Problems manifested within social-ecological systems (SES) exhibit dynamic complexity and hold implications for current and future human well-being and environmental sustainability. The complexity of these issues, the ever-present uncertainty inherent to SES, and the multi-stakeholder settings in which they are discussed call for participatory modelling to support decision-making on socio-environmental issues. Yet, this challenging endeavour requires a structured approach — a modelling cycle — to facilitate engagement with the implications of participation and uncertainty as focal points for Good Modelling Practice (GMP). Here we propose an integrated policy analysis framework for SES modelling using System Dynamics (SD). This framework stems from integrating two existing modelling cycles that individually consider participation and uncertainty in SD modelling. Three global modelling phases and a set of tools to address the participation and uncertainty features in SES modelling are distinguished. The framework contributes to mainstreaming GMP, offering a structured model-based approach to enhance the robustness and social acceptance of policies on critical socio-environmental issues.

The social-ecological systems (SES) approach elicits a broad understanding of some of the most pressing socionatural challenges (e.g. resource scarcity, biodiversity loss, and climate change) and the responsibility that humans have in addressing them. System dynamics has proven a powerful paradigm for dealing with complex SES-related issues. Here we discuss some ethical considerations of using system dynamics (SD) to model SES, something that is often either overlooked or discussed as an isolated issue. Sustainable development and human rights are used as ethical standpoints across the modelling cycle, opening the discussion around guiding principles that need to be considered when modelling SES. Based on these, a set of guiding ethical questions are identified and classified across a participatory SD modelling cycle. This structured approach is a simple yet potentially useful tool for SD practitioners to examine the ethical implications of their modelling endeavours in the context of grand societal challenges.

Water enables health, education, and economic well-being opportunities for humanity. Access to basic water and sanitation services, freshwater variability, and water storage are some of the dimensions that may impact on human development worldwide. Yet few studies quantitatively explore the relationship between water and human development. This study uses a statistical approach to quantify the Water-Human Development relation in a global sample, both in terms of correlation and causality between variables. Correlation is established using a multiple linear regression approach, while causality is explored by implementing the multi-spatial convergent cross mapping technique. Our study finds strong interdependence between water-related variables and human development globally. Access to water services positively influences the Human Development Index (HDI), seasonal variability of freshwater resources restricts it, and large water storage is not significant. The analysis is robust between 2000 and 2017, and implies that a 1% increment in a country's HDI is associated with a 1.3%–3.2% increment in water and sanitation access. Causal analyses show strong coupling, suggesting positive feedback between access to water services and HDI that could be exploited. Reaching Sustainable Development Goal 6 requires closing the water and sanitation access gaps while addressing freshwater variability challenges. This will result in global human development benefits.