Matching Items (43)
Description
This dissertation creates models of past potential vegetation in the Southern Levant during most of the Holocene, from the beginnings of farming through the rise of urbanized civilization (12 to 2.5 ka BP). The time scale encompasses the rise and collapse of the earliest agrarian civilizations in this region. The archaeological record suggests that increases in social complexity were linked to climatic episodes (e.g., favorable climatic conditions coincide with intervals of prosperity or marked social development such as the Neolithic Revolution ca. 11.5 ka BP, the Secondary Products Revolution ca. 6 ka BP, and the Middle Bronze Age ca. 4 ka BP). The opposite can be said about periods of climatic deterioration, when settled villages were abandoned as the inhabitants returned to nomadic or semi nomadic lifestyles (e.g., abandonment of the largest Neolithic farming towns after 8 ka BP and collapse of Bronze Age towns and cities after 3.5 ka BP during the Late Bronze Age). This study develops chronologically refined models of past vegetation from 12 to 2.5 ka BP, at 500 year intervals, using GIS, remote sensing and statistical modeling tools (MAXENT) that derive from species distribution modeling. Plants are sensitive to alterations in their environment and respond accordingly. Because of this, they are valuable indicators of landscape change. An extensive database of historical and field gathered observations was created. Using this database as well as environmental variables that include temperature and precipitation surfaces for the whole study period (also at 500 year intervals), the potential vegetation of the region was modeled. Through this means, a continuous chronology of potential vegetation of the Southern Levantwas built. The produced paleo-vegetation models generally agree with the proxy records. They indicate a gradual decline of forests and expansion of steppe and desert throughout the Holocene, interrupted briefly during the Mid Holocene (ca. 4 ka BP, Middle Bronze Age). They also suggest that during the Early Holocene, forest areas were extensive, spreading into the Northern Negev. The two remaining forested areas in the Northern and Southern Plateau Region in Jordan were also connected during this time. The models also show general agreement with the major cultural developments, with forested areas either expanding or remaining stable during prosperous periods (e.g., Pre Pottery Neolithic and Middle Bronze Age), and significantly contracting during moments of instability (e.g., Late Bronze Age).
ContributorsSoto-Berelov, Mariela (Author) / Fall, Patricia L. (Thesis advisor) / Myint, Soe (Committee member) / Turner, Billie L (Committee member) / Falconer, Steven (Committee member) / Arizona State University (Publisher)
Created2011
Description
Two critical limitations for hyperspatial imagery are higher imagery variances and large data sizes. Although object-based analyses with a multi-scale framework for diverse object sizes are the solution, more data sources and large amounts of testing at high costs are required. In this study, I used tree density segmentation as the key element of a three-level hierarchical vegetation framework for reducing those costs, and a three-step procedure was used to evaluate its effects. A two-step procedure, which involved environmental stratifications and the random walker algorithm, was used for tree density segmentation. I determined whether variation in tone and texture could be reduced within environmental strata, and whether tree density segmentations could be labeled by species associations. At the final level, two tree density segmentations were partitioned into smaller subsets using eCognition in order to label individual species or tree stands in two test areas of two tree densities, and the Z values of Moran's I were used to evaluate whether imagery objects have different mean values from near segmentations as a measure of segmentation accuracy. The two-step procedure was able to delineating tree density segments and label species types robustly, compared to previous hierarchical frameworks. However, eCognition was not able to produce detailed, reasonable image objects with optimal scale parameters for species labeling. This hierarchical vegetation framework is applicable for fine-scale, time-series vegetation mapping to develop baseline data for evaluating climate change impacts on vegetation at low cost using widely available data and a personal laptop.
