HS2.4.6 | Approaches and management perspectives to address flood protection and drought reduction
Approaches and management perspectives to address flood protection and drought reduction
Convener: Nicole Rudolph-Mohr | Co-conveners: Doris Wendt, Maria Staudinger, Wilson Chan, Benni Thiebes, Lea Augustin, Udo Satzinger
| Mon, 24 Apr, 10:45–12:25 (CEST)
Room 2.17
Posters on site
| Attendance Mon, 24 Apr, 14:00–15:45 (CEST)
Hall A
Posters virtual
| Attendance Mon, 24 Apr, 14:00–15:45 (CEST)
vHall HS
Orals |
Mon, 10:45
Mon, 14:00
Mon, 14:00
With global climate change the frequency and intensity of floods and droughts are increasing in many parts of the world. Floods and droughts cover the entire hydrological spectrum with many similarities and links between the two types of extremes. Approaches, tools and management strategies can be, in some way, applicable to both contradicting extremes. For example, stress testing and storyline approaches have been developed recently to better understand systems under extreme conditions. They explicitly seek to understand the drivers of hydro-climatological extremes and their management implications. Stress tests and storylines can be informed by expert knowledge and used in conjunction with traditional sources of information (such as climate model projections). From a management perspective, coupling of flood risk reduction with drought management is one key to sustainable future water management.
We welcome contributions focusing on the whole strategic and operative management processes of these extreme events. We welcome contributions on the following topics:
- Stress testing approaches to analyse hydrological or climatological extremes
- Modelling experiments for the hydrological hazards, sensitivity and their consequences
- Interdisciplinary approaches for managing scarce water resources and flooding event and to support decision-making (e.g. public water supply, agriculture, industry or environmental water use)
- Stress tests to complement climate change scenarios to identify system vulnerability, hazard risk, tipping points and low-likelihood, high impact events

Orals: Mon, 24 Apr | Room 2.17

Chairpersons: Wilson Chan, Udo Satzinger, Maria Staudinger
Climate change assessment
Virtual presentation
Saritha Padiyedath Gopalan, Naota Hanasaki, and Taikan Oki

Climate change will increase the intensity and frequency of flood and drought events and the global population exposed to these extreme events, thereby enhancing economic damage. Therefore, adaptation measures should be taken to combat the inevitable consequences of climate change, particularly flooding and water scarcity. However, quantitative and concrete views on what adaptation measures should be taken have yet to be explored, especially in developing countries. Hence, in this study, the effect of several combinations of adaptation measures was examined to address both the future extremes in the Chao Phraya River in Thailand. The selected adaptation measures were (i) structural measures, which include dam construction, dam capacity enhancement, use of water-efficient irrigation equipment, and diversion channels, and (ii) non-structural measures, which include reforestation, changing the reservoir operation rules, and retention area enhancement. Future climate scenarios were constructed from the bias-corrected outputs of three general circulation models from 2080 to 2099 under RCP4.5 and RCP8.5.

Future flood and drought risk were analyzed using the number of flooding days and cumulative abstraction to demand (CAD) index, respectively. The major findings that can be drawn from this study are as follows: (i) the structural measures are capable of reducing the number of flooding days and increasing the CAD index; however, this pattern varies from region to region within the basin. (ii) the non-structural measures reduced both flooding days and CAD index, significantly impacting the basin’s water availability during the dry season. The reduction of the CAD index was mainly due to the increased evapotranspiration from the reforested land use that resulted in a decreased runoff. (iii) the adaptation portfolio (combination of structural and non-structural measures) exhibited a reduced number of flooding days and increased CAD index similar to the structural measures. The results revealed that the adaptation measures for flood or drought risk reduction could negatively impact the risk of the other hazard (i.e., reforestation reduces the flood risk but increases the drought risk). Therefore, different combinations of adaptation measures and basin-wide actions would allow us to better address the tradeoffs between these extremes and measures taken at different temporal and spatial scales.

How to cite: Padiyedath Gopalan, S., Hanasaki, N., and Oki, T.: Adaptation portfolio to combat future climate change impacts in the water sector of the Chao Phraya River Basin, Thailand, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13979, https://doi.org/10.5194/egusphere-egu23-13979, 2023.

