HS2.4.5

To analyze the river floods dynamics, it is common to fix the observations of the flow at a characteristic checkpoint of the basin, showing its evolution over time:  the hydrograph. A less common way of studying this hydrological phenomenon is the analysis of the unit peak discharge of the flood (i.e., the peak flow divided by the contributory area of the basin) along different checkpoints of the drainage axis.

If this second methodology is chosen for the analysis of the river flooding, the circulation of flows through the river network generally shows that as the contributory area of the basin increases the unit peak discharge decreases. This is due to the reduction in the amount of precipitation and the slope of the riverbed with the increase of the basin area as it moves away from the headwaters. However, this simple scheme can have very different behavior depending on factors such as the spatial and temporal distribution of precipitation, the presence of snow, the soil moisture, the geological substrate, land uses, or human activities.

This study compares the hydrological data of several historical and recent floods in NE basins of the Iberian Peninsula from the perspective of observing the unit peak flows depending on the size of the drained basin (i.e., the spatial evolution of the specific maximum discharge). These basins are small in size (usually below 500 km²) and drain regions such as the central Pyrenees (Garonne, Noguera Pallaresa), the Ebro Depression (rivers Ribera Salada, Sió, Ondara, Corb) and the Catalan Coastal System (Francolí), that is, they belong to very diverse geographical environments.

The results allow to compare the magnitude of the unit peak flows in the headwaters and the decreasing of this variable when moving downstream. The unit peak discharges of the tributaries of the Ebro Depression, near the Catalan Coastal System are much higher when comparing with the flow of the Pyrenean rivers. For many floods of the Ebro basin of medium magnitude, the unit peak flow is reduced by the runoff infiltration in the flood plains favored by agricultural activities. In the Pyrenean rivers the spatial decrease of the unit peak discharge is gentle than in those of the Ebro Depression. The results show different patterns of flow generation and propagation that have implications for managing the dangerousness of flood risk, especially in very small basins (< 10 km²), where peak flows can be unexpectedly large and devastating.

How to cite: Balasch, J. C., Tuset, J., Barriendos, M., Castelltort, X., and Pino, D.: The unit peak discharge as a tool for flood magnitude comparison and analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11192, https://doi.org/10.5194/egusphere-egu21-11192, 2021.

Extreme value theory (EVT) is commonly applied in hydrology to study extreme events. The univariate approach has been widely used in literature on this topic, but this limits the analysis to single sites. A more recent approach considers multivariate techniques applied to larger datasets, to detect the spatial structure of these events. However, how to properly define events and which variables should be considered for their identification and characterization in a regional domain is still a matter of debate. Moreover, recent studies have pointed out the increasing need of establishing connections between the different processes entering the hydrological cycle at larger spatial scales, especially in the context of global climate change. This work presents a non-parametric method for extracting the largest hydrological events occurring over the Northwestern Italy in the last decades and correlates them to spatially averaged extreme climate indices (ETCCDI). In particular, the extraction of extreme hydrological events started from the calculation of the empirical non-exceedance probability of the daily runoff values, at each station of the stream gauge network, and of a corresponding empirical return time. Then, a daily regional return time was determined by averaging the return time values over all stations for each day, with a sliding time window and site-related weights. Finally, the local maxima of the regional return time were extracted by intersecting the signal with a filter of the return time itself and the largest annual event was considered for each year. The spatial dependence of these events was analysed by extracting the local maximum discharge values at each station, corresponding to the occurrence of the maximum regional return times. A correlation with regional values of the ETCCDI indices was also performed to get some insights on the meteorological extremes playing a role in the formation of floods. Results show a rank of the extracted events for the study area and some considerations on their relative impact in terms of damage are provided. This gives an indication of the long-term variability of extreme events at the regional scale.

How to cite: Pesce, M., Viglione, A., Borre, A., Gabellani, S., von Hardenberg, J., and Ganora, D.: Identification of meteo-hydrological extreme events at the regional scale: the Northwestern Italy case study, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13376, https://doi.org/10.5194/egusphere-egu21-13376, 2021.

Economic losses and social consequences caused by floods have been steadily increasing over the last decades over Europe. In such a situation, the detection of changes in flood behaviour is crucial and the scientific community itself calls for a common effort to better understand recent flood dynamics and their evolution in space and time.

