scholarly journals Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

2017 ◽  
Vol 32 (2) ◽  
pp. 619-639 ◽  
Author(s):  
B. Mehdi ◽  
K. Schulz ◽  
R. Ludwig ◽  
F. Ferber ◽  
B. Lehner
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Agricultural Watershed ◽  
Water Quality Variables ◽  
Behavioural Parameter

Impacts of climate change on surface water quality in relation to drinking water production

2009 ◽  
Vol 35 (8) ◽  
pp. 1225-1233 ◽  
Author(s):  
I. Delpla ◽  
A.-V. Jung ◽  
E. Baures ◽  
M. Clement ◽  
O. Thomas
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Drinking Water ◽  
Surface Water ◽  
Surface Water Quality ◽  
Water Production ◽  
Drinking Water Production ◽  
Impacts Of Climate Change

scholarly journals THE IMPLICATIONS OF ECONOMIC DEVELOPMENT, CLIMATE CHANGE AND EUROPEAN WATER POLICY ON SURFACE WATER QUALITY THREATS

2017 ◽  
Vol 3 ◽  
pp. 111-123 ◽  
Author(s):  
Jolanta Dąbrowska ◽  
◽  
Katarzyna Pawęska ◽  
Paweł B. Dąbek ◽  
Radosław Stodolak ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Economic Development ◽  
Surface Water ◽  
Water Policy ◽  
Surface Water Quality ◽  
European Water

scholarly journals At-grade stabilization structure impact on surface water quality of an agricultural watershed

2015 ◽  
Vol 153 ◽  
pp. 50-59 ◽  
Author(s):  
Kyle R. Minks ◽  
Matthew D. Ruark ◽  
Birl Lowery ◽  
Fred W. Madison ◽  
Dennis Frame ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Agricultural Watershed

Climate Change how does Weather Affect Surface Water Quality?

Opflow ◽  
2013 ◽  
Vol 39 (1) ◽  
pp. 10-15 ◽  
Author(s):  
Ben Wright ◽  
Ben Stanford ◽  
Josh Weiss ◽  
Jean Debroux ◽  
Jan Routt ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality

scholarly journals Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development?

2017 ◽  
Vol 21 (3) ◽  
pp. 1593-1609 ◽  
Author(s):  
Mark Honti ◽  
Nele Schuwirth ◽  
Jörg Rieckermann ◽  
Christian Stamm
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Land Use ◽  
Surface Water ◽  
Management Strategies ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Model Structure ◽  
Predictive Uncertainty ◽  
Socio Economic Development

Abstract. The design and evaluation of solutions for integrated surface water quality management requires an integrated modelling approach. Integrated models have to be comprehensive enough to cover the aspects relevant for management decisions, allowing for mapping of larger-scale processes such as climate change to the regional and local contexts. Besides this, models have to be sufficiently simple and fast to apply proper methods of uncertainty analysis, covering model structure deficits and error propagation through the chain of sub-models. Here, we present a new integrated catchment model satisfying both conditions. The conceptual iWaQa model was developed to support the integrated management of small streams. It can be used to predict traditional water quality parameters, such as nutrients and a wide set of organic micropollutants (plant and material protection products), by considering all major pollutant pathways in urban and agricultural environments. Due to its simplicity, the model allows for a full, propagative analysis of predictive uncertainty, including certain structural and input errors. The usefulness of the model is demonstrated by predicting future surface water quality in a small catchment with mixed land use in the Swiss Plateau. We consider climate change, population growth or decline, socio-economic development, and the implementation of management strategies to tackle urban and agricultural point and non-point sources of pollution. Our results indicate that input and model structure uncertainties are the most influential factors for certain water quality parameters. In these cases model uncertainty is already high for present conditions. Nevertheless, accounting for today's uncertainty makes management fairly robust to the foreseen range of potential changes in the next decades. The assessment of total predictive uncertainty allows for selecting management strategies that show small sensitivity to poorly known boundary conditions. The identification of important sources of uncertainty helps to guide future monitoring efforts and pinpoints key indicators, whose evolution should be closely followed to adapt management. The possible impact of climate change is clearly demonstrated by water quality substantially changing depending on single climate model chains. However, when all climate trajectories are combined, the human land use and management decisions have a larger influence on water quality against a time horizon of 2050 in the study.

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