A stochastic event-based approach for flood estimation in catchments with mixed rainfall and snowmelt flood regimes

Abstract

Abstract. The estimation of extreme floods is associated with high uncertainty, in part due to the limited length of streamflow records. Traditionally, statistical flood frequency analysis and an event-based model (PQRUT) using a single design storm have been applied in Norway. We here propose a stochastic PQRUT model, as an extension of the standard application of the event-based PQRUT model, by considering different combinations of initial conditions, rainfall and snowmelt, from which a distribution of flood peaks can be constructed. The stochastic PQRUT was applied for 20 small- and medium-sized catchments in Norway and the results give good fits to observed peak-over-threshold (POT) series. A sensitivity analysis of the method indicates (a) that the soil saturation level is less important than the rainfall input and the parameters of the PQRUT model for flood peaks with return periods higher than 100 years and (b) that excluding the snow routine can change the seasonality of the flood peaks. Estimates for the 100- and 1000-year return level based on the stochastic PQRUT model are compared with results for (a) statistical frequency analysis and (b) a standard implementation of the event-based PQRUT method. The differences in flood estimates between the stochastic PQRUT and the statistical flood frequency analysis are within 50 % in most catchments. However, the differences between the stochastic PQRUT and the standard implementation of the PQRUT model are much higher, especially in catchments with a snowmelt flood regime.

Downsizing parameter ensembles for simulations of rare floods

“…Also, as we focused only on large annual floods (annual maxima), we did not represent the flood seasonality in our analysis. Yet, some recent works emphasize the need to include such information on the flood type (Brunner et al, 2017) or on flood seasonality (Brunner et al, 2018c) into bivariate analysis of floods or to represent a mixture of both flood type and flood seasonality in flood frequency analysis (Fischer et al, 2016;Fischer, 2018). Thus, the proposed selection methods could potentially be extended to account for different flood types during representative parameter selection, e.g.…”

“…Moreover, as they usually do not simulate antecedent conditions prior to the event and do not account explicitly for storm patterns (duration, spatial and temporal variability), they may yield biased flood frequency distributions (Viglione and Blöschl, 2009;Grimaldi et al, 2012a). Although some modern extensions of this event-based concept account for variable initial conditions prior to the event through sensitivity tests (Filipova et al, 2019), most of the work using event-based simulations assume default initial conditions. Indeed, such event-based simulation is still in use, in particular in the context of probable maximum flood (PMF) estimation based on probable maximum precipitation (PMP) (Beauchamp et al, 2013;Gangrade et al, 2019).…”

Long-term magnetic anomalies and its possible relationship to the latest Greater Chilean earthquakes in the context of the seismo-electromagnetic theory

“…Similarly, Venegas-Aravena et al (2019) also found that the growth of microcracks and magnetic signals are hosted by these stress conditions within this large area. Recently, large areas of fast stress and strain changes, that surround the impending earthquakes, has been also confirmed by GPS analysis (Bedford et al, 2020).…”

“…This indicate that anomalies behavior could correspond to a lithospherical origin. Currently, it has been shown that the origin of these anomalies is associated with the cracking (or micro-cracking) of the semi-fragile-ductile part of the lithosphere (crust) due to changes in stress (Venegas-Aravena et al, 2019). Typically, strain appear when solids undergoes loads or stress accumulation.…”

“…Experimentally, it has been shown that these conditions break the electrical neutrality within materials and generate an electrical flux through rocks in a process known as pressure stimulated currents or PSC (e.g., Anastasiadis et al, 2004). Furthermore, it has been shown that PSCs can explain that the fractal nature of cracks is sufficient to generate the frequency spectrum, co-seismic variations, the generation and behavior of anomalies, and variation in the ionosphere in a theory known as seismo-electromagnetic theory (Venegas-Aravena et al, 2019). Regarding the time evolution of magnetic anomalies, De Santis et al…”