On-site presentation
Bart Van Den Hurk and the RECEIPT project team

Complex interactions involving climatic features, socio-economic vulnerability or responses, and long impact transmissions are associated with substantial uncertainty. Physical climate storylines are proposed as approach to explore complex impact transmission pathways and possible alternative unfolding of event cascades under future climate conditions. These storylines are particularly useful for climate risk assessment for complex domains, including event cascades crossing multiple disciplinary or geographical borders. For an effective role in climate risks assessments, practical guidelines are needed to consistently develop and interpret the storyline event analyses.

This presentation elaborates on the suitability of physical climate storyline approaches involving climate event induced shocks propagating into societal impacts. It proposes a set of common elements to construct the event storylines. In addition, criteria for their application for climate risk assessment are given, referring to the need for storylines to be physically plausible, relevant for the specific context, and risk-informative.

A number of examples of varying scope and complexity are presented, all involving the potential climate change impact on European socio-economic sectors induced by remote climate change features occurring far outside the geographical domain of the European mainland. The storyline examples illustrate the application of the proposed storyline components. It thereby contributes to the standardization of the design and application of event-based climate storyline approaches.

How to cite: Van Den Hurk, B. and the RECEIPT project team: Climate impact storylines for assessing socio-economic responses to remote events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1180, https://doi.org/10.5194/egusphere-egu23-1180, 2023.

On-site presentation
Kerstin Stahl, Jost Hellwig, and Michael Stoelzle

Increasingly severe drought events demand a basis for prioritizing water uses and protection goals. In addition to classical methods of hydrological design, model experiments can support such aims. They can help investigate the response of hydrological systems to scenarios of exacerbated drought forcing. For known events of the past they might ask: "how much more would water resources be depleted, if forcing conditions had been more severe?". In such a stress-testing approach, this study investigated the sensitivity of low flows and low spring discharges to a range of exacerbated antecedent forcing conditions for a multi-catchment and multi-spring dataset in southwest Germany. Different model realizations for the forcing groundwater recharge, a baseflow separation and various conceptual groundwater storage and release models were combined into a model ensemble and system responses were analyzed in terms of elasticity metrics. Stress was applied as a systematic reduction in groundwater recharge with different magnitudes over different time periods preceding the main event of drought impact. All scenarios caused further reductions in low flow and spring discharge compared to the reference simulations. The presentation elaborates systematic thresholds: for example, the low-flow response of some catchments becomes maximal after a few months, and in others only after two years of stress duration. The experiments illustrate the sensitivities within the study area and allow to expand the derived 'story' as: "in a hydrological systems with (certain, e.g.) hydrogeological characteristics, low flows as in a (certain) memorable summer might be further depleted up to a (certain) maximum additional amount under (certain) drier preceding conditions". However, the importance of a specifically adapted model architecture as well as the estimation of model-related uncertainties becomes apparent from the ensemble experiment. Applied for selected well-validated model structures, the approach can help elucidate and communicate potential limits of drought stress.

How to cite: Stahl, K., Hellwig, J., and Stoelzle, M.: A model ensemble-elasticity-stress test for drought impact on spring discharge and low flow, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6482, https://doi.org/10.5194/egusphere-egu23-6482, 2023.

Virtual presentation
Lisa Ferrari, Sandra Ricart, Claudio Gandolfi, and Andrea Castelletti

Agriculture is one of the most vulnerable sectors to changes in climate patterns. Moreover, climate change is a complex and interdisciplinary problem, where natural processes are closely intertwined with socio-economic aspects, especially in areas where human activities are widespread. Thus, when planning for natural resources management, it becomes essential to consider how storylines, attitudes and behaviours can influence the decision-making towards adaptation measures. In particular, when considering an agricultural system, farmers are key agents that cannot be neglected, as the decision to adapt or to change their agricultural practice is ultimately in the hands of the individuals. Understanding the reasoning behind farmer adaptation can help create a sounder framework to recognize farmers’ awareness and experiences regarding climate change, while reinforcing their resilience to face climate change scenarios. Consequently, finding patterns in attitudes and similarities between farmers is essential both to better share an overall picture of climate change effects and perspectives in a specific study area and to summarize the complex set of factors influencing farmers’ behaviours to facilitate their modelling.

