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HS2.4.3

EDI
Space-time dynamics of floods: processes, controls, and risk

The space-time dynamics of floods are controlled by atmospheric, catchment, river system and anthropogenic processes and their interactions. The natural oscillatory behaviour of floods (between flood-rich and flood-poor periods) superimpose with anthropogenic climate change and human interventions in river morphology and land uses. In addition, flood risk is further shaped by continuous changes in exposure and vulnerability. Despite more frequent exploratory analyses of the changes in spatio-temporal dynamics of flood hazard and risk, it remains unclear how and why these changes are occurring. The scope of this session is to report when, where, how (detection) and why (attribution) changes in the space-time dynamics of floods occur. Of particular interest is what drivers are responsible for observed changes. Presentations on the impact of climate variability and change, land use changes and morphologic changes in streams, as well as on the role of pre-flood catchment conditions in shaping flood hazard and risk are welcome. Furthermore, contributions on the impact of structural measures and demographic and socio-economic factors on past and future risk changes are invited. This session is jointly organised by the Panta Rhei Working Groups “Understanding Flood Changes” and “Changes in Flood Risk”. The session will further stimulate scientific discussion on flood change detection and attribution. Specifically, the following topics are of interest for this session:
- Decadal oscillations in rainfall and floods
- Process-informed extreme value statistics
- Interactions between spatial rainfall and catchment conditions shaping flood patterns
- Detection and attribution of flood hazard changes: atmospheric drivers, land use controls and river training, among others
- Changes in flood risk: urbanisation of flood prone areas; implementation of multi-scale risk mitigation measures, such as natural water retention measures and private precautionary measures; changes of economic, societal and technological aspects driving flood vulnerability and damages, among others.
- Future flood risk scenarios and the role of adaptation and mitigation strategies

Convener: William FarmerECSECS | Co-conveners: Luis Mediero, Sergiy Vorogushyn, Larisa TarasovaECSECS, Nivedita SairamECSECS
Presentations
| Thu, 26 May, 17:00–18:30 (CEST)
 
Room 2.15

Thu, 26 May, 17:00–18:30

Chairperson: William Farmer

17:00–17:02
Introduction

17:02–17:09
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EGU22-3001
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On-site presentation
Ross Woods et al.

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 research reported here is part of a larger project to estimate the probability distribution of flood peak magnitude in ungauged catchments, using an event-based derived distribution method. The derived distribution approach at the event scale typically combines the following elements: a stochastic rainfall model, an event-scale rainfall-runoff model (usually with “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, though previous research has typically considered only the rainfall as stochastic. The flood peak distribution is obtained by integrating over joint distributions of the model elements.

One of the novel aspects of the proposed approach is that, in place of an explicit routing method, we estimate the flood peak magnitude as the ratio of the event runoff depth (mm) to a characteristic timescale of the hydrograph (hours). The event runoff depth is the product of rainfall depth and event runoff coefficient, which in turn depends on both antecedent conditions and event rainfall. The characteristic timescale of the hydrograph is a second temporal moment (temporal “width” of the hydrograph). Although a comprehensive theory exists for space-time influences on this hydrograph time scale, research to date suggests that it depends, to first order, on time scales associated with rainfall and catchment response.

Here we report on extensive (many events, many catchments) testing in the UK of (i) whether the temporal standard deviation of the flow hydrograph is a good choice for the characteristic time scale of the hydrograph in the context of predicting the flood peak (Viglione et al 2010, Journal of Hydrology) (ii) whether the temporal standard deviation of the hydrograph can be predicted from time scales associated with rainfall and catchment response, as proposed by Woods and Sivapalan (1999, Water Resources Research) and Gaál et al (2012, Water Resources Research).

How to cite: Woods, R., Zheng, Y., Quaglia, R., Giani, G., Han, D., Rico-Ramirez, M., and Coxon, G.: Estimating Flood Peaks from Event Runoff Depth and Hydrograph Time Scales, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3001, https://doi.org/10.5194/egusphere-egu22-3001, 2022.

17:09–17:16
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EGU22-13509
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ECS
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On-site presentation
Miriam Bertola et al.

Regional envelope curves represent the current level of information about the most extreme flood events observed in a region. In this study, we derive and compare regional envelope curves across European regions, with a multi-scale approach. A large flood database, containing more than 7000 annual maximum discharge series from gauges located all over Europe, is used for the analysis. Multiple spatial scales are adopted to take into account the uneven gauge density in the study domain. In each region, we derive the slope of the regional envelope curve and the envelope flood for a representative catchment of size 1000km2. Based on the framework of probabilistic envelope curves, we also make a probabilistic statement about the regional envelope curves in terms of its return period. Results show that the slope of the regional envelope curves varies substantially across European regions and the correlation between envelope flood and the estimated return period is investigated.

