simultaneously determines the peak stormwater inflow from watershed parameters and optimizes the size of the basin and the number and depth of dry wells based on infiltration, evapotranspiration (ET), and dry well characteristics and cost inputs. The modified rational method is used for the design storm hydrograph, and the Green-Ampt method is used for infiltration. ET rates are calculated using the Penman Monteith method or the Hargreaves-Samani method. The dry well flow rate is determined using an equation developed for reverse auger-hole flow.
The first phase of development of the model is to expand a nonlinear programming (NLP) for the optimal design of infiltration basins for use with bioretention basins. Next a single dry well is added to the NLP bioretention basin optimization model. Finally the number of dry wells in the basin is modeled as an integer variable creating a MINLP problem. The NLP models and MINLP model are solved using the General Algebraic Modeling System (GAMS). Two example applications demonstrate the efficiency and practicality of the model.
The model developed simultaneously determines the peak stormwater inflow from watershed parameters and optimizes the size of the basin and the number and depth of dry wells based on infiltration, evapotranspiration (ET), and dry well characteristics and cost inputs. The modified rational method is used for the design storm hydrograph, and the Green-Ampt method is used for infiltration. ET rates are calculated using the Penman Monteith method or the Hargreaves-Samani method. The dry well flow rate is determined using an equation developed for reverse auger-hole flow.
The first phase of development of the model is to expand a nonlinear programming (NLP) for the optimal design of infiltration basins for use with bioretention basins. Next a single dry well is added to the NLP bioretention basin optimization model. Finally the number of dry wells in the basin is modeled as an integer variable creating a MINLP problem. The NLP models and MINLP model are solved using the General Algebraic Modeling System (GAMS). Two example applications demonstrate the efficiency and practicality of the model.
ContributorsLacy, Mason (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2016
Description
Vegetative filter strips (VFS) are an effective methodology used for storm water management particularly for large urban parking lots. An optimization model for the design of vegetative filter strips that minimizes the amount of land required for stormwater management using the VFS is developed in this study. The resulting optimization model is based upon the kinematic wave equation for overland sheet flow along with equations defining the cumulative infiltration and infiltration rate.
In addition to the stormwater management function, Vegetative filter strips (VFS) are effective mechanisms for control of sediment flow and soil erosion from agricultural and urban lands. Erosion is a major problem associated with areas subjected to high runoffs or steep slopes across the globe. In order to effect economy in the design of grass filter strips as a mechanism for sediment control & stormwater management, an optimization model is required that minimizes the land requirements for the VFS. The optimization model presented in this study includes an intricate system of equations including the equations defining the sheet flow on the paved and grassed area combined with the equations defining the sediment transport over the vegetative filter strip using a non-linear programming optimization model. In this study, the optimization model has been applied using a sensitivity analysis of parameters such as different soil types, rainfall characteristics etc., performed to validate the model
In addition to the stormwater management function, Vegetative filter strips (VFS) are effective mechanisms for control of sediment flow and soil erosion from agricultural and urban lands. Erosion is a major problem associated with areas subjected to high runoffs or steep slopes across the globe. In order to effect economy in the design of grass filter strips as a mechanism for sediment control & stormwater management, an optimization model is required that minimizes the land requirements for the VFS. The optimization model presented in this study includes an intricate system of equations including the equations defining the sheet flow on the paved and grassed area combined with the equations defining the sediment transport over the vegetative filter strip using a non-linear programming optimization model. In this study, the optimization model has been applied using a sensitivity analysis of parameters such as different soil types, rainfall characteristics etc., performed to validate the model
ContributorsKhatavkar, Puneet N (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Wang, Zhihua (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2015
Description
A model is presented for real-time, river-reservoir operation systems. It epitomizes forward-thinking and efficient approaches to reservoir operations during flooding events. The optimization/simulation includes five major components. The components are a mix of hydrologic and hydraulic modeling, short-term rainfall forecasting, and optimization and reservoir operation models. The optimization/simulation model is designed for ultimate accessibility and efficiency. The optimization model uses the meta-heuristic approach, which has the capability to simultaneously search for multiple optimal solutions. The dynamics of the river are simulated by applying an unsteady flow-routing method. The rainfall-runoff simulation uses the National Weather Service NexRad gridded rainfall data, since it provides critical information regarding real storm events. The short-term rainfall-forecasting model utilizes a stochastic method. The reservoir-operation is simulated by a mass-balance approach. The optimization/simulation model offers more possible optimal solutions by using the Genetic Algorithm approach as opposed to traditional gradient methods that can only compute one optimal solution at a time. The optimization/simulation was developed for the 2010 flood event that occurred in the Cumberland River basin in Nashville, Tennessee. It revealed that the reservoir upstream of Nashville was more contained and that an optimal gate release schedule could have significantly decreased the floodwater levels in downtown Nashville. The model is for demonstrative purposes only but is perfectly suitable for real-world application.
ContributorsChe, Daniel C (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Wang, Zhihua (Committee member) / Lansey, Kevin (Committee member) / Wahlin, Brian (Committee member) / Arizona State University (Publisher)
Created2015