Physical Sciences and Mathematics Commons^™

Uncertainty In Climatic Change Impacts On Multiscale Watershed Systems, Olga V. Tsvetkova

Open Access Dissertations

Uncertainty in climate change plays a major role in watershed systems. The increase in variability and intensity in temperature and precipitation affects hydrologic cycle in spatial and temporal dimensions. Predicting uncertainty in climate change impacts on watershed systems can help to understand future climate-induced risk on watershed systems and is essential for designing policies for mitigation and adaptation. Modeling the temporal patterns of uncertainties is assessed in the New England region for temperature and precipitation patterns over a long term. The regional uncertainty is modeled using Python scripting and GIS to analyze spatial patterns of climate change uncertainties over space …

Slides: What Does Climate Change Mean For Cold Water Fisheries, Stan Bradshaw

Water, Climate and Uncertainty: Implications for Western Water Law, Policy, and Management (Summer Conference, June 11-13)

1 page "Abstract" and 8 slides

Slides: Is There A Dust Bowl In Our Future?: Projections For The Eastern Rockies And Central Great Plains, Dennis Ojima

Water, Climate and Uncertainty: Implications for Western Water Law, Policy, and Management (Summer Conference, June 11-13)

Presenter: Dennis Ojima, Senior Research Scientist, Natural Resource Ecology Laboratory, Colorado State University (NREL/CSU)

30 slides

Slides: Future Water Availability In The West: Will There Be Enough?, Michael Dettinger

Water, Climate and Uncertainty: Implications for Western Water Law, Policy, and Management (Summer Conference, June 11-13)

Presenter: Michael Dettinger, USGS, Scripps Institution of Oceanography, La Jolla, CA

30 slides

"with contributions from Julio Betancourt, Dan Cayan, & others"

Slides: A History Of Climate Variability And Change In The American West, Kelly T. Redmond

Water, Climate and Uncertainty: Implications for Western Water Law, Policy, and Management (Summer Conference, June 11-13)

Presenter: Kelly T. Redmond, Regional Climatologist, Western Regional Climate Center (WRCC), Desert Research Institute

65 slides

Source And Magnitude Of Error In An Inexpensive Image-Based Water Level Measurement System, Troy E. Gilmore, François Birgand, Kenneth W. Chapman

School of Natural Resources: Faculty Publications

Recent technological advances have opened the possibility to use webcams and images as part of the environmental monitoring arsenal. The potential sources and magnitude of uncertainties inherent to an image-based water level measurement system are evaluated in an experimental design in the laboratory. Sources of error investigated include image resolution, lighting effects, perspective, lens distortion and water meniscus. Image resolution and meniscus were found to weigh the most in the overall uncertainty of this system. Image distortion, although largely taken into account by the software developed, may also significantly add to uncertainty. Results suggest that ‘‘flat’’ images with little distortion …

Confronting Socially Generated Uncertainty In Adaptive Management, Andrew J. Tyre, Sarah Michaels

Andrew J Tyre

As more and more organizations with responsibility for natural resource management adopt adaptive management as the rubric in which they wish to operate, it becomes increasingly important to consider the sources of uncertainty inherent in their endeavors. Without recognizing that uncertainty originates both in the natural world and in human undertakings, efforts to manage adaptively at the least will prove frustrating and at the worst will prove damaging to the very natural resources that are the management targets. There will be more surprises and those surprises potentially may prove at the very least unwanted and at the worst devastating. We …

Evaluating The Efficacy Of Adaptive Management Approaches: Is There A Formula For Success?, Jamie E. Mcfadden, Tim L. Hiller, Andrew J. Tyre

Andrew J Tyre

Within the field of natural-resources management, the application of adaptive management is appropriate for complex problems high in uncertainty. Adaptive management is becoming an increasingly popular management-decision tool within the scientific community and has developed into two primary schools of thought: the Resilience-Experimentalist School (with high emphasis on stakeholder involvement, resilience, and highly complex models) and the Decision-Theoretic School (which results in relatively simple models through emphasizing stakeholder involvement for identifying management objectives). Because of these differences, adaptive management plans implemented under each of these schools may yield varying levels of success. We evaluated peer-reviewed literature focused on incorporation of …

The Agricultural Model Intercomparison And Improvement Project (Agmip): Protocols And Pilot Studies, Cynthia Rosenzweig, J. W. Jones, J. L. Hatfield, Alex Ruane, K. J. Thornburn, J. M. Antle, G. C. Nelson, C. Porter, S. Janssen, B. Basso, F. Ewert, D. Wallach, G. Baigorria, J. M. Winter

School of Natural Resources: Faculty Publications

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model …

The Agricultural Model Intercomparison And Improvement Project (Agmip): Protocols And Pilot Studies, Cynthia Rosenzweig, J. W. Jones, J. L. Hatfield, A. C. Ruane, K. J. Boote, P. Thornburn, J. M. Antle, G. C. Nelson, C. Porter, S. Janssen, S. Asseng, B. Basso, F. Ewert, D. Wallach, G. Baigorria, J. M. Winter

School of Natural Resources: Faculty Publications

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model …

Developing A Group Decision Support System (Gdss) For Decision Making Under Uncertainty, Soroush Mokhtari

Electronic Theses and Dissertations

Multi-Criteria Decision Making (MCDM) problems are often associated with tradeoffs between performances of the available alternative solutions under decision making criteria. These problems become more complex when performances are associated with uncertainty. This study proposes a stochastic MCDM procedure that can handle uncertainty in MCDM problems. The proposed method coverts a stochastic MCDM problem into many deterministic ones through a Monte-Carlo (MC) selection. Each deterministic problem is then solved using a range of MCDM methods and the ranking order of the alternatives is established for each deterministic MCDM. The final ranking of the alternatives can be determined based on winning …

Propagation Of Interval And Probabilistic Uncertainty In Cyberinfrastructure-Related Data Processing And Data Fusion, Christian Servin

Open Access Theses & Dissertations

Data uncertainty affects the results of data processing. So, it is necessary to find out how the data uncertainty propagates into the uncertainty of the results of data processing. This problem is especially important when cyberinfrastructure enables us to process large amounts of heterogeneous data. In the ideal world, we should have an accurate description of data uncertainty, and well-justified efficient algorithms to propagate this uncertainty. In practice, we are often not yet in this ideal situation: the description of uncertainty is often only approximate, and the algorithms for uncertainty propagation are often not well-justified and not very computationally efficient. …