|Wednesday, September 16th|
1:20 PM - 1:40 PM
Participatory modelling (PM) has far-reaching potential to support the governance of complex socio-environmental systems. Although many PM case studies have been published, there is a lack of classification and characterization of the studies in their ensemble. To progress the systematic and theory-based development of PM and its applications with respect to participatory planning and decision-making, we have reviewed the field with a focus on planning and procedural issues. To do this, a random sample (n=60) of PM case articles is drawn from a larger pool of compiled PM articles that itself represented a nearly complete set of peer reviewed PM studies. A novel, theory-based, PM process evaluation instrument was used for compiling case data and for analysis against a comprehensive set of planning process criteria. When it comes to issues of knowledge integration and learning, the PM field can already make important contributions to participatory planning and decision-making, especially for its approaches and tools that integrate knowledge. Questions of values and democracy however have been given too little attention, and so far, most PM processes do not employ best practices set out for value-based and democratic participatory processes. Most urgently, the idea that participatory processes need to be understood by, and connected to, their surrounding governance systems is not well-established in the field. This is a fundamental question for the possibility of implementing PM in practice and for upscaling its utilization. Based on our findings, we formulate a research program aimed at developing PM into a more useful approach including an efficient set of tools for real-world participatory planning and decision-making – an area that urgently calls for innovative, efficient and knowledge-based process support. Examples from cases will be discussed.
1:40 PM - 2:00 PM
Reviews of the water resources systems literature show considerable interest in methodological issues and less so in implementation experiences. This talk will offer some thoughts on the use of our analysis tools in the political environment where water management decisions are typically made. I’ll illustrate this based on some experiences I’ve had in South-East Asia, North Africa and the Middle East. In every case the results of the analyses had an impact on the debates that took place regarding what decisions to make, and occasionally on the decisions themselves.
2:00 PM - 2:20 PM
Effectively engaging community stakeholders in urban system decision making is becoming increasingly important considering the complex environmental conditions threatening the well-being of citizens and their cities. Participatory Modeling, coupled with complementary participatory techniques, can be a powerful approach that helps communities take charge of their future and develop solutions to address the complex problems they are facing. Community stakeholder satisfaction with the modeling experience can be positively impacted by designing for strategic engagement through conversations. While conversations are the smallest and the largest unit of human change, we spend very little time carefully designing them. Well-designed and executed conversations can help create and sustain the clarity, trust, agreements, and roles necessary for strategic community engagement throughout all phases of the modeling project. Taking a conversation-based approach directly engages community stakeholders in defining diverse pathways for their participation. When planning a modeling project, design engagement conversations to define modeling team roles and to staff the roles, determine the types of engagement needed from each role during each phase of the project, and ask community stakeholders about their capacity and availability (don’t assume they are too busy or unwilling to participate deeply). Prioritizing and undertaking an intentional conversation-based process will help to achieve diverse engagement driven by stakeholders who identify and own their own participation level and contributions. I will present lessons learned from food systems modeling projects in Flint, MI, and Cleveland, OH, as well as, discuss the aspects of those projects that might be appropriate to replicate in Detroit, MI. The session builds on concepts introduced in the iEMSs 2018 session “Making Meaningful Models: Partnering with Stakeholders Throughout the Modelling Process”; and the “Identifying and Engaging Stakeholders in Participatory Modeling Projects” workshop facilitated at the Innovations in Collaborative Modeling – Participatory Modeling Field School hosted in Detroit in 2019.
2:20 PM - 2:40 PM
It is evident that participatory modelling is a useful approach when dealing with wicked, multi-actor, multi-perspective problems, such as the energy transition or climate change. Literature considers social learning to be the process taking place during participatory modelling. It is understood as the process of co-creation of knowledge, leading to convergence of goals and criteria, and a change in behaviour. While it is a key concept in the field of participatory modelling, the basic processes that drive social learning in this context remain unclear. This lack of a consistent theoretical basis diminishes our ability to consistently and purposefully design participatory processes and increase their effectiveness. We theorize that social learning is an emergent pattern, arising out of social (inter)actions of individuals over time, taking place during and around participatory modelling. Actors negotiate and conceptualize a situation, and use this conceptualisation as the basis for formalizing a model. This process is subject to differences in opinions; social mechanisms, such as status or power; different - and possibly - conflicting goals, perspectives, and rationalities. During these social (inter)actions, actors co-create knowledge by integrating and transforming shared knowledge. What these actions are precisely and how they lead to social learning is unclear. Concepts from social psychology and communication sciences about information processing and its impact on the thoughts and behaviour of participants offer a useful starting point. In order to systematically explore these concepts, we are developing an agent based model of the participatory modelling process, focusing on psychological and social processes within and between individuals during this process. We will present our model design and initial findings in how the model compares to a reference case study. Furthermore, we discuss possible development directions and potential impacts on process design.
