Complexity of water management: System Dynamics versus Conventional methods

Water management issues have significant short- and long-term repercussions. They are under constant pressure from factors such as population growth, socio-economic policies, intensive irrigation and the impact of climate change. Systems thinking aims to understand how the interactions between subsystems impact the overall behavior of a system in order to tackle these challenges. System dynamics, a systemic approach that assesses the impact of policy options on a system, facilitates a holistic understanding of complex water resource systems and strategic decision-making by providing qualitative and quantitative insights into the system. This study aims to highlight the applications of system dynamics modelling in sustainable water resource management and compare it with conventional water resource management methods. To this end, a methodological assessment was conducted on several articles from the literature, considering the social, environmental, hydrological, and economic subsystems and the modeling approaches used. The results of this study show that conventional analysis of water resource management systems does not always provide a complete picture of the problem and sometimes leads to biased strategies. Traditional approaches often focus on increasing supply and reducing demand without considering the complex interactions governing water resource behavior. The result is quick-fix solutions that often lead to unforeseen and sometimes catastrophic long-term results. Therefore, System dynamics is a solution that considers the system's physical, legal and behavioral processes, adopting a holistic vision to analyze the complex structure that generates the systemic behavior of water resources. In conclusion, we demonstrate that through system dynamics modelling, sustainable water resource management enables the design of strategies that promote integrated water resource management, considering physical, economic, social and legal dimensions. It also enables in-depth exploration and facilitates communication of results to decision-makers.