Preprints
https://doi.org/10.5194/gmd-2022-222
https://doi.org/10.5194/gmd-2022-222
Submitted as: model description paper
16 Dec 2022
Submitted as: model description paper | 16 Dec 2022
Status: this preprint is currently under review for the journal GMD.

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

Edward R. Jones1, Marc F. P. Bierkens1,2, Niko Wanders1, Edwin H. Sutanudjaja1, Ludovicus P. H. van Beek1, and Michelle T. H. van Vliet1 Edward R. Jones et al.
  • 1Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, The Netherlands
  • 2Deltares, Unit Soil and Groundwater Systems, Utrecht, The Netherlands

Abstract. Maintaining good surface water quality is crucial to protect ecosystem health and for safeguarding human water use activities. Yet, our quantitative understanding of surface water quality is mostly predicated upon observations at monitoring stations that are highly limited in space and fragmented across time. Physically-based models, based upon pollutant emissions and subsequent routing through the hydrological network, provide opportunities to overcome these shortcomings. To this end, we have developed the dynamical surface water quality model (DynQual) for simulating water temperature (Tw) and concentrations of total dissolved solids (TDS), biological oxygen demand (BOD) and fecal coliform (FC) with a daily timestep and at 5 arc-minute (~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. Furthermore, we describe both the spatial patterns and temporal trends in TDS, BOD and FC concentrations for the period 1980–2019, also attributing the dominant contributing sectors. The model code is available open-source (https://github.com/UU-Hydro/DYNQUAL) and we provide global datasets of simulated hydrology, Tw, TDS, BOD and FC at 5 arc-minute resolution with a monthly timestep (https://doi.org/10.5281/zenodo.7139222). This data has potential to inform assessments in a broad range of fields, including ecological, human health and water scarcity studies.

Edward R. Jones et al.

Status: open (until 26 Feb 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on gmd-2022-222', Jason Ke, 28 Dec 2022 reply
    • AC1: 'Reply on CC1', Edward R. Jones, 26 Jan 2023 reply

Edward R. Jones et al.

Data sets

Global monthly hydrology and water quality datasets, derived from the dynamical surface water quality model (DynQual) at 10 km spatial resolution Jones, Edward R.; Bierkens, Marc F. P.; Wanders, Niko; Sutanudjaja, Edwin H.; van Beek, Ludovicus P. H.; van Vliet, Michelle T. H. https://doi.org/10.5281/zenodo.7139222

Model code and software

DynQual Model https://github.com/UU-Hydro/DYNQUAL https://github.com/UU-Hydro/DYNQUAL

Edward R. Jones et al.

Viewed

Total article views: 711 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
577 125 9 711 33 3 6
  • HTML: 577
  • PDF: 125
  • XML: 9
  • Total: 711
  • Supplement: 33
  • BibTeX: 3
  • EndNote: 6
Views and downloads (calculated since 16 Dec 2022)
Cumulative views and downloads (calculated since 16 Dec 2022)

Viewed (geographical distribution)

Total article views: 677 (including HTML, PDF, and XML) Thereof 677 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 28 Jan 2023
Download
Short summary
DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.