Different tools and methods have been provided by the literature in the last two decades to delve into farmers’ attitudes and perspectives regarding climate change. One of the most used tools are structured surveys, mainly due to their strongly case-specific nature and the capacity to synthesize climate change scenarios in a standardized way. Here, we provide an overview of the results obtained through a survey of 460 farmers from northern Italy about climate change risk awareness, perceived impacts, and adaptive capacity. In addition to a descriptive statistical analysis to delve into farmers’ profiles and farming characteristics, this triple-loop approach was analysed through Multiple Correspondence Analysis (MCA), an interesting data analysis technique that allows to highlight underlying structures in categorical data used to recap farmers’ behaviours and define the association between dependent and independent variables. The resulting factor map allows for the identification of those variables that most explain the variance in the dataset and expected similarities and differences between respondents. The obtained results show how certain variables describing the agricultural practice of the respondents, such as farm extension or the preferred irrigation method, are key driving factors in differentiating and grouping individuals’ behaviour. In general, farmers with the same modus operandi share similar behaviour with respect to other aspects of their activity (e.g., water source). Interestingly, and contradicting similar experiences from the literature, this pattern differs among farmers with comparable demographic background, requiring more attention to farmers’ heuristics. These results can be useful in multiple ways: from creating an informative picture of farmers’ attitudes and concerns regarding climate change in a certain area, to its application in profiling farmers to identify common demands and shared worries; from helping with the creation of customized policies at the regional scale from a bottom-up approach, to the implementation of farmers’ profiles into Agent-Based Models to reinforce the human dimension in decision-making processes.

How to cite: Ferrari, L., Ricart, S., Gandolfi, C., and Castelletti, A.: Underlying farmers' storylines and behaviour on climate change to reinforce risk assessment in northern Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4401, https://doi.org/10.5194/egusphere-egu23-4401, 2023.

On-site presentation
Helen Griffith and Hannah Cloke

A storyline is defined as a physically self-consistent unfolding of past events or of plausible possible futures (Shepherd et al., 2018). It has advantages in effective risk communication and adaption, as it moves the emphasis away from probability across to plausibility (Butler et al., 2020). Working as part of the EvoFlood (Quantifying the Evolution of Flood hazard and risk across a changing world) project, this work presents a novel methodology for estimating future hydrology based on not only climatic drivers, but the wider impacts of dams, river regulation and changing land-use. Grounded in historical atmospheric river floods, storylines are extracted from the large ensemble reforecast dataset provided by the Global Flood Awareness System (GloFAS; http://www.globalfloods.eu/).

Butler, J. R. A., Bergseng, A. M., Bohensky, E., Pedde, S., Aitkenhead, M., & Hamden, R. (2020). Adapting scenarios for climate adaptation: Practitioners’ perspectives on a popular planning method. Environmental Science & Policy, 104, 13–19. https://doi.org/10.1016/j.envsci.2019.10.014

Shepherd, T. G., Boyd, E., Calel, R. A., Chapman, S. C., Dessai, S., Dima-West, I. M., Fowler, H. J., James, R., Maraun, D., Martius, O., Senior, C. A., Sobel, A. H., Stainforth, D. A., Tett, S. F. B., Trenberth, K. E., van den Hurk, B. J. J. M., Watkins, N. W., Wilby, R. L., & Zenghelis, D. A. (2018). Storylines: An alternative approach to representing uncertainty in physical aspects of climate change. Climatic Change, 151(3–4), 555–571. https://doi.org/10.1007/s10584-018-2317-9

How to cite: Griffith, H. and Cloke, H.: Building Storylines of Future Atmospheric River Floods, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17254, https://doi.org/10.5194/egusphere-egu23-17254, 2023.

On-site presentation
Arne Reinecke and Insa Neuweiler

Convective rainfall cells have a maximum prediction time of 30 to 120 minutes, which means that physically based models are usually too slow to calculate the expected flooding depths within the available time. For this reason, novel models for short-term flood and flash flood prediction are needed.