In this context, our study considers an extensive dataset of annual maximum series of peak flow discharges for more than 3400 catchments across Europe for the period 1820-2016 (average record length of 53 years). Based on this extensive dataset, our study analyses the behaviour of the specific flood of record (i.e. the largest flood observed in the time interval of interest divided by the drainage area of the corresponding catchment, hereafter also referred to as SFOR) in space and time across the European continent. In particular, we consider the spatial variability of SFOR computed for the entire observation period and for two 30-years sub-samples, namely 1987-2016 and 1957-1986. We focus on three macro-regions over northwestern, southern and eastern Europe, which have been identified by previous studies as homogeneous in terms of flood regime changes and processes driving flood changes. For the selected different timespans and macro-regions, we analyse the spatial variability of the year in which SFOR was observed, and the number of times in which a new record was observed at each and every gauge, also evaluating their relationship with catchment area. By referring to the theory of record-breaking processes, we also evaluate the non-stationarity in flood sequences by accounting for the presence of spatial correlation among flood sequences.

Finally, we provide a continuous spatial representation of SFOR values across Europe by referring to the dataset of elementary catchments identified by the Joint Research Centre (JRC) of the European Commission. For each elementary catchment of the JRC dataset, we interpolate empirical SFOR values by means of the geostatistical procedure termed top-kriging, which accounts for nesting between catchments.

The outcomes of our study provide useful information on the spatio-temporal evolution of flooding potential across Europe, enabling a visualization of the current flooding potential across Europe and of significant changes and shifts of the flood of record occurred during the last five decades.

How to cite: Arletti, F., Persiano, S., Bertola, M., Parajka, J., Blöschl, G., and Castellarin, A.: Recent spatio-temporal dynamics of floods of record across Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14910, https://doi.org/10.5194/egusphere-egu21-14910, 2021.

Flood estimation in ungauged basins is important for flood design, and for improving our understanding of the sensitivity of flood magnitude to changes in climate and land cover. Flood estimates by current methods (e.g. statistical regression, unit hydrograph) have high uncertainty, even in places with dense observing networks (e.g. +/- 50-100% in the UK). Reductions in this uncertainty are being sought by using alternative methods, such as continuous simulation using hydrological models (spatially-distributed or lumped), and event-scale derived distribution approaches. The very significant challenges for reliable application of continuous simulation models in ungauged catchments are well described in the literature.

The event-scale derived distribution approach also has challenges, which we explore below. The derived distribution approach at the event scale typically combines the following elements: a stochastic rainfall model, an event-scale rainfall-runoff model (including “losses” and a “baseflow” component), and a runoff routing model. In principle, every element of this approach may be considered as a (seasonally varying) random variable. The flood peak distribution is obtained by integrating over joint distributions of the model elements.

First challenge: what is the physical basis for estimating the event runoff coefficient? In the 1970s, this was addressed using infiltration theory, but other runoff generation mechanisms are often more important. How do we connect our knowledge of seasonal water balance and runoff generation processes to the probability distribution of event runoff coefficients, and its seasonal variation? We suggest (i) begin with locations which are dominated by a small number of runoff generation mechanisms (ii) make use of existing theory on links between climate, catchment characteristics and seasonal water balance (iii) adapt relevant simple concepts of runoff generation which link seasonal water balance to runoff generation.

Second challenge: how do we parsimoniously quantify the impacts of within-storm temporal rainfall patterns on the flood hydrograph? Existing approaches use stochastic rainfall models to explicitly generate (hourly) time series of rainfall; since catchments damp out high frequency forcing, we suggest that these rainfall series often contain excessive temporal detail and obscure the most informative interactions between rainfall and catchment response. We propose that we use stochastic models that can generate hydrologically relevant attributes of rainfall events (e.g. intensity/depth/duration, spatial and temporal moments), and then apply rainfall-runoff transformations which operate on rainfall moments, and do not require excess detail in temporal (or spatial) patterns of rainfall.

Third challenge: What is an event? This is no problem for theoretical models, but it is hard as a data analysis question, and we need data analysis to implement and evaluate the derived distribution method. The event identification methods of engineering hydrology are subjective, require manual intervention and are poorly suited for large sample hydrology! We suggest the answer lies in the catchment’s response time.

