scholarly journals Extreme floods in Europe: going beyond observations using reforecast ensemble pooling

2021 ◽  
Author(s):  
Manuela I. Brunner ◽  
Louise Slater
Keyword(s):  
Sample Size ◽  
Central Europe ◽  
Extreme Events ◽  
Hydrological Model ◽  
Model Performance ◽  
Added Value ◽  
Lead Times ◽  
Flood Events ◽  
New Approach ◽  
Extreme Flood

Abstract. Assessing the rarity and magnitude of very extreme flood events occurring less than twice a century is challenging due to the lack of observations of such rare events. Here we develop a new approach, pooling reforecast ensemble members from the European Flood Awareness System (EFAS) to increase the sample size available to estimate the frequency of extreme local and regional flood events. We assess the added value of such pooling, determine where in Central Europe one might expect the most extreme events, and evaluate how event extremeness is related to physiographic and meteorological catchment characteristics. We work with a set of 234 catchments from the Global Runoff Data Center for which performance of simulated floods is satisfactory when compared to observed streamflow. We pool EFAS-simulated flood events for 10 perturbed ensemble members and lead times from 22 to 46 days, where flood events are only weakly dependent (< 0.25 average correlation across lead times). The resulting large ensemble (130 time series instead of one) enables analyses of very extreme events, which occur less than twice a century. We demonstrate that such ensemble pooling produces more robust estimates with considerably reduced uncertainty bounds (by ~80 % on average) than observation-based estimates but may equally introduce biases arising from the simulated meteorology and hydrological model. Our results show that specific flood return levels are highest in steep and wet regions and are comparably low in regions with strong flow regulation through dams. Furthermore, our pooled flood estimates indicate that the probability of regional flooding is higher in Central Europe and Great Britain than in Scandinavia. We conclude that reforecast ensemble pooling is an efficient approach to increase sample size and to derive robust local and regional flood estimates in regions with sufficient hydrological model performance.

Investigating hydrological model versatility to simulate extreme flood events 

2021 ◽  
Author(s):  
Daniela Peredo Ramirez ◽  
Maria-Helena Ramos ◽  
Vazken Andréassian ◽  
Ludovic Oudin
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Original Model ◽  
Model Structure ◽  
Model Adaptation ◽  
Flood Events ◽  
Runoff Generation ◽  
Local Climate ◽  
Extreme Flood ◽  
The Impact

&lt;p&gt;&lt;span&gt;High-impact flood events in the Mediterranean region are often the result of a combination of local climate and topographic characteristics of the region. Therefore, the way runoff generation processes are represented in hydrological models is a key factor to simulate and forecast floods. In this study, we adapt an existing model in order to increase its versatility to simulate flood events occurring under different conditions: during or after wet periods and after long and dry summer periods. The model adaptation introduces a dependency on rainfall intensity in the production function. The impact of this adaptation is analysed considering model performance over selected flood events and also over a continuous 10-year period of flows. The event-based assessment showed that the adapted model structure performs better than or equal to the original model structure in terms of differences in the timing of peak discharges, regardless of the season of the year when the flood occurs. The most important improvement was observed in the simulation of the magnitude of the flood peaks. A visualisation of model versatility is proposed, which allows detecting the time steps when the new model structure tends to behave more similarly or differently from the original model structure in terms of runoff production. Overall, the results show the potential of the model adaptation proposed to simulate floods originated by different hydrological processes and the value of increasing hydrological model versatility to simulate extreme events.&lt;/span&gt;&lt;/p&gt;

Simulating spatially coherent widespread flood events for risk modelling in the UK

2021 ◽  
Author(s):  
Adam Griffin ◽  
Lisa Stewart ◽  
Alison Kay ◽  
Vicky Bell ◽  
Paul Sayers ◽  
...  
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
River Flow ◽  
Hydrological Model ◽  
Extreme Event ◽  
Flood Frequency ◽  
Climate Projections ◽  
Flood Events ◽  
Risk Modelling ◽  
Extreme Flood

&lt;p&gt;Within risk modelling, event &amp;#8216;footprints&amp;#8217; are used to demonstrate how an extreme event impacts different locations at a similar time. Currently, estimates of future impacts from extreme events are derived by applying climate change allowances to at-site flood frequency estimates based on observations from the current period. These modified flow frequency estimates are then used to calculate flood risk and associated losses using a variety of means.&lt;/p&gt;&lt;p&gt;The present work brings together these two strands to develop spatially resolved projections of changes in river flow and, together with new analyses of the spatial coherence, to generate a wider collection of plausible events to improve risk modelling of the rarest events. This wide collection of extreme flood events provides the foundational input for an event-based assessment of risk.&lt;/p&gt;&lt;p&gt;The research extends proven methods to generate extreme, widespread flood events directly based on outputs from a 1km grid-based hydrological model driven by UKCP18 datasets. These modelled events provide coherent and highly credible descriptions of changes in flow based on spatially coherent climate change information. In addition to the small number of widespread extreme events generated directly from the gridded hydrological model, copula-based methods have been extended and applied on a regional and even national scale at a 1km resolution over the GB river network. These extensions to the Heffernan-Tawn model and Empirical Copula models are being used to generate a collection of plausible extreme based on the climate of 1980-2010 and on climate projections for 2050-2080. The collection of events is then used to compare the characteristics and variability of widespread events across different climate ensemble members and compare between present and future estimates.&lt;/p&gt;