The work is being carried out as part of the WaX program and its aim is to develop a fast flood prediction model for temporal and spatial precipitation data (for example high-resolution radar forecast) and runoff-relevant soil parameters with machine learning methods for catchments with strong topography.

The developed AI model aims to predict maximum flood depths for an urban catchment (Emmendingen in Baden-Württemberg, Germany) and temporally resolved flood depths in predefined neuralgic areas. It is based on supervised learning and therefore requires a database of input and associated output for training and validation.

The effective rainfall, which is based on spatially and temporally distributed rainfall (from radar hindcast) and runoff-relevant parameters such as land use, slope, soil type and especially soil moisture, serves as the training input. The associated results for training and validation are the spatially distributed flood depth within the catchment. To build up the database both, the flood depths and effective rainfall rates, were precalculated using established hydrological respectively hydrodynamic models. To predict flood depths during real heavy rainfall events, a number of different high-resolution radar forecasts are used and combined with a range of soil moisture assumptions.

The model is a combined method, in which the hydrological processes are done by a fast and calibrated physically based model, while the time-consuming hydrodynamic calculation is replaced by machine learning methods. This leads to a utilization of the low calculation time in the range of seconds with promising accuracy compared to the results from hydrodynamic simulations. Due to the fast prognosis time it is possible to calculate a series of ensembles for different soil moisture conditions and precipitation loads as a result of the uncertain soil moisture conditions and the uncertain radar forecast. The contribution will compare preliminary AI model predictions to the physically based model results to assess the potential and limitations of the model.

How to cite: Reinecke, A. and Neuweiler, I.: Development of a flood prediction model for heavy rainfall based on spatially and temporally distributed precipitation using machine learning techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13714, https://doi.org/10.5194/egusphere-egu23-13714, 2023.

Nature based solutions
Virtual presentation
Mahdi Hosseinipoor, Armin Mollaei Rudsary, Yasna Yeganeh, Zahra Kazempour, and Mohammad Danesh-Yazdi

The combined impacts of climate change and anthropogenic activities have altered runoff generation and flood regime in many regions, worldwide.  While hydraulic structures have been successfully operated to control flood for decades, their expected performance may be currently less certain under the augmented frequency of extreme precipitation events. The goal of this study was to examine the above hypothesis by utilizing both remote sensing and field data on the Imamzadeh Davood catchment in the northern Iran, which experienced a devastating flash flood in the summer of 2022. To this end, we surveyed the main river path to collect data on river morphology, structural characteristics of check dams, and sedimentation patterns. We also processed satellite imagery to extract and temporally trace back land-use land-cover change in the study area. Finally, we used recorded data from synoptic stations to explore the distinct role of extreme precipitation in intensifying the flood hazard. The results proved the occurrence of unprecedented precipitation with a return period of over 100 years, supporting the climate change effect in the region. In-situ observations revealed that all 18 check dams were destroyed between 20% and 100% during the flood event, while higher degree of destruction was observed towards upstream. The sliding and overturning stability analysis demonstrated that all check dams were stable with respect to sliding, while 30% of them were prone to overturning. Given the destruction of all check dams during the flood event, as well as the observed high deposition depth of sediment in the river corridor, we concluded that the shock imposed by the debris flow was responsible for the cascade failure of check dams from upstream to downstream. The findings of this study highlight the need for revisiting the design principles of hydraulic structures, such that they are adapted to the ongoing impacts of climate change in order to increase the resiliency of flood control systems.

How to cite: Hosseinipoor, M., Mollaei Rudsary, A., Yeganeh, Y., Kazempour, Z., and Danesh-Yazdi, M.: Why should structural solutions for flood control be adapted to climate change?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2281, https://doi.org/10.5194/egusphere-egu23-2281, 2023.