ContributorsLiau, Yan-ting (Author) / Franklin, Janet (Thesis advisor) / Turner, Billie (Committee member) / Myint, Soe (Committee member) / Arizona State University (Publisher)
Created2013
Description
Land transformation under conditions of rapid urbanization has significantly altered the structure and functioning of Earth's systems. Land fragmentation, a characteristic of land transformation, is recognized as a primary driving force in the loss of biological diversity worldwide. However, little is known about its implications in complex urban settings where interaction with social dynamics is intense. This research asks: How do patterns of land cover and land fragmentation vary over time and space, and what are the socio-ecological drivers and consequences of land transformation in a rapidly growing city? Using Metropolitan Phoenix as a case study, the research links pattern and process relationships between land cover, land fragmentation, and socio-ecological systems in the region. It examines population growth, water provision and institutions as major drivers of land transformation, and the changes in bird biodiversity that result from land transformation. How to manage socio-ecological systems is one of the biggest challenges of moving towards sustainability. This research project provides a deeper understanding of how land transformation affects socio-ecological dynamics in an urban setting. It uses a series of indices to evaluate land cover and fragmentation patterns over the past twenty years, including land patch numbers, contagion, shapes, and diversities. It then generates empirical evidence on the linkages between land cover patterns and ecosystem properties by exploring the drivers and impacts of land cover change. An interdisciplinary approach that integrates social, ecological, and spatial analysis is applied in this research. Findings of the research provide a documented dataset that can help researchers study the relationship between human activities and biotic processes in an urban setting, and contribute to sustainable urban development.
ContributorsZhang, Sainan (Author) / Boone, Christopher G. (Thesis advisor) / York, Abigail M. (Committee member) / Myint, Soe (Committee member) / Arizona State University (Publisher)
Created2013
Description
Ponderosa pine forests are a dominant land cover type in semiarid montane areas. Water supplies in major rivers of the southwestern United States depend on ponderosa pine forests since these ecosystems: (1) receive a significant amount of rainfall and snowfall, (2) intercept precipitation and transpire water, and (3) indirectly influence runoff by impacting the infiltration rate. However, the hydrologic patterns in these ecosystems with strong seasonality are poorly understood. In this study, we used a distributed hydrologic model evaluated against field observations to improve our understandings on spatial controls of hydrologic patterns, appropriate model resolution to simulate ponderosa pine ecosystems and hydrologic responses in the context of contrasting winter to summer transitions. Our modeling effort is focused on the hydrologic responses during the North American Monsoon (NAM), winter and spring periods. In Chapter 2, we utilized a distributed model explore the spatial controls on simulated soil moisture and temporal evolution of these spatial controls as a function of seasonal wetness. Our findings indicate that vegetation and topographic curvature are spatial controls. Vegetation controlled patterns during dry summer period switch to fine-scale terrain curvature controlled patterns during persistently wet NAM period. Thus, a climatic threshold involving rainfall and weather conditions during the NAM is identified when high rainfall amount (such as 146 mm rain in August, 1997) activates lateral flux of soil moisture and frequent cloudy cover (such as 42% cloud cover during daytime of August, 1997) lowers evapotranspiration. In Chapter 3, we investigate the impacts of model coarsening on simulated soil moisture patterns during the NAM. Results indicate that model aggregation quickly eradicates curvature features and its spatial control on hydrologic patterns. A threshold resolution of ~10% of the original terrain is identified through analyses of homogeneity indices, correlation coefficients and spatial errors beyond which the fidelity of simulated soil moisture is no longer reliable. Based on spatial error analyses, we detected that the concave areas (~28% of hillslope) are very sensitive to model coarsening and root mean square error (RMSE) is higher than residual soil moisture content (~0.07 m3/m3 soil moisture) for concave areas. Thus, concave areas need to be sampled for capturing appropriate hillslope response for this hillslope. In Chapter 4, we investigate the impacts of contrasting winter to summer transitions on hillslope hydrologic responses. We use a distributed hydrologic model to generate a consistent set of high-resolution hydrologic estimates. Our model is evaluated against the snow depth, soil moisture and runoff observations over two water years yielding reliable spatial distributions during the winter to summer transitions. We find that a wet winter followed by a dry summer promotes evapotranspiration losses (spatial averaged ~193 mm spring ET and ~ 600 mm summer ET) that dry the soil and disconnect lateral fluxes in the forested hillslope, leading to soil moisture patterns resembling vegetation patches. Conversely, a dry winter prior to a wet summer results in soil moisture increases due to high rainfall and low ET during the spring (spatially averaged 78 mm ET and 232 mm rainfall) and summer period (spatially averaged 147 mm ET and 247 mm rainfall) which promote lateral connectivity and soil moisture patterns with the signature of terrain curvature. An opposing temporal switch between infiltration and saturation excess runoff is also identified. These contrasting responses indicate that the inverse relation has significant consequences on hillslope water availability and its spatial distribution with implications on other ecohydrological processes including vegetation phenology, groundwater recharge and geomorphic development. Results from this work have implications on the design of hillslope experiments, the resolution of hillslope scale models, and the prediction of hydrologic conditions in ponderosa pine ecosystems. In addition, our findings can be used to select future hillslope sites for detailed ecohydrological investigations. Further, the proposed methodology can be useful for predicting responses to climate and land cover changes that are anticipated for the southwestern United States.
