Quantifying space-time dynamics of flood event types

497

335

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 traditionally been obtained through two alternative research approaches. The first approach is the data-based detection of changes in 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 nonlinear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities associated with flood change scenarios are discussed 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 long duration records and flood-rich and flood-poor periods rather than on short duration 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.

Section: (I) Change Analysis Of Individual Time Seriesmentioning

confidence: 99%

Understanding flood regime changes in Europe: a state-of-the-art assessment

Hall

Arheimer

Borga

et al. 2014

497

335

“…Analytical models (e.g. Viglione et al, 2010a) and/or simple hydrological models may also be considered to better characterize the spatially variable hydrological response as a function of the spatial rainfall and the measured discharge.…”

Section: Regional-scale Modellingmentioning

confidence: 99%

“…Spatial and temporal rainfall variability, landscape characteristics and soil humidity are recognized as important influential factors in flash flood generation . Several authors Viglione et al, 2010a, b) proposed methods to determine the characteristic spatial and temporal scales of the processes leading to flash floods. Borga et al (2008) and Bouilloud et al (2010) showed that it is essential to use high-resolution space-time rainfall fields provided by weather radars to properly analyse and understand flash floods.…”

mentioning

confidence: 99%

Multi-scale hydrometeorological observation and modelling for flash flood understanding

Braud¹,

Ayral

Bouvier

et al. 2014

Abstract. This paper presents a coupled observation and modelling strategy aiming at improving the understanding of processes triggering flash floods. This strategy is illustrated for the Mediterranean area using two French catchments (Gard and Ardèche) larger than 2000 km 2 . The approach is based on the monitoring of nested spatial scales: (1) the hillslope scale, where processes influencing the runoff generation and its concentration can be tackled; (2) the small to medium catchment scale (1-100 km 2 ), where the impact of the network structure and of the spatial variability of rainfall, landscape and initial soil moisture can be quantified; (3) the larger scale (100-1000 km 2 ), where the river routing and flooding processes become important. These observations are part of the HyMeX (HYdrological cycle in the Mediterranean EXperiment) enhanced observation period (EOP), which will last 4 years (2012)(2013)(2014)(2015). In terms of hydrological modelling, the objective is to set up regional-scale models, while addressing small and generally ungauged catchments, which represent the scale of interest for flood risk assessment. Topdown and bottom-up approaches are combined and the models are used as "hypothesis testing" tools by coupling model development with data analyses in order to incrementally evaluate the validity of model hypotheses. The paper first presents the rationale behind the experimental set-up and the instrumentation itself. Second, we discuss the associated modelling strategy. Results illustrate the potential of the approach in advancing our understanding of flash flood processes on various scales.

“…First, most previous studies have been limited to a single catchment or only a few catchments (Ajami et al, 2004;Bell and Moore, 2000;Das et al, 2008;Finnerty et al, 1997;Lindström et al, 1997;Reed et al, 2004;Smith et al, , 2012Winchell et al, 1998;Zhang et al, 2004), which makes conclusions highly dependent on the characteristics of the catchments studied. Interestingly, their contradictory conclusions show that the impact of the rainfall spatial distribution on runoff depends on catchment and event characteristics (Segond et al, 2007;Singh, 1997;Tetzlaff and Uhlenbrook, 2005;Viglione et al, 2010;Woods and Sivapalan, 1999;Zoccatelli et al, 2011). Second, many studies are virtual experiments based on synthetic flows, in which model simulations are compared to other simulations chosen as references.…”

Section: Introductionmentioning

confidence: 99%

When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation using 3620 flood events

Lobligeois¹,

Andréassian²,

Perrin³

et al. 2014

184

138

Abstract. Precipitation is the key factor controlling the highfrequency hydrological response in catchments, and streamflow simulation is thus dependent on the way rainfall is represented in a hydrological model. A characteristic that distinguishes distributed from lumped models is the ability to explicitly represent the spatial variability of precipitation. Although the literature on this topic is abundant, the results are contrasting and sometimes contradictory. This paper investigates the impact of spatial rainfall on runoff generation to better understand the conditions where higher-resolution rainfall information improves streamflow simulations. In this study, we used the rainfall reanalysis developed by Météo-France over the whole country of France at 1 km and 1 h resolution over a 10 yr period. A hydrological model was applied in the lumped mode (a single spatial unit) and in the semidistributed mode using three unit sizes of subcatchments. The model was evaluated against observed streamflow data using split-sample tests on a large set of French catchments (181) representing a variety of sizes and climate conditions. The results were analyzed by catchment classes and types of rainfall events based on the spatial variability of precipitation. The evaluation clearly showed different behaviors. The lumped model performed as well as the semidistributed model in western France, where catchments are under oceanic climate conditions with quite spatially uniform precipitation fields. By contrast, higher resolution in precipitation inputs significantly improved the simulated streamflow dynamics and accuracy in southern France (Cévennes and Mediterranean regions) for catchments in which precipitation fields were identified to be highly variable in space. In all regions, natural variability allows for contradictory examples to be found, showing that analyzing a large number of events over varied catchments is warranted.