How to cite: Bertola, M., Castellarin, A., Valtancoli, E., Viglione, A., and Blöschl, G.: Probabilistic regional envelope curves in Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13509, https://doi.org/10.5194/egusphere-egu22-13509, 2022.

17:16–17:23
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EGU22-3060
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ECS
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Virtual presentation
Stefano Basso et al.

Reliable assessment of the flooding hazard of river basins is crucial for many social and economic activities. We present here the Physically-based Extreme Value (PHEV) distribution of river discharges. PHEV is a process-based alternative to empirical estimates and statistical methods hitherto used to characterize extremes of hydrometeorological variables. It arises from a description of key hydro-meteorological processes driving runoff production (e.g., precipitation inputs, evapotranspiration rates, soil moisture states and catchment responses) through solution of the master equation for the probability distribution of streamflow in a catchment. PHEV pairs physical understanding of the mechanisms producing extreme events and defining their chance of occurrence with an easily tractable mathematical descriptions of them, thus providing a theoretical underpinning to the study of manifold flood-related issues, such as the emergence of heavy tails in streamflow and flood distributions, flood rich and poor periods, and the reasons leading to the occurrence of extreme flood events.

In this work we benchmark capabilities of PHEV for predicting odds and magnitudes of floods against a standard distribution and the latest statistical approach for extreme estimation. The methods are first applied to an extensive dataset to compare their skills for predicting observed flood quantiles in a wide range of case studies. Synthetic time series of streamflow, generated for select river basins from contrasting hydro-climatic regions, are later used to assess performances for rare events. The analyses outline the domain of applicability of PHEV and reveal less biased capabilities to estimate flood magnitudes with return periods much longer than the sample size used for calibration. Results also show reduced prediction uncertainty of PHEV for rare floods, notably if the flood magnitude-frequency curve displays an inflection point.

Such discontinuities typically hinder estimation of high streamflow quantiles. PHEV reveals itself as a reliable tool to foresee their occurrence in a large set of case studies from the US and Germany, also when using shortened data series where the highest observations were removed. Case studies for which PHEV predicts the occurrence of an inflection point which is not visible in the empirical flood magnitude-frequency curve mostly belong to river flow regimes characterized by values weakly oscillating around their mean, which rarely exhibit extreme flow values by their nature. The limited length of the available data series might be thus constraining the possibility to observe extreme floods that shall be expected. These results indicate the possibility to reliably appraise the propensity of rivers to generate extreme floods by means of a process-based description of watershed dynamics, thus laying the foundation for a better comprehension of their physio-climatic controls.

How to cite: Basso, S., Botter, G., Merz, R., and Miniussi, A.: The Physically-Based Extreme Value (PHEV) distribution of river discharges, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3060, https://doi.org/10.5194/egusphere-egu22-3060, 2022.

17:23–17:30
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EGU22-2556
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ECS
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Virtual presentation
Hsing-Jui Wang et al.

Heavy-tailed probability distributions of streamflow are frequently observed in river basins. In case of right skewed distributions, the larger probability assigned to relatively high flows translates into an unneglectable chance of occurrence of extreme floods in a long-term hydrological response. Although the spatial variability of rainfall has been identified as an impactful driver of flood events, delineating its effects for the emergence of heavy tails of streamflow distributions is still challenging.

In this study we apply a simple stochastic approach to generate spatially various rainfall as the input of a well-established continuous hydrological model. The model embeds the soil water balance in hillslopes, the probability distributions of transit times in the hillslopes of subcatchments, and the response time distribution in channels derived from a geomorphological analysis of the river network. We investigate the role of spatially variable rainfall for the emergence of heavy tails in streamflow distributions by simulating a wide range of spatial rainfall variability in five catchments in Germany, and then put the modelling results into real world context by analyzing historical data in 175 catchments across the whole Germany.

We find that increasing spatial variability of rainfall determines heavier streamflow tails only beyond a certain increase threshold which depends on physiographic features of catchments. Small and elongated catchments are less resilient to increasing spatial rainfall variability, i.e., their streamflow distributions begin to exhibit heavier tails for smaller increments of the spatial variability of rainfall. The distribution of runoff-routing pathway is suggested to be an effective attribute of catchments in this process.

How to cite: Wang, H.-J., Yang, S., Merz, R., and Basso, S.: The role of spatial rainfall variability for the emergence of heavy tails in streamflow distributions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2556, https://doi.org/10.5194/egusphere-egu22-2556, 2022.

