DynQual v1.0: a high-resolution global surface water quality model

Maintaining good surface water quality is crucial to protect ecosystem health and for safeguarding human wa-ter use activities. However, our quantitative understanding of surface water quality is mostly predicated upon observa-tions at monitoring stations that are highly limited in space and fragmented across time. Physical models based upon pollutant emissions and subsequent routing through the hy-drological network provide opportunities to overcome these shortcomings. To this end, we have developed the dynamical surface water quality model (DynQual) for simulating water temperature (T-w) and concentrations of total dissolved solids (TDS), biological oxygen demand (BOD) and fecal coliform (FC) with a daily time step and at 5 arcmin (similar to 10 km) spatial resolution. Here, we describe the main components of this new global surface water quality model and evaluate model performance against in situ water quality observations. Fur-thermore, we describe both the spatial patterns and temporal trends in TDS, BOD and FC concentrations for the period 1980-2019, and we also attribute the dominant contribut-ing sectors to surface water pollution. Modelled output in-dicates that multi-pollutant hotspots are especially prevalent across northern India and eastern China but that surface wa-ter quality issues exist across all world regions. Trends to-wards water quality deterioration have been most profound in the developing world, particularly sub-Saharan Africa and South Asia. The model code is available open source (https://doi.org/10.5281/zenodo.7932317, Jones et al., 2023), and we provide global datasets of simulated hydrology, T-w, TDS, BOD and FC at 5 arcmin resolution with a monthly time step (https://doi.org/10.5281/zenodo.7139222, Jones et al., 2022b). These data have the potential to inform assess-ments in a broad range of fields, including ecological, human health and water scarcity studies.