Flood generation: process patterns from the raindrop to the ocean

This article reviews river flood generation processes and flow paths across space scales. The scale steps include the pore, profile, hillslope, catchment, regional and continental scales, representing a scale range of a total of 10 orders of magnitude. Although the processes differ between the scales, there are notable similarities. At all scales, there are media patterns that control the flow of water, and are themselves influenced by the flow of water. The processes are therefore not spatially random (as in thermodynamics) but organised, and preferential flow is the rule rather than the exception. Hydrological connectivity, i.e. the presence of coherent flow paths, is an essential characteristic at all scales. There are similar controls on water flow and thus on flood generation at all scales, however, with different relative magnitudes. Processes at lower scales affect flood generation at the larger scales not simply as a multiple repetition of pore scale processes, but through interactions, which cause emergent behaviour of process patterns. For this reason, when modelling these processes, the scale transitions need to be simplified in a way that reflects the relevant structures (e.g. connectivity) and boundary conditions (e.g. groundwater table) at each scale. In conclusion, it is argued that upscaling as the mere multiple application of small scale process descriptions will not capture the larger scale patterns of flood generation. Instead, there is a need to learn from observed patterns of flood generation processes at all spatial scales.

The relative importance of antecedent soil moisture and precipitation in flood generation in the middle and lower Yangtze River basin

Floods have caused severe environmental and social economic losses worldwide in human history, and are projected to exacerbate due to climate change. Many floods are caused by heavy rainfall with highly saturated soil, however, the relative importance of rainfall and antecedent soil moisture and how it changes from place to place has not been fully understood. Here we examined annual floods from more than 200 hydrological stations in the middle and lower Yangtze River basin. Our results indicate that the dominant factor of flood generation shifts from rainfall to antecedent soil moisture with the increase of watershed area. The ratio of the relative importance of antecedent soil moisture and daily rainfall (SPR) is positively correlated with topographic wetness index and has a negative correlation with the magnitude of annual floods. This linkage between watershed characteristics that are easy to measure and the dominant flood generation mechanism provides a quantitative method for flood control and early warnings in ungauged watersheds in the middle and lower Yangtze River basin.

Identifying sensitivities in flood frequency analyses using a stochastic hydrologic modeling system

This study employs a stochastic hydrologic modeling framework to evaluate the sensitivity of flood frequency analyses to different components of the hydrologic modeling chain. The major components of the stochastic hydrologic modeling chain, including model structure, model parameter estimation, initial conditions, and precipitation inputs were examined across return periods from 2 to 100 000 years at two watersheds representing different hydroclimates across the western USA. A total of 10 hydrologic model structures were configured, calibrated, and run within the Framework for Understanding Structural Errors (FUSE) modular modeling framework for each of the two watersheds. Model parameters and initial conditions were derived from long-term calibrated simulations using a 100 member historical meteorology ensemble. A stochastic event-based hydrologic modeling workflow was developed using the calibrated models in which millions of flood event simulations were performed for each basin. The analysis of variance method was then used to quantify the relative contributions of model structure, model parameters, initial conditions, and precipitation inputs to flood magnitudes for different return periods. Results demonstrate that different components of the modeling chain have different sensitivities for different return periods. Precipitation inputs contribute most to the variance of rare floods, while initial conditions are most influential for more frequent events. However, the hydrological model structure and structure–parameter interactions together play an equally important role in specific cases, depending on the basin characteristics and type of flood metric of interest. This study highlights the importance of critically assessing model underpinnings, understanding flood generation processes, and selecting appropriate hydrological models that are consistent with our understanding of flood generation processes.

Identifying Sensitivities in Flood Frequency Analyses using a Stochastic Hydrologic Modeling System

This study assesses sources of variance in stochastic hydrologic modelling to support flood frequency analyses. The major components of the modelling chain, including model structure, model parameter estimation, initial conditions, and precipitation inputs were examined across return periods from 2 to 100,000 years at two watersheds representing different hydro-climates across the western United States. Ten hydrologic model structures were configured, calibrated and run within the Framework for Understanding Structural Errors (FUSE) modular modelling framework for each of the two watersheds. Model parameters and initial conditions were derived from long-term calibrated simulations using a 100-member historical meteorology ensemble. A stochastic event-based hydrologic modelling workflow was developed using the calibrated models; millions of flood event simulations were performed at each basin. The analysis of variance method was then used to quantify the relative contributions of model structure, model parameters, initial conditions, and precipitation inputs to flood magnitudes for different return periods. The attribution of the variance of flood frequencies to each component of a stochastic hydrological modelling framework, including several hydrological model structures, is a novel contribution to the flood modelling literature. Results demonstrate that different components of the modelling chain have different sensitivities for different return periods. Precipitation inputs contribute most to the variance of rare events, while initial conditions are most influential for the more frequent events. However, the hydrological model structure and structure-parameter interactions together play an equally important role in specific cases, depending on the basin characteristics and type of flood metric of interest. This study highlights the importance of critically assessing model underpinnings, understanding flood generation processes, and selecting appropriate hydrological models that are consistent with our understanding of flood generation processes.

