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Nexus Tools Platform (beta)

An interactive Nexus Tools Platform (NTP) for inter-model comparison of existing tools was developed to facilitate the selection of the most appropriate (set of) model(s) for exploring interlinkages of water, soil and waste resources and advancing integrated management.

Advancing the Nexus approach

Realizing the Water-Soil-Waste-Nexus Approach requires a holistic understanding of the interlinkages of environmental processes, while also taking into consideration global change and socioeconomic aspects. Exploring these interlinkages and advancing an integrated management approach requires integrated modelling tools. However, no single modelling tool is available or conceivable that covers all processes, interactions and drivers in the Water-Soil-Waste Nexus. Instead, a vast number of models are available and in use addressing particular (sets of) processes and resources. To address nexus-oriented research questions or management issues, instead of developing a tool from scratch, it should more efficient and effective to make use of available tools and modify or couple them as required. For this to be possible, we first need a database that allows the interactive comparison of such tools.

In 2015, UNU-FLORES launched the alpha version of an interactive Nexus Tools Platform (NTP) for inter-model comparison of existing tools. Continually being improved, NTP aims to provide detailed information on a subset of a larger compilation of available modelling tools. For this subset of models key features and parameters, as given in the table columns have been compiled based on available model descriptions. When looking for particular features or processes to be considered by a model NTP allows to select and deselect columns as appropriate. Empty table fields indicate that we did not have information about that aspect; „true“ and „false“ indicate that this aspect is or is not considered by the model. The platform offers interactive charts and advanced search and filter functions that allow selecting the most appropriate (set of) model(s) for the specific needs and to do a gap analysis of current model capabilities.

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