Analysis and modelling of a 9.3 kyr palaeoflood record: correlations, clustering, and cycles

Abstract

Abstract. In this paper, we present a unique 9.5 m palaeolacustrine record of 771 palaeofloods which occurred over a period of 9.3 kyr in the Piànico-Sèllere Basin (southern Alps) during an interglacial period in the Pleistocene (sometime from 780 to 393 ka) and analyse its correlation, clustering, and cyclicity properties. We first examine correlations, by applying power-spectral analysis and detrended fluctuation analysis (DFA) to a time series of the number of floods per decade, and find weak long-range persistence: a power-spectral exponent β PS ≈ 0.39 and an equivalent power-spectral exponent from DFA, β DFA ≈ 0.25. We then examine clustering using the one-point probability distribution of the inter-flood intervals and find that the palaeofloods cluster in time as they are Weibull distributed with a shape parameter k W = 0.78. We then examine cyclicity in the time series of number of palaeofloods per year, and find a period of about 2030 years. Using these characterizations of the correlation, clustering, and cyclicity in the original palaeoflood time series, we create a model consisting of the superposition of a fractional Gaussian noise (FGN) with a 2030-year periodic component and then peaks over threshold (POT) applied. We use this POT FGN+Period model to create 2 600 000 synthetic realizations of the same length as our original palaeoflood time series, but with varying intensity of periodicity and persistence, and find optimized model parameters that are congruent with our original palaeoflood series. We create long realizations of our optimized palaeoflood model, and find a high temporal variability of the flood frequency, which can take values of between 0 and > 30 floods century −1 . Finally, we show the practical utility of our optimized model realizations to calculate the uncertainty of the forecasted number of floods per century with the number of floods in the preceding century. A key finding of our paper is that neither fractional noise behaviour nor cyclicity is sufficient to model frequency fluctuations of our large and continuous palaeoflood record, but rather a model based on both fractional noise superimposed with a long-range periodicity is necessary.

Hydroclimatic variability of opposing Late Pleistocene climates in the Levant revealed by deep Dead Sea sediments

“…3). Similarly, other high-resolution palaeo-hydrological records (e.g., Witt et al, 2017) and modern observations (e.g., Metzger et al, 2020) have demonstrated non-uniform and non-Poissonian flood frequencies. In addition, the clusters observed during lakelevel fall are characterized by flood frequencies similar to those appearing in the background episodes during lakelevel rise (Figs.…”

“…Furthermore, the impacts of climate change on short-term phenomena such as individual storms and floods, which have substantial influence on the in situ water cycle in the Mediterranean Sea, are harder to determine from the available short historical records because the extent of available data does not adequately capture the full diversity of possible hydroclimatic states (e.g., Greenbaum et al, 2010;Tarolli et al, 2012;Metzger et al, 2020). Because palaeohydrologic archives often record centennial and millennial intervals at various resolutions (e.g., Allen et al, 2020;Baker, 2008;Brauer et al, 2008;Redmond et al, 2002;Witt et al, 2017), they have the potential to improve our understating of how climate change is manifested locally as short-term hydroclimatic variability (e.g., Ahlborn et al, 2018;Swierczynski et al, 2012). Nevertheless, this requires continuous high-resolution archives, which are rare, especially in subtropical terrestrial environments (e.g., Zolitschka et al, 2015).…”

Fluvial palaeohydrology in the 21st century and beyond

“…Dulski et al, 2015; Kämpf et al, 2019; Lapointe et al, 2012; Schlolaut et al, 2014; Støren et al, 2010). When these layers are constrained within laminated lacustrine sediments that provide a detailed chronology, it becomes possible to construct time series of events that reveal their frequency and clustering, and sometimes even relative magnitudes (Czymzik et al, 2010; Witt et al, 2017).…”

“…Such frequency changes and non‐stationarity occurred under different climatic conditions (Brauer et al, 2008; Corella et al, 2016, 2021; Swierczynski et al, 2013), as observed in modern records (Blöschl et al, 2020; Redmond et al, 2002). An increasingly large number of studies indicate that, over centennial time scales, non‐stationarity characterizes both the mean and the variance of flood series, thus forming decadal to centennial clusters of increased flood frequency that stem directly from hydroclimatic variability (Ben Dor et al, 2018; Chiverrell et al, 2019; Czymzik et al, 2010; Witt et al, 2017).…”

“…Furthermore, the investigation of floods within annually deposited lake sediments reveals their degree of stationarity. Several studies of flood deposits within varve‐bearing lacustrine sections demonstrated that flood frequency is not stationary at the decadal to centennial time scales (Brauer et al, 2008; Corella et al, 2021; Witt et al, 2017). Such frequency changes and non‐stationarity occurred under different climatic conditions (Brauer et al, 2008; Corella et al, 2016, 2021; Swierczynski et al, 2013), as observed in modern records (Blöschl et al, 2020; Redmond et al, 2002).…”