## 5 Analysis of Existing Models by Thematic Applications  
In this section, we analyse existing models focusing on agricultural systems by main thematic applications with an emphasis on models used for agricultural policy development at the national level. The analysis focuses on an existing suite of models, skills and data needed to run the models, and how they are used to address global sustainability and adaptation challenges. A wide range of skills are needed to run the models, such as GIS knowledge, statistical or geostatistical knowledge, crop/soils/climate knowledge, and computer skills like programming. The models selected are organised into six thematic applications where DST directly informs policy and the decision-making process, and other environmental models create knowledge of environmental issues and can be used directly or as inputs of DST to inform policy of decision-making (Table 1):  
* Decision Support Tools (DST) are developed to support decision-makers in addressing policy or conservation questions (Table 1). For example, the Integrated Sustainable Development Goals (iSDG) is a DST that was developed by the UN via the Millennium Institute to analyse the 17 SDG goals and impacts of changes for each country to help in the development of appropriate policies. The European Common Agricultural Policy Regionalised Impact (CAPRI) Modelling System is another DST example that was developed to support decision-making related to the Common Agricultural Policy [41]. The American Trade-Off Analysis-Multidimensional (TOA-MD) impact assessment model simulates economic, environmental, and social impacts of agricultural systems [38]. The Australian Multi-Criteria Analysis Shell (MCAS-S) for Spatial Decision Support allows stakeholders seeing the effects of land-use change decisions [115]. The American Agricultural Conservation Planning Framework (ACPF) identifies site-specific opportunities to install conservation practices across small watersheds [116; 117; 118]. The Reflexive Interactive Design (RIO) conceptual approach works as an expert consultation guideline [119; 120]. * Crop models are simulation models describing the crop growth processes and development for varying weather, soil, and management conditions. Widely used crop models (Table 1) include the Agricultural Model Intercomparison and Improvement Project (AgMip) linking climate, crop, and economic modelling to improve models and project scenarios under climate change conditions for several agricultural sectors [121]. The Agricultural Production System sIMulator (APSIM) [93], the Decision SupportSystem for Agrotechnology Transfer (DSSAT) [122], or Aquacrop model to assess crop growth, crop yield or food security issues [123]. Other crop models not presented in Table 1 included models that are focussed on enhancing scientific understanding, more complex to use, and required a large amount of data and skills. * General water models (Table 1) are developed to understand or manage water quality and quantity of hydrological processes under different physical and management conditions. Two water models provided by FAO are CropWat, that links crop and water modelling to calculate crop water and irrigation requirements based on soil, climate, and crop data [124], and Aquastats, which monitors the SDG 6 (ensure availability and sustainable management of water and sanitation for all), and in particular on water stress and water use efficiency [125]. Other widely used water models include WaterWorld [126], developed to understand hydrological processes and water resources, and the Soil and Water Assessment Tool (SWAT), a small watershed to river basin-scale model used to simulate the quality and quantity of surface and ground water, and predict the environmental impact of land use, land management practices, and climate change [127; 128]. Additionally, many multi-service platforms provide general water modelling tools. * Greenhouse gas emission (GHG) calculators mostly focus on deterministically estimating carbon and methane emissions (Table 1).