There is a growing interest in the literature on the theme of the water–energy–food nexus, as there is growing recognition that sectors that share natural resources have interdependent and interconnected systems. Despite the widespread popularity of nexus thinking, it still lacks standardized procedures and methodologies to assist in its development. Therefore, this paper proposes, from a literature review, a systematic procedure to assist in the development of management models based on nexus thinking. To this end, 304 papers were analyzed using the following criteria: nexus concept, type of approach, geographic scale, elements in the nexus system, application context, and types of assessment methods and tools. The results of the review served as the basis for determining the procedure, which consisted of four steps: (a) understanding nexus thinking, (b) identification of composing variables, (c) evaluation (diagnosis and prognosis), and (d) decision-making. In addition to the standardization of these steps, the main information used to compose the procedure was organized and synthesized with a mind map.

Obtaining databases to develop multidisciplinary studies in complex intersectoral network systems presents great challenges. Databases often lack compatibility or data standardization because they are organized differently by sector. Therefore, this article aims to propose a Decision Support System (DSS) to assist in the identification, analysis, and selection of sectoral databases to support the development of quantitative studies. The concept of the “Nexus of water, energy, agriculture, and the environment" is used to illustrate the development of the DSS. To this end, a conceptual structure defined in six stages was presented: institutional analysis, definition of alternatives, definition of criteria, analysis of databases, classification matrix, and organization and selection of alternatives. Validation of the proposed DSS was carried out using national-scale databases for the Brazilian context. From the application of DSS in the databases surveyed, it appears that: Brazil does not have interconnected databases, nor does it share databases between sectors; the information is dispersed across a large number of institutions, and includes a multiplicity of spatial and temporal scales, hindering their integration; the adoption of macro-scales, both spatially and temporally, facilitates the integration of the collected information, and the country’s sectoral organizational structures tend to hamper the development of systems integrated into complex networks. The proposed DSS allows a better understanding and visualization of possible simplifications and limitations inherent in integrated studies of quantitative scope, minimizes uncertainties, and directs systemic planning and management strategies.