# Causal mechanism of extreme river discharges in the upper Danube basin network

## TL;DR

This paper introduces CausEV, a novel method combining extreme value modeling and causal discovery to identify causal links between extreme river discharges, revealing significant causal relations in the upper Danube basin.

## Contribution

It develops a new causal inference approach for extreme events using Kolmogorov complexity and the minimum description length principle, applied to hydrological data.

## Key findings

- Identifies causal links between Danube and Lech river discharges.
- Uncovers causal mechanisms underlying extreme hydrological events.
- Demonstrates effectiveness of the CausEV method in hydrology.

## Abstract

Extreme hydrological events in the Danube river basin may severely impact human populations, aquatic organisms, and economic activity. One often characterizes the joint structure of the extreme events using the theory of multivariate and spatial extremes and its asymptotically justified models. There is interest however in cascading extreme events and whether one event causes another. In this paper, we argue that an improved understanding of the mechanism underlying severe events is achieved by combining extreme value modelling and causal discovery. We construct a causal inference method relying on the notion of the Kolmogorov complexity of extreme conditional quantiles. Tail quantities are derived using multivariate extreme value models and causal-induced asymmetries in the data are explored through the minimum description length principle. Our CausEV, for Causality for Extreme Values, approach uncovers causal relations between summer extreme river discharges in the upper Danube basin and finds significant causal links between the Danube and its Alpine tributary Lech.