ANEMI3: An updated tool for global change analysis

Abstract

The ANEMI model is an integrated assessment model of global change that emphasizes the role of water resources. The model is based on the principles of system dynamics simulation to analyze changes in the Earth system using feedback processes. Securing water resources for the future is a key issue of global change, and ties into global systems of population growth, climate change, carbon cycle, hydrologic cycle, economy, energy production, land use and pollution generation. Here the third iteration of the model–ANEMI3 is described, along with the methods used for parameter estimation and model testing. The main differences between ANEMI3 and previous versions include: (i) implementation of the energy-economy system based on the principles of system dynamics simulation; (ii) incorporation of water supply as an additional sector in the global economy that parallels the production of energy; (iii) inclusion of climate change effects on land yield and potentially arable land for food production, and (iv) addition of nitrogen and phosphorus based nutrient cycles as indicators of global water quality, which affect the development of surface water supplies. The model is intended for analyzing long-term global feedbacks which drive global change. Because of this, there are limitations related to the spatial scale that is used. However, the model’s simplicity can be considered a strength, as it allows for the driving feedbacks to be more easily identified. The model in its current form allows for a variety of scenarios to be created to address global issues such as climate change from an integrated perspective, or to examine the change in one model sector on Earth system behaviour. The endogenous structure of the model allows for global change to be driven entirely by model structure rather than exogenous inputs. The new additions to the ANEMI3 model are found to capture long term trends associated with global change, while allowing for the development of water supplies to be represented using an integrated approach considering global economy and surface water quality.

Global Change Explorer—A Web-Based Tool for Investigating the Complexities of Global Change †

“…The model sectors that comprise the ANEMI model are climate, carbon, nutrient, and hydrologic cycles; population dynamics; land use; food production; sea level rise; energy production; the global economy; persistent pollution; water demand; and water supply development (detailed descriptions of each model sector are available in [4]). The high-level model structure is shown in Figure 1.…”

“…Up to now, the main investigations conducted by the ANEMI model focused on simulating various future scenarios related to five main themes: (i) climate change; (ii) population dynamics; (iii) food production; (iv) water quality; and (v) water quantity. For a detailed description of the tested scenarios, please refer to [4].…”

“…GCE allows for the interactive investigation of global change complexities. It uses ANEMI, a system dynamics simulation model developed at the University of Western Ontario [2][3][4]. ANEMI is named after the Greek Anemoi gods of the four winds: Boreas the north wind (bringing the cold breath of winter), Zephryos the west wind (the god of spring breezes), Notos the south wind (the god of summer rain-storms), and Euros the east wind (associated with the season of autumn).…”

Development of a water‐energy‐food nexus model for multiscale studies

“…The CLEWs (Saif & Almansoori, 2017) model focuses on assessing interlinkages between resources to understand how security depends on the production and use of food, energy and water. Also, the ANEMI3 model (Breach & Simonovic, 2021) includes the integrated assessment of global change. Water resources play an essential part in this model, which incorporates system dynamics simulation to allow users to experiment with various policy options in light of global climate change, but food and energy security is ignored.…”

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

“…Projections of future land change vary considerably across methods, scenarios, initial conditions, assumptions, and goals (Alexander et al, 2017), but the total land area remains relatively constant. Land‐use models include stock and flow models (Strapasson et al, 2017), rule‐based spatial allocation models (e.g., Ball et al, 2022; Engström et al, 2016; Meiyappan et al, 2014), demand‐driven spatial allocation models (e.g., Stehfest et al, 2014; Van Asselen & Verburg, 2013), computable general equilibrium models (e.g., Fujimori et al, 2014; Woltjer & Kuiper, 2014), partial equilibrium models (e.g., Calvin et al, 2019; Dietrich et al, 2019; Havlík et al, 2011; Steinbuks & Hertel, 2016), and disequilibrium models (Breach & Simonovic, 2021). Scenarios are related to research goals, as SSP/RCP scenarios focus on mitigation targets and are used by earth system models (Popp et al, 2017; Riahi et al, 2017), bioenergy scenarios explore various limits and tradeoffs to bioenergy production (Calvin et al, 2014; Humpenöder et al, 2018; Kraxner et al, 2013; Rose et al, 2022; Searle & Malins, 2015; Strapasson et al, 2017), and food security and biodiversity studies consider impacts of changing agricultural productivity and land use in the context of food, fuel, and fiber demands (Delzeit et al, 2017; Henry et al, 2018; Hof et al, 2018; Santangeli et al, 2016; Zabel et al, 2019).…”