Eight grand challenges in socio-environmental systems modeling

Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices

Generating policies for sustainable water use in complex scenarios: An integrated land -use and water -use model of Monroe County, Michigan.

Rapidly declining groundwater levels in Southeast Michigan have raised serious concern since the early 1990s. Hydrological studies suggest that land-use changes have caused this decline. The mechanisms linking land-use and groundwater dynamics are not clear, however. To examine this link, I developed the Water-Use Land-Use Model (WULUM), an agent-based model that serves as an analytical framework to understand how these processes interact to create the observed patterns of resource depletion, and to suggest policies to reverse the process. The agent-based model is empirically based on Monroe County, Michigan, and informed with land-use and survey data and expert knowledge about the case. The land-use component includes the main groundwater extractors in the county: stone quarries, golf courses, farms and households. The groundwater component includes the glacial deposits and the underlying bedrock aquifer. The behavior of water users is defined by simple rules that determine their location and consumption decisions. The dynamics of groundwater are represented through simple diffusion rules between each cell and its immediate neighbors. Scenario-based simulations provided the medium for exploratory analysis of the integrated land-use/groundwater system. Pre-testing of WULUM highlighted the importance of the glacial recharge rate of the aquifer in determining the regional hydraulic gradient, recommending reexamination of the parameter values cited in literature. Although quarries extract 75 percent of the total withdrawal, simulations showed that eliminating quarry dewatering did not entirely reverse groundwater decline. Urbanization, on the other hand, contributed significantly to long-term decline. Both low-density and high-density zoning restrictions improved aquifer conditions over medium-density development, suggesting a non-linear relationship between intensity of residential use and groundwater levels. Moreover, of all the natural and policy variables, zoning had the greatest influence on urban settlement and therefore on resource consumption. Medium to high values of hydraulic conductivity in some cases reinforced drought conditions by extending the area affected by excess withdrawals, so that land-use policies should discourage residential concentration in those areas. Thus, while quarries currently affect large areas, expanding suburbanization may lead to regional groundwater depletion in the near future, depending on the spatial distribution and the intensity of development.Ph.D.Environmental scienceGeographyHealth and Environmental SciencesSocial SciencesUrban planningUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/125557/2/3192831.pd

Generating policies for sustainable water use in complex scenarios: an integrated land-use and water-use model of Monroe County, Michigan

Rapidly declining groundwater levels since the early 1990s have raised serious concern in Monroe County, Michigan. Hydrological studies suggest that land-use changes have caused this decline. The mechanisms linking land-use and groundwater dynamics are not clear, however. In this paper I present WULUM, the Water-Use and Land-Use Model, an agent-based model that serves as an analytical framework to understand how these processes interact to create the observed patterns of resource depletion, and to suggest policies to reverse the process. The land-use component includes the main groundwater extractors in the county—stone quarries, golf courses, farms, and households. The groundwater component includes the glacial deposits and the underlying bedrock acquifer. The behavior of water users is defined by simple rules that determine their location and consumption. The dynamics of groundwater are represented through infiltration and diffusion rules between each cell and its immediate neighbors. Initial explorations with the model showed that land-use patterns contributed significantly to groundwater declines, while eliminating quarry dewatering did not entirely solve the problem. Both low-density and high-density zoning restrictions improved aquifer conditions over medium-density development, suggesting a nonlinear relationship between intensity of residential use and groundwater levels. Moreover, of all the natural and policy variables, zoning had the greatest influence on urban settlement and therefore on resource consumption.

Modeling benefits and tradeoffs of green infrastructure: Evaluating and extending parsimonious models for neighborhood stormwater planning