17:30–17:37
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EGU22-9872
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ECS
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Virtual presentation
Maureen Wanzala et al.

The frequency and magnitude of flood events in Kenya have increased over the past decade. Observations show a shift in timing and variability in flood occurrences in most parts of the country. Trend analysis is useful in detecting and supporting the evidence of change in flow series, as well as variability in flood timing. In this study, the frequency and magnitude of floods observed in the annual maximum flood (AMAX) and peak over threshold (POT) flood series from 1981 to 2016 are compared in 19 Kenyan catchments. Flood peaks are identified using a threshold technique from Kenyan daily discharge data, and notable patterns in the AMAX series are compared to those in the POT series, which is created for three distinct exceedance criteria. The timing and variability of the annual floods is determined from the AMAX flow. Our findings show that, the AMAX series detects more trends in flood magnitude than the POT series, while the POT series detects more significant trends in flood frequency than flood magnitude. Sensitivity of trends to different exceedance thresholds selection reveal variable trend patterns across the stations. The timing of inter-annual floods occurs in peak rainfall months of April, May and November and shows a higher variability index in most of the coastal and western stations, and a low variability in stations whose annual floods occur in dry months of June, July, and August. This information is useful to hydrological applications such as flood protection facility design, risk assessment, and risk management for improved livelihoods in Kenya

How to cite: Wanzala, M., Cloke, H., Stephens, E., Ficchi, A., and Harrigan, S.: Detecting trends in flood series and shifts in flood timing across Kenya, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9872, https://doi.org/10.5194/egusphere-egu22-9872, 2022.

17:37–17:44
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EGU22-4086
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ECS
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On-site presentation
Mirko Barada et al.

Floods are a constant threat to communities within and around estuaries worldwide. This is because several drivers may occur there at the same time which leads to the compound flooding (e.g. high river discharge + storm surge). In this study LISFLOOD-FP hydrodynamic model is applied to examine the efficiency of different management strategies on flooding in the Dyfi Estuary, in Mid Wales. Five different bathymetries, including the current one, were developed in ArcGIS and included in the analysis: a) “hold the line”, b) “remove the line”, c) “advance the line”, d) “retreat the line”, e) “breach in the line”. Modified November 2020 compound flood event boundary conditions were forced from the coast and from the Dyfi bridge. Model results shown, among other things, that nature-based solutions in the lower estuary, represented by salt marshes and floodplain restoration measures, have a great potential in reducing water elevations across the estuary, unlike the advance the line scenario or the current bathymetry.

Additionally, results obtained from different management scenarios are analyzed and compared against results from the selected design storm events. These events were based on modifying parameters such as 1) relative timing of flood peaks, 2) storm duration and 3) climate change sensitivity (SLR and increase in discharge) which provided set of different compound flood events that were forced by LISFLOOD, in combination with the current estuary shape, unlike when modelling different management scenarios. This approach enabled us to perform an effective comparative analysis which addressed the key hypothesis of the research stating that changes in estuary shape will have bigger effect on flooding than changes in flood event itself. Indeed, it is shown that variability in water elevations caused by different management scenarios is bigger compared to variability caused by changing the boundary conditions only, although not always leading to higher water elevations along the estuary.

How to cite: Barada, M., Robins, P., Lewis, M., and Skov, M.: The importance of estuary shape in evaluating the flood risk in estuaries, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4086, https://doi.org/10.5194/egusphere-egu22-4086, 2022.

17:44–17:51
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EGU22-11024
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Virtual presentation
Lydie Sichoix et al.

Flooding in the tropical high islands of French Polynesia located in the South Pacific represents a major threat for tens of thousands of people, in particular in coastal urban areas. In this context,  this study aims to assess rainfall and streamflow changes at local scale and daily interval (hourly when data are available) over the Islands of Tahiti and Moorea during the period 1977-2020, and to provide new indicators for integrated water resource management under high anthropogenic pressure, as well as flood risk anticipation, especially over the northwestern urban part of Tahiti.

Our analysis is based on quantile regression combining linear and annual cycle components applied on 18 rain gauge and 2 river discharge time series. Results show a moderate to high decrease of extreme precipitation (percentiles > 0.90) on the western leeward side. This finding is in line with recent studies on trends in precipitation in the Pacific. More surprisingly, we also observe a moderate increase in rainfall for the windward (North-East) and southern areas, as well as an overall decline in streamflow over two watersheds encompassing the urban zone of North-West Tahiti. This last finding is correlated with the precipitation decline in leeward slopes.

