Articles | Volume 21, issue 3
https://doi.org/10.5194/hess-21-1593-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-1593-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
16 Mar 2017
Research article |
| 16 Mar 2017
Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development?
Mark Honti
CORRESPONDING AUTHOR
MTA-BME Water Research Group, Hungarian Academy of Sciences, Műegyetem rkp. 3, Budapest, 1111, Hungary
Nele Schuwirth
Eawag: Swiss Federal Institute of Aquatic Sciences and Technology, Ueberland Strasse 133, Dübendorf, 8600, Switzerland
Jörg Rieckermann
Eawag: Swiss Federal Institute of Aquatic Sciences and Technology, Ueberland Strasse 133, Dübendorf, 8600, Switzerland
Christian Stamm
Eawag: Swiss Federal Institute of Aquatic Sciences and Technology, Ueberland Strasse 133, Dübendorf, 8600, Switzerland
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Cited
15 citations as recorded by crossref.
- An integrated modelling system for water quality forecasting in an urban eutrophic estuary: The Swan-Canning Estuary virtual observatory P. Huang et al. 10.1016/j.jmarsys.2019.103218
- Multi-criteria decision analysis for integrated water quality assessment and management support N. Schuwirth et al. 10.1016/j.wroa.2018.100010
- Modelling biocide and herbicide concentrations in catchments of the Rhine basin A. Moser et al. 10.5194/hess-22-4229-2018
- Evaluation of a coupled hydrodynamic-closed ecological cycle approach for modelling dissolved oxygen in surface waters V. Camacho Suarez et al. 10.1016/j.envsoft.2019.06.003
- Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex World M. Bedinger et al. 10.3390/su11041163
- A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions C. Schürz et al. 10.5194/hess-23-1211-2019
- Recent insights on uncertainties present in integrated catchment water quality modelling F. Tscheikner-Gratl et al. 10.1016/j.watres.2018.11.079
- Pulling the rabbit out of the hat: Unravelling hidden nitrogen legacies in catchment‐scale water quality models S. Lutz et al. 10.1002/hyp.14682
- Interaction of hydro-socio-technology-knowledge indicators in integrated water resources management using soft-computing techniques M. Zeinali et al. 10.2166/ws.2020.327
- Applicability of a processes-based model and artificial neural networks to estimate the concentration of major ions in rivers C. Nhantumbo et al. 10.1016/j.gexplo.2018.07.003
- Pesticides in surface waters: from edge-of-field to global modelling A. Ippolito & G. Fait 10.1016/j.cosust.2018.10.023
- A review of modeling pesticides in freshwaters: Current status, progress achieved and desirable improvements. M. Centanni et al. 10.1016/j.envpol.2022.120553
- Modelled impacts of policies and climate change on land use and water quality in Austria M. Schönhart et al. 10.1016/j.landusepol.2018.02.031
- Preparing for the future: integrating spatial ecology into ecosystem-based management S. Lowerre-Barbieri et al. 10.1093/icesjms/fsy209
- Emerging investigators series: a critical review of decision support systems for water treatment: making the case for incorporating climate change and climate extremes W. Raseman et al. 10.1039/C6EW00121A
14 citations as recorded by crossref.
- An integrated modelling system for water quality forecasting in an urban eutrophic estuary: The Swan-Canning Estuary virtual observatory P. Huang et al. 10.1016/j.jmarsys.2019.103218
- Multi-criteria decision analysis for integrated water quality assessment and management support N. Schuwirth et al. 10.1016/j.wroa.2018.100010
- Modelling biocide and herbicide concentrations in catchments of the Rhine basin A. Moser et al. 10.5194/hess-22-4229-2018
- Evaluation of a coupled hydrodynamic-closed ecological cycle approach for modelling dissolved oxygen in surface waters V. Camacho Suarez et al. 10.1016/j.envsoft.2019.06.003
- Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex World M. Bedinger et al. 10.3390/su11041163
- A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions C. Schürz et al. 10.5194/hess-23-1211-2019
- Recent insights on uncertainties present in integrated catchment water quality modelling F. Tscheikner-Gratl et al. 10.1016/j.watres.2018.11.079
- Pulling the rabbit out of the hat: Unravelling hidden nitrogen legacies in catchment‐scale water quality models S. Lutz et al. 10.1002/hyp.14682
- Interaction of hydro-socio-technology-knowledge indicators in integrated water resources management using soft-computing techniques M. Zeinali et al. 10.2166/ws.2020.327
- Applicability of a processes-based model and artificial neural networks to estimate the concentration of major ions in rivers C. Nhantumbo et al. 10.1016/j.gexplo.2018.07.003
- Pesticides in surface waters: from edge-of-field to global modelling A. Ippolito & G. Fait 10.1016/j.cosust.2018.10.023
- A review of modeling pesticides in freshwaters: Current status, progress achieved and desirable improvements. M. Centanni et al. 10.1016/j.envpol.2022.120553
- Modelled impacts of policies and climate change on land use and water quality in Austria M. Schönhart et al. 10.1016/j.landusepol.2018.02.031
- Preparing for the future: integrating spatial ecology into ecosystem-based management S. Lowerre-Barbieri et al. 10.1093/icesjms/fsy209
Latest update: 23 Nov 2024
Short summary
We present a new catchment model that covers most major pollutants and is suitable for uncertainty analysis. The effects of climate change, population dynamics, socio-economic development, and management strategies on water quality are demonstrated in a small catchment in the Swiss Plateau. Models and data are still the largest sources of uncertainty for some water quality parameters. Uncertainty assessment helps to select robust management and focus research and monitoring efforts.
We present a new catchment model that covers most major pollutants and is suitable for...
