University of Twente Student Theses


Trend Analysis in the peak flows of the Meuse river and its tributaries through the use of series of ensemble forecasts events

Urbano Guerrero, V.E. (2023) Trend Analysis in the peak flows of the Meuse river and its tributaries through the use of series of ensemble forecasts events.

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Abstract:Climate change is not a future issue. There is evidence that extreme events are changing in terms of frequency, intensity, duration, location, and timing due to climate change (Easterling et al., 2000 & IPCC, 2012, as cited by Rypkema & Tuljapurkar, 2021). Experts and decision-makers are concerned that these climate changes may be affecting extreme events on essential rivers such as the Meuse river. In addition to these changes in extreme events, it should be considered that a large part of the Netherlands is below water level and other areas are prone to flooding. That is why for Dutch water managers, finding a possible climate-induced trend in the probability of extreme discharges is a matter of great concern; because it could affect the design of the flood defense systems (Diermanse, et al., 2010). Historical observations could have been an excellent tool to better understand what could happen in the future due to human-induced climate change (Villarini, et al., 2011). However, the problem when analyzing extreme events is that there is not enough historical data available, and the rarer the event, the more difficult it will be to identify changes (IPCC, 2012). According to van den Brink, et al. (2005), this dearth of data problem can be addressed through the use of ensemble weather forecasts obtained from the ECMWF (European Centre for Medium-Range Weather Forecasts). In previous research conducted by te Booij (2022), this ensemble re-forecasts technique was used to overcome the lack of data and increase the number of suitable extreme precipitation events to perform a trend analysis on these precipitation events of the Meuse catchment. In this report, special attention was given to the extreme discharge events derived from a selection of extreme precipitation events identified from the reforecasts of the ECMWF in the previous research done by te Booij (2022). The selected extreme precipitation events for this investigation were the two most extreme events for each year (within a period of 20 years from 1996 until 2015) extracted from the list of 5-day accumulative rainfall volumes. These extreme precipitation extreme events served as input for a hydrological model (wflow model) to perform simulations for two possible scenarios (dry and wet) and to obtain the forecasted extreme discharge events. The initial conditions for both dry and wet scenarios and the historical simulated maximum annual discharges were determined using E-OBS gridded data as the main input in the wflow model. So, the three resulting datasets of discharge extremes that were used for the comparison and trend analysis are: 1. historical simulated maximum annual discharges 2. highest maximum annual discharges obtained with the dry initial states (forecasted dataset) 3. highest maximum annual discharges obtained with the wet initial states (Forecasted dataset)
Item Type:Essay (Bachelor)
Faculty:ET: Engineering Technology
Programme:Civil Engineering BSc (56952)
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