SF33A-0722 1340h
Agent Based Modeling Applications for Geosciences
Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in a thermodynamic framework as a set of reactions that roll-up the integrated effect that diverse biological communities exert on a geological system. This approach may work well to predict the effect of certain biological communities in specific environments in which experimental data is available. However, it does not further our knowledge of how the geobiological system actually functions on a micro scale. Agent-based techniques may provide a framework to explore the fundamental interactions required to explain the system-wide behavior. This presentation will present a survey of several promising applications of agent-based modeling approaches to problems in the geosciences and describe specific contributions to some of the inherent challenges facing this approach.
SF33A-0723 1340h
Evaluating Water Demand Using Agent-Based Modeling
The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.
SF33A-0724 1340h
Simulating the effects of native vegetation configurations on water quality using a multi-agent system coupled to a distributed hydrological process model
Within Australia, excessive clearing of native vegetation has resulted in many landscapes becoming increasingly dysfunctional with respect to the retention of water and nutrients, and the maintenance of biodiversity. This problem is being addressed by the National Action Plan for Salinity and Water Quality, which promotes the management of vegetation cover at the farm and catchment scale to: stabilize soils; regulate groundwater to control dryland salinity; minimize chemical residues, nutrients, and sediment run-off to streams and waterways; as well as the maintenance of environmental flows for healthy waterways. However, the performance of potential landscape designs for the retention of water, nutrients and sediments, such as the reestablishment of tree belts and riparian vegetation, must be socially and economically feasible as well as improving landscape function. The implementation of alternative design strategies occurs at the farm-scale, but also must be applicable at the hill-slope and catchment scales, as well as incorporating temporal variability, and be practical to implement where data is limiting. A method is presented based upon a coupled multi-agent system (MAS) simulation and distributed parameter hydrological process model to optimize the integration of native vegetation within agroecosystems, in order to maintain desired outcomes for sustainable landscape function.
SF33A-0725 1340h
Integrating Agent Models of Subsistence Farming With Dynamic Models of Water Distribution
Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate, and the feedback between rainfall, crop growth and land clearance, and their coupling to the hydrological cycle. Temporal fluctuations in rainfall on timescales from annual through to decadal and longer, and the associated changes in in the spatial distribution of water availability mediated by the soil-type, slope and landcover determine the locations within the landscape that can support agriculture, and control sustainability of farming practices. We seek to make an integrated modelling system to represent land use change by coupling an agent based model of subsistence farming, and the associated exploitation of natural resources, to a realistic representation of the hydrology at the catchment scale, using TOPMODEL to map the spatial distribution of crop water stress for given time-series of rainfall. In this way we can, for example, investigate how demographic changes and associated removal of forest cover influence the possibilities for field locations within the catchment, through changes in ground water availability. The framework for this modelling exercise will be presented and preliminary results from this system will be discussed.
SF33A-0726 1340h
Toward an Agent-Based Model of Socially Optimal Water Rights Markets
There has been considerable interest lately in using public markets for buying and selling the rights to local water usage. Such water rights markets, if designed correctly, should be socially optimal, that is, should sell rights at prices that reflect the true value of water in the region, taking into account that water rights buyers and sellers represent a disparate group of private industry, public authorities, and private users, each having different water needs and different priority to local government. Good market design, however, is hard. As was experienced in California short-run electric power markets, a market design that on paper looks reasonable but in practice is mal-constructed can have devastating effects: firms can learn to manipulate prices by `playing' both sides of the market, and sellers can under-provide so as to create exorbitant prices which buyers have no choice but to pay. Economic theory provides several frameworks for developing a good water rights market design; for example, the structure-conduct-performance paradigm (SCPP) suggests that, among other things, the number and types of buyers and sellers (structure), and transaction clearing rules and government policies (conduct) affect in very particular ways the prices and quantities (performance) in the market. In slow-moving or static markets, SCPP has been a useful predictor of market performance; in faster markets the market dynamics that endogenously develop over time are often too complex to predict with SCPP or other existing modeling techniques. New, more sophisticated combinations of modeling and simulation are needed. Toward developing a good (i.e., socially optimal) water rights market design that can take into account the dynamics inherent in the water sector, we are developing an agent-based model of water rights markets. The model serves two purposes: first, it provides an SCPP-based framework of water rights markets that takes into account the particular structure of buyers and sellers in water markets, reservation prices for water, the mechanics with which these buyers and sellers can participate in water rights markets, and the role of government authorities. Second it provides a virtual laboratory for studying the dynamic effects of different water market designs on the prices and quantities of water sold in the market. This design and laboratory work will help regional water authorities develop water rights markets that best reflect the needs of their regions.
SF33A-0727 1340h
An Integrated Framework for Analysis and Modelling of Changes in Water Use and Land Use in the Indo-Gangetic Plains
Agricultural land use changes have been quite dramatic in the last few decades in the Indo-Gangetic plains as an outcome of many factors including the green revolution. But, there are wide-spread disparities in the agricultural land use practices and its intensification, in addition to the economic outcome of these sub-regions within the Gangetic basin as one moves from the west to the east. In addition to the geo-physical and ecological differences, this can be attributed to a mix of demographic, social, economic, and political and policy differences. Water use within the agricultural system is widely influenced by these human factors. An integrated framework has been proposed by the authors for identifying and quantifying the linkages between land use and water use in this coupled human-environment system. The research being carried out here will discuss the framework with reference to the analysis of the changes in the agricultural system in the past five decades within the Indo-Gangetic plains, with links to the water use, and the ecological, economical and social indicators of change within the coupled system context. Based on the experiences of the authors in developing agent based land use (AGENT-LUC) models at the regional and national scales, this integrated framework will also form the basis for the agent based modelling approach. It is estimated that the model proposed would help understand the competition and allocation of water needs of the different land use regimes (for eg. agricultural vs. urban water use) and help evaluate sustainable management strategies within the basin.