The csv files "Fig2_mean_cv_50", "Fig3_interGCM_agreement_5percent" and "Fig4_MultiPollutant_agreement" contain the main results of Bak, Micella et al. (2025). The model results are presented by river sub-basin for the years 2010 and 2050. These results are obtained by the VIC-MARINA-Multi modelling framework using forcing data from 5 global climate models for 2010 and 2050 under an economy-driven and high global warming scenario (SSP5-RCP8.5), following the methodology as described in the "Methods" section of the paper and in the "Supplementary Information" of the paper. The folder contains "Fig2_codebook.csv", "Fig3_codebook.csv" and "Fig4_codebook.csv" files for further description of the parameters.

Analyzing the impacts of drought and climate change on hydropower requires detailed data not only on hydropower attributes such as plant type, head, and installed capacity, but also on reservoir characteristics like area, depth, and volume. Current open-source hydropower datasets typically lack information on reservoirs, while reservoir datasets often omit hydropower details. GloHydroRes is a global dataset that integrates open-source hydropower and reservoir data, offering 29 attributes, including key information such as installed capacity, plant type, dam height, reservoir depth, area, volume, and river name. Overall, GloHydroRes provides data on 7,775 hydropower plants across 128 countries.

Analyzing the impacts of drought and climate change on hydropower requires detailed data not only on hydropower attributes such as plant type, head, and installed capacity, but also on reservoir characteristics like area, depth, and volume. Current open-source hydropower datasets typically lack information on reservoirs, while reservoir datasets often omit hydropower details. GloHydroRes is a global dataset that integrates open-source hydropower and reservoir data, offering 29 attributes, including key information such as installed capacity, plant type, dam height, reservoir depth, area, volume, and river name. Overall, GloHydroRes provides data on 7,775 hydropower plants across 128 countries.

Output data of water withdrawals and water allocation per water source from the sectoral water use and allocation model (QUAlloc).Dataset properties:spatial resolution: 10 km (global-scale)temporal resolution: monthly time-stepperiod: 1980 - 2019units: m3/monthOutput datasets:     _allocated_to_monthlyTot_1980_2019.nc"withdrawal": refers to the water that is withdrawn at a water source level to satisfy the demands within an allocation zone"demand": refers to the withdrawn water that is supplied to each location (cell) where there are demands to satisfy"domestic""irrigation""livestock""manufacture""thermoelectric""renewable_surfacewater": refers to water obtained from the surface water system components (e.g., direct runoff, base flow, interflow, etc.)"renewable_groundwater": refers to water obtained from aquifers that are recharged by percolation from the upper soil layers"nonrenewable_groundwater": refers to water obtained from aquifers not replenished on a human time scaleThe sectoral water use and allocation model used, QUAlloc, can be found at: https://github.com/SustainableWaterSystems/QUAlloc.

Output data of water withdrawals and water allocation per water source from the sectoral water use and allocation model (QUAlloc).Dataset properties:spatial resolution: 10 km (global-scale)temporal resolution: monthly time-stepperiod: 1980 - 2019units: m3/monthOutput datasets:     _allocated_to_monthlyTot_1980_2019.nc"withdrawal": refers to the water that is withdrawn at a water source level to satisfy the demands within an allocation zone"demand": refers to the withdrawn water that is supplied to each location (cell) where there are demands to satisfy"domestic""irrigation""livestock""manufacture""thermoelectric""renewable_surfacewater": refers to water obtained from the surface water system components (e.g., direct runoff, base flow, interflow, etc.)"renewable_groundwater": refers to water obtained from aquifers that are recharged by percolation from the upper soil layers"nonrenewable_groundwater": refers to water obtained from aquifers not replenished on a human time scaleThe sectoral water use and allocation model used, QUAlloc, can be found at: https://github.com/SustainableWaterSystems/QUAlloc.

Analyzing the impacts of drought and climate change on hydropower requires detailed data not only on hydropower attributes such as plant type, head, and installed capacity, but also on reservoir characteristics like area, depth, and volume. Current open-source hydropower datasets typically lack information on reservoirs, while reservoir datasets often omit hydropower details. GloHydroRes is a global dataset that integrates open-source hydropower and reservoir data, offering 29 attributes, including key information such as installed capacity, plant type, dam height, reservoir depth, area, volume, and river name. Overall, GloHydroRes provides data on 7,775 hydropower plants across 128 countries.

Population exposure to clean water scarcity (expressed in billion people, and as a percentage) per geographic region under uncertain climate change and socioeconomic developments.Water scarcity is quantified considering water quantity aspects only (WS) and also including surface water quality (WSq). Assessments are made on the basis of monthly output data of sectoral water demands (domestic, industrial, livestock and irrigation), water availability (e.g. discharge) and water quality (total dissolved solids, biological oxygen demand and fecal coliform) simulated by a coupled global hydrological (PCR-GLOBWB2) and surface water quality (DynQual) model.

In this study, we assessed clean-water scaricty for >10,000 sub-basins worldwide. To do this, we developed clean-water scarcity indicators including a water quantity-based indicator and a water quality-based indicator. To quantify these indicators, we combined the MARINA-Nutrients (Model to Assess River Inputs of pollutaNts to seAs), MAgPIE (Model of Agricultural Production and its Impact on the Environment), and VIC (Variable Infiltration Capacity) models into an integrated modelling framework (in Figure 1 of the publication).

Population exposure to clean water scarcity (expressed in billion people, and as a percentage) per geographic region under uncertain climate change and socioeconomic developments.Water scarcity is quantified considering water quantity aspects only (WS) and also including surface water quality (WSq). Assessments are made on the basis of monthly output data of sectoral water demands (domestic, industrial, livestock and irrigation), water availability (e.g. discharge) and water quality (total dissolved solids, biological oxygen demand and fecal coliform) simulated by a coupled global hydrological (PCR-GLOBWB2) and surface water quality (DynQual) model.

Global ~50km (30 arcmin) surface water quality data from the dynamical surface water quality model (DynQual) from 1980-2019, with annual, monthly and daily temporal resolution. Simulations are made following the ISIMIP3a protocol (https://protocol.isimip.org/#/ISIMIP3a).Output data includes:Salinity; as indicated by TDS concentrations (mg l-1)Organic pollution; as indicated by BOD concentrations (mg l-1)Pathogen/bacterial pollution; as indicated by FC concentrations (cfu 100ml-1)Simulations were originally made at 5-arcmin resolution and aggregated to 30 arcmin 0.5 degree by summing the in-stream (routed) loadings and channel storage over the aggregated area (at daily, monthly and annual timesteps), and subsequently calculating in-stream concentrations. Please note the aggregation technique is provisional and thus the data is subject to change.Note. A minimum discharge threshold of 0.1 m3 s-1 was used when computing TDS, BOD and FC concentrations, as uncertainties in absolute values of water availabilities have large impacts on resulting in-stream concentrations. Concentrations in these gridcells are assigned as NA.Hydrology and water quality simulations made at DynQuals native spatial resolution (5 arcmin) can be found at: https://zenodo.org/records/14673871.