Abstract. There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has been obtained through two approaches. The first approach is the detection of change based on observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for non-linear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities are discussed again such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on flood-rich and flood-poor periods rather than on flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.

Abstract. The L-moment-based regionalization approach developed by Hosking and Wallis (1997) is a frequently used tool in regional frequency modeling of heavy precipitation events. The method consists of the delineation of homogeneous pooling groups with a fixed structure, which may, however, lead to undesirable step-like changes in growth curves and design value estimates in the case of a transition from one pooling group to another. Unlike the standard methodology, the region-of-influence (ROI) approach does not make use of groups of sites (regions) with a fixed structure; instead, each site has its own "region", i.e. a group of sites that are sufficiently similar to the site of interest. The aim of the study is to develop a version of the ROI approach, which was originally proposed in order to overcome inconsistencies involved in flood frequency analysis, for the modeling of probabilities of heavy precipitation amounts. Various settings of the distance metric and pooled weighting factors are evaluated, and a comparison with the standard regional frequency analysis over the area of Slovakia is performed. The advantages of the ROI approach are assessed by means of simulation studies. It is demonstrated that almost any setting of parameters of the ROI method yields estimates of growth curves and design values at individual sites that are superior to the standard regional and at-site estimates.

Abstract. This paper presents a method to identify intense warm season storms of convective character based on intensity thresholds and lightning, and analyzes their statistical properties. Long records of precipitation and lightning data at 4 stations and 10 min resolution in different climatological regions in Switzerland are used. Our premise is that thunderstorms associated with lightning generate bursts of high rainfall intensity. We divided all storms into those accompanied by lightning and those without lightning and found the threshold I* that separates intense events based on peak 10 min intensity Ip ≥ I* for a chosen misclassification rate α. The performance and robustness of the selection method was tested by investigating the inter-annual variability of I* and its relation to the frequency of lightning strikes. The probability distributions of the main storm properties (rainfall depth R, event duration D, average storm intensity Ia and peak 10 min intensity Ip) for the intense storm subsets show that the event average and peak intensities are significantly different between the stations, and highest in Lugano in southern Switzerland. Non-parametric correlations between the main storm properties were estimated for the subsets of intense storms and all storms including stratiform rain. The differences in the correlations between storm subsets are greater than those between stations, which indicates that care must be exercised not to mix events when they are sampled for multivariate analysis, e.g. copula fitting to rainfall data.

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Flood recovery is an important period in the flood risk management cycle. Recently, flood recovery has become viewed as an opportunity for future flood damage mitigation. Financial flows to cover flood damages and rules regarding their allocation are crucial for supporting or undermining mitigation efforts. In this paper, we map and compare state flood recovery funding in the so-called Visegrad Group Countries (V4), i.e. Czechia, Hungary, Poland and Slovakia, over the past 30 years of their democratic history. We apply a qualitative comparative approach to identify differences and similarities in risk sharing and state flood recovery funding approaches among these countries. Additionally, we reveal how risk sharing is addressed by existing flood recovery funding schemes. The results indicate that national governments have a low willingness to institutionalise ex-ante compensation schemes. Ad hoc instruments initiated shortly after disastrous flooding usually do not provide incentives to reduce future flood damages.