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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

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
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Description
Woody plant encroachment is a worldwide phenomenon linked to water availability in semiarid systems. Nevertheless, the implications of woody plant encroachment on the hydrologic cycle are poorly understood, especially at the catchment scale. This study takes place in a pair of small semiarid rangeland undergoing the encroachment of Prosopis velutina

Woody plant encroachment is a worldwide phenomenon linked to water availability in semiarid systems. Nevertheless, the implications of woody plant encroachment on the hydrologic cycle are poorly understood, especially at the catchment scale. This study takes place in a pair of small semiarid rangeland undergoing the encroachment of Prosopis velutina Woot., or velvet mesquite tree. The similarly-sized basins are in close proximity, leading to equivalent meteorological and soil conditions. One basin was treated for mesquite in 1974, while the other represents the encroachment process. A sensor network was installed to measure ecohydrological states and fluxes, including precipitation, runoff, soil moisture and evapotranspiration. Observations from June 1, 2011 through September 30, 2012 are presented to describe the seasonality and spatial variability of ecohydrological conditions during the North American Monsoon (NAM). Runoff observations are linked to historical changes in runoff production in each watershed. Observations indicate that the mesquite-treated basin generates more runoff pulses and greater runoff volume for small rainfall events, while the mesquite-encroached basin generates more runoff volume for large rainfall events. A distributed hydrologic model is applied to both basins to investigate the runoff threshold processes experienced during the NAM. Vegetation in the two basins is classified into grass, mesquite, or bare soil using high-resolution imagery. Model predictions are used to investigate the vegetation controls on soil moisture, evapotranspiration, and runoff generation. The distributed model shows that grass and mesquite sites retain the highest levels of soil moisture. The model also captures the runoff generation differences between the two watersheds that have been observed over the past decade. Generally, grass sites in the mesquite-treated basin have less plant interception and evapotranspiration, leading to higher soil moisture that supports greater runoff for small rainfall events. For large rainfall events, the mesquite-encroached basin produces greater runoff due to its higher fraction of bare soil. The results of this study show that a distributed hydrologic model can be used to explain runoff threshold processes linked to woody plant encroachment at the catchment-scale and provides useful interpretations for rangeland management in semiarid areas.
ContributorsPierini, Nicole A (Author) / Vivoni, Enrique R (Thesis advisor) / Wang, Zhi-Hua (Committee member) / Mays, Larry W. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level.

Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
ContributorsRiaño, Alejandro (Author) / Mays, Larry W. (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Land-atmosphere interactions of semiarid shrublands have garnered significant scientific interest. One of the main tools used for this research is the eddy covariance (EC) method, which measures fluxes of energy, water vapor, and carbon dioxide. EC fluxes can be difficult to interpret due to complexities within the EC footprint (i.e.

Land-atmosphere interactions of semiarid shrublands have garnered significant scientific interest. One of the main tools used for this research is the eddy covariance (EC) method, which measures fluxes of energy, water vapor, and carbon dioxide. EC fluxes can be difficult to interpret due to complexities within the EC footprint (i.e. the surface conditions that contribute to the flux measurements). Most EC studies use a small number of soil probes to estimate the land surface states underlying the measured fluxes, which likely undersamples the footprint-scale conditions, especially in semiarid shrublands which are characterized by high spatial and temporal variability. In this study, I installed a dense network of soil moisture and temperature probe profiles in the footprint region of an EC tower at two semiarid sites: a woody savanna in southern Arizona and a mixed shrubland in southern New Mexico. For data from May to September 2013, I link land surface states to EC fluxes through daily footprints estimated using an analytical model. Novel approaches are utilized to partition evapotranspiration, estimate EC footprint soil states, connect differences in fluxes to footprint composition, and assess key drivers behind soil state variability. I verify the hypothesis that a small number of soil probes poorly estimates the footprint conditions for soil moisture, due to its high spatial variability. Soil temperature, however, behaves more consistently in time and space. As such, distributed surface measurements within the EC footprint allow for stronger ties between evapotranspiration and moisture, but demonstrate no significant improvement in connecting sensible heat flux and temperature. I also find that in these systems vegetation cover appears to have stronger controls on soil moisture and temperature than does soil texture. Further, I explore the influence of footprint vegetation composition on the measured fluxes, which reveals that during the monsoon season evaporative fraction tends to increase with footprint bare soil coverage for the New Mexico site and that the ratio of daily transpiration to evapotranspiration increases with grass coverage at the Arizona site. The thesis results are useful for understanding the land-atmosphere interactions of these ecosystems and for guiding future EC studies in heterogeneous landscapes.
ContributorsAnderson, Cody Alan (Author) / Vivoni, Enrique R (Thesis advisor) / Wang, Zhihua (Committee member) / Mays, Larry W. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The North American Monsoon (NAM) is characterized by high inter- and intra-seasonal variability, and potential climate change effects have been forecasted to increase this variability. The potential effects of climate change to the hydrology of the southwestern U.S. is of interest as they could have consequences to water resources, floods,

