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The document defines rural land-use planning as a continuous and participatory process designed to align objectives and goals while managing risks and uncertainties. It outlines the methodology's role in decision-making and indicates that the text details the specific steps, activities, resulting products, and common techniques used in this planning process.

The authors demonstrate how combining service design—specifically using archetypes and prototyping—with discrete choice experiments can create effective development interventions, such as Weather Index Insurance for Ugandan farmers, by involving users in the design process and testing core assumptions.

The document details the development of SELECT ECOTECH, a serious game system (SGS) designed as a learning platform for stakeholders in the Baltic Sea Region (BSR). The game aims to foster systemic awareness and adaptive capacity when selecting eco-technologies to reduce nutrient and carbon emissions while maximizing co-benefits. Co-designed with stakeholders from three case study catchments—Fyrisån (Sweden), Vantaanjoki (Finland), and Slupia (Poland)—the game uses a board game format to simulate 'wicked' situations, including system shocks and policy changes. The report outlines a three-phase participatory design process, the game's rules regarding baseline emissions and resource management, and the specific eco-technologies and developments integrated into the system. The findings suggest that the iterative, playful nature of the SGS allows stakeholders to cross knowledge boundaries and experiment with innovative technology constellations beyond technocratic solutions.

The document introduces Aqueduct 3.0, a framework that translates complex hydrological data into intuitive water-related risk indicators. It combines 13 indicators covering quantity, quality, and reputational risks into a composite score to help decision-makers identify high-risk regions or assets. The updated version features a new hydrological model with integrated supply and demand, surface and groundwater modeling, higher spatial resolution, and monthly time series data.

The Stockholm Environment Institute (SEI) utilizes a Robust Decision Support (RDS) approach that integrates water systems modelling, participatory techniques, and interactive data visualization via Tableau. This method addresses the challenge of communicating vast amounts of data from complex models, such as the Water Evaluation and Planning (WEAP) system, to non-scientists. By using multi-field graphics and interactive filters, stakeholders can evaluate system vulnerability across numerous scenarios and assess the trade-offs of different management strategies, such as dam construction, to identify robust solutions for an uncertain future.

The document outlines the use of HadCM3 and Parallel Climate Model (PCM) data, combined with IPCC 2000 emission scenarios and a century of historical records, to project climate changes in the Great Lakes region. The analysis indicates greater temperature increases, especially in summer, and general drying during summer and fall compared to previous assessments.

The CRED v.1.4 technical report details an integrated assessment model designed to optimize the pace and distribution of emissions mitigation investments across 16 global regions. The model utilizes a Cobb-Douglas production function that accounts for the productivity of 'green capital' and employs a vulnerability index to apportion global climate damages. Key updates in version 1.4 include a 2010 base year, expanded regional disaggregation, and a climate module recalibrated to match the MAGICC5.3 model. The model's optimization process maximizes a global utility function based on regional per capita consumption, with an optional feature to calculate the social cost of carbon.

The CRED v.1.3 model is an integrated assessment tool designed to project global climate and development scenarios over a 300-year period. It focuses on the distribution of climate damages and policy costs across nine global regions, utilizing a Cobb-Douglas production function and a vulnerability index to allocate damages. The model incorporates updated population data, four selectable damage functions, and abatement cost curves based on McKinsey data to inform global climate negotiations.

The Resources and Energy Analysis Programme (REAP) is a software tool developed by the Stockholm Environment Institute (SEI) that uses an environmentally extended input-output model to track greenhouse gas emissions, air pollutants, and ecological footprints based on consumption rather than just production. By distinguishing between domestic and imported goods across 178 sectors, REAP allows users to create quantifiable scenarios based on the IPAT formula (Population, Affluence, and Technology) to test policy interventions. The tool has been applied to various UK sectors, including the NHS and tourism, and used in regional planning, such as housing scenarios in the Tees Valley. SEI is expanding the tool's application to EU-27 members, Sweden, and the Basque Country.

The project addresses the lack of long-term climate data in the tropical Andes by combining dendrochronology, improved hydrometeorological networks, in-situ digital sensors, and global circulation models. These diverse data streams—including tree-ring chronologies spanning 100 to 200 years and simulations for 2011-2030 and 2045-2065—are integrated to reduce uncertainty in climate projections and inform the NatureServe vulnerability index for conservation management.

The World Resources Institute developed a baseline water risk model for Ethiopia using 2015 data to help decision-makers incorporate water-related climate risk into sectoral planning. The model utilizes geospatially-explicit estimates for irrigation, livestock, domestic, and industrial water use, combined with 36 years of remotely-sensed renewable water resources data. It generates four key indicators: baseline water stress, months of water scarcity, seasonal variability, and interannual variability. The model is intended for national-level scenario analysis and monitoring of Sustainable Development Goal target 6.4.2, though it excludes water storage infrastructure, environmental flow requirements, and transboundary water obligations.

The document outlines the data sources and assumptions used to calculate annual GHG reduction rates for Canada, the EU-28, Japan, and the US between 2020 and 2030. It specifies that estimates are provided both with and without the land use, land-use change, and forestry (LULUCF) sector to ensure comparability. The calculations rely on historical emissions data from national inventory reports submitted to the UNFCCC and specific target percentages for 2020 and 2030 (or 2025/2050 for the US) relative to various base years.

The World Resources Institute (WRI) developed BWS-China to provide more granular water risk mapping by using prefecture-level water withdrawal data for over 300 cities. While BWS-China shares similar spatial patterns with Aqueduct's global indicator, the use of detailed country-specific data reveals more accurate spatial patterns and sector-specific risks in certain catchments. This approach serves as a model for other countries to develop detailed baseline water stress indicators to support corporate investment decisions and government policymaking.