# Explaining and Measuring Social-Ecological Pathways: The Case of Global Changes and Water Security
## 1 Introduction  
Pressures on natural resources are increasing and a number of challenges need to be overcome to address growing population in a period of environmental variability. The key to sustainable development is achieving a balance between the exploitation of natural resources for socio-economic development, and conserving ecosystem services that are critical to humans' wellbeing and livelihoods [1]. The policy objective of water security is symptomatic of this challenge [2; 3; 4]. Water is a crucial natural resource supporting life on Earth and underpinning equitable, stable, and productive societies and ecosystems [5]. The cumulative effects of overexploitation, pollution, and challenges posed by climate change demand careful monitoring and assessing of trends and evolution of water resources [6]. This is an essential pre-condition to ensure a sustainable use and access to water that can serve as a basis for water security. This important role has been recognized as one of the seventeen Sustainable Development Goals (SDGs) defined by the United Nations. From a territorial management perspective, to support monitoring and reporting commitments and obligations, managers and decision-makers need information that is synoptic, consistent, spatially explicit and sufficiently detailed to capture anthropogenic effects [7]. The Social-Ecological Systems (SES) framework combines different components to organize consistently the analysis of human and nature co-evolution [8]. It is designed as a diagnostic tool tosupport identification of relevant variables that can determine sustainability in SESs and allow for analysis of relationships among levels and scales. As such, it contributes to a common framework to facilitate multidisciplinary research efforts, better understanding and study of the complexity of these systems [8], and cross-institutional comparisons and evaluations [9]. However, SES lacks a robust understanding of change because of a limited number of empirical studies and its use as a checklist [10]. We argue an analytical and methodological approach to engaging global changes in SES is critical to strengthening the scope and relevance of the SES framework. Identifying the methodological needs for carrying-out large-N (>100 observations) dynamic analyses of SESs is needed for knowledge accumulation. In this paper, we put forward a way to explain change and dynamics in SES that could be testable across many cases. Current literature offers mainly in-depth investigations highlighting mechanisms and triggers of changes. However, there is a need to scale-up the knowledge toward more generalizable results [11; 12]. Relying on SES and resilience thinking, we propose an institutional and cognitive model of change for SES where institutions and natural resource systems co-evolve. Our SES model of change offers a dynamic understanding of SES, and stands on three causal mechanisms: institutional complexity trap, rigidity trap, and learning processes. We argue that this model of change can enable systematic and explanatory tests, and combine them. Methodologically, we highlight current methodological limitations regarding measurement heterogeneity and time-limited analysis and emphasize the need for carrying out studies about SES dynamics. Then, we provide insights on how to operationalize this, mainly through measurement rather than methodological tools. Data cube technology could overcome current methodological limitations. This technology is a new big data tool providing ready-for-analysis datasets that combine Earth observation data over years as well as space [13; 14]. It requires no major technical skills from users or researchers and offers reliable avenues to test hypothesis about the dynamics of social-ecological systems and water security by offering to combine spatial and time data with no major technical requirements for users.