Extensive model evaluation for seasonal and spatial dynamics of dissolved oxygen in SWAT+

Dissolved oxygen (DO) is a critical indicator of aquatic ecosystem health, but multidecadal trends show a general decline in DO concentrations in riverine ecosystems, highlighting the need to better understand the driving dynamics and improve predictions. This study presents the first implementation of dissolved oxygen (DO) dynamics in SWAT+ (SWAT+DO). A rich dataset of spatially high resolution observed DO data is used to investigate modelled and observed differences in seasonal and spatial DO dynamics related to stream temperature and hydrological conditions. The spatial model performance was improved by introducing a spatially distributed formulation of the parameter and achieved a KGE of 0.73 on a daily resolution without further calibration. The influence of streamflow and stream temperature on DO has strong seasonal and spatial differences. With these findings our study highlights the strengths and limitations of a process-based ecohydrological model, depending on the scale that it is applied on. • Spatial model improvement with SWAT+DO using dynamic reaeration rate • Climatic effects on modelled DO concentrations • Interactions of DO, stream temperature and streamflow depend on scale and season

Authors

Institutions

Publication Details

Journal
Environmental Modelling & Software
Published
2026-03-17
DOI
https://doi.org/10.1016/j.envsoft.2026.106959
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Extensive model evaluation for seasonal and spatial dynamics of dissolved oxygen in SWAT+

Luan Farias, Nicola Fohrer, Jens Kiesel, Kristin Peters
Environmental Modelling & Software
Marine and coastal ecosystems
article

Extensive model evaluation for seasonal and spatial dynamics of dissolved oxygen in SWAT+

Luan Farias, Nicola Fohrer, Jens Kiesel, Kristin Peters
article en

Abstract

Dissolved oxygen (DO) is a critical indicator of aquatic ecosystem health, but multidecadal trends show a general decline in DO concentrations in riverine ecosystems, highlighting the need to better understand the driving dynamics and improve predictions. This study presents the first implementation of dissolved oxygen (DO) dynamics in SWAT+ (SWAT+DO). A rich dataset of spatially high resolution observed DO data is used to investigate modelled and observed differences in seasonal and spatial DO dynamics related to stream temperature and hydrological conditions. The spatial model performance was improved by introducing a spatially distributed formulation of the parameter and achieved a KGE of 0.73 on a daily resolution without further calibration. The influence of streamflow and stream temperature on DO has strong seasonal and spatial differences. With these findings our study highlights the strengths and limitations of a process-based ecohydrological model, depending on the scale that it is applied on. • Spatial model improvement with SWAT+DO using dynamic reaeration rate • Climatic effects on modelled DO concentrations • Interactions of DO, stream temperature and streamflow depend on scale and season

Environmental Modelling & SoftwareVol. 200
Christian-Albrechts-Universität zu Kiel (DE), University of Duisburg-Essen (DE)
Clean water and sanitation
Openalex Percentile: Top 18%
Marine and coastal ecosystems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Extensive model evaluation for seasonal and spatial dynamics of dissolved oxygen in SWAT+ — Luan Farias, Nicola Fohrer, et al. · Environmental Modelling & Software (2026) | TGRS Research Map | TGRS