The world is facing severe and growing challenges in maintainig water quality and meeting the rapidly growing demand for water resources. In addition, water used for irrigation, the largest use of water in most developing countries, will likely have to be diverted increasingly to meet the needs of urban areas and industry whilst remaining a prime engine of agricultural growth. Finally, environmental and other in-stream water demands become more important as economies develop. The river basin has been acknowledged to be the appropriate unit of analysis to address these chanllenges facing water resources management: and modeling at this scale can provide essential information for policy makers in their decisions on allication of resources. This paper reviews the state of the art of modeling approaches to integrated water resources management at the river basin scale, with particular focus on the potential of coupled economic hydrologic models, and concludes with directions for future modeling exercises.

Population growth, urbanization and climate change threaten urban water systems. The rise of demands caused by growing urban areas and the potential decrease of water availability caused by the increase of frequency and severity of droughts challenge the continued well-being of society. Due to increasing environmental and financial constraints, water management paradigms have shifted from supply augmentation to demand management, and water conservation initiatives may efficiently decrease water demands to more sustainable levels. To provide reliable assessment of the efficiencies of different demand management strategies, new modeling techniques are needed that can simulate decentralized decisions of consumers and their interactions with the water system. An integrated simulation-optimization framework, based on the paradigm of Complex Adaptive Systems, is developed here to model dynamic interactions and adaptations within social, built, and natural components of urban water systems. The framework goes beyond tradition engineering simulations by incorporating decentralized, heterogeneous and autonomous agents, and by simulating dynamic feedback loops among modeling components. The framework uses modeling techniques including System Dynamics, Cellular Automata, and Agent-based Modeling to simulate housing and population growth, a land use change, residential water consumption, the hydrologic cycle, reservoir operation, and a policy/decision maker. This research demonstrates the applicability of the proposed framework through a series of studies applied to a water supply system of a large metropolitan region that is located in a semi-arid region and suffers recurrently from severe droughts. A set of adaptive demand management strategies, that apply contingency restrictions, land use planning, and water conservation technologies, such as rainwater harvesting systems, are evaluated. A multi-objective Evolutionary Algorithm is coupled with the CAS simulation framework to identify optimal strategies and explore conflicting objectives within a water system. The results demonstrate the benefits of adaptive management by updating management decisions to changing conditions. This research develops a new hydrologic sustainability metric, developed to quantify the stormwater impacts of urbanization. The Hydrologic Footprint Residence captures temporal and spatial hydrologic characteristics of a flood wave passing through a stream segment and is used to assess stormwater management scenarios, including Best Management Practices and Low Impact Development.

The greatest challenge facing humanity today is the transition to a more sustainable energy infrastructure while reducing greenhouse gas emissions. Meeting this challenge will require a diversified array of solutions spanning across multiple industries. One of the solutions rising to the fore is the potential to rapidly build out carbon sequestration, which involves the removal of CO2 from the atmosphere and its storage in the subsurface. Integrated Aquifer Characterization and Modeling for Energy Sustainability: Key Lessons from the Petroleum Industry provides a comprehensive and practical technical guide into the potential that aquifers hold as sites for carbon and energy storage. Aquifers occupy a significant part of the Earth’s available volume in the subsurface and thus hold immense potential as sites for carbon storage. Many aquifers have been studied extensively as part of oil and gas energy development projects and, as such, they represent an opportunity to sequester carbon within existing areas of infrastructure that have already been impacted by, and integrated into, an inherited energy framework. Moreover, future efforts to reconfigure the landscape of our national and global energy systems can extract valuable lessons from this existing trove of data and expertise. From a multidisciplinary perspective, this book provides a valuable and up-to-date overview of how we can draw on the wealth of existing technologies and data deployed by the petroleum industry in the transition to a more sustainable future. Integrated Aquifer Characterization and Modeling for Energy Sustainability will be of value to academic, professional and business audiences who wish to evaluate the potential underground storage of carbon and/or energy, and for policy makers in developing the right policy tools to further the goals of a sustainable energy transition.

Uncertainty modeling in health risk assessment and groundwater resources a management Elcin Kentel 339 Pages Directed by Dr. M. Mustafa Aral Real-world problems especially the ones that involve natural systems are complex and they are composed of many non-deterministic components. Uncertainties associated with these non-deterministic components may originate from randomness or from imprecision due to lack of information. Until recently, uncertainty, regardless of its nature or source has been treated by probability concepts. However, uncertainties associated with real-world systems are not limited to randomness. Imprecise, vague or incomplete information may better be represented by other mathematical tools, such as fuzzy set theory, possibility theory, belief functions, etc. New approaches which allow utilization of probability theory in combination with these new mathematical tools found applications in various engineering fields. Uncertainty modeling in human health risk assessment and groundwater resources management areas are investigated in this thesis. In the first part of this thesis two new approaches which utilize both probability theory and fuzzy set theory concepts to treat parameter uncertainties in carcinogenic risk assessment are proposed. As a result of these approaches fuzzy health risks are generated. For the fuzzy risk to be useful for practical purposes its acceptability with respect to compliance guideline has to be evaluated. A new fuzzy measure, the risk tolerance measure, is proposed for this purpose. The risk tolerance measure is a weighed average of the possibility and the necessity measures which are currently used for decision making purposes. In the second part of this thesis two decision making frameworks are proposed to determine the best groundwater resources management strategy in the Savannah region, Georgia. Groundwater resources management problems, especially ones in the coastal areas are complex and require treatment of various uncertain inputs. The first decision making framework proposed in this study is composed of a coupled simulation-optimization model followed by a fuzzy multi-objective decision making approach while the second framework includes a groundwater flow model in which the parameters of the flow equation are characterized by fuzzy numbers and a decision making approach which utilizes the risk tolerance measure proposed in the first part of this thesis.