Predicting adaptive responses - simulating occupied environments

Simulation of building performance is increasingly being used in design practice to predict comfort of occupants in finished buildings. This is an area of great uncertainty: what actions does a person take when too warm or suffering from glare; how is comfort measured; how do groups of people interact to control environmental conditions, etc? An increasing attention to model these issues is evident in current research. Two issues are covered in this paper: how comfort can be assessed and what actions occupants are likely to make to achieve and maintain a comfortable status. The former issue describes the implementation of existing codes within a computational framework. This is non-trivial as information on local air velocities, radiant temperature and air temperature and relative humidity have to be predicted as they evolve over time in response to changing environmental conditions. This paper also presents a nascent algorithm for modelling occupant behaviour with respect to operable windows. The algorithm is based on results of several field studies which show the influence of internal and external temperatures on decision making in this respect. The derivation and implementation of the algorithm is discussed, highlighting areas where further effort could be of benefit

Creating space for biodiversity by planning swath patterns and field marging using accurate geometry

Potential benefits of field margins or boundary strips include promotion of biodiversity and farm wildlife, maintaining landscape diversity, exploiting pest predators and parasites and enhancing crop pollinator populations. In this paper we propose and demonstrate a method to relocate areas of sub-efficient machine manoeuvring to boundary strips so as to optimise the use of available space. Accordingly, the boundary strips will have variable rather than fixed widths. The method is being tested in co-operation with seven farmers in the Hoeksche Waard within the province of Zuid Holland, The Netherlands. In a preliminary stage of the project, tests were performed to determine the required accuracy of field geometry. The results confirmed that additional data acquisition using accurate measuring devices is required. In response, a local contracting firm equipped a small all-terrain vehicle (quad) with an RTK-GPS receiver and set up a service for field measurement. Protocols were developed for requesting a field measurement and for the measurement procedure itself. Co-ordinate transformation to a metric system and brute force optimization of swath patterns are achieved using an open source geospatial library (osgeo.ogr) and Python scripting. The optimizer basically tests all orientations and relevant intermediate angles of input field boundaries and tries incremental positional shifts until the most efficient swath pattern is found. Inefficient swaths intersecting boundary areas are deleted to create space for field margins. The optimised pattern can be forwarded to an agricultural navigation system. At the time of the conference, the approach will have been tested on several farm fields

Uncertainty quantification for CO2 sequestration and enhanced oil recovery

This study develops a statistical method to perform uncertainty quantification for understanding CO2 storage potential within an enhanced oil recovery (EOR) environment at the Farnsworth Unit of the Anadarko Basin in northern Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil-water flow and reactive transport in the Morrow formation are conducted for global sensitivity and statistical analysis of the major uncertainty metrics: net CO2 injection, cumulative oil production, cumulative gas (CH4) production, and net water injection. A global sensitivity and response surface analysis indicates that reservoir permeability, porosity, and thickness are the major intrinsic reservoir parameters that control net CO2 injection/storage and oil/gas recovery rates. The well spacing and the initial water saturation also have large impact on the oil/gas recovery rates. Further, this study has revealed key insights into the potential behavior and the operational parameters of CO2 sequestration at CO2-EOR sites, including the impact of reservoir characterization uncertainty; understanding this uncertainty is critical in terms of economic decision making and the cost-effectiveness of CO2 storage through EOR.Comment: 9 pages, 6 figures, in press, Energy Procedia, 201

Tools for Assessing Climate Impacts on Fish and Wildlife

Climate change is already affecting many fish and wildlife populations. Managing these populations requires an understanding of the nature, magnitude, and distribution of current and future climate impacts. Scientists and managers have at their disposal a wide array of models for projecting climate impacts that can be used to build such an understanding. Here, we provide a broad overview of the types of models available for forecasting the effects of climate change on key processes that affect fish and wildlife habitat (hydrology, fire, and vegetation), as well as on individual species distributions and populations. We present a framework for how climate-impacts modeling can be used to address management concerns, providing examples of model-based assessments of climate impacts on salmon populations in the Pacific Northwest, fire regimes in the boreal region of Canada, prairies and savannas in the Willamette Valley-Puget Sound Trough-Georgia Basin ecoregion, and marten Martes americana populations in the northeastern United States and southeastern Canada. We also highlight some key limitations of these models and discuss how such limitations should be managed. We conclude with a general discussion of how these models can be integrated into fish and wildlife management

Toward a relational concept of uncertainty: about knowing too little, knowing too differently, and accepting not to know

Uncertainty of late has become an increasingly important and controversial topic in water resource management, and natural resources management in general. Diverse managing goals, changing environmental conditions, conflicting interests, and lack of predictability are some of the characteristics that decision makers have to face. This has resulted in the application and development of strategies such as adaptive management, which proposes flexibility and capability to adapt to unknown conditions as a way of dealing with uncertainties. However, this shift in ideas about managing has not always been accompanied by a general shift in the way uncertainties are understood and handled. To improve this situation, we believe it is necessary to recontextualize uncertainty in a broader way¿relative to its role, meaning, and relationship with participants in decision making¿because it is from this understanding that problems and solutions emerge. Under this view, solutions do not exclusively consist of eliminating or reducing uncertainty, but of reframing the problems as such so that they convey a different meaning. To this end, we propose a relational approach to uncertainty analysis. Here, we elaborate on this new conceptualization of uncertainty, and indicate some implications of this view for strategies for dealing with uncertainty in water management. We present an example as an illustration of these concepts. Key words: adaptive management; ambiguity; frames; framing; knowledge relationship; multiple knowledge frames; natural resource management; negotiation; participation; social learning; uncertainty; water managemen