A system water management meta-model based on Green-Red loop concepts on global scale

With the fast development of human society, achieving global sustainable development still remains a huge challenge. To address this challenge, environmental management within the coupled human-nature system (CHANS) plays a key role. Among many concepts of sustainability, the Green-Red loop (GRL) theory describes generic patterns of environmental management embedded in global human development, but has been so far explained via statistical analysis. In the context of water management, Community Sensitivity (CS) socio-hydrological model simulates regional environmental management decisions based on detailed local physical processes. To have strengths of both dynamic simulation and generic application with a reasonable complexity, we propose a meta-model to investigate integrated land and water management decisions and their feedback effects on human development on global scale. This model includes three loops (two reinforced and one balancing loop) linking five major components that describe a balanced sustainable development from the perspective of environmental management, including quality of life (QoL), development, water infrastructure, footprint and environment. This model is developed and validated based on structural equations using global datasets, for scenarios where systems have degrees of greenness and redness. Results show that (1) social development is currently the dominant factor affecting QoL, while the role of environment is relatively minor; (2) redder systems have stronger effects in social development links, while greener countries have stronger effects in local environment links. This study also calls for a more coordinated future environmental management strategies between water and land. The relationship between people and environment should be strengthened, especially the feedback from environment to indicators describing the QoL. Such models provide a platform for the development of interdisciplinary collaboration to explore the coupled social-environmental systems, to generate options for sustainable future.