Flash-flooding of Ephemeral Streams in the Context of Climate Change

Ephemeral streams, which are more extended than expected, entail a significant flood risk. Historically they have been underestimated due to their intermittent flow and the lack of knowledge on their hydro-geomorphology. Currently, European legislation recognizes their associated risk and supports research into them, adapting the scale and methodology to their characteristics. Based on the compilation of various works carried out in four Valencian catchments (Eastern Spain), this paper approaches the key questions of rainfall-runoff conversion and flood generation in ephemeral streams, taking into account their hydro-geomorphological specificity. Moreover, the consequences which derive from current environmental changes are addressed in the wider scale of Júcar River Water Authority.The study is based on 5-minute data, registered by the SAIH-Júcar network (Authomatic Hydrological Information System). The investigation has been conducted in two phases. Firstly, key issues determining flash-flood generation at basin scale have been addressed, based on the study of 138 floods, registered between 1989 and 2018, in four Valencian ephemeral streams (Barranc del Carraixet, Rambla de Poyo, Riu Vernissa and Rambla de Gallinera). Secondly, concerning a broader scale (Júcar River Water Authority), the evolution of 698 rain episodes (1989-2007) has been analysed. Finally, the consequences that environmental changes (climatic, anthropogenic and morphogenetic) might mean for flash-flood generation have been discussed.The results show how environmental changes point towards an increase in risk to the detriment of resource. Rain episodes tend to increase in intensity and decrease accumulated precipitation. As a consequence, hydrological connectivity will become more dependent on rain intensity, thus reducing runoff thresholds and basin response times. Anthropic changes enhance this behaviour, reducing infiltration and increasing surface runoff and erosion, while accelerating the hydrological cycle. An increase in process-form disequilibrium in Mediterranean catchments can be expected due to the increase in morphogenetic phases (because of the intensification of events) and a decrease in the efficiency of low-magnitude recovery episodes.Consequently, the behaviour of ephemeral-streams under current climate change conditions points firstly to an increase in intense flash-flood events, which will be difficult to manage with the current flood control measures, and secondly an increase in the general aridity conditions of catchments.

Biases in national and continental flood risk assessments by ignoring spatial dependence

Recently, flood risk assessments have been extended to national and continental scales. Most of these assessments assume homogeneous scenarios, i.e. the regional risk estimate is obtained by summing up the local estimates, whereas each local damage value has the same probability of exceedance. This homogeneity assumption ignores the spatial variability in the flood generation processes. Here, we develop a multi-site, extreme value statistical model for 379 catchments across Europe, generate synthetic flood time series which consider the spatial correlation between flood peaks in all catchments, and compute corresponding economic damages. We find that the homogeneity assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139%, 188% and 246% for the United Kingdom (UK), Germany and Europe, respectively. Our study demonstrates the importance of considering the spatial dependence patterns, particularly of extremes, in large-scale risk assessments.

The role of extremity of summer floods for the annual statistic

<p>Within the annual maximum series (AMS), which is the basis for assessing most of the flood protection measurements, summer as well as winter flood events are included. However, these do not only differ in their flood generation but also in their statistical distribution. While the distribution of winter floods is mostly light-tailed, summer floods often show a heavy-tailed behaviour. A light-tailed behaviour leads to a bounded distribution, which means that winter floods cannot exceed a certain magnitude. Heavy-tailed distributions are unbounded and extrapolation to annualities of several hundred years can lead to infinitely large design floods.  A combination of these different tail behaviours in the AMS often leads to heavy-tail behaviour for the annual series. In a study of the large river basins of Rhine, Danube and Elbe we investigate the impact of summer floods on the AMS. Spatial patterns become visible that can be linked to weather patterns like Vb. Moreover, an impact of the catchment size can be seen, where larger catchments tend to have lighter tailed distributions and a smaller impact of summer floods.  The results are then compared concerning their causality using deterministic models that include dam failure and inundation and the role of tributaries is shown.</p>

Mutual increases in flood extents and magnitudes intensify flood hazard in Central and Western Europe

<p>Climate change has led to changing flood synchrony scales (extents) and flood magnitudes across Europe. We discovered a tight alignment between extents and magnitudes and found the drivers of their joint trends. We analyzed the annual maximum floods of 3872 hydrometric stations across Europe from 1960-2010 and classified all floods in terms of their generating processes based on antecedent weather conditions. There is a positive correlation between flood extents and magnitudes for 95% of the stations. While both parameters increased in Central and Western Europe, they jointly decreased in the East. This widespread magnitude extent correlation is caused by similar correlations for precipitation, soil moisture and snowmelt. We found trends in the relevance of the different flood generation processes, which explain the regional flood trends. The aligned increases of flood extents and magnitudes emphasize the growing importance of transnational flood risk management.</p>

Understanding catchment influences on flood generating processes - accounting for correlated attributes

<p>Understanding flood generating mechanisms is critical for model development and evaluation. While several studies analyse how catchment attributes influence flood magnitude and duration, very few studies examine how they influence flood generating processes. Based on prior knowledge about runoff behaviour and flood generation, we assume that flood processes depend not only on climate, but also on catchment characteristics such as topography, vegetation and geology. Specifically, we hypothesize that the influence of catchment attributes on flood processes will vary between different climate types. We tested our hypothesis on the CAMELS dataset, a large sample (671) of catchments in the United States. We classified 61,828 flood events into flood process types using a previously published location-independent classification methodology. Then we quantified the importance of both individual attributes (comparing probability distributions of different flood types) and interacting attributes (using random forests). Accumulated local effects allow interpretability of random forest with correlated attributes. Results show that climate attributes most strongly influence the distribution of flood generating processes within a catchment. However, other catchment attributes can be influential, depending on climate type. Based on the subset of influential catchment attributes, a random forest model can predict flood generating processes with high accuracy for most processes and climates, demonstrating capabilities to predict flood processes in ungauged catchments. Some attributes proved less influential than common hydrologic knowledge would suggest and are not informative in predicting flood process distribution.</p>