2:40 PM - 3:00 PM
Climate change is expected to affect water availability for agriculture and increase the risk of crop loss. While in North East Lower Saxony (NELS) an intensification of irrigation might be a temporary solution, a long-term increase in water extraction, especially during drought periods, is not a sustainable option. Based on this issue, we implemented a participatory system dynamics approach, namely Group Model Building (GMB), to develop a qualitative system dynamics model (QSDM) describing the agricultural system and its relation to water resources in the study region. Through the development of such a model, we seek to understand the complexity of the interactions between both sectors, recognize the stakeholders’ needs and identify risks and weaknesses. By doing this, we expect to subsequently reinforce the adaptation and decision-making process and avoid conflicts. The model incorporates a wide range of perceptions, as twenty stakeholders ranging from farmers, government agencies, environmental protection organizations and local water authorities were involved in the study. Through the inclusion of a variety of perceptions, the study seeks to increase information exchange to reduce subjectivity and knowledge gaps. These perceptions were recorded and embedded in a QSDM using GMB. Through the QSDM, we identified and mapped the structure and connections between agriculture and the water balance. It was also possible to identify the strongest feedback loops governing both sectors as well as their influence on the current situation. The causal loops include the different uses for the available water of the region, the impact of irrigation, the significance of crop selection and the importance of sustainable soil management. We concluded that climate change poses a risk to the region as elevated temperatures could increase the crop water demand and increase the need for irrigation. In the same way, changes in the rain patterns could affect the water balance of the region. The agricultural system has, however, potential to adapt by implementing new water management strategies such as restructuring water rights, water storage and reuse and conjunctive water use and by changing agricultural practices.
3:20 PM - 3:40 PM
The related research areas of framed field experiments and participatory modelling stake out contrasting poles in the approach of informing models via behavioural experiment. Along the spectrum between them, researchers make trade-offs in simplicity (for improved statistical power) and specificity (for better representation and participant engagement). Where researchers land along this spectrum shapes the generalizability and external validity of their findings. Additionally, wherever researchers land along this spectrum, they have produced a ‘game stylization’ that differs from the perceived reality of their participants, and may still differ from the ‘model stylization’ through which processes are implemented in their model. I present a framework for building spatial games in Netlogo, demonstrate the simplicity-specificity problem via several different game applications, and discuss approaches (such as flexible game module toolkits and community planning sessions, through which participants contribute to designing the game structure and rules) that may help to reconcile some of the conflicting challenges in developing games that connect to participants, to models, and to statistical analysis alike.
Jonatan Godinez Madrigal
3:40 PM - 4:00 PM
4:20 PM - 4:40 PM
Low crop yield is a growing concern all over the world. One of the reasons for this is lack of precise knowledge and preparedness among farmers about different factors that affect crop yield. Worsening weather conditions and ecological imbalances only made the matters worse. In a country like India where small and marginal farmers account for more than 80% of the farming community face several challenges with rising temperature and unpredictable rainfall. Many a time seed germination process takes a hit resulting in total crop failure or low crop yield. Numerous studies have been carried out to improve the crop yield, seed quality and seed germination. After reviewing more than 40 research papers, it is clear that different machine learning models developed primarily focused on nutrients and seed quality but not much involvement of farmers and environmental factors. Mostly regression technique is used for precision agriculture and K-NN for seed quality. Artificial Neural Networks, Deep Learning and Support Vector Machines are used for classification and regression to identify diseases and growth. But most of these algorithms won’t work well in the fields. To illustrate this more, water required for a crop depends on temperature, humidity, soil type and type of crop. Taking this reality into account and after conducting some studies and taking farmers’ input, it has become clear that multiple interactions with farmers would be of immense help in seed germination process a success. Participatory modeling (PM) for farms helped include many challenges including environmental factors in the data. Data, qualitative and quantitative, from 20 different farmers at the seed stage was prepared and analyzed using data science and data visualization techniques. Temperature, moisture, air, and light conditions must be correct for seeds to germinate. The visualizations made it easy for farmers to understand different patterns during germination of seeds. The feedback given by them helped come up with new models. As the data available was limited, transfer learning and deep learning were used to analyze come up with different seedling growth patterns for different types of seeds. This definitely is of help to farmers as many a time, crop failure occurs at the germination stage itself.
