Integrated environmental modeling: A vision and roadmap for the future

TLDR: This paper organizes and presents the results of a number of workshops held that brought IEM practitioners together to share experiences and discuss future needs and directions, and presents IEM as a landscape containing four interdependent elements: applications, science, technology, and community.

Abstract: Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and decision making; and providing a web-based platform for community interactions (e.g., continuous virtual workshops).

Figures

Figure 3: IEM Science Roadmap

Figure 2 : IEM Applications Roadmap

Table 5. Summary of methods used for model evaluation

Table 7. IEM Relevant Communities or Communities of Practice.

Table 4. Examples of data access initiatives of relevance to IEM

Table 2. Examples of IEM Applications.

Full text

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Integrated Environmental Modeling: A Vision and Roadmap for the Future
Author List: Gerard F. Laniak
1*
, Gabriel Olchin
2
, Jonathan Goodall
3
, Alexey Voinov
4
, Mary
Hill
5
, Pierre Glynn
5
, Gene Whelan
1
, Gary Geller
6
, Nigel Quinn
7
, Michiel Blind
8
, Scott
Peckham
9
, Sim Reaney
10
,
Noha Gaber
11
, Robert Kennedy
12
, Andrew Hughes
13
1
US Environmental Protection Agency, Office of Research and Development
2
US Environmental Protection Agency, Office of the Science Advisor
3
University of South Carolina, Department of Civil and Environmental Engineering, USA
4
University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC),
Netherlands
5
US Geological Survey, National Research Program
6
Jet Propulsion Laboratory, California Institute of Technology, USA
7
Berkeley National Laboratory, USA
8
Deltares, Netherlands
9
INSTAAR, University of Colorado – Boulder, USA
10
Durham University, Department of Geography, UK
11
US Environmental Protection Agency, Office of the Administrator
12
US Army Corps of Engineers, Engineer Research and Development Center
13
British Geological Survey, Keyworth, UK
* Corresponding Author. Tel +1 706 355 8316; fax +1 706 355 8302. E-mail address:
laniak.gerry@epa.gov
U.S. Environmental Protection Agency
960 College Station Road
Athens, Georgia 30605 USA

2
Abstract:
Integrated environmental modeling (IEM) is inspired by modern environmental problems,
decisions, and policies and enabled by transdisciplinary science and computer capabilities that
allow the environment to be considered in a holistic way. The problems are characterized by the
extent of the environmental system involved, dynamic and interdependent nature of stressors and
their impacts, diversity of stakeholders, and integration of social, economic, and environmental
considerations. IEM provides a science-based structure to develop and organize relevant
knowledge and information and apply it to explain, explore, and forecast the behavior of
environmental systems in response to human and natural sources of stress. During the past
several years a number of workshops were held that brought IEM practitioners together to share
experiences and discuss future needs and directions. In this paper we organize and present the
results of these discussions. IEM is presented as a landscape containing four interdependent
elements: applications, science, technology, and community. The elements are described from
the perspective of their role in the landscape, current practices, and challenges that must be
addressed. Workshop participants envision a global scale IEM community that leverages modern
technologies to streamline the movement of science-based knowledge from its sources in
research, through its organization into databases and models, to its integration and application for
problem solving purposes. Achieving this vision will require that the global community of IEM
stakeholders transcend social, political, and organizational boundaries and pursue greater levels
of collaboration. Among the highest priorities for community action are the development of
standards for publishing IEM data and models in forms suitable for automated discovery, access,
and integration; education of the next generation of environmental stakeholders, with a focus on
transdisciplinary research, development, and decision making; and providing a web-based
platform for community interactions (e.g., continuous virtual workshops).
Keywords: integrated environmental modeling, community of practice, roadmap, model
integration

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1.0 Introduction
Integrated environmental modeling (IEM) is a discipline inspired by the need to solve
increasingly complex real-world problems involving the environment and its relationship to
human systems and activities (social and economic). The complex and interrelated nature of real-
world problems has led to a need for higher-order systems thinking and holistic solutions (EPA,
2008b; Jakeman and Letcher, 2003; MEA, 2005; Parker et al., 2002). IEM provides a science-
based structure to develop and organize multidisciplinary knowledge. It provides a means to
apply this knowledge to explain, explore, and forecast environmental-system response to natural
and human-induced stressors. By its very nature, it breaks down research silos and brings
scientists from multiple disciplines together with decision makers and other stakeholders to solve
problems for which the social, economic, and environmental considerations are highly
interdependent. This movement toward transdisciplinarity (Tress et al., 2005) and participatory
modeling (Voinov and Bousquet, 2010) fosters increased knowledge and understanding of the
system, reduces the perception of ‘black-box’ modeling, and increases awareness and detection
of unintended consequences of decisions and policies.
IEM concepts and early models are now more than thirty years old (Bailey et al., 1985; Cohen,
1986; Mackay, 1991; Meadows et al., 1972; Walters, 1986). With the emergence of problems
related to regional-scale land-use management, impacts of global climate change, valuation of
ecosystem services, fate and transport of nanomaterials, and life-cycle analysis, the application
of IEM is growing. National and international organizations have commissioned studies to
determine research directions and priorities for integrated modeling (Blind et al., 2005a, 2005b;
EC, 2000; ICSU, 2010; NSF; Schellekens et al., 2011). Senior managers in government,
academia, and commercial organizations are restructuring operations to facilitate integrated and
transdisciplinary approaches (EPA, 2008b). Mid-level managers who realize that no single group
has the comprehensive expertise needed for integrated modeling are actively pursuing inter-
organization collaborations (e.g. Delsman et al., 2009, ISCMEM; OpenMI, 2009).
Environmental assessors are utilizing IEM science and technologies to build integrated modeling
systems that will address specific problems at varying scales (Akbar et al., 2012, Bergez et al.,
2012, Linker et al., 1999, Mohr et al., 2012, Quinn and Jacobs, 2006). Finally, policy developers