ContributorsMahmood, Taufique Hasan (Author) / Vivoni, Enrique R. (Thesis advisor) / Whipple, Kelin X. (Committee member) / Shock, Everett (Committee member) / Heimsath, Arjun M. (Committee member) / Ruddell, Benjamin (Committee member) / Arizona State University (Publisher)
Created2012
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, 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
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 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
Description
Problem: The prospect that urban heat island (UHI) effects and climate change may increase urban temperatures is a problem for cities that actively promote urban redevelopment and higher densities. One possible UHI mitigation strategy is to plant more trees and other irrigated vegetation to prevent daytime heat storage and facilitate nighttime cooling, but this requires water resources that are limited in a desert city like Phoenix.
Purpose: We investigated the tradeoffs between water use and nighttime cooling inherent in urban form and land use choices.
Methods: We used a Local-Scale Urban Meteorological Parameterization Scheme (LUMPS) model to examine the variation in temperature and evaporation in 10 census tracts in Phoenix's urban core. After validating results with estimates of outdoor water use based on tract-level city water records and satellite imagery, we used the model to simulate the temperature and water use consequences of implementing three different scenarios.
Results and conclusions: We found that increasing irrigated landscaping lowers nighttime temperatures, but this relationship is not linear; the greatest reductions occur in the least vegetated neighborhoods. A ratio of the change in water use to temperature impact reached a threshold beyond which increased outdoor water use did little to ameliorate UHI effects.
Takeaway for practice: There is no one design and landscape plan capable of addressing increasing UHI and climate effects everywhere. Any one strategy will have inconsistent results if applied across all urban landscape features and may lead to an inefficient allocation of scarce water resources.
Research Support: This work was supported by the National Science Foundation (NSF) under Grant SES-0345945 (Decision Center for a Desert City) and by the City of Phoenix Water Services Department. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF.
ContributorsGober, Patricia (Author) / Brazel, Anthony J. (Author) / Quay, Ray (Author) / Myint, Soe (Author) / Grossman-Clarke, Susanne (Author) / Miller, Adam (Author) / Rossi, Steve (Author)
Created2010-01-04
Description
This study addresses a classic sustainability challenge—the tradeoff between water conservation and temperature amelioration in rapidly growing cities, using Phoenix, Arizona and Portland, Oregon as case studies. An urban energy balance model— LUMPS (Local-Scale Urban Meteorological Parameterization Scheme)—is used to represent the tradeoff between outdoor water use and nighttime cooling during hot, dry summer months. Tradeoffs were characterized under three scenarios of land use change and three climate-change assumptions. Decreasing vegetation density reduced outdoor water use but sacrificed nighttime cooling. Increasing vegetated surfaces accelerated nighttime cooling, but increased outdoor water use by ~20%. Replacing impervious surfaces with buildings achieved similar improvements in nighttime cooling with minimal increases in outdoor water use; it was the most water-efficient cooling strategy. The fact that nighttime cooling rates and outdoor water use were more sensitive to land use scenarios than climate-change simulations suggested that cities can adapt to a warmer climate by manipulating land use.