4:40 PM - 5:00 PM
The participatory modeling field has grown quickly and new applications are continuing to be developed. A recent review of participatory modeling case studies has identified that various forms of the practice exist (e.g., different ways to identify participants, define problems, include values, manage power dynamics, etc.), and that practices can generate very important positive outcomes such as knowledge integration, learning, and uncertainty management. However, results found that not all approaches were successful in achieving objectives. The uncertainty in successful practices may discourage practitioners from using this approach and limits future advances in participatory modeling. Therefore, knowing which characteristics are associated with positive outcomes can inform future practices and increase utilization. To address this gap, we collected data from 157 participatory modeling case studies in the peer-reviewed literature and used a random forest model to identify attributes associated with positive outcomes. We present results from this analysis and share insights in how these findings can inform planning and use of different types of participatory processes.
|Thursday, September 17th|
8:20 AM - 8:40 AM
Participatory Modelling (PM) engages a suite of conceptual and numerical modelling tools and techniques that assist stakeholders to understand a complex issue or system. Although the value of PM has been amply demonstrated in many policy settings and management contexts over more than 30 years, it is not yet widely known or used in stakeholder engagement processes such as citizens juries or planning proposal consultations. The lack of consistent, standardised reporting of PM processes and their outcomes is greatly restricting the dissemination of lessons learnt from past engagement efforts. Having a systematic way to document these lessons could help participatory modellers and stakeholders (1) avoid pitfalls, (2) replicate successes, and (3) better recognize and realize the intrinsic value of PM (Glynn et al, 2018). One limitation to furthering these goals and getting wider adoption of PM is the lack of consistent reporting about PM tools and outcomes that could assist future engagement practitioners (Glynn et al, 2018). This issue led Cockerill et al (2019) and others to call for standardised Records of Engagement and Decisions (RoED) for stakeholder engagement processes and outcomes. We are currently addressing this challenge in the context of rural communities in Australia engaging in the planning and approval process of mining and energy-related proposals. By weaving PM and RoED into this process, we aim to: (1) help stakeholders understand proposals and their potential impacts more efficiently and effectively, and (2) identify and articulate quantitative thresholds related to key stakeholder concerns. Meeting these objectives can greatly strengthen and improve the traditional Environmental Impact Statement process. We are developing a prototype RoED and advancing standards for minimum engagement data, as well as providing guidance on how digital media and documents can best be structured and visualised to record future engagements and decisions.
8:40 AM - 9:00 AM
Geo-problem solving is an exploratory process in which lots of resources and expertise, including geographic data, algorithms, strategies, and models, are used to clarify various geographic processes and phenomena. Due to the complexity of the geo-problem, resources and knowledge from many different domains, including hydrology, meteorology, ecology, and even sociology, are usually adopted for geo-problem solving. Therefore, there is a necessity to conduct geo-problem solving in a participatory manner. However, previous participatory geographic and environmental research mainly focused on several activities, especially modelling and decision-making. For supporting a whole-process exploration of geo-problem solving, existing approaches still require to be improved, and participatory iterative attempts are needed. This paper proposed a participatory strategy for geo-problem solving. Focused on coordinating iterative attempts that conducted by distributed participants, this strategy employs eight tagged activities: (1) context definition and resource collection, (2) data processing, (3) visualization and representation, (4) model construction, (5) model evaluation, (6) quantitative and qualitative analysis, (7) simulation and prediction, (8) decision-making and management. Based on the directed-graph structure, tagged activities can be co-maintained online by distributed participants and linked together to drive the solving progress. Meanwhile, some online tools could be provided in these tagged activities to assist geographically distributed participants in geographic practices. Furthermore, by using the proposed strategy, a prototype web system was developed. And two cases are demonstrated in the prototype system to verify the feasibility and capability of the proposed strategy.
