Research

Seasonal and long-term prediction of low flows in the Rhine basin

Short project description

Low flows in rivers may result in several types of problems to society, e.g. lack of water for drinking water supply, irrigation, industrial use and power production, hindrance to navigation and deterioration of water quality. It is expected that climate changes will to lead to drier summers in Western Europe and therefore possibly to more frequent and more severe low flows in rivers in the future. Facing these problems, it is crucial for low flow management that more accurate seasonal (months) and long-term (decades) predictions of low flows become available. The objective of this project is to contribute to the improvement of seasonal and long-term prediction of low flows in the Rhine basin by analysing historical trends and estimating future trends of low flow generating mechanisms (such as precipitation deficits, groundwater discharge and snow melt) and determining related low flows. This will be done using data-based methods (such as statistical modelling, time series analysis and trend analysis techniques), output from climate and hydrological models, and climatological, hydrological and geographical data. Results of the project include improved insight in low flow generating mechanisms in the Rhine basin for different seasons, tools for seasonal and long-term prediction of low flows and improved insight in climate change impacts on low flows in the Rhine basin.

Persons involved

Mehmet C. Demirel MSc (PhD student)

dr. ir. Martijn J. Booij (daily supervisor)

prof. dr. ir. Arjen Y. Hoekstra (promotor)

Publications [see ‘Publications’ for PDF-file or request free hard copy]

Bisterbosch, J., 2010. Impacts of climate change on low flows in the Rhine basin. MSc-thesis. University of Twente, Enschede.

Bouwma, P.R., 2011. Low flow forecasts for the Rhine at Lobith 14 days ahead. MSc-thesis. University of Twente, Enschede.

Demirel, M.C. and Booij, M.J., 2009. Identification of an appropriate low flow forecast model for the Meuse River. In: I.D. Cluckie, Y. Chen, V. Babovic, L. Konikow, A. Mynett, S. Demuth and D.A. Savic (Eds.), Hydroinformatics in hydrology, hydrogeology and water resources. Proc. Symposium JS.4 at the Joint IAHS & IAH Convention, 6-12 September 2009, Hyderabad, India. IAHS Publ. no. 331, 296-303.

Demirel, M.C. and Booij, M.J., 2010. Identification of appropriate temporal scales of dominant low flow indicators in the Main River, Germany. In: E. Servat, S. Demuth, A. Dezetter and T. Daniell (Eds.), Global Change: Facing Risks and Threats to Water Resources. Proc. Sixth World FRIEND Conference, 25-29 October 2010, Fez, Morocco. IAHS Publ. no. 340, 538-543.

Demirel, M.C. and Booij, M.J., 2011. Uncertainty analysis of a low flow model for the Rhine River. Geophysical Research Abstracts, 13, EGU2011-8280-1.

Demirel, M.C. and Booij, M.J., 2011. Low flow forecasting with a lead time of 14 days for navigation and energy supply in the Rhine River. Geophysical Research Abstracts, 13, EGU2011-8198-1.

Demirel, M.C. and Booij, M.J., 2015. Climate change impacts on the seasonality of low flows for multiple catchments with different discharge regimes. Abstract Workshop HW02 at IUGG2015, 22 June-2 July 2015, Prague, Czech Republic.

Demirel, M.C., Booij, M.J. and Hoekstra, A.Y., 2008. Seasonal and long-term prediction of low flows in the Rhine Basin. In: A.G. van Os and C.D. Erdbrink (Eds.), Proc. NCR-days 2008, 20-21 November 2008, Dalfsen, the Netherlands, 54-55.

Demirel, M.C., Booij, M.J. and Hoekstra, A.Y., 2013. Effect of different uncertainty sources on the skill of 10 day ensemble low flow forecasts for two hydrological models. Water Resources Research, 49, 4035-4053.

Demirel, M.C., Booij, M.J. and Hoekstra, A.Y., 2013. Identification of appropriate lags and temporal resolutions for low flow indicators in the River Rhine to forecast low flows with different lead times. Hydrological Processes, 27, 2742-2758.

Demirel, M.C., Booij, M.J. and Hoekstra, A.Y., 2013. Impacts of climate change on the seasonality of low flows in 134 catchments in the River Rhine basin using an ensemble of bias-corrected regional climate simulations. Hydrology and Earth System Sciences, 17, 4241-4257.

Demirel, M.C., Booij, M.J. and Hoekstra, A.Y., 2015. The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models . Hydrology and Earth System Sciences, 19, 275-291.

Tongal, H., Demirel, M.C. and Booij, M.J., 2013. Seasonality of low flows and dominant processes in the Rhine River. Stochastic Environmental Research and Risk Assessment, 27, 489-503.