Apart from research publications, the work of Michelle and her group of PhDs and postdocs also resulted in several publicly available datasets and research codes.

DynQual water quality modelling:

• Global monthly hydrology (PCR-GLOBWB model) and water quality datasets (DynQual model) for 1980-2019 at 10 km spatial resolution (link) and at 0.5 degree resolution (link) and in Google Earth Engine (link)
• Global monthly averaged TDS, BOD and FC concentrations between 2021 and 2030 at 10km spatial resolution (link)
• Global hydrological and surface water quality output for 2005-2100 at 10 km resolution, per GCM and global change scenario (RCP–SSP) (link)
• DynQual global surface water quality model code (link)

Water quality monitoring data:

• Global dataset of surface water and groundwater salinity measurements from 1980–2019 (link)
• Global water quality monitoring data and python scripts for analysing impacts of droughts and heatwaves on global river water quality (1980-2021) (link)

Wastewater data:

• Country-level and gridded estimates of wastewater production, collection, treatment and reuse (link)

Sectoral water use data:

• Sectoral water use responses to droughts and heatwaves: analyses from local to global scales for 1990–2019 (link)