scholarly journals Inundation mapping based on reach-scale effective geometry

2018 ◽  
Vol 22 (11) ◽  
pp. 5967-5985 ◽  
Author(s):  
Cédric Rebolho ◽  
Vazken Andréassian ◽  
Nicolas Le Moine
Keyword(s):  
Model Performance ◽  
Model Complexity ◽  
Hydraulic Geometry ◽  
Future Event ◽  
New Approach ◽  
Flow Equations ◽  
Geometrical Properties ◽  
Inundation Maps ◽  
Extreme Flood ◽  
Inundation Mapping

Abstract. The production of spatially accurate representations of potential inundation is often limited by the lack of available data as well as model complexity. We present in this paper a new approach for rapid inundation mapping, MHYST, which is well adapted for data-scarce areas; it combines hydraulic geometry concepts for channels and DEM data for floodplains. Its originality lies in the fact that it does not work at the cross section scale but computes effective geometrical properties to describe the reach scale. Combining reach-scale geometrical properties with 1-D steady-state flow equations, MHYST computes a topographically coherent relation between the “height above nearest drainage” and streamflow. This relation can then be used on a past or future event to produce inundation maps. The MHYST approach is tested here on an extreme flood event that occurred in France in May–June 2016. The results indicate that it has a tendency to slightly underestimate inundation extents, although efficiency criteria values are clearly encouraging. The spatial distribution of model performance is discussed and it shows that the model can perform very well on most reaches, but has difficulties modelling the more complex, urbanised reaches. MHYST should not be seen as a rival to detailed inundation studies, but as a first approximation able to rapidly provide inundation maps in data-scarce areas.

scholarly journals Towards assimilation of crowdsourced observations for different levels of citizen engagement: the flood event of 2013 in the Bacchiglione catchment

2017 ◽  
Author(s):  
Maurizio Mazzoleni ◽  
Vivian Juliette Cortes Arevalo ◽  
Uta Wehn ◽  
Leonardo Alfonso ◽  
Daniele Norbiato ◽  
...  
Keyword(s):  
Real Time ◽  
Hydrological Model ◽  
Population Distribution ◽  
Model Performance ◽  
Flood Event ◽  
Target Point ◽  
Citizen Engagement ◽  
Physical Sensors ◽  
Extreme Flood ◽  
Social Sensors

Abstract. Accurate flood predictions are essential to reduce the risk and damages over large urbanized areas. To improve prediction capabilities, hydrological measurements derived by traditional physical sensors are integrated in real-time within mathematic models. Recently, traditional sensors are complemented with low-cost social sensors. However, measurements derived by social sensors (i.e. crowdsourced observations) can be more spatially distributed but less accurate. In this study, we assess the usefulness for model performance of assimilating crowdsourced observations from a heterogeneous network of static physical, static social and dynamic social sensors. We assess potential effects on the model predictions to the extreme flood event occurred in the Bacchiglione catchment on May 2013. Flood predictions are estimated at the target point of Ponte degli Angeli (Vicenza), outlet of the Bacchiglione catchment, by means of a semi-distributed hydrological model. The contribution of the upstream sub-catchment is calculated using a conceptual hydrological model. The flow is propagated along the river reach using a hydraulic model. In both models, a Kalman filter is implemented to assimilate the real-time crowdsourced observations. We synthetically derived crowdsourced observations for either static social or dynamic social sensors because crowdsourced measures were not available. We consider three sets of experiments: (1) only physical sensors are available; (2) probability of receiving crowdsourced observations and (3) realistic scenario of citizen engagement based on population distribution. The results demonstrated the importance of integrating crowdsourced observations. Observations from upstream sub-catchments assimilated into the hydrological model ensures high model performance for high lead time values. Observations next to the outlet of the catchments provide good results for short lead times. Furthermore, citizen engagement level scenarios moved by a feeling of belonging to a community of friends indicated flood prediction improvements when such small communities are located upstream a particular target point. Effective communication and feedback is required between water authorities and citizens to ensure minimum engagement levels and to minimize the intrinsic low-variable accuracy of crowdsourced observations.

