A guideline for spatio‐temporal consistency in water quality modelling in rural areas

Fohrer, Nicola ORCIDiD
Wagner, Paul D. ORCIDiD
Kiesel, Jens ORCIDiD
Haas, Marcelo
Guse, Björn ORCIDiD

DOI: https://doi.org/10.1002/hyp.14711
Persistent URL: http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/10475
Fohrer, Nicola; Wagner, Paul D.; Kiesel, Jens; Haas, Marcelo; Guse, Björn, 2022: A guideline for spatio‐temporal consistency in water quality modelling in rural areas. In: Hydrological Processes, 36, 11, DOI: https://doi.org/10.1002/hyp.14711. 
 
Wagner, Paul D.; 1 Department of Hydrology and Water Resources Management Kiel University Kiel Germany
Kiesel, Jens; 1 Department of Hydrology and Water Resources Management Kiel University Kiel Germany
Haas, Marcelo; 1 Department of Hydrology and Water Resources Management Kiel University Kiel Germany
Guse, Björn; 1 Department of Hydrology and Water Resources Management Kiel University Kiel Germany

Abstract

To summarize, we suggest a guideline for water quality modelling:

  1. Spatial and temporal patterns of land use and land management are critical to adequately represent water quality in models. Remote sensing and land use models are very useful resources to be exploited.
  2. The transfer of a model diagnostic analysis to water quality leads to a better understanding of how water quality variables are controlled by model structures and corresponding model parameters.
  3. Assessing multiple model outputs regarding their temporal, spa- tial and process performance using observed time series, remotely sensed spatial patterns, knowledge about transport pathways and even soft data can significantly enhance model consistency.
  4. Multi-metric calibration using performance metrics and signa- ture measures both for discharge and water quality, such as FDC and NDC, leads to more balanced model simulations that represent all magnitudes of discharge and water quality accurately.
  5. Scenarios and storylines should be co-developed with stake- holders in the river basin to make them more realistic and increase the acceptance of model results. They should be realistic in space and time, and provide a mix of available management options.
  6. The interpretation of BMPs can be supported by diagnostic tools to show the effectiveness of measures and their combinations while considering their costs and impacts on ecosystem services.