The underlying conceptual framework to link seasonal climate and hydrology to floods is already available (Sivapalan et al, 2005). What these challenges require is that we integrate and apply more of our existing hydrological concepts and knowledge to implement the process-based theory of flood frequency. 

How to cite: Woods, R., Zheng, Y., Quaglia, R., Giani, G., Han, D., and Rico-Ramirez, M.: Challenges for Application of the Derived Distribution Approach to Flood Frequency, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15044, https://doi.org/10.5194/egusphere-egu21-15044, 2021.

For derived flood frequency analyses, stochastic rainfall models can be linked with rainfall-runoff models to improve the accuracy of design flood estimations when the length of observed rainfall and runoff data is not sufficient. The stochastic rainfall time series, which are used as input for the rainfall-runoff model, can be generated with different spatial resolution: (a) Point rainfall, which is stochastically generated rainfall at a single site. (b) Areal rainfall, which is catchment rainfall averaged over multiple sites before using the single-site stochastic rainfall model. (c) Multiple point rainfall, which is stochastically generated at multiple sites with spatial correlation before averaging to catchment rainfall. To find the most applicable spatial representation of stochastically generated rainfall for derived flood frequency analysis, simulated and observed runoff time series will be compared based on runoff statistics. The simulated runoff time series are generated utilizing the rainfall-runoff model HBV-IWW with an hourly time step. The rainfall-runoff model is driven with point, areal and multiple point stochastic rainfall time series generated by an Alternating Renewal rainfall model (ARM). In order to take into account the influence of catchment size on the results, catchments of different sizes within Germany are considered in this study.  While point rainfall may be applicable for small catchments, it is expected that above a certain catchment size a more detailed spatial representation of stochastically generated rainfall is necessary. Here, it would be advantageous if the results based on areal rainfall are comparable to those of the multiple point rainfall. The stochastically generation of areal rainfall is less complex compared to the stochastically generation of multiple point rainfall and extremes at the catchment scale may also be better represented by areal rainfall.    

How to cite: Thiele, L.-B., Pidoto, R., and Haberlandt, U.: Spatial representation of stochastically generated rainfall for derived flood frequency analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1971, https://doi.org/10.5194/egusphere-egu21-1971, 2021.

The Rhône River has undergone many anthropogenic transformations to improve his navigability and produce hydroelectricity since the mid-19th century. From the longitudinal dikes of the 1850’s to the hydroelectric diversion schemes of the 1950’s and 1960’s, these structures had a direct impact on the channel geometry along the 300km of river course between Lyon (France) and the Mediterranean Sea. An indirect consequence could be a change in the flood dynamics along the channel course, caused by the simplification of the channel patterns and the floodplain accretion. This communication aims to assess the potential changes in the flood propagation along the middle and lower Rhône valley throughout a century of anthropogenic reconfigurations of the channel. The possible impact of these human pressures on the inundation risk and the attenuation of the flood peak discharge is also discussed. Through the use of digitized hydrometric data recorded since 1840 on multiple stream gauges of the Rhône river, a variety of floods of the same type and magnitude are selected. The oceanic flood types (as described by Pardé, 1925) that take their origin from heavy rainfalls upstream of the area of interest are preferred. Thus, complex flood waves due to floods from the lower Rhône valley tributaries are avoided, to keep the analysis as simple as possible. The flood travel time and the peak discharge attenuation of the selected events are compared over the years of channel transformations, permitting us to estimate the impact of anthropogenic pressures on the flood dynamics.

How to cite: Lucas, M., Lang, M., Le Coz, J., Renard, B., and Piegay, H.: Effects of channel engineering on flood dynamics along the middle and lower Rhône over the last two centuries., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9577, https://doi.org/10.5194/egusphere-egu21-9577, 2021.

