Changes in hydrological extremes and climate variability in the Severn Uplands

Abstract

Hydrological extremes within the UK have increased in intensity, frequency and
persistence over recent years and are predicted to increase in variability throughout the 21st
century. Past and future changes in hydrological extremes relative to climate change were
investigated within Severn Uplands, a climate sensitive catchment. Using the Mann-
Kendall trend detection test, time-series analysis over a 30-year period revealed a
significant increase in winter and autumn precipitation and a decrease in summer
precipitation. The analysis of flow time-series indicated an increase in winter and July
flows and a decrease in spring flows. Changes in climate variability over the same period
showed increases in air temperature and SST, and a reduction in snow cover. Climate
variables were found to largely correlate with hydrological extremes which were
characteristic of certain weather types and largely influenced by the NAO.

To model future flows within the Severn Uplands a hydrological model (HEC-HMS) was
used to simulate hydrological processes. The extreme hydrological event of November-
December 2006 was used to calibrate the model. The difference between using radar and
gauge precipitation data to drive the model was quantified. Radar data resulted in the
smallest prediction accuracy followed by gauge-corrected radar data (corrected using the
mean-field bias where gauge rainfall was interpolated using cokriging) and then gauge
precipitation which had the largest prediction accuracy. Model accuracy was sufficient
using the gauge corrected radar and gauge precipitation data as inputs, so both were altered
for future predictions to investigate the propagation of uncertainty. Predicted changes in
temperature and precipitation by the UKCIP02 scenarios were used to alter the baseline
extreme event to predict changes in peak flow and outflow volume. Both radar- and gaugedriven
hydrological modelling predicted large flow increases for the 21st century with
increases up to 8% by the 2020s, 18% by the 2050s and 30% by the 2080s. Discrepancies
between predictions were observed when using the different data inputs.

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Identifiers

ORCID for Peter M Atkinson: orcid.org/0000-0002-5489-6880

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