HR: 1340h
AN: SF33A-0723 [Abstracts]
TI: Evaluating Water Demand Using Agent-Based Modeling
AU: * Lowry, T S
EM: tslowry@sandia.gov
AF: Sandia National Laboratories, P.O. Box 5800 MS 0735, Albuquerque, NM 87185-0735
United States
AB:
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.
DE: 6309 Decision making under uncertainty
DE: 6314 Demand estimation
DE: 6339 System design
DE: 1878 Water/energy interactions
DE: 1884 Water supply
SC: Special Focus: Advances in Data Acquisition, Management, Analysis and Display [SF]
MN: 2004 AGU Fall Meeting