Systemic feedback modelling for sustainable water resources management and agricultural development: An application of participatory modelling approach in the Volta River Basin
Graphical abstract
Introduction
In the last two decades, concerns have been raised at the global scale about the need and challenge for sustainable water resource management in an era of rapid global change, and pervasive water and food insecurity (Pahl-Wostl et al., 2013, Girard et al., 2015, Sivapalan, 2015). Although our understanding of water resource problems has grown in recent years, our ability to improve decision-making is still limited (Pahl-Wostl et al., 2011, Pahl-Wostl et al., 2013). New approaches have been exploring the potential of computer modelling methods that allow environmental problems to be considered in a holistic manner with active stakeholder involvement (Videira et al., 2011). More specifically, participatory modelling (PM) and stakeholder engagement is seen as an important tool that can facilitate strategic decision-making in complex environmental/natural resource management systems (Voinov and Bousquet, 2010, Stave, 2010, Laniak et al., 2013, Videira et al., 2014, Voinov et al., 2016). According to Reed (2008) the dynamic and complex nature of environmental issues call for a flexible and transparent decision-making that balances scientific findings with multi-faceted input from a range of stakeholders and decision-makers, many of whom have different values, perspectives, and objectives.
PM is particularly well-suited for the growing emphasis on integrated water resources management that aims to provide an improved understanding of water resources systems while considering biophysical and socio-economic concerns (Voinov and Gaddis, 2008). The involvement of stakeholders in modelling complex systems has grown considerably in the last decade (d’aquino and Bah, 2014). PM has been designed and implemented in several river basins or watersheds around the world (e.g., Metcalf et al., 2010, Beall et al., 2011, Carmona et al., 2013, Hewitt et al., 2014, Robles-Morua et al., 2014, Butler and Adamowski, 2015, Inam et al., 2015, Safavi et al., 2015). However, a search in Google Scholar, Scopus, and Web of Science revealed that some forms of PM have been used to develop models for land use polices in dryland Sahelian region in Africa (e.g., d’aquino and Bah, 2013, d’aquino and Bah, 2014), but it has only been implemented in one out of the over 60 river basins or watersheds across Africa. The study by Farolfi et al. (2010) used a form of PM (Companion Modelling) to develop multi-agent models to represent water supply and demand dynamics for the Kat River Valley in South Africa but the models developed did not consider the feedback processes operating between the system components. Simonovic et al. (1997) has also used the system dynamics approach for long-term water resources planning and policy analysis for the Nile River basin in Egypt, but the study is mainly quantitative and more importantly, did not benefit from stakeholder perspectives. Therefore, there is the need to complement quantitative simulations with conceptual or qualitative models that incorporate stakeholder knowledge and perspectives.
Indeed, conceptual modelling has been an important component of PM and of successful application of adaptive management to natural resource problems (Argent et al., 2016). However, system conceptualisation within the integrated environmental modelling community remains limited (Laniak et al., 2013). A review of dynamic modelling in water resources systems indicates that a majority of system dynamics applications have not made adequate use of qualitative modelling tools (Mirchi et al., 2012). However, a number of studies (e.g., Gupta et al., 2012, Herr et al., 2015, Argent et al., 2016) suggest that qualitative or conceptual modelling provides a means to developing an understanding of a complex system, particularly when there is uncertainty about the system or limitations of quantitative data. Moreover, many of existing PM studies tend to focus on the modelling process rather than the model itself (Voinov et al., 2014). Consequently, it has been suggested that modellers pay attention to the participatory as well as the modelling process and the model outcomes/outputs (e.g., van den Belt et al., 2010, Voinov and Bousquet, 2010, Videira et al., 2012).
The preceding knowledge gaps need to be filled in order to improve our understanding and management of environmental/natural resource systems. Thus, this paper presents the participatory and methodological processes involved in the development of an integrated qualitative, conceptual model that captures the causal non-linear relationships between the key and multiple biophysical and socio-economic drivers and processes in the Volta River Basin (VRB) in West Africa, highlighting the key or dominant feedback loops. According to Kelly et al. (2013), models are built for a number of purposes including, prediction, forecasting, management and decision-making under uncertainty, for social learning, and for developing system understanding/experimentation. The purpose of the model developed in this study is to provide for a better understanding of the feedback structure and dynamic behaviour of the basin, and to provide a knowledge base in the form a decision support tool that would assist water resources management and sustainable agricultural development. The approach adopted herein, focuses on both the model development process and an evaluation of the participatory process as well as the model outcomes/outputs, highlighting some salient lessons in the light of recent progress in PM approach and systems thinking research.
Section snippets
Context of the study
The PM exercise was implemented in the VRB, which is one of Africa's most important river systems (or 'catchment'). It occupies an area of approximately 400,000 Km2 within the sub-humid to semi-arid West African savannah zone (Fig. 1). The river basin is a transboundary watershed shared among six riparians West African countries: Burkina Faso, Ghana, Togo, Benin, Cote d’Ivoire, and Mali. The basin is made up of three sub-basin basins: the Black Volta, the White Volta, and the Oti river basin
Participatory modelling approach
PM approach based on the principles of system thinking is the use of a system dynamics perspective in which stakeholders or clients participate to some degree in different stages of the process, including problem definition, system description, identification of policy levers, model development and/or policy analysis (Stave, 2010. p. 2766). The approach is based on the notion that people who reside and work in a system may be better informed about its processes and probably have observed
Biophysical/environmental sub-model
The CLD representing the biophysical/environmental domain is shown in Fig. 3. Stakeholders within this domain have identified 19 drivers of change and issues. The model was constructed around the issues of climate change, available ground and surface water, total agricultural production, and crop yield.
Economic and policy sub-model
The economic and technology sub-model is depicted in Fig. 4. The model consists of 23 variables. Overall, the economic and policy sub-model appears to be underpinned by five fundamental drivers
Systemic feedback effects and leverage points
In this paper, a qualitative conceptual model was developed to enhance our holistic understanding and management of water resources and improve agricultural development in the VRB. The integrated conceptual model developed here differ from other science based-models in that it is not linear, rather, it is cyclical, giving consideration to the complex non-linear feedbacks between the critical suite of biophysical, socioeconomic, policy and institutional processes that determine the structure and
Conclusions
The overarching purpose of this study was to develop an integrated qualitative, conceptual system dynamic model that can be used to understand the feedback structure and behaviour of the VRB system as well as a decision support tool to assist sustainable water resources management and agricultural development. Toward this end, a PM approach, based on the principle of system thinking and system dynamics was employed. Within this approach, CLDs were used as system visualisation tools to capture
Acknowledgments
This research was supported financially by The Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia through the Integrated Natural Resource Management (INRM) science program and School Research Grant (SRG) from the School of Geography, Planning and environmental Management (GPEM), University of Queensland, Australia. We are grateful to Dr. Dr Oscar Yawson (University of Cape Coast) for helping to facilitate the workshop. More importantly, the participants who
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