The North American Monsoon (NAM) is characterized by high inter- and intra-seasonal variability, and potential climate change effects have been forecasted to increase this variability. The potential effects of climate change to the hydrology of the southwestern U.S. is of interest as they could have consequences to water resources, floods, and land management. I applied a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, and soils distribution. As such, it can serve to illustrate the utility of distributed models for change assessment studies. Model calibration was performed utilizing radar-based NEXRAD data, and comparisons were done to two additional sources of precipitation data: ground-based stations and the North American Land Data Assimilation System (NLDAS). Comparisons focus on the spatiotemporal distributions of precipitation and stream discharge. Utilizing the calibrated model, I applied scenarios from the HadCM3 General Circulation Model (GCM) which was dynamically downscaled by the Weather Research and Forecast (WRF) model, to refine the representation of Arizona's regional climate. Two time periods were examined, a historical 1990-2000 and a future 2031-2040, to evaluate the hydrologic consequence in the form of differences and similarities between the decadal averages for temperature, precipitation, stream discharge and evapotranspiration. Results indicate an increase in mean air temperature over the basin by 1.2 ºC. The average decadal precipitation amounts increased between the two time periods by 2.4 times that of the historical period and had an increase in variability that was 3 times the historical period. For the future period, modeled streamflow discharge in the summer increased by a factor of 3. There was no significant change in the average evapotranspiration (ET). Overall trends of increase precipitation and variability for future climate scenarios have a more significant effect on the hydrologic response than temperature increases in the system during NAM in this study basin. The results from this study suggest that water management in the Beaver Creek will need to adapt to higher summer streamflow amounts.
ContributorsHawkins, Gretchen (Author) / Vivoni, Enrique R. (Thesis advisor) / Semken, Steven (Committee member) / Mays, Larry W. (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This doctoral thesis investigates the predictability characteristics of floods and flash floods by coupling high resolution precipitation products to a distributed hydrologic model. The research hypotheses are tested at multiple watersheds in the Colorado Front Range (CFR) undergoing warm-season precipitation. Rainfall error structures are expected to propagate into hydrologic simulations

This doctoral thesis investigates the predictability characteristics of floods and flash floods by coupling high resolution precipitation products to a distributed hydrologic model. The research hypotheses are tested at multiple watersheds in the Colorado Front Range (CFR) undergoing warm-season precipitation. Rainfall error structures are expected to propagate into hydrologic simulations with added uncertainties by model parameters and initial conditions. Specifically, the following science questions are addressed: (1) What is the utility of Quantitative Precipitation Estimates (QPE) for high resolution hydrologic forecasts in mountain watersheds of the CFR?, (2) How does the rainfall-reflectivity relation determine the magnitude of errors when radar observations are used for flood forecasts?, and (3) What are the spatiotemporal limits of flood forecasting in mountain basins when radar nowcasts are used into a distributed hydrological model?. The methodology consists of QPE evaluations at the site (i.e., rain gauge location), basin-average and regional scales, and Quantitative Precipitation Forecasts (QPF) assessment through regional grid-to-grid verification techniques and ensemble basin-averaged time series. The corresponding hydrologic responses that include outlet discharges, distributed runoff maps, and streamflow time series at internal channel locations, are used in light of observed and/or reference data to diagnose the suitability of fusing precipitation forecasts into a distributed model operating at multiple catchments. Results reveal that radar and multisensor QPEs lead to an improved hydrologic performance compared to simulations driven with rain gauge data only. In addition, hydrologic performances attained by satellite products preserve the fundamental properties of basin responses, including a simple scaling relation between the relative spatial variability of runoff and its magnitude. Overall, the spatial variations contained in gridded QPEs add value for warm-season flood forecasting in mountain basins, with sparse data even if those products contain some biases. These results are encouraging and open new avenues for forecasting in regions with limited access and sparse observations. Regional comparisons of different reflectivity -rainfall (Z-R) relations during three summer seasons, illustrated significant rainfall variability across the region. Consistently, hydrologic errors introduced by the distinct Z-R relations, are significant and proportional (in the log-log space) to errors in precipitation estimations and stream flow magnitude. The use of operational Z-R relations without prior calibration may lead to wrong estimation of precipitation, runoff magnitude and increased flood forecasting errors. This suggests that site-specific Z-R relations, prior to forecasting procedures, are desirable in complex terrain regions. Nowcasting experiments show the limits of flood forecasting and its dependence functions of lead time and basin scale. Across the majority of the basins, flood forecasting skill decays with lead time, but the functional relation depends on the interactions between watershed properties and rainfall characteristics. Both precipitation and flood forecasting skills are noticeably reduced for lead times greater than 30 minutes. Scale dependence of hydrologic forecasting errors demonstrates reduced predictability at intermediate-size basins, the typical scale of convective storm systems. Overall, the fusion of high resolution radar nowcasts and the convenient parallel capabilities of the distributed hydrologic model provide an efficient framework for generating accurate real-time flood forecasts suitable for operational environments.
ContributorsMoreno Ramirez, Hernan (Author) / Vivoni, Enrique R. (Thesis advisor) / Ruddell, Benjamin L. (Committee member) / Gochis, David J. (Committee member) / Mays, Larry W. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2012
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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

