Landscape and climate alterations foreshadow global-scale shifts of river flow regimes. However, a theory that identifies the range of foreseen impacts on streamflows resulting from inhomogeneous forcings and sensitivity gradients across diverse regimes is lacking. Here, we derive a measurable index embedding climate and landscape attributes (the ratio of the mean interarrival of streamflow-producing rainfall events and the mean catchment response time) that discriminates erratic regimes with enhanced intraseasonal streamflow variability from persistent regimes endowed with regular flow patterns. Theoretical and empirical data show that erratic hydrological regimes typical of rivers with low mean discharges are resilient in that they hold a reduced sensitivity to climate fluctuations. The distinction between erratic and persistent regimes provides a robust framework for characterizing the hydrology of freshwater ecosystems and improving water management strategies in times of global change.

A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large‐scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph‐based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space–time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods.This article is categorized under: Science of Water > Water Extremes Science of Water > Hydrological Processes Science of Water > Methods

Analyzing a response of catchments to rainfall inputs allows for deeper insights on the mechanisms of runoff generation at catchment scale. In this study an automated time series‐based event separation procedure consisting of available base flow separation, runoff event identification, and rainfall attribution methods and of a novel iterative procedure for the adjustment of thresholds used to identify single‐peak components of multiple‐peak events is proposed. Event runoff coefficient, time scale, rise time, and peak discharge of more than 220,000 identified rainfall‐runoff events are then used to analyze dynamics of event runoff response in 185 catchments at multiple temporal scales. In mountainous catchments with poor storage event runoff response is strongly controlled by the characteristics of rainfall and is generated by event‐fed saturation or infiltration excess. A distinct switch between saturated and unsaturated states occurs in these catchments. A weak relation between rainfall and runoff event properties is instead observed in lowland and hilly catchments with substantial storage, where a gradual transformation between functioning states occurs and the response is driven by preevent saturation. The seasonality of their event characteristics is governed by the contribution of snowmelt and the seasonality of the aridity index rather than of rainfall properties. Long‐term changes of total precipitation amount alone do not explain season‐specific long‐term changes of event characteristics that are rather consistent with changes of seasonal indicators of the wetness state. The effects of land use changes are detectable only in a few cases and display themselves mostly in the characteristic response time of catchments.

Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage. Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented. In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice. Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system. We then discuss to which extent the current knowledge supports or contradicts these hypotheses. We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms. We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.

Anomalies in the frequency of river floods, i.e., flood-rich or -poor periods, cause biases in flood risk estimates and thus make climate adaptation measures less efficient. While observations have recently confirmed the presence of flood anomalies in Europe, their exact causes are not clear. Here we analyse streamflow and climate observations during 1960-2010 to show that shifts in flood generation processes contribute more to the occurrence of regional flood anomalies than changes in extreme rainfall. A shift from rain on dry soil to rain on wet soil events by 5% increased the frequency of flood-rich periods in the Atlantic region, and an opposite shift in the Mediterranean region increased the frequency of flood-poor periods, but will likely make singular extreme floods occur more often. Flood anomalies driven by changing flood generation processes in Europe may further intensify in a warming climate and should be considered in flood estimation and management.