d2c5c550-3460-469e-af50-390ba0455d86 English 2024-05-09T09:17:57.07538Z UK GEMINI 2.3 EPSG:27700 WSIMOD (the Water Systems Integration Modelling framework) WSIMOD has been developed at Imperial College London, bringing together 3 years of integrated urban and rural water cycle modelling into a single Python package. The package enables: -Automated parameter extraction and model setup for any English river catchments, with extensive documentation on acquiring datasets used. -A component library that contains a default Python implementation of many different parts of the water cycle. -An integration framework and model object that enables assembling components into a simulation model, and for running simulations. WSIMOD is a Python package that will be made open source and continuously updated and support by WSI group researchers. The intention is that its use will become more widespread and continue to be developed by a community of users. Imperial College London Dr Barnaby Dobson b.dobson@imperial.ac.uk https://camellia-metadata.bgs.ac.uk/geonetwork/srv/api/records/d2c5c550-3460-469e-af50-390ba0455d86/attachments/wsimod.PNG wsimod.PNG GEMET - INSPIRE themes, version 1.0 2008-06-01 geonetwork.thesaurus.external.theme.httpinspireeceuropaeutheme-theme CAMELLIA, Integrated Water Systems Modelling, England license – BSD-3 Clause (though to be confirmed) license – BSD-3 Clause (though to be confirmed) English inlandWaters environment utilitiesCommunication http://data.os.uk/id/country/england -6.41894185058714 1.7689121033873 49.8646362595373 55.8116598334548 2000-01-01 2020-01-01 Python package https://github.com/barneydobson/wsi WWW:LINK-1.0-http--samples GitHub Repository for WSIMOD Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 false WSIMOD brings together a range of existing software and models, based on both the code and our experience with other case studies. The iterations of our approach that it most closely builds on are CityWat-SemiDistributed (https://doi.org/10.3389/frwa.2021.641462) and CatchWat (https://doi.org/10.1016/j.scitotenv.2021.150642).