9:00 AM - 9:20 AM
9:20 AM - 9:40 AM
Over 60% of agriculture in India is rainfed; this provides employment opportunities to a large percentage of the population while also contributing substantially to the country's GDP. In recent years rainfed agriculture is becoming unviable because of unpredictable rainfall. As a temporary solution, farmers engaged in agriculture, overcame this shortcoming by using groundwater through tube wells. The policy governing groundwater use in the country is ambiguous to say the least and its implementation is arbitrary. Therefore, groundwater use in many parts of the country has increased exponentially and have led to several adverse effects. The impacts are particularly dire on the poor. Proposed innovations in the efficient use of groundwater to supplement rainfed agriculture are limited to small geographical areas. Experiences of using the System Dynamic (SD) methods in different parts of the world and adopting technology to promote sustainable use of groundwater are well documented. Participatory GIS experiences in order to achieve equity and increase community participation have led to positive impacts for the poor. This paper reviews recent publications in 5 areas connected to rainfed agriculture: rainfed agriculture, climate change, groundwater, system dynamics(SD) and participatory GIS. While focusing on issues of rainfed agriculture and its protection in the Indian context It particularly emphasises the integration of technology and participatory methods in agriculture and groundwater-related issues. The paper concludes with recommendations for scaling up the innovation of integrating socio-technological aspects such as system dynamics and participatory GIS.
10:00 AM - 10:20 AM
A collaborative modelling approach to develop an operational impact-based forecasting system to guide implementation of humanitarian early actions to minimize the impact of flood on vulnerable communities in Ethiopia
10:40 AM - 11:00 AM
Many parts of Ethiopia are frequently affected by flooding, which affects livelihoods of communities. Ethiopian Red cross National Society(ERCS), in collaboration with other stakeholders developed a forecast based action (FBA) plan which aims to reduce the impact of flooding. For ERCS and partners this FBA plan is a guiding tool for timely and effective implementation of early actions during flood emergency response. National disaster risk management commission(NDRPPC),National Meteorological Agency(NMA), Basin Development Authority(BDA), Ministry of Agriculture (MoA), WFP and FAO in Ethiopia are the main stakeholders in the design phase of the FBA, 510 provided technical support for FBA system design. The outcome of FBA system design is an Early Action Protocol (EAP) for floods, which is a guiding document for activation and implementation of early actions when FBA is activated. The EAP is not a replacement of existing DRR plans, it complement existing DRRM plans of NDRPPC and ERCS. Flood anticipatory actions are important to mitigate the impact of flooding but needs to be guided by a credible and reliable early warning system. To fill this requirement an Impact Based Forecasting (IBF) model was developed. In IBF model development, we first identified potential stakeholders and data sources during feasibility study. Based on the outcome of the feasibility study ERCS developed a roadmap for FBA, which includes forming a multi stakeholder TWG committee, among others. The TWG committee is responsible for evaluating IBF model, defining early actions and associated trigger levels. An interactive user interface is created to visualize the implication of danger level selection for each specific areas by evaluating performance of selected danger level based on historical flood events. This helps TWG to define a trigger level for activating early actions. The EAP, after approval international federation of red cross, will be put in action in the coming flood season.
12:00 PM - 12:20 PM
Participatory modelling (PM) is a craft that is often learnt by training ‘on the job’, and mastered through years of experience. There is little explicit knowledge available on identifying and documenting the skills needed to perform PM. The absence of a curriculum for PM is a barrier for building capacity and expertise in research and practice, and the field’s progression to a mature profession. If we cannot define the fundamental skills needed to perform PM practices effectively and the developmental roadmap towards proficiency, then how will we know if participatory modellers are sufficiently qualified for running projects that deliver on the aspirations (e.g. learning) that PM promises? In the absence of some guidelines, PM teachers are left to rely on a network of peers, scattered research literature, and much trial-and-error for developing their teaching resources and practices. The situation is aggravated by PM being a transdisciplinary craft, with no single discipline of skill set to borrow ideas and recommendations from. The ultimate goal of this presentation is to contribute towards building a pedagogical culture for PM. Creating this culture involves promoting debate, investigations, and evaluations concerning the basic and advanced skills for PM, and educational resources needed to acquire and improve these skills. Towards this goal, we focus our effort on the development of a competency framework to characterise PM skills. Our preliminary inquiry into this topic evolves around three subtopics: (1) reviewing and compiling literature on competencies in problem-solving research areas related to PM (e.g. systems thinking), (2) developing guidelines for the competency framework drawing on literature, past experience and expert opinion, and (3) distilling some critical questions for advancing the pedagogy of PM. We augment our inquiry with a conceptual map that positions and links existing definitions and advancements on competency in terms of their relevance to PM.
