The Regional Hydrology of Extreme Floods in an Urbanizing Drainage Basin

Abstract. The 2 June 2008 flood-producing storm on the Starzel river basin in South-West Germany is examined as a prototype for organized convective systems that dominate the upper tail of the precipitation frequency distribution and are likely responsible for the flash flood peaks in Central Europe. The availability of high-resolution rainfall estimates from radar observations and a rain gauge network, together with indirect peak discharge estimates from a detailed post-event survey, provided the opportunity to study in detail the hydrometeorological and hydrological mechanisms associated with this extreme storm and the ensuing flood. Radar-derived rainfall, streamgauge data and indirect estimates of peak discharges are used along with a distributed hydrologic model to reconstruct hydrographs at multiple locations. Observations and model results are combined to examine two main questions, (i) assessment of the distribution of the runoff ratio for the 2008 flash flood and how it compares with other less severe floods; and (ii) analysis of how the spatial and temporal distribution of the extreme rainfall, and more specifically storm motion, controls the flood response. It is shown that small runoff ratios (less than 20 %) characterized the runoff response and that these values are in the range of other, less extreme, flood events. The influence of storm structure, evolution and motion on the modeled flood hydrograph is examined by using the "spatial moments of catchment rainfall". It is shown that downbasin storm motion (in the range of 0.7-0.9 m s −1 ) had a noticeable impact on flood response by increasing the modeled flood peak by 13 %.

Section: Ruiz-villanueva Et Al: Extreme Flood Response To Short-dmentioning

confidence: 93%

Extreme flood response to short-duration convective rainfall in South-West Germany

Ruíz-Villanueva

Borga

Zoccatelli

et al. 2012

“…They also identified limitations of this and similar modeling studies, where hydrologic response may be attributable to errors in radar rainfall estimates or to features that were omitted or poorly represented in the model, such as detention ponds, the spatial distribution of layered soils and, in particular, initial soil moisture. Smith et al (2002) used a data-driven approach to study relationships between temporal and spatial rainfall variability and hydrological response in urban basins. They introduced the concept of rainfall-weighted flow distance, representing storm position and movement relative to the flow-path network in the basin.…”

Section: Introductionmentioning

confidence: 99%

The role of storm scale, position and movement in controlling urban flood response

Veldhuis

Zhou

Yang

et al. 2018

Abstract. The impact of spatial and temporal variability of rainfall on hydrological response remains poorly understood, in particular in urban catchments due to their strong variability in land use, a high degree of imperviousness and the presence of stormwater infrastructure. In this study, we analyze the effect of storm scale, position and movement in relation to basin scale and flow-path network structure on urban hydrological response. A catalog of 279 peak events was extracted from a high-quality observational dataset covering 15 years of flow observations and radar rainfall data for five (semi)urbanized basins ranging from 7.0 to 111.1 km 2 in size. Results showed that the largest peak flows in the event catalog were associated with storm core scales exceeding basin scale, for all except the largest basin. Spatial scale of flood-producing storm events in the smaller basins fell into two groups: storms of large spatial scales exceeding basin size or small, concentrated events, with storm core much smaller than basin size. For the majority of events, spatial rainfall variability was strongly smoothed by the flowpath network, increasingly so for larger basin size. Correlation analysis showed that position of the storm in relation to the flow-path network was significantly correlated with peak flow in the smallest and in the two more urbanized basins. Analysis of storm movement relative to the flow-path network showed that direction of storm movement, upstream or downstream relative to the flow-path network, had little influence on hydrological response. Slow-moving storms tend to be associated with higher peak flows and longer lag times. Unexpectedly, position of the storm relative to impervious cover within the basins had little effect on flow peaks. These findings show the importance of observation-based analysis in validating and improving our understanding of interactions between the spatial distribution of rainfall and catchment variability.

“…Observational and modelling studies have shown that the river network geometry plays a central role in the structure of the catchment dampening properties, particularly for cases of extreme floods when the impact of land properties heterogeneity on runoff generation is less significant with respect to moderate floods and the stream network extends to previously unchanneled topographic elements, hence increasing drainage density and flow response rate of hillslopes (Naden, 1992;Woods and Sivapalan, 1999;Smith et al, 2002;Nicotina et al, 2008;Sangati et al, 2009). Runoff routing through branched channel networks imposes an effective averaging of spatial rainfall excess across locations with equal routing time, in spite of the inherent spatial variability.…”

Section: Introductionmentioning

confidence: 99%

“…Smith et al (2002Smith et al ( , 2005, Zhang et al (2001) and Borga et al (2007), in a series of monographs on extreme floods and flash floods, systematically employed a scaled measure of distance from the storm centroid and scaled measures of rainfall variability to quantify the storm spatial organisation and variability from the perspective of a distance metric imposed by the river network. Smith et al (2004a) examined basin outflow response to observed spatial variability of rainfall for several basins in the Distributed Model Intercomparison Project (Smith et al, 2004b), by using, among other indexes, a rainfall location index based on the distance from the centroid of the catchment to the centroid of the rainfall pattern.…”

Section: Introductionmentioning

confidence: 99%

Spatial moments of catchment rainfall: rainfall spatial organisation, basin morphology, and flood response

Zoccatelli

Borga

Viglione

et al. 2011

Abstract. This paper describes a set of spatial rainfall statistics (termed "spatial moments of catchment rainfall") quantifying the dependence existing between spatial rainfall organisation, basin morphology and runoff response. These statistics describe the spatial rainfall organisation in terms of concentration and dispersion statistics as a function of the distance measured along the flow routing coordinate. The introduction of these statistics permits derivation of a simple relationship for the quantification of catchment-scale storm velocity. The concept of the catchment-scale storm velocity takes into account the role of relative catchment orientation and morphology with respect to storm motion and kinematics. The paper illustrates the derivation of the statistics from an analytical framework recently proposed in literature and explains the conceptual meaning of the statistics by applying them to five extreme flash floods occurred in various European regions in the period 2002-2007. High resolution radar rainfall fields and a distributed hydrologic model are employed to examine how effective are these statistics in describing the degree of spatial rainfall organisation which is important for runoff modelling. This is obtained by quantifying the effects of neglecting the spatial rainfall variability on flood modelling, with a focus on runoff timing. The size of the study catchments ranges between 36 to 982 km 2 . The analysis reported here shows that the spatial moments of catchment rainfall can be effectively employed to isolate and describe the features of rainfall spatial organization which have significant impact on runoff simulation. These statistics provide useful information on what space-time scales rainfall has to be monitored, given certain catchment and flood characteristics, and what are the effects of space-time aggregation on flood response modeling.