Riverine floods are exhibiting temporal shifts in both magnitude and timing under the context of climate change as well as human alternations of the river systems (i.e., construction of reservoirs and land management practices). A nation-wide assessment of changes in riverine floods is still lacking over China, despite the societal perception that recent Chinese flood trends are dictated by drastic environmental changes associated with rapid economic development. Here we examine changes in flood magnitude and timing based on the most comprehensive database of annual maximum flood peak discharge (AMF) over China during the period 1960-2017. We find both increasing and decreasing trends in AMF magnitude and timing. Trends in AMF magnitudes range from -4.29% to 2.86% (per year relative to long-term mean flood peak discharge). Decreased AMF magnitudes are observed in central and northern China, while increased AMF magnitudes mainly in northwestern and southern China. The shifts of AMF timing range from -16 days to +18 days per decade. Changes in AMF timing show less spatial consistency than that in AMF magnitude. We categorize the gauged watersheds into human-modified and natural categories. Flood changes in natural watersheds can only be attributed to climate variability. The spatial pattern of changes in AMF magnitude and timing in human-modified watersheds resembles those in natural watersheds, pointing towards the dominant role of climate in dictating recent flood changes over China. Impacts of reservoirs and land management practices are only isolated cases. We further provide a predictive understanding of climatic controls on flood hazards over China (and East Asian countries) by establishing connections between changes in AMF magnitude/timing and climate indices. Our analyses, together with similar efforts in other continents, contribute to a general understanding of space-time dynamics of riverine floods around the globe.

How to cite: Yang, Y. and Yang, L.: Climate dominates changes in flood magnitude and timing across China during 1960-2017, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10604, https://doi.org/10.5194/egusphere-egu21-10604, 2021.

Changes in European floods during past decades have been analysed and detected by several studies. These studies typically focused on the mean flood behaviour, without distinguishing small and large floods. In this work, we investigate the causes of the detected flood trends across Europe over five decades (1960-2010), as a function of the return period. We adopt a regional non-stationary flood frequency approach to attribute observed flood changes to potential drivers, used as covariates of the parameters of the regional probability distribution of floods. The elasticities of floods with respect to the drivers and the regional contributions of the drivers to changes in flood quantiles associated with small and large return periods (i.e. 2-year and 100-year floods, respectively) are estimated by Bayesian inference, with prior information on the elasticity parameters obtained from expert knowledge and the literature. The data-based attribution approach is applied to annual maximum flood discharge seires from 2370 hydrometric stations in Europe. Extreme precipitation, antecedent soil moisture and snowmelt are the potential drivers considered. Results show that extreme precipitation mainly contributes to positive flood changes in North-western Europe. Both antecedent soil moisture and extreme precipitation contribute to negative flood changes in Southern Europe, with relative contributions varying with the return period. Antecedent soil moisture contributes the most to changes in small floods (i.e. T=2-10 years), while the two drivers contribute with comparable magnitude to changes in more extreme events. In eastern Europe, snowmelt clearly drives negative changes in both small and large floods.

How to cite: Bertola, M., Viglione, A., Vorogushyn, S., Lun, D., Merz, B., and Blöschl, G.: Data-based attribution of changes in flood quantiles across Europe between 1960 and 2010, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2604, https://doi.org/10.5194/egusphere-egu21-2604, 2021.

Understanding how floods are expected to change is essential for decision making and flood risk management, as flood risks are expected to increase in the future. Several studies have analysed the impact of climate change on flood risks with rainfall-runoff models and climate projections as input data. Nevertheless, most of these studies involve large-scale river basins instead of focusing on smaller river basins or points of interest like urban areas. This study quantifies the expected changes in flood quantiles at the River Arga in the city of Pamplona (Spain) within the SAFERDAMS project (PID2019-107027RB-I00) funded by the Spanish Ministry of Science and Innovation. It uses climate change projections from 12 climate models of the EURO-CORDEX programme for two Representative Concentration Pathways - RCPs as input data of the RIBS distributed hydrological model (Garrote and Bras 1995 ab, JoH). The analysis considers seven return periods (2, 5, 10, 50, 100, 500 and 1000 years), two greenhouse gas emission scenarios (RCP4.5 and RCP8.5) and three time windows (2011-2040, 2041-2070 and 2070-2100).

First, the RIBS model has been calibrated with a set of objective functions to minimise the bias between simulations and observations recorded at a streamflow-gauging station located in the Arga River in Pamplona. The seven greatest flood events occurred in Pamplona in the last decade are considered. A long set of random combinations of model parameter values are used. The combination of parameter values that led to the smallest errors were selected.

