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Return period of low water periods in the river Rhine

Brenk, S.H. van (2021) Return period of low water periods in the river Rhine.

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Abstract:The year 2018 is in the top 5 of driest years since the beginning of regulated recordings in the Netherlands [Sprokkereef, 2019, KNMI, 2021b]. The precipitation deficit of August 2018 even passed record year 1976 for a few days according to the Droogtemonitor [KNMI, 2021a]. Furthermore, the water level measured in the Rhine at Lobith has never been as low as in 2018 [Sprokkereef, 2019]. However, how extreme this event was is currently unknown. Low flow return periods are important for shipping applications, risk assessments concerning water availability or preventing salinisation. Low flow return periods depend on three important aspects: discharge, duration and interdependency between low flows. However, no suitable method was found to accurately take these aspects into account. The goal of this study was to quantify the return period for the 2018 low flows and determine the effect of climate change on low flow return periods in the Rhine at Lobith. The first step in this study was to find a suitable method to determine low flow return periods. The block method and peak-under threshold method were used to determine low flow frequency curves, based on discharges, measured at Lobith from 1901 to 2020 [Rijkswaterstaat, 2021]. The methods differ in how they determine events and they fit a different distribution. The block method takes less events into account than the peak-under threshold method, which makes the peak-under threshold method more favourable. However, the block method resulted in a better fit compared to the peak-under threshold method. Therefore, the block method was used in the remainder of this study. The biggest differences between the two methods are found for the smaller return periods and higher discharges, where the peak-under threshold method gives lower discharges than the block method. Next, the low flow frequency curves based on the measured data were compared to low flow frequency curves based on the GRADE Reference data. GRADE is a model that can simulate 50,000 years of daily discharges at Lobith, which is interesting for extreme value statistics. The estimated fit shows constantly lower discharges compared to the measured data. The largest difference between the two estimated fits is found in the higher discharges, which occur more often. The GRADE model is also used to determine discharges for the KNMI’14 scenarios. All 8 climate scenarios show higher discharges compared to the GRADE Reference scenario, which is unexpected. The WH scenarios have the lowest discharges of the climate scenarios and the GL scenarios have the highest discharges. Finally, the low flows of 2018 were quantified and a projection was made of similar events in the future. A 1 day discharge of 732 m3/s, which was the minimum of 2018, is likely to occur once every 17.6 years. Due to climate change this can occur once every 6.5 to 22.6 years in 2085 based on the KNMI’14 scenarios and the GRADE model. In 2085, a 1 day event that will occur once every 17.6 years will have a discharge between 655 and 753 m3/s. This shows that, depending on which climate scenario evolves to be more realistic, an event like 2018 is likely to become more or less common. A 30 day discharge of 789 m3/s, which was the minimum of 2018, is likely to occur once every 21.8 years. Due to climate change this can occur once every 8.7 to 34.8 years in 2085 based on the KNMI’14 scenarios and the GRADE model. In 2085, a 30 days event that will occur once every 21.8 years will have a discharge between 708 and 832 m3/s. This again shows that, depending on which climate scenario evolves to be more realistic, an event like 2018 is likely to become more or less common. The 180 day discharge of 2018, which was 1017 m3/s, has an even larger return period of 29.5 years. This shows that the drought of 2018 was severe due to the length of the event.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering and Management MSc (60026)
Link to this item:https://purl.utwente.nl/essays/89051
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