scholarly journals The suitability of remotely sensed soil moisture for improving operational flood forecasting

2014 ◽  
Vol 18 (6) ◽  
pp. 2343-2357 ◽  
Author(s):  
N. Wanders ◽  
D. Karssenberg ◽  
A. de Roo ◽  
S. M. de Jong ◽  
M. F. P. Bierkens
Keyword(s):  
Soil Moisture ◽  
Satellite Data ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Remotely Sensed ◽  
Added Value ◽  
Lead Times ◽  
Validation Data ◽  
Data Set ◽  
Discharge Data

Abstract. We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model (LISFLOOD) for flood predictions with lead times of up to 10 days. For this study, satellite-derived soil moisture from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) and SMOS (Soil Moisture and Ocean Salinity) is assimilated into the LISFLOOD model for the Upper Danube Basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into the hydrological model, an ensemble Kalman filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure increased performance of the EnKF. For the validation, additional discharge observations not used in the EnKF are used as an independent validation data set. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the mean absolute error (MAE) of the ensemble mean is reduced by 35%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of baseflows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the continuous ranked probability score (CRPS) shows a performance increase of 5–10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more observational data is assimilated into the system. The added values of the satellite data is largest when these observations are assimilated in combination with distributed discharge observations. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

Hydrological modelling and anthropogenic water use

2021 ◽  
Author(s):  
Ponnambalam Rameshwaran ◽  
Ali Rudd ◽  
Vicky Bell ◽  
Matt Brown ◽  
Helen Davies ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Use ◽  
Hydrological Model ◽  
Model Performance ◽  
River Flows ◽  
Discharge Data ◽  
New Approach ◽  
Water Demands ◽  
The Impact ◽  
Grid Based

&lt;p&gt;Despite Britain&amp;#8217;s often-rainy maritime climate, anthropogenic water demands have a significant impact on river flows, particularly during dry summers. In future years, projected population growth and climate change are likely to increase the demand for water and lead to greater pressures on available freshwater resources.&lt;/p&gt;&lt;p&gt;Across England, abstraction (from groundwater, surface water or tidal sources) and discharge data along with &amp;#8216;Hands off Flow&amp;#8217; conditions are available for thousands of individual locations; each with a licence for use, an amount, an indication of when abstraction can take place, and the actual amount of water abstracted (generally less than the licence amount). Here we demonstrate how these data can be used in combination to incorporate anthropogenic artificial influences into a grid-based hydrological model. Model simulations of both high and low river flows are generally improved when abstractions and discharges are included, though for some catchments model performance decreases. The new approach provides a methodological baseline for further work investigating the impact of anthropogenic water use and projected climate change on future river flows.&lt;/p&gt;

Considerations on the influence of extreme events on the phosphorus transport from river catchments to the sea

2005 ◽  
Vol 51 (11) ◽  
pp. 193-204 ◽  
Author(s):  
M. Zessner ◽  
C. Postolache ◽  
A. Clement ◽  
A. Kovacs ◽  
P. Strauss
Keyword(s):  
Extreme Events ◽  
High Flow ◽  
Danube River ◽  
Flood Event ◽  
Phosphorus Transport ◽  
Flood Events ◽  
Relative Contribution ◽  
Extreme Flood ◽  
Flooded Areas ◽  
Total P

In this paper, results from rivers of different sizes in Romania, Hungary and Austria are presented. The paper shows the dynamics of extreme events and their contribution to the total P and suspended solids transported in these rivers. Special attention is paid to the influence of the size of the catchment and the event probability on the relative contribution of a single event to the total loads transported in the river. Further, the development of phosphorus loads along the Danube River at a flood event is shown. From the results it can be concluded that there is no immediate influence of high flow and flood events in upstream parts of the Basin on the transport of phosphorus from the catchment to the receiving Sea. Particle-bound phosphorus is mobilised from the catchment (through erosion) and the river bottom to a high extent at high flow events and transported at peak discharges to downstream, where retention by sedimentation of particles takes place. On the one hand this retention is a transport to flooded areas. In this case it can be considered as more or less long term retention. On the other hand sedimentation takes place in the riverbed, in case the tractive effort of the river is reduced. In this second case the P-pool in the sediments of the sedimentation area will be increased. If anaerobic conditions in the sediment appear, part of the phosphorus will be transformed to soluble ortho-phosphate and will continuously contribute to the phosphorus transport to the receiving sea. Part of the P-retained in the river sediment will be mobilised by resuspension at the next biggest high flow event. Altogether, these alternating processes of suspension, transport, export to flooded areas or sedimentation in the river bed with partly solution and partly resuspension at the next event decrease the share of the phosphorus transport during high flow events on the total loads transported in the more downstream parts of a catchments as compared to the more upstream parts. In the year of occurrence of an extreme flood event the P-transport of this year is dominated by the flood event. As an average over many years the contribution of high flow events to the total P-transport still may be between 7 and 20% in smaller catchments (around 1,000 km2). In a big catchment (e.g. river Danube) much smaller contributions of flood events on the total P-transport can be expected as an average over many years.

