A Process‐Based Framework to Characterize and Classify Runoff Events: The Event Typology of Germany

Abstract

This study proposes a new process-based framework to characterize and classify runoff events of various magnitudes occurring in a wide range of catchments. The framework uses dimensionless indicators that characterize space-time dynamics of precipitation events and their spatial interaction with antecedent catchment states, described as snow cover, distribution of frozen soils, and soil moisture content. A rigorous uncertainty analysis showed that the developed indicators are robust and regionally consistent. Relying on covariance-and ratio-based indicators leads to reduced classification uncertainty compared to commonly used (event-based) indicators based on absolute values of metrics such as duration, volume, and intensity of precipitation events. The event typology derived from the proposed framework is able to stratify events that exhibit distinct hydrograph dynamics even if streamflow is not directly used for classification. The derived typology is therefore able to capture first-order controls of event runoff response in a wide variety of catchments. Application of this typology to about 180,000 runoff events observed in 392 German catchments revealed six distinct regions with homogeneous event type frequency that match well regions with similar behavior in terms of runoff response identified in Germany. The detected seasonal pattern of event type occurrence is regionally consistent and agrees well with the seasonality of hydroclimatic conditions. The proposed framework can be a useful tool for comparative analyses of regional differences and similarities of runoff generation processes at catchment scale and their possible spatial and temporal evolution.

Climate More Important for Chinese Flood Changes Than Reservoirs and Land Use

“…To shed light on the role of different climate drivers in flood change, we classify all 50,121 flood events into five flood types, that is, snowmelt, rain, rain‐on‐ice, rain‐on‐snow, and mixture of snowmelt/rainfall, based on a process‐based framework (Tarasova et al., 2020, supporting information). We relate the changes in the potential drivers (i.e., precipitation, snow depth, and soil moisture) to changes in floods across China and more specifically in six hotspots that are representative of the spatial distribution of flood types and climate drivers (see supporting information).…”

Transformation of Generation Processes From Small Runoff Events to Large Floods

“…All events were categorized according to the multi‐layer process‐based framework of Tarasova et al (2020). The framework uses indicators that characterize space‐time dynamics of inducing precipitation events and their spatial interaction with antecedent catchment states, such as snow cover, frozen soils, and soil moisture content (Figure 1b).…”

“…(c) A decision tree for hierarchical event classification that combines all layers of the framework into event types (Text S3). Modified from Tarasova et al (2020) CC BY.…”

“…The states categorized at each layer of the framework can be combined hierarchically (Figure 1c) to obtain a unique type for each event. The framework and hierarchical decision tree applied for classification of runoff events in Germany showed regionally consistent performance allowing comparison of classified events in the study catchments (Tarasova et al, 2020).…”

Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events

“…The approach based on the model-dependent realism is quite general and could be extended in different directions: (1) including, in the hydrological model, other mechanisms generating flood events like snow-melt, rain-on-snow, glacier-melt floods [44][45][46] , (2) considering other hydrological models, with more realistic assumptions ( [47][48][49][50] , among others), and comparing these with the simplified model used here; (3) investigating other hydrological problems in order to study the typology of dependence between the variables, and the existence or not of causality.…”