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and decision makers are asking for and processing information synthesized from holistic
systems-based modeling approaches (EPA, 2008b; ABARE-BRS, 2010).
The primary motivation and input for this paper are drawn from a series of workshops held
during the past several years (Table 1). The workshops were open forums convened to share
knowledge, experience, and future visions related to IEM. The workshops were attended by a
cross-section of IEM practitioners including environmental modelers, software technologists,
decision analysts, and managers. Participants represented government, academia, and the private
sector.
The principal message from the workshops is a call to elevate solutions to key IEM issues and
challenges to a level of community above individual groups and organizations. In effect, to
establish an open international community environment for pursuing the ability to share and
utilize the broad science of IEM by communicating ideas, approaches, and utilizing modern
technologies and software standards. The purpose of this paper is to synthesize the knowledge
and perspectives shared during the workshops and present a holistic view of the IEM landscape
and a roadmap, consisting of goals and activities, to guide its navigation. The remainder of this
introduction is intended to provide a definition of IEM relative to several similar terms, describe
the role of IEM in the decision making and policy development
1
1
For efficiency, in this paper when we refer to decision making alone we intend to include policy development as
well.
process, and establish a
conceptual view of IEM as a landscape with interdependent elements. Sections 2 through 5 then
present each element of the IEM landscape, including an integrated roadmap of activities that
addresses the associated collection of issues and challenges. Conclusions and a summary are
presented in Section 6.

5
Table 1. IEM Workshops
Workshop Title
Sponsor
Date
Organizations Represented
Outputs
Environmental Software Systems Compatibility and
Linkage Workshop
US NRC
DOE
March
2000
 >40 attendees
a,b,c,d,e
Report: NRC (2002)
Integrated Modeling for Integrated Environmental
Decision Making
US EPA
January
2007
 >100 attendees
b,f,g
Report: EPA (2007)
White Paper: EPA (2008b)
Collaborative Approaches to Integrated Modeling:
Better Integration for Better Decision making
US EPA
December
2008
 >50 attendees
b,h,i,j,k,l,m,n,r,t,v
Report: EPA (2008a)
iEMSs 2010 Conference
Science session: Integrated Modeling Technologies
Workshop: The Future of Science and Technology
of Integrated Modeling
iEMSs July 2010
 >75 attendees
b,e,j,m,n,p,v
 International Conference (most
organizations listed below and others)
This roadmap paper
The International Summit on Integrated
Environmental Modeling
BGS
USGS
US EPA
December
2010

>50 attendees
a,b,d,e,h,I,m,o,v
 International Conference (most
organizations listed below and others)
Report
(https://iemhub.org/resourc
es/386/supportingdocs)
a
US NRC: US Nuclear Regulatory Commission (http://www.nrc.gov/)
b
US EPA: US Environmental Protection Agency (http://www.epa.gov)
c
DOE: Department of Energy (US) (http://energy.gov/)
d
US ACoE: US Army Corps of Engineers (http://www.usace.army.mil)
e
NGO: Non-Governmental Organizations
f
EC: Environment Canada (http://www.ec.gc.ca/)
g
EU: European Union (http://europa.eu/)
h
ISCMEM: Interagency Steering Committee for Multi-media Environmental Modeling (US Federal Agencies) (http://iemhub.org/topics/ISCMEM)
i
CEH UK: Center for Ecology and Hydrology, UK (http://www.ceh.ac.uk/)
j
iEMSs: International Environmental Modeling and Software Society (http://www.iemss.org/society/)
k
OGC: Open Geospatial Consortium (http://www.opengeospatial.org/)
l
CUAHSI: Consortium of Universities for the Advancement of Hydrologic Science, Inc. (http://www.cuahsi.org/)
m
OpenMI: Open Modeling Interface (Association) (http://www.openmi.org/)
n
USDA: US Department of Agriculture (http://www.usda.gov)
o
CSDMS: Community Surface Dynamics Modeling System (http://csdms.colorado.edu/wiki/Main_Page)
p
NRC (Italy): National Research Council (Italy) (http://www.cnr.it/sitocnr/Englishversion/Englishversion.html)
q
NSF: National Science Foundation (http://www.nsf.gov/)
r
ONR: Office of Naval Research (US) (http://www.onr.navy.mil/)
s
NASA: National Aeronautics and Space Administration (US) (http://www.nasa.gov/)
t
USGS: US Geological Survey (http://www.usgs.gov)
u
NOAA: National Oceanic and Atmospheric Administration (US) (http://www.noaa.gov/)
v
BGS: British Geological Survey (http://www.bgs.ac.uk/)

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Integrated environmental modeling: a vision and roadmap for the future" ?