Second, 24-h design rainfall storms with a time step of 1 h in the current scenario at a set of rainfall gauge stations in the Arga River catchment are obtained by using an extreme frequency analysis. Expected changes in daily rainfall quantiles in the Arga River catchment obtained by processing climate change projections are used (Garijo and Mediero 2019, Water). Current and future design rainfall storms were obtained for the seven return periods, two RCPs and three time windows. The input data in the RIBS model are provided in a raster format. Hence, design rainfall storms were transformed into spatial distributions of precipitation with the Thiessen polygons technique.

The findings show a decrease in design peak discharges for return periods smaller than 10 years and an increase for the 500- and 1000-year floods for both RCPs in the three time windows. However, 50- and 100-year return period flood quantiles are expected to increase especially in the 2041-2070 and 2071-2100 time windows only in the emission scenario RCP8.5. The emission scenario RCP8.5 always provides greater increases in flood quantiles than RCP4.5, except for the more frequent floods (2, 5 and 10 years) in the time window 2011-2040. The increases of design discharges are 10-30% higher in RCP8.5 than in RCP4.5 for the greatest return periods. Therefore, flood magnitude changes for the most extreme events seem to be related to the evolution of greenhouse gasses emissions, following the same behaviour of the RCPs: the greatest expected changes are in the 2040 for the RCP4.5 and in the 2100 for the RCP8.5.

How to cite: Lompi, M., Mediero, L., and Caporali, E.: Impact of climate change on floods in Pamplona (Spain) by using climate change projections and a distributed hydrological model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9753, https://doi.org/10.5194/egusphere-egu21-9753, 2021.

The catastrophic flood following the Gleno dam break, which occurred in 1923, has been investigated in the literature (Pilotti et al., 2011, Milanesi and Pilotti, 2021) considering the 20 km long steep alpine valley separating the dam location from the hamlet of Corna. In this contribution, we investigate the propagation of the flood wave from Corna, where the computed hydrograph from previous investigation provides the upstream boundary condition, as far as the Lake Iseo outlet in Sarnico, where two controversial documents attest its effect on the lakeshore. In the middle, the flood crossed 30 km of a wide pre-alpine floodplain that has been deeply modified over the last century  and crossed 25 km of a deep lake.

The simulation has been accomplished by coupling 2 different 2D solver of the Shallow Water Equations: the well-known HEC-RAS 2D software was used to cover the floodplain from Corna up to the Lake Iseo inlet, while a finite volume scheme was used to simulate the lake behaviour in response to the incoming flood. The finite volume scheme used to model the lake is based on the WAF solver developed by Toro (Toro, 2001) and further adapted to account for the geometry of lake Iseo using an unstructured mesh. The scheme used retains shock-capturing capabilities and well-balanced properties able to withstand the constantly changing bathymetry of the lake as well as the unsteadiness of the hydrodynamics modelled. As a first step, the simulation was performed on the topography derived from the LIDAR DTM surveyed in 2008-2009. A computational mesh was built with average grid size of 10 m aligned in correspondence of levees and other singularities. This first simulation dramatically shows how the propagation of the flood wave was affected by the presence of linear structures such as levees and road embankments, absent in 1923 as shown by historical maps. For this purpose, the linear structure that affect the flow was removed from the 2008-2009 DTM and a second simulation was performed in order to compare the different flow hydrograph at the inlet of the lake.

An important fallout of the modeling effort is the reconstruction of the 1923 original bathymetry of the river in Valle Camonica, to be compared with the present one, affected by 100 years of river training works. The comparison of the flood propagation using the two bathymetries highlights the consequences of systematic hydraulic works on the hazard distribution for the same event. Paradoxically, the residual risk is now much higher than 100 years ago. Moreover, the simulations show that the claim of a 50 cm high bore at the inlet of the Oglio river is unsubstantiated by the model results and that an important request of damages was probably based on a false statement.

How to cite: Bonomelli, R., Pilotti, M., and Farina, G.: Effects of anthropic changes on the propagation of the Gleno dam break wave in the Valle Camonica floodplain, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9983, https://doi.org/10.5194/egusphere-egu21-9983, 2021.