On-site presentation
Ilias Karapanos and Ellie Powers

The Chalk is considered an important aquifer in the Southeast of the UK as it supports flows in ecologically sensitive Chalk streams, as well as significant groundwater abstractions for public water supply purposes. Based on the Water Framework Directive (EU directive) objectives, all rivers need to be in good ecological status or support good ecological potential by 2027. The environmental regulatory body (Environment Agency) have designated the area located Northwest of London as over-licensed and over-abstracted in terms of groundwater availability from the Chalk aquifer. As a result of this, a long-term management strategy has been proposed, allowing for significant groundwater abstraction reductions for implementation between now and 2050.

Whilst under a range of river flow conditions, the proposed abstraction reductions are expected to allow greater baseflow to enter the rivers, it is possible that under higher flow conditions there will be an elevated risk of flooding, especially in downstream locations. An alternative approach is presented in this case study near London, aiming to utilise the well-established river-aquifer interactions during a range of hydrological conditions to balance the effects of winter floods and low flows during droughts.

The proposal for this case study is in an unconfined Chalk aquifer setting, supporting a number of groundwater abstractions, as well as providing baseflow to a river which is also supported by an effluent discharge. A nearby surface water reservoir located on top of clay deposits, is also available but currently unused for public water supply. Groundwater abstractions in the area are known to be supported by river flows during drought conditions, via a leaky river bed. Based on river bed leakage assessments undertaken under different hydrological conditions, it was found that a certain proportion of the total river flow can recharge the unconfined chalk aquifer via the leaky river bed in a 2-3 km stretch of river.

Therefore, the idea of capturing high river flows above a certain trigger at a downstream location through the urban areas where the river is in a concrete channel and refilling the currently disused reservoir storage, has been explored. Instead of then having to treat this water as surface water before using it for public water supply, by releasing this water back into the river at the head of the catchment during times of low flows it could support both river flows and also the output of the groundwater sources via artificial leakage. This unconventional type of Managed Aquifer Recharge has been tested under various hydrological conditions and could also prove a cost-effective scheme due to the lack of additional treatment needed for the surface-derived water.

This study demonstrates that enhanced understanding of the natural processes in a river catchment can provide alternative ways of managing the effects arising from both flood and drought events, whilst creating a resilient water supply in a changing climate.

How to cite: Karapanos, I. and Powers, E.: Innovative approaches to water resources management during flood and drought periods using semi-natural processes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2677, https://doi.org/10.5194/egusphere-egu23-2677, 2023.

Virtual presentation
Fabian Rackelmann, Rainer Bell, and Zita Sebesvari

The potential of healthy ecosystems in providing a multi-purpose and sustainable approach to Disaster Risk Reduction (DRR) and Climate Change Adaptation is widely acknowledged and, e.g., also highlighted in the latest Adaptation Strategy of the European Commission. However, to what extent an ecosystem can support DRR is largely determined by its condition. This holds also true for forest ecosystems. Their potential in supporting water retention and, therefore, in reducing drought and flood risk is widely recognized. However, often their potential to retain water is impaired by many stressors. Many of them are related directly to the trade-offs that come along with the forest management objectives. This is particularly the case when the ecosystem management’s target is to maximize the provision of one Ecosystem Service (ES), such as the provision of timber, which often leads to a considerable decline in the ecosystem’s ability to provide other ES, such as water retention. In alpine regions exists, for example, the concept of protective forests where financial interests in timber production are subordinate to address the trade-offs between forest ES. However, this concept has not received much attention in low mountain ranges so far even though they can already cause considerable orographic precipitation. 

Within this study, we investigated possible challenges and approaches for increased implementation of water retentive forest management in low mountain ranges. This was exemplarily done for the Rhineland-Palatinate part of the Ahr catchment. 19 investigative semi-structured expert interviews were conducted with 20 actors from the forestry, water, and nature conservations sector which included practitioners, academics, and personnel in higher and lower administrative levels and advisory centers. The qualitative analysis of the interviews has shown that the extreme 2021 floods (return period at minimum 500 years) were a warning shot that sparked interest in the water retention potential of forests at various levels, which was before majorly in the focus to reduce the drought risk on forests. However, several interacting barriers exist, ranging from rather silvicultural to socio-structural challenges. As reported by other research, a key challenge was related to finance. For example, the clearance of dead spruce stands is often financially motivated. However, research shows that this impairs the forest’s water retention capacity. Furthermore, a financial bottleneck was observed regarding infrastructural adaptations for enhanced water retention. Our work shows that due to the various potential co-benefits water retention measures in the forest can potentially profit from different funding mechanisms. Especially from the water sector, funding opportunities are available for measures that might not be covered under current funding schemes from the forest sector. However, a key prerequisite is that observed compound and cascading interactions are addressed. The limited cooperation between the different actors should be enhanced in this regard which will require improved coordination from the respective higher authorities and greater awareness locally.