US Environmental Protection Agency, Office of Research and Development US Environmental Protection Association, Office-of-Research and Development United States Geological Survey, National Research Program 6 Jet Propulsion Laboratory, California Institute of Technology, USA 7 Berkeley National Laboratory, USA 8 Deltares, Netherlands 9 INSTAAR, University of Colorado-Boulder, USA 10 Durham University, Department of Geography, UK 11 US Environmental Environmental Protection Agent, Officeof the Administrator 12 US Army Corps of Engineers, Engineer Research and development Center 13 British Geological Survey UK Geological Survey this paper, Keyworth, UK 

Q2. What are the dominant themes in the workshop discussions concerning IEM applications?

Dominant themes throughout workshop discussions concerning IEM applications included stakeholder involvement, adaptive management strategies, education, peer review, andreusability. 

Q3. What is the key aspect of the implementation of the IEM roadmap?

A key aspect of the implementation is that solutions to common issues and challenges reflect community-wide participation and acceptance. 

Q4. What is the key challenge to the IEM community for achieving the full potential of the web?

A key challenge to the IEM community for achieving the full potential of the web is to advance their understanding of how to optimize data and operations between traditional personal computer (PC) environments and remote computers on the Web. 

Q5. What are the roles of the modeler in the decision/policy process?

Because of the modelers natural systems orientation he/she may perform roles8that include facilitator, knowledge broker, technical specialist, and leader. 

Q6. What is the main challenge to the IEM community?

New means of ensuring the veracity of thescience-based products and applications represents a prime challenge to the IEM science community. 

Q7. What criteria were used to evaluate the tools?

They evaluated these tools based on the number of literature citations, robustness of documentation, and form of software distribution. 

Q8. What are the main roles of citizen-science networks in the IEM process?

Citizen-science networks can contribute in many different ways, including direct12monitoring of natural resources and environmental conditions2 , facilitate knowledge transfer between scientists and lay public, test IEM and monitoring technologies and processes (e.g. Smartphone apps), and provide historical knowledge and local stakeholder continuity to ensure persistence and improvement of IEM application efforts. 

Q9. What are the main roles of decision stakeholders in the development of an IEM?

Decision stakeholders are primarily responsible for the content of the problem statement and the science stakeholders must ensure that the content is sufficiently focused and detailed to achieve its purpose. 

Q10. What is the definition of a hypothesis-testing framework?

Refutability requires a hypothesis-testing framework in which data are used in specific ways to test the model’s ability to simulate the system of interest. 

Q11. Why is the adoption of specific modeling frameworks unlikely to change in the near future?

The adoption of specific modeling frameworks within local communities is understandable and unlikely to change in the near future because maintaining local control over the user experience, in particular the design and implementation of the Graphical User Interface (GUI), is important for buy-in and effective use within specialized communities. 

Q12. What is the main advantage of using cloud computing and web services?

The approach of using cloud computing and web services has several advantages over traditional modeling approaches, including the potential to greatly reduce the cost and time required for the development of an IEM solution through the re-use of modeling components. 

Q13. What is the need for interoperability between tools?

Within this ecosystem of software tools required to perform IEM, there is a strong need to provide interoperability between tools to simplify and automate data transfer across applications. 

Q14. What are the main barriers to interoperability?

Mattot et al. (2009) note several software technology-based barriers to interoperability, such as different programming languages, compilers, and development platforms; inconsistent separation of system and model components (e.g., user and model interface code, executables, algorithmic code, execution management code, warning and error handling, and statistical functionality); and different input/output (I/O) file formats. 

Q15. Why do the authors discuss the steps in the IEM process?

The authors discuss each of these modeling steps to emphasize the manner in which IEM issues and challenges manifest and also to point out that to efficiently share IEM science products across the global community the authors will need to be more explicit and compartmentalized in their implementations. 

Q16. What is the role of the W3C in the IEM community?

The challenge for the IEM community is to bring these concepts and standards to bear on IEM systems in an effort to establish a unifying publishing capability for software that facilitates discovery and utilization of individual IEM components and systems independent of the source of their development. 

Q17. What is the definition of stakeholders in the case of IEM applications?

The definition of stakeholders in this case is quite broad (Krueger et al., 2012) and in the case of IEM applications includes experts (scientists, engineers, educators, and decision makers) as well as non-experts (in the traditional sense). 

Q18. What is the importance of involving the full stakeholder community in the decision and application process?

While the importance and value of involving the full stakeholder community in the decision and application process is recognized there remains a significant need for guidelines for managing, facilitating, and reporting the dynamic interactions among stakeholders (Arciniegas et al., 2012).