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- All Subjects: Climate Change
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
Approximately 71% of the great lakes, lakes, reservoirs, and ponds, together with 51% of rivers and streams assessed in the US are impaired or threatened by pollution or do not meet the minimum water quality requirements. Pathogens, sediments, and nutrients are leading causes of impairment, with agriculture being a top source of pollution. Agricultural pollution has become a global concern overtaking urban contamination as the major factor of inland and coastal waters degradation in many parts of the world. High-yielding crop production has been achieved by the intensive use of inorganic fertilizers that are mainly composed of Nitrogen (N) and Phosphorus (P). N and P are essential nutrients for ecosystem structure, processes, and functions. However, N and P in excess can be problematic to the environment. One of the major impacts of the increasing amount of these nutrients in the environment is the global expansion of harmful algal blooms (HABs). Major agricultural nutrient pollution sources and climate change can exacerbate these risks. This dissertation aims to guide future policies to mitigate issues linked to excess nutrient loads in the U.S. by evaluating the impact of climate change on nutrient loads and assessing the environmental impact as well as the spatial patterns of one of the major agricultural sources of nutrient pollution - Concentrated Animal Feeding Operations (CAFOs). Specifically, I first investigated the impact of bias correction techniques when modeling mid-century nutrient loads in a watershed heavily impacted by CAFOs. Second, I evaluated the role of CAFOs in land use change and subsequent environmental degradation of the surrounding environment. Finally, I assessed the spatial organization of CAFOs and its links to water quality conditions. The findings revealed unique insights for future nutrient management strategies in the U.S.
ContributorsMiralha, Lorrayne (Author) / Muenich, Rebecca L. (Thesis advisor) / Garcia, Margaret (Committee member) / Xu, Tianfang (Committee member) / Myint, Soe W. (Committee member) / Arizona State University (Publisher)
Created2021
Description
Nonlinear responses in the dynamics of climate system could be triggered by small change of forcing. Interactions between different components of Earth’s climate system are believed to cause abrupt and catastrophic transitions, of which anthropogenic forcing is a major and the most irreversible driver. Meantime, in the face of global climate change, extreme climatic events, such as extreme precipitations, heatwaves, droughts, etc., are projected to be more frequent, more intense, and longer in duration. These nonlinear responses in climate dynamics from tipping points to extreme events pose serious threats to human society on a large scale. Understanding the physical mechanisms behind them has potential to reduce related risks through different ways. The overarching objective of this dissertation is to quantify complex interactions, detect tipping points, and explore propagations of extreme events in the hydroclimate system from a new structure-based perspective, by integrating climate dynamics, causal inference, network theory, spectral analysis, and machine learning. More specifically, a network-based framework is developed to find responses of hydroclimate system to potential critical transitions in climate. Results show that system-based early warning signals towards tipping points can be located successfully, demonstrated by enhanced connections in the network topology. To further evaluate the long-term nonlinear interactions among the U.S. climate regions, causality inference is introduced and directed complex networks are constructed from climatology records over one century. Causality networks reveal that the Ohio valley region acts as a regional gateway and mediator to the moisture transport and thermal transfer in the U.S. Furthermore, it is found that cross-regional causality variability manifests intrinsic frequency ranging from interannual to interdecadal scales, and those frequencies are associated with the physics of climate oscillations. Besides the long-term climatology, this dissertation also aims to explore extreme events from the system-dynamic perspective, especially the contributions of human-induced activities to propagation of extreme heatwaves in the U.S. cities. Results suggest that there are long-range teleconnections among the U.S. cities and supernodes in heatwave spreading. Findings also confirm that anthropogenic activities contribute to extreme heatwaves by the fact that causality during heatwaves is positively associated with population in megacities.
ContributorsYang, Xueli (Author) / Yang, Zhihua (Thesis advisor) / Lai, Ying-Cheng (Committee member) / Li, Qi (Committee member) / Xu, Tianfang (Committee member) / Zeng, Ruijie (Committee member) / Arizona State University (Publisher)
Created2023