The differences in observed rainfall and streamflow trends may be related to differences in forcings involved. To better understand the influence of the regional climate on our hydrometeorological observations, we investigate the modulating effect of the El Niño Southern Oscillation (ENSO), the Madden-Julian Oscillation (MJO) and Pacific Decadal Oscillation (PDO) on rainfall and runoff by testing a fast inference for time-varying quantiles via a flexible dynamic quantile linear approach. Increase and decline in precipitation are tied to respective positive and negative PDO phases.  However, further validation is required to disentangle the short-term influence of different modes of variability contained in distinct time scales.

How to cite: Sichoix, L., Tanguy, G., and Benoit, L.: Local Changes in Rainfall and Streamflow via Quantile Regression Methods and their relationship with the PDO, MJO and ENSO: Application to French Polynesia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11024, https://doi.org/10.5194/egusphere-egu22-11024, 2022.

17:51–17:58
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EGU22-11641
Rainer Bell et al.

Rain driven flash floods have severe impacts on society and landscape functions. The July 2021 flood in the Eifel region, west Germany, was one drastic example of such impact. While media and scientists rightfully highlighted the meteorological and hydrological aspects of this flood, it was the concurrent reorganisation of important landscape conditions and the debris carried by the fast flowing water that made this flood so devastating and unpredictable.

Here, we take a process-based impact perspective and systematically ask, which were the specific roles of non-hydraulic but geomorphic dynamics that implemented the damage, caused flood non-linearities and amplified the landscape deterioration. We combine insights from field mapping campaigns during, right after and within the relaxation phase of the flood with high resolution geophysical and LiDAR surveys to discuss the role of hillslopes, vegetation, fluvial sediment mobilisation and the legacy of anthropogenic landscape reorganisation. We conclude that some of these elements emerged as the flood event evolved, causing either transient effects or persistent landscape features, thus modifying the response of the landscape to future events, also to less intense precipitation events.

Our findings not only support more tailored recovery efforts for the flood affected Eifel catchments, but should also inform landscape development trajectories and potentially crucial factors in other Central European regions.

How to cite: Bell, R., Dietze, M., Thieken, A., Cook, K., Andermann, C., Beer, A., Vela, A. L., Ries, J. B., Brell, M., Eltner, A., Roessner, S., Schrott, L., Iserloh, T., Seeger, M., and Öztürk, U.: More than just fast flowing water: the landscape impact of the July 2021 west Germany flood, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11641, https://doi.org/10.5194/egusphere-egu22-11641, 2022.

17:58–18:05
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EGU22-12637
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ECS
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On-site presentation
Stefano Cipollini et al.

The influence of the human activity (e.g. land use changes, alterations of the river system, hydraulic structures realization) on the flood frequency curves, represents a notable information to understand hydrologic changes identifying some of its drivers. In this work we provide a simple yet physically-based global index to assess the effect of multiple reservoirs, located in series along the main channel, on peak flood quantile at the catchment scale. The index formulation is based on an Instantaneous Unit Hydrograph (IUH) method, and it takes into account the main parameters of the system, such as the relative location and relative storage coefficient of the reservoirs, their number, and a climatic parameter. An analytical formulas of the index is provided, and it is independent of the return period. Numerical experiments and a comparison with the literature indices confirm the efficiency of the proposed index and allow to disentangle the role of the parameters on the flood peak reduction. Finally, we also present and discuss results of the index application for a real case study, that is the reservoirs system of the Tiber River (Central Italy).    

How to cite: Cipollini, S., Fiori, A., and Volpi, E.: Multiple reservoirs impact on flood frequency curves: a new global and physically-based index, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12637, https://doi.org/10.5194/egusphere-egu22-12637, 2022.

18:05–18:12
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EGU22-4576
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Virtual presentation
Luis Mediero et al.

Dam design and safety assessment analyses require flood quantile estimates for high return periods up to 10000 years. However, systematic flood series are usually short with around 20-40 years, leading to high uncertainties. Historical information about floods is generally recognised as useful for estimating the magnitude of flood quantiles with return periods in excess of 100 years. Therefore, incorporating historical information in flood frequency analyses can reduce uncertainties and improve reliability of flood quantiles for high return periods. However, several techniques for incorporating historical information in flood frequency analyses have been proposed.

This study presents a methodology to select the best technique to fit a flood frequency curve considering historical information. The methodology is based on a stochastic analysis that quantifies the accuracy and uncertainty for each technique. Monte Carlo simulations are used to generate synthetic flood series. Varying lengths of both historical and systematic periods are considered. The floods that exceed a given perception threshold are considered statistically as historical floods, regardless they occur in the systematic or historical period. A varying number of historical floods are also considered.