ContributorsGober, Patricia (Author) / Middel, Ariane (Author) / Brazel, Anthony J. (Author) / Myint, Soe (Author) / Chang, Heejun (Author) / Duh, Jiunn-Der (Author) / House-Peters, Lily (Author)
Created2013-05-16
Description
Pathogenic contamination is a significant factor contributing to the degradation of surface water both globally and within the United States. This leads to negative economic impacts, sickness, and, in severe cases, fatalities. As the world's population grows, pollution increases, placing more stress on water resources, particularly in arid regions. The situation is made worse by climate change. The forecasted expansion of arid and semi-arid land areas and alterations in precipitation patterns could have a significant impact on those living in poverty and dry regions. This dissertation aims to investigate previously undocumented threats to water quality through understanding pathogen drivers in arid and semi-arid environments and documenting wastewater infrastructure on Tribal lands. Specifically, I first investigated how ephemeral streams (common in arid and semiarid areas) impact the presence of pathogens in surface waters by identifying the main drivers of E. coli concentration from a series of proposed predictors. Second, I identified unknown potential sources of water quality impairments on Tribal lands, which are mainly rural and in arid or semiarid areas, focusing on wastewater infrastructure in these systems. I specifically quantified populations served by wastewater treatment plants and then used a remote sensing approach to identify possible unpermitted wastewater lagoons that often serve as the only wastewater infrastructure in some areas. The findings revealed unique insights that could help aid water management in arid and semiarid regions as well as in rural areas.
ContributorsMenchu Maldonado, Maria Elena (Author) / Muenich, Rebecca L. (Thesis advisor) / Vivoni, Enrique R. (Committee member) / Conroy-Ben, Otakuye (Committee member) / Hamilton, Kerry (Committee member) / Arizona State University (Publisher)
Created2023
Description
The fast pace of global urbanization makes cities the hotspots of population density and anthropogenic activities, leading to intensive emissions of heat and carbon dioxide (CO2), a primary greenhouse gas. Urban climate scientists have been actively seeking effective mitigation strategies over the past decades, aiming to improve the environmental quality for urban dwellers. Prior studies have identified the role of urban green spaces in the relief of urban heat stress. Yet little effort was devoted to quantify their contribution to local and regional CO2 budget. In fact, urban biogenic CO2 fluxes from photosynthesis and respiration are influenced by the microclimate in the built environment and are sensitive to anthropogenic disturbance. The high complexity of the urban ecosystem leads to an outstanding challenge for numerical urban models to disentangling and quantifying the interplay between heat and carbon dynamics.This dissertation aims to advance the simulation of thermal and carbon dynamics in urban land surface models, and to investigate the role of urban greening practices and urban system design in mitigating heat and CO2 emissions. The biogenic CO2 exchange in cities is parameterized by incorporating plant physiological functions into an advanced single-layer urban canopy model in the built environment. The simulation result replicates the microclimate and CO2 flux patterns measured from an eddy covariance system over a residential neighborhood in Phoenix, Arizona with satisfactory accuracy. Moreover, the model decomposes the total CO2 flux from observation and identifies the significant CO2 efflux from soil respiration. The model is then applied to quantify the impact of urban greening practices on heat and biogenic CO2 exchange over designed scenarios. The result shows the use of urban greenery is effective in mitigating both urban heat and carbon emissions, providing environmental co-benefit in cities. Furthermore, to seek the optimal urban system design in terms of thermal comfort and CO2 reduction, a multi-objective optimization algorithm is applied to the machine learning surrogates of the physical urban land surface model. There are manifest trade-offs among ameliorating diverse urban environmental indicators despite the co-benefit from urban greening. The findings of this dissertation, along with its implications on urban planning and landscaping management, would promote sustainable urban development strategies for achieving optimal environmental quality for policy makers, urban residents, and practitioners.
ContributorsLi, Peiyuan (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Myint, Soe (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2021