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.
ContributorsGautam, Jenita (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Soil moisture (θ) is a fundamental variable controlling the exchange of water and energy at the land surface. As a result, the characterization of the statistical properties of θ across multiple scales is essential for many applications including flood prediction, drought monitoring, and weather forecasting. Empirical evidences have demonstrated the

Soil moisture (θ) is a fundamental variable controlling the exchange of water and energy at the land surface. As a result, the characterization of the statistical properties of θ across multiple scales is essential for many applications including flood prediction, drought monitoring, and weather forecasting. Empirical evidences have demonstrated the existence of emergent relationships and scale invariance properties in θ fields collected from the ground and airborne sensors during intensive field campaigns, mostly in natural landscapes. This dissertation advances the characterization of these relations and statistical properties of θ by (1) analyzing the role of irrigation, and (2) investigating how these properties change in time and across different landscape conditions through θ outputs of a distributed hydrologic model. First, θ observations from two field campaigns in Australia are used to explore how the presence of irrigated fields modifies the spatial distribution of θ and the associated scale invariance properties. Results reveal that the impact of irrigation is larger in drier regions or conditions, where irrigation creates a drastic contrast with the surrounding areas. Second, a physically-based distributed hydrologic model is applied in a regional basin in northern Mexico to generate hyperresolution θ fields, which are useful to conduct analyses in regions and times where θ has not been monitored. For this aim, strategies are proposed to address data, model validation, and computational challenges associated with hyperresolution hydrologic simulations. Third, analyses are carried out to investigate whether the hyperresolution simulated θ fields reproduce the statistical and scaling properties observed from the ground or remote sensors. Results confirm that (i) the relations between spatial mean and standard deviation of θ derived from the model outputs are very similar to those observed in other areas, and (ii) simulated θ fields exhibit the scale invariance properties that are consistent with those analyzed from aircraft-derived estimates. The simulated θ fields are then used to explore the influence of physical controls on the statistical properties, finding that soil properties significantly affect spatial variability and multifractality. The knowledge acquired through this dissertation provides insights on θ statistical properties in regions and landscape conditions that were never investigated before; supports the refinement of the calibration of multifractal downscaling models; and contributes to the improvement of hyperresolution hydrologic modeling.
ContributorsKo, Ara (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique R. (Thesis advisor) / Myint, Soe (Committee member) / Wang, Zhihua (Committee member) / Muenich, Rebecca (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Land surface fluxes of energy and mass developed over heterogeneous mountain landscapes are fundamental to atmospheric processes. However, due to their high complexity and the lack of spatial observations, land surface processes and land-atmosphere interactions are not fully understood in mountain regions. This thesis investigates land surface processes and their

Land surface fluxes of energy and mass developed over heterogeneous mountain landscapes are fundamental to atmospheric processes. However, due to their high complexity and the lack of spatial observations, land surface processes and land-atmosphere interactions are not fully understood in mountain regions. This thesis investigates land surface processes and their impact on convective precipitation by conducting numerical modeling experiments at multiple scales over the North American Monsoon (NAM) region. Specifically, the following scientific questions are addressed: (1) how do land surface conditions evolve during the monsoon season, and what are their main controls?, (2) how do the diurnal cycles of surface energy fluxes vary during the monsoon season for the major ecosystems?, and (3) what are the impacts of surface soil moisture and vegetation condition on convective precipitation?