Green infrastructure is often proposed to complement conventional urban stormwater management systems that are stressed by extreme storms and expanding impervious surfaces. Established hydrological and hydraulic models inform stormwater engineering but are time- and data-intensive or aspatial, rendering them inadequate for rapid exploration of solutions. Simple spreadsheet models support quick site plan assessments but cannot adequately represent spatial interactions beyond a site. The present study builds on the Landscape Green Infrastructure Design (L-GrID) Model, a process-based spatial model that enables rapid development and exploration of green infrastructure scenarios to mitigate neighborhood flooding. We first explored how well L-GrID could replicate flooding reports in a neighborhood in Chicago, Illinois, USA, to evaluate its potential for green infrastructure planning. Although not meant for prediction, L-GrID was able to replicate the flooding reported and helped identify strategies for flood control. Once evaluated for this neighborhood, we extended the model to include water quality through the representation of dispersion and settling mechanisms for two pollutant surrogates—total nitrogen and total suspended solids. With the extended model, Landscape Green Infrastructure Design Model-Water Quality (L-GrID-WQ), we examined benefits, costs, and tradeoffs for different green infrastructure strategies. Bioswales were slightly more effective than other green infrastructure types in reducing flooding extent and downstream runoff and pollution, through increased infiltration and settling capacity. Permeable pavers followed in effectiveness and are suggested where spatial constraints may limit the installation of bioswales. Although green infrastructure supports both flooding and pollution control, small tradeoffs between these functions emerged across spatial layouts: strategies based on only curb-cuts better controlled pollution, while layouts that followed the path of water flow better controlled flooding. By illuminating such tradeoffs, L-GrID-WQ can support green infrastructure planning that prioritizes unique concerns in different areas of a landscape

A new framework for urban sustainability assessments: Linking complexity, information and policy

Urban systems emerge as distinct entities from the complex interactions among social, economic and cultural attributes, and information, energy and material stocks and flows that operate on different temporal and spatial scales. Such complexity poses a challenge to identify the causes of urban environmental problems and how to address them without causing greater deterioration. Planning has traditionally focused on regulating the location and intensity of urban activities to avoid environmental degradation, often based on assumptions that are rarely revisited and producing ambiguous effects. The key intellectual challenge for urban policy-makers is a fuller understanding of the complexity of urban systems and their environment. We address this challenge by developing an assessment framework with two main components: (1) a simple agent-based model of a hypothetical urbanizing area that integrates data on spatial economic and policy decisions, energy and fuel use, air pollution emissions and assimilation, to test how residential and policy decisions affect urban form, consumption and pollution; (2) an information index to define the degree of order and sustainability of the hypothetical urban system in the different scenarios, to determine whether specific policy and individual decisions contribute to the sustainability of the entire urban system or to its collapse

Emerging Private Sector Roles in Urban Transport Case Study of an Innovative Telecom-GIS Solution in Bangalore

Our article examines the role of public-private innovation in the development of the Bangalore Transport Information System (BTIS). BTIS is a successful example of new institutional arrangements that integrate perspectives, needs, and tools developed in all sectors of society to address the increasing complexity of transportation problems in Indian cities facing rapid socioeconomic transformation. Traditional transport planning approaches, such as road infrastructure development, have not kept up with the growing number of vehicles and have led to more, rather than less, congestion and air pollution. In response, the city is leading the application of now ubiquitous telecom infrastructure to support creative urban transport solutions. The lessons learned in the Bangalore case have been applied to other cities in India and have potential for other countries

Understanding the Mechanisms of Collective Decision Making in Ecological Restoration: An Agent-Based Model of Actors and Organizations

Ecological restoration, particularly in urban contexts, is a complex collective decision-making process that involves a diversity of stakeholders and experts, each with their own perceptions and preferences about what landscapes should and can look like, how to get them to the desired state, and on what timeline. We investigate how structural and behavioral factors may influence collective decision making in the context of ecological restoration, with the purpose of establishing general relationships between management styles (defined by structural and behavioral factors of the organization) and decision outcomes. Informed by existing literature on collective decision making and by empirical data from the Chicago Wilderness region, we present a stylized agent-based model that maps out and simulates the processes by which individuals within restoration organizations communicate, discuss, and ultimately make a decision. Our study examines how structural and behavioral characteristics - including: (a) the number of actors and groups involved in decision making, (b) the frequency and type of interactions among actors, (c) the initial setup of positions and respect, (d) outside information, and (e) entrenchment and cost of dissent - lead to or prohibit group convergence in terms of collective position, variation in position across actors, and final decision strategies. We found that formal meetings and group leaders are important facilitators of convergence, especially when multiple groups are present, new information is introduced in the process, and participants are polarized around an issue. Also, intergroup interactions are particularly important for overall convergence. Position entrenchment slows the convergence process and increases the need for decision strategies involving outside intervention. Cost of dissent can reinforce these effects. Our study formalizes collective decision-making processes within the context of ecological restoration, establishes generalizable relationships between these processes and decision outcomes, and provides a foundation for further empirical and modeling research