Five streamflow gauging stations located in Spain are considered, where both systematic data and historical information are available. The analysis aims to find the best technique in each location in terms of flood quantile reliability and uncertainty reduction. It has been found that accuracy and uncertainty reduction in flood quantile estimates for each technique depend on the statistical properties of flood series.

The results show that the maximum likelihood estimator (MLE) and weighted moments (WM) techniques are the best option in regions with a milder climate, where skewness in flood series is smaller. However, in regions with more extreme climates, where skewness of flood series increases, the biased partial probability weighted moments (BPPWM) and the unbiased partial probability weighted moments (UPPWM) techniques obtain the best results.

Incorporating historical information about floods before the systematic period can improve the accuracy of flood quantile estimates, as well as reduce estimate uncertainties. The improvement is higher for shorter systematic periods and a greater number of historical floods available. In addition, historical information about floods can be crucial in arid regions where the greatest floods with low probability of occurrence are not usually recorded in the systematic period. The proposed methodology can be useful for reducing the uncertainty in design flood estimates for designing spillways and assessing hydrological dam safety.

Acknowledgments: This research has been supported by the project SAFERDAMS (PID2019-107027RB-I00) funded by the Spanish Ministry of Science and Innovation.

How to cite: Mediero, L., Jiménez, A., and Soriano, E.: Stochastic methodology to select the best technique to incorporate historical information in flood frequency analyses for dam safety assessment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4576, https://doi.org/10.5194/egusphere-egu22-4576, 2022.

18:12–18:19
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EGU22-5543
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Virtual presentation
Enrique Soriano Martín et al.

Dam breaks can be driven by a flood that exceeds the design spillway capacity, causing important economic and human losses. Dam spillways are designed for a flood that is usually estimated through either hydrometeorological or statistical analyses with observed data. However, time series of observations are usually short, incomplete and recorded at a daily time step. Moreover, design floods have to be estimated for high return periods greater than 500 years, leading to high uncertainties. In addition, climate change is expected to increase the frequency and magnitude of floods in the future. Therefore, new methodologies are required to assess hydrological dam safety considering both short time series of observations and climate change.

A stochastic methodology is presented here to assess hydrological dam safety considering the impact of climate change on floods, by integrating a stochastic rainfall generator and a rainfall-runoff model. The methodology is applied to the Eugui Dam on the Arga River in the north of Spain. The Eugui Dam has a draining catchment area of 69 km2, a reservoir volume of 22 hm3, and a gated spillway.

First, the stochastic rainfall generator STORAGE (De Luca and Petroselli, 2021) based on the Neymann-Scott Rectangular Pulse Model has been used to simulate long time series of 500 years of precipitation with a time step of 15 minutes. The generator has been calibrated with rainfall observations. In addition, the STORAGE model has been used to generate synthetic time series of precipitation considering climate change. Delta changes extracted from precipitation projections of 12 climate models, three periods (2011-2040, 2041-2070, 2071-2100) and two emission scenarios (RCP 4.5 and RCP 8.5) are considered (Garijo and Mediero, 2019).

Second, the stochastic precipitation time series are transformed into runoff time series by using the COSMO4SUB model (Grimaldi et al., 2021). COSMO4SUB is a continuous model that uses a high-resolution digital terrain model, land cover / soil type data, and precipitation supplied by the STORAGE model as input data, providing continuous runoff time series as output. The COSMO4SUB parameters have been calibrated with runoff observations by minimizing a set of objective functions.

Third, annual maximum hydrographs, peak flows and hydrograph volumes are extracted from the runoff time series generated by COSMO4SUB. The Volume Evaluation Method (MEV) (Girón, 1988) is used to simulate the operation of spillway gates in flood events, obtaining maximum water levels in the reservoir and outflow hydrographs. The MEV method specifies when the spillway gates are opened and closed to reach the target reservoir water level at the end of the flood event. Hydrological dam safety at the Eugui Dam is assessed by analysing the frequency curve of maximum water levels in the reservoir for the 12 climate models, three return periods and two emission scenarios mentioned above. Therefore, the methodology proposed allows practitioners and dam owners to check the hydrological dam safety requirements detailed in the regulations, accounting for climate change.

Acknowledgments: This research has been supported by the project SAFERDAMS (PID2019-107027RB-I00) funded by the Spanish Ministry of Science and Innovation.

How to cite: Soriano Martín, E., Mediero Orduña, L., Petroselli, A., De Luca, D. L., and Grimaldi, S.: A methodology to assess hydrological dam safety in dams with gated spillways under the effect of climate change., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5543, https://doi.org/10.5194/egusphere-egu22-5543, 2022.

18:19–18:30
Open Discussion