Hydrologic simulation using the TIN-based Real-time Integrated Basin Simulator (tRIBS) is firstly carried out to examine the seasonal evolution of land surface conditions. Results reveal that the spatial heterogeneity of land surface temperature and soil moisture increases dramatically with the onset of monsoon, which is related to seasonal changes in topographic and vegetation controls. Similar results are found at regional basin scale using the uncoupled WRF-Hydro model. Meanwhile, the diurnal cycles of surface energy fluxes show large variation between the major ecosystems. Differences in both the peak magnitude and peak timing of plant transpiration induce mesoscale heterogeneity in land surface conditions. Lastly, this dissertation examines the upscale effect of land surface heterogeneity on atmospheric condition through fully-coupled WRF-Hydro simulations. A series of process-based experiments were conducted to identify the pathways of soil moisture-rainfall feedback mechanism over the NAM region. While modeling experiments confirm the existence of positive soil moisture/vegetation-rainfall feedback, their exact pathways are slightly different. Interactions between soil moisture, vegetation cover, and rainfall through a series of land surface and atmospheric boundary layer processes highlight the strong land-atmosphere coupling in the NAM region, and have important implications on convective rainfall prediction. Overall, this dissertation advances the study of complex land surface processes over the NAM region, and made important contributions in linking complex hydrologic, ecologic and atmospheric processes through numerical modeling.
ContributorsXiang, Tiantian (Author) / Vivoni, Enrique R (Thesis advisor) / Gochis, David J (Committee member) / Huang, Huei-Ping (Committee member) / Mascaro, Giuseppe (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Rapid urbanization and population growth occurring in the cities of South Western

United States have led to significant modifications in its environment at local and

regional scales. Both local and regional climate changes are expected to have massive

impacts on the hydrology of Colorado River Basin (CRB), thereby accentuating the need

of study of

Rapid urbanization and population growth occurring in the cities of South Western

United States have led to significant modifications in its environment at local and

regional scales. Both local and regional climate changes are expected to have massive

impacts on the hydrology of Colorado River Basin (CRB), thereby accentuating the need

of study of hydro-climatic impacts on water resource management in this region. This

thesis is devoted to understanding the impact of land use and land cover (LULC) changes

on the local and regional hydroclimate, with the goal to address urban planning issues

and provide guidance for sustainable development.

In this study, three densely populated urban areas, viz. Phoenix, Las Vegas and

Denver in the CRB are selected to capture the various dimensions of the impacts of land

use changes on the regional hydroclimate in the entire CRB. Weather Research and

Forecast (WRF) model, incorporating the latest urban modeling system, is adopted for

regional climate modeling. Two major types of urban LULC changes are studied in this

Thesis: (1) incorporation of urban trees with their radiative cooling effect, tested in

Phoenix metropolitan, and (2) projected urban expansion in 2100 obtained from

Integrated Climate and Land Use Scenarios (ICLUS) developed by the US

Environmental Protection Agency for all three cities.

The results demonstrated prominent nocturnal cooling effect of due to radiative

shading effect of the urban trees for Phoenix reducing urban surface and air temperature

by about 2~9 °C and 1~5 °C respectively and increasing relative humidity by 10~20%

during an mean diurnal cycle. The simulations of urban growth in CRB demonstratedii

nocturnal warming of about 0.36 °C, 1.07 °C, and 0.94 °C 2m-air temperature and

comparatively insignificant change in daytime temperature, with the thermal environment

of Denver being the most sensitive the urban growth. The urban hydroclimatic study

carried out in the thesis assists in identifying both context specific and generalizable

relationships, patterns among the cities, and is expected to facilitate urban planning and

management in local (cities) and regional scales.
ContributorsUpreti, Ruby (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique R. (Committee member) / Mascaro, Giuseppe (Committee member) / White, Dave (Committee member) / Arizona State University (Publisher)
Created2017