How to cite: Rackelmann, F., Bell, R., and Sebesvari, Z.: Challenges to and approaches for water retentive forest management in low mountain ranges in Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10897, https://doi.org/10.5194/egusphere-egu23-10897, 2023.

On-site presentation
Angelique Lansu, Charlotte Wieles-Rietveld, Nico Ruysseveldt, Borjana Bogatinoska, Jikke van Wijnen, Frank van Lamoen, and Jetse Stoorvogel

Drought is a topical issue, given extreme drought records in NW Europe, the establishment of water coordination bodies and the perceived impact of drought on society. Climate change is driving disruptions in the hydrological cycle. In North-West Europe, in recent years, solutions to counter the effects of floods and flooding have been co-designed in a participatory manner in society. The question in this study is whether these Nature-based Solutions (NbS) to adapt to flooding are also effective to mitigate the effects of drought. We studied this research question based on field expertise from some 40 water professionals involved in the co-creation and implementation of NbS in 8 headwater catchments in NW Europe (southern England, northern France, Flanders, southern Netherlands; project Interreg 2 Seas Co-Adapt (2019-2023).
Based on the concept of evidence-based practice (EBP), we combined the field expertise of these water professionals with scientific knowledge to arrive at best practices. The NbS studied were predefined by process function (geomorphological, hydrological. soil-land).  To collect and evaluate the field expertise (practical knowledge), we conducted a Consensus Decision Process. This process consisted of a brainstorming phase (collecting) and a consensus phase (evaluating). This process at two time-intervals was conducted online, in the form of synchronous, online sessions in an online collaboration tool (Mural). The scientific knowledge from a Systematic literature review on NbS as flood measures were compared in the EBP with the collected practical knowledge from the Consensus Decision Process, and evaluated based on the criteria 'effect on drought' and 'synergy/trade-off with NbS'. Obtained results have been tested on outcomes from modelling NbS and drought in catchment Aa/Weerijs (NL; H2020 EIFFEL4Climate; 2021-2024) and expertise of the water professionals of this catchment. The result is that the most effective drought mitigation measures are: storage solutions, slow the flow measures and soil processes. If the underlying steering processes (geomorphology, hydrology, soil-land) are included in the design of flood measures, it is expected that after implementation of NbS in head waters, the water storage capacity will increase and ecological drought will decrease.

How to cite: Lansu, A., Wieles-Rietveld, C., Ruysseveldt, N., Bogatinoska, B., van Wijnen, J., van Lamoen, F., and Stoorvogel, J.: Effectiveness for Drought of Nature-based Flood Measures in Headwater Streams: Evidence-Based Practise in NW-Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16671, https://doi.org/10.5194/egusphere-egu23-16671, 2023.

Posters on site: Mon, 24 Apr, 14:00–15:45 | Hall A

Chairpersons: Doris Wendt, Lea Augustin
Eleni Kritidou, Martina Kauzlaric, Marc Vis, Maria Staudinger, Jan Seibert, and Daniel Viviroli

Globally, floods are the most frequent natural hazard. Reliable estimates of flood characteristics are key in measures that reduce or even prevent damage. Traditionally, floods and their impacts have been studied through statistical techniques based on historical observations. Due to the relatively short available streamflow records, extrapolation techniques based on the observed hydrographs are usually implemented. Furthermore, assumptions about antecedent conditions of an event (e.g., soil moisture, snowpack, storage levels of lakes and reservoirs) and their spatiotemporal variability are made. However, these methods incorporate several limitations related to the estimation of floods, especially when the focus is on very rare flood events.