Assessment of 1D/2D coupled model for prediction of flood inundation

2021 ◽  
Author(s):  
Rashmi Yadav ◽  
Sanjay M. Yadav
Keyword(s):  
Extreme Events ◽  
Dynamic Models ◽  
Coupled Model ◽  
Hyperbolic Partial Differential Equations ◽  
Finite Difference Schemes ◽  
Flood Inundation ◽  
Flood Events ◽  
Coupled Models ◽  
Extreme Flood ◽  
Spatio Temporal

&lt;p&gt;In the era of increased extreme events, the assessment and management of the consequences become a necessity. Since the past twenty years floods affected more than two billion people worldwide. Urbanisation, overpopulation, insufficient drainage systems, spatio-temporal variation of rainfall events, climate change, unplanned settlements over the coastal areas and flood-prone areas can be few of the causes of floods. 1D, 2D and 1D/2D coupled hydro-dynamic models are developed to study such flood events. Some of the popular models used for the analysis of floods are HEC RAS, MIKE 11, MIKE 21, MIKE Urban, SWMM, SOBEK, FLO-2D and SWAT. These models use implicit and explicit finite difference schemes are used for solving one and two-dimensional hyperbolic partial differential equations. The data requirements and methodology for the development and assessment of modelling extreme flood events across the globe is highlighted and presented in the paper. Importance of developing the framework beforehand for optimising of model suitability, availability of data and objective function is reviewed. The present study discusses important 1D/2D coupled models case studies used for flood inundation studies.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;Floods, extreme events, modelling, HEC RAS, shallow water equations.&lt;/p&gt;

scholarly journals Information content of stream level class data for hydrological model calibration

2017 ◽  
Vol 21 (9) ◽  
pp. 4895-4905 ◽  
Author(s):  
H. J. Ilja van Meerveld ◽  
Marc J. P. Vis ◽  
Jan Seibert
Keyword(s):  
Time Series ◽  
Citizen Science ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Added Value ◽  
Distributed Data ◽  
Vertical Resolution ◽  
Level Data ◽  
Spatially Distributed

Abstract. Citizen science can provide spatially distributed data over large areas, including hydrological data. Stream levels are easier to measure than streamflow and are likely also observed more easily by citizen scientists than streamflow. However, the challenge with crowd based stream level data is that observations are taken at irregular time intervals and with a limited vertical resolution. The latter is especially the case at sites where no staff gauge is available and relative stream levels are observed based on (in)visible features in the stream, such as rocks. In order to assess the potential value of crowd based stream level observations for model calibration, we pretended that stream level observations were available at a limited vertical resolution by transferring streamflow data to stream level classes. A bucket-type hydrological model was calibrated with these hypothetical stream level class data and subsequently evaluated on the observed streamflow records. Our results indicate that stream level data can result in good streamflow simulations, even with a reduced vertical resolution of the observations. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was some added value in using up to five stream level classes, but there was hardly any improvement in model performance when using more level classes. These results are encouraging for citizen science projects and provide a basis for designing observation systems that collect data that are as informative as possible for deriving model based streamflow time series for previously ungauged basins.

scholarly journals Information content of stream level class data for hydrological model calibration

2017 ◽  
Author(s):  
Ilja van Meerveld ◽  
Marc Vis ◽  
Jan Seibert
Keyword(s):  
Time Series ◽  
Citizen Science ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Added Value ◽  
Data Sets ◽  
Distributed Data ◽  
Vertical Resolution ◽  
Level Data

Abstract. Citizen science can provide spatially distributed data over large areas, including hydrological data. Stream levels are easier to measure than streamflow and can be observed more easily by citizen scientists. However, the challenge with crowd-based stream level data is that observations are taken at irregular time intervals and with a limited vertical resolution. The latter is especially the case at sites where no staff gauge is available and relative stream levels are observed based on (in)visible features in the stream, such as rocks. In order to assess the potential value of crowd-based stream level observations for model calibration, we pretended that stream level observations were available at a limited vertical resolution by transferring streamflow data into stream level classes. A bucket-type hydrological model was calibrated with these hypothetical data sets and subsequently evaluated on the observed streamflow records. Our results indicate that stream level data can result in good streamflow simulations, even with a reduced vertical resolution of the observations. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was some added value in using up to five stream level classes but there was hardly any improvement in model performance when using more level classes. These results are encouraging for citizen science projects and provide a basis for designing observation systems that collect data that are as informative as possible for deriving model-based streamflow time series for previously ungauged basins.

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