12:20 PM - 12:40 PM
Participatory simulation is increasingly being used to raise awareness and support collective action on complex environmental problems. During the design of simulation models, choosing between an abstract (or idealized) model that can be used with a wide range of stakeholders, and a more descriptive (or realistic) model that better fits the expectations of certain stakeholders, is often a dilemma. The LittoSIM-GEN project opts for a descriptive simulation approach, but with the possibility to adapt the content to different geographical conditions, and thus increase its reusability. The LittoSIM participatory simulation aims to reinforce social learning among elected municipal officials and risk managers in relation to prevention measures for coastal flooding management. Participatory simulation workshops were organized with local stakeholders, during which they experienced different prevention strategies and assessed their impact against the results of a flooding simulation calculated by a hydrodynamic model. The software architecture used enables the simulation content (land use map, set of available prevention measures, hydrodynamic conditions, etc.) to be adapted to different geographical configurations (e.g. sandy or cliff coastline, highly urbanized or more rural areas). In addition, the way the project was deployed in the field (e.g. the design of the participatory simulation workshop, the stakeholders and institutions invited) was also adapted from one case study to another. This paper reports on the use of LittoSIM in different case studies carried out in three varying geographic contexts along the French coast: the island of Oléron (Atlantic coast), Camargue (Mediterranean coast) and Dieppe-Criel (Channel coast). The results look at the adaptations to the software, simulation content, and to the field deployment method that were needed in order to meet stakeholders' expectations, fit with how risk was managed locally, and encourage stakeholders' engagement in the participatory process.
12:40 PM - 1:00 PM
Decision making required for dealing with wicked socio-technical problems like the energy transition or climate change requires a diversity of perspectives. These different perspectives are hard, if not impossible, to capture within a single model or simulation, created from a single perspective. Participatory multi-modelling offers a way to use participatory modelling methods to connect different models, datasets and stakeholder questions into a coherent boundary object (BO) which can be used for decision support. While constructing a single model within a participatory process is already difficult, multi-modelling brings several new challenges. First, there are multiple models that need to be created, and they may require vastly different domain expertise and modelling tools. Second, the interfaces between models need to be developed both technically and conceptually, thus requiring many additional BOs on which consensus must be reached. Third, the multi-model is a BO that dynamically emerges from interactions between sub-models and whose structure may change while being used. Participatory modelling literature insufficiently addresses the specific challenges of multi-modelling. We explore the participatory multi-modelling process from the lens of many BOs interacting and co-evolving during the process: a boundary object ecology. This perspective provides us with the concepts and vocabulary to explore the interactions in a structured manner. For example, notion of temporal path dependency can reveal (lack of) design choices, as a series of BOs are being constructed and the notion of BO co-evolution within a coupled fitness landscape allows us to explicitly design parallel participatory modelling processes, and their interaction over time. We apply this perspective on a case study and derive several specific design principles for structuring the modelling process.
1:00 PM - 1:20 PM
This work reports on methodological developments of and findings from a series of participatory modelling processes implemented and adapted during several years of participatory action research, in multiple locations in Mexico, facilitating community-based climate change adaptation. The participatory modelling process involves the co-construction and joint use of qualitative, paper-based, causal loop models of the complex, socio-ecological systems in which community livelihoods and wellbeing thrive or fail. The process permits in situ collaborative system identification; co-evaluation of drivers of and threats to that system; and the co-evaluation of measures to mitigate those threats. A community´s vulnerability to climate change tends to be multilocal, that is, its vulnerability can be exacerbated by actors and communities outside, and potentially distant from it. Thus, adaptation measures need to be multi-local too. A problem during the years has been how to upscale the participatory modelling process from households and communities to include networks of communities across larger spatial scales, e.g. at county scale-level, to identify the most effective multi-local adaptation measures. Methodological developments supporting such upscaling include a simple, expressive, livelihoods- and capitals-based syntax and grammar that has permitted both the co-construction of comparable and consistent models, and the rapid training of participatory modelling teams. Model linkage and meta-model development have also contributed, alongside the use of manual, qualitative simulation techniques to allow modellers and participants to directly and jointly use the co-constructed model without software know-how and in locations where reliable energy supplies are not available. This research has led to: a hypothesis explaining socio-ecological system mal-adaptation to threats at different scale-levels leading to county-wide damage to livelihoods, wellbeing and the natural environment; a better understanding of the critical impact that non-extreme climate change events have on vulnerable systems; and warnings of unexpected international policy problems at the community scale.