Here, we explore the robustness of an elaborate framework based on continuous simulations with a hydrometeorological modeling chain (Viviroli et al., 2022). The modeling chain starts with a multi-site stochastic weather generator, focusing on the generation of extremely high precipitation events. Then, the bucket-type hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) is used to simulate discharge time series. Finally, the RS Minerve model is employed to implement simplified representations of river channel hydraulics, floodplain inundations and lake dynamics. To explore the robustness of simulation results and derived flood estimates, we selected the potentially most sensitive elements of the weather generator and the hydrological model and varied them across a palusible range. For the weather generator, the chosen elements include different precipitation lapse rates between 0-10%, a parameterization dependent on 4 different weather types, and 10 different parameterizations of the Extended Generalized Pareto Distribution, describing the precipitation intensities. For the hydrological model, firstly, another model structure will be tested. Then, the model’s precipitation lapse rates, distributing the mean catchment precipitation input from the weather generator to the different elevation zones, will be varied within 0–10%. Considering a set of small (a few 10 km²) to large (a few 1’000 km²) study catchments in Switzerland, we evaluate the impact of each of these changes on the simulated extreme floods and thus assess the robustness of the approach.

The robustness experiments will shed light on the applicability and feasibility of the hydrometeorological modeling chain for estimating very rare floods and help point out this approach's benefits and limitations. These findings are also expected to identify sensitive modeling decisions that should be treated carefully or for which further research would be highly beneficial. They should also provide a clearer picture of uncertainties important for hazard assessment, safety analyses and hydraulic engineering projects.



Viviroli D, Sikorska-Senoner AE, Evin G, Staudinger M, Kauzlaric M, Chardon J, Favre AC, Hingray B, Nicolet G, Raynaud D, Seibert J, Weingartner R, Whealton C, 2022. Comprehensive space-time hydrometeorological simulations for estimating very rare floods at multiple sites in a large river basin. Natural Hazards and Earth System Sciences, 22(9), 2891–2920, doi:10.5194/nhess-22-2891-2022

How to cite: Kritidou, E., Kauzlaric, M., Vis, M., Staudinger, M., Seibert, J., and Viviroli, D.: Robustness experiments on simulated extreme floods over Switzerland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1621, https://doi.org/10.5194/egusphere-egu23-1621, 2023.

Maria Staudinger, Martina Kauzlaric, and Daniel Viviroli

Continuous simulation has proven to be a promising base for flood frequency analysis since it avoids some of the shortcomings of other methods, such as assumptions about antecedent conditions or omission of relevant processes. In the EXAR project (hazard information for extreme flood events on the rivers Aare and Rhine), we have elaborated long continuous simulations of streamflow using a hydrometeorological modeling chain. This chain consists of a stochastic weather generator that provides precipitation and temperature series to a hydrological model, whose outputs are finally processed with a hydrological routing system, including and emulating the effect of regulated lakes, bank overflow and floodplain retention. As a result, distinctively long (several 100’000 years) continuous simulations are available at hourly resolution.

These simulations do not only cover streamflow but also other model internal fluxes and such as snow pack and soil moisture storage. With that, they allow to infer which hydro-meteorological story lines lead to extreme floods, i.e. floods with return periods of 100 years and higher. The story lines cover the important aspects of antecedent conditions, triggering precipitation, and their spatial and temporal interaction from the sub-catchment scale up to the large basin scale. The resulting story lines already cover a very broad range of possibilities due to the recombination of observations by the stochastic weather generator and the continuous simulation. They may help to further develop targeted story lines beyond what we already observed in changing climatic conditions.

How to cite: Staudinger, M., Kauzlaric, M., and Viviroli, D.: The role of antecedent conditions in the generation of large floods using long continuous simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7490, https://doi.org/10.5194/egusphere-egu23-7490, 2023.

