Areal Models for Spatially Coherent Trend Detection: The Case of British Peak River Flows. Issue 22 (29th November 2019)

• Record Type: Journal Article
• Authors: Prosdocimi, Ilaria; Dupont, Emiko; Augustin, Nicole H.; Kjeldsen, Thomas R.; Simpson, Dan P.; Smith, Theresa R.
• Is Part Of: Geophysical research letters. Volume 46:Issue 22(2019)
• Page Start: 13054
• Page End: 13061
• Publication Date: 2019-11-29
• Subjects: floods -- trend detection -- statistics -- flood frequency analysis -- areal models -- Great Britain; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2019GL085142
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: With increasing concerns on the impacts of climate change, there is wide interest in understanding whether hydrometric and environmental series display any sort of trend. Many studies however, focus on the analysis of highly variable individual series at each measuring location. We propose a novel and straightforward approach to trend detection, modelling the test statistic for trend at each location via an areal model in which the information across measuring locations is pooled together. We exemplify the method with a detailed study of change in high flows in Great Britain. Using areal models, we detect a statistically relevant signal for a positive trend across Great Britain in the recent decades. This evidence is also found when different temporal subsets of the records are analysed. Further, the model identifies areas where the increase has been higher or lower than average, thus providing a way to prioritise intervention. Plain language summary: With growing concerns over the potential impacts of climate change, many studies are investigating whether river extremes, such as floods, are changing. Studies based on climate change projections indicate that changes might be expected in several parts of the world, including Great Britain where floods are predicted to increase. However, studies investigating measured river flow records have mostly found inconclusive evidence of change. This does not mean that change is not happening, but finding the evidence of this change is difficult because flow records are short and very variable. In this study we suggest that river flow measuring stations on the same river will experience similar changes since they are affected by the same climate. We therefore propose to use advanced statistical models, which combine information from nearby stations and apply these model to high flows measurements in Great Britain. The analysis of data from closely located measuring stations demonstrates that flows have generally become bigger in Great Britain recently. The methods proposed in the manuscript could be easily applied to other type of data routinely measured and which might have been changing over time as a result of climate change or other drivers. Key Points: We propose a novel approach to regional detection of trends in measured series based on areal models We detect a clear signal that peak flows magnitudes are increasing over time in Great Britain These changes are still found when different periods of record are analyzed, with an accelerated upward trend from 1980 onward