Wilson Chan, Nigel Arnell, Geoff Darch, Katie Facer-Childs, Theodore Shepherd, and Maliko Tanguy

The UK has experienced recurring periods of hydrological droughts in the past, including the recent 2022 drought. Different types of large ensemble simulations such as single model initial condition climate model simulations or weather hindcasts provide a large sample of seasonal to decadal simulations. They can help overcome challenges in understanding extreme droughts presented by limited observations, the multivariate nature of individual drought events and internal variability of the climate system. Here, we demonstrate how weather reforecasts can be used to create physical climate storylines to assist water resources planning and understand plausible worst cases.

Using the 2022 drought as a case study, event-based storylines of how the drought could unfold over winter 2022/23 and beyond can be created by using the SEAS5 hindcast dataset which consists of 2850 physically plausible winters since 1982 across three lead times and 25 ensemble members. Storylines were defined based on the possible combinations of ENSO, the North Atlantic Oscillation (NAO) and the East Atlantic Pattern (EA) (e.g. La Nina/NAO+/EA-). Storylines constructed in this way provide outlooks of ongoing events and supplement traditional weather forecasts to explore a wider range of plauasible outcomes. Circulation storylines can be used in hydrological/groundwater models to explore the possible ranges of river flow, groundwater and reservoir levels. Outlooks can be periodically updated as certain storylines may become implausible over time.

How to cite: Chan, W., Arnell, N., Darch, G., Facer-Childs, K., Shepherd, T., and Tanguy, M.: Large ensemble simulations for water resources planning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12833, https://doi.org/10.5194/egusphere-egu23-12833, 2023.

Global sensitivity of inundation extent and population exposure to flood magnitude
Laura Devitt, Jeffrey Neal, Gemma Coxon, Thorsten Wagener, and James Savage
Henrique Moreno Dumont Goulart, Karin van der Wiel, Christian Folberth, Esther Boere, and Bart van den Hurk

Soybeans are globally used as the main source of protein for livestock. However, most soybean production is concentrated in regions in The United States of America, Brazil and Argentina, rendering the supply chain vulnerable to regional disruptions. In 2012, simultaneous soybean losses in these three countries led to shortages in global supplies and to record prices. The losses were linked to anomalous weather conditions in all three countries. In this experiment, we investigate how climate change may affect future events with similar or larger impacts than the one from 2012 for each country individually and simultaneously. For that, we develop a hybrid model, coupling a process-based crop model with a machine learning model, to improve the simulation of soybean production. We assess the frequency and magnitude of events with similar or larger impacts than 2012 under different future climatic forcing conditions. We also evaluate the events with respect to present day and future conditions to disentangle the impacts of (changing) climate variability from the long-term mean trends. Results indicate that long-term trends of mean climate increase the occurrence and magnitude of 2012 analogue crop yield losses. Conversely, 2012 analogue crop yield losses that are caused by changes in climate variability show an increase in frequency in each country individually, but not simultaneously across the Americas.

How to cite: Moreno Dumont Goulart, H., van der Wiel, K., Folberth, C., Boere, E., and van den Hurk, B.: Changes in regional and simultaneous soybean losses in the Americas due to projected global warming, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17098, https://doi.org/10.5194/egusphere-egu23-17098, 2023.

Thomas Baumann, Lea Augustin, and Annette Dietmaier

Climate changes in the anthropocene lead to an increase of rainfall
intensity while the infiltration capacity of the soil is reduced
during extended dry periods. As a consequence surface runoff increases
and groundwater levels are reaching all-time lows: even close to the
alps water becomes scarce. Keeping precipitation water local is a must
and one option is to direct flood water into local aquifers
(Flood-MAR). This comes with a number of challenges, first of all, a
pronounced asymmetry of floods with very high volume flow in very
short times, and droughts requiring long-term storage. From a
hydrogeological perspective, infiltration of flood waves requires
extremely well-connected groundwater bodies with high hydraulic
conductivity contrasting with slow groundwater flow required for
long-term storage. Geotechnical measures like sheet-pile walls or sand
injections can be used to control the release of groundwater back to
the river. The infiltrated water has to be conditioned to meet
hydrochemical and sanitary criteria. In contrast to conventional
managed aquifer recharge (MAR) the time frame for treatment is
extremely limited. As floods are not occurring regularly, any treatment
system has to work autonomously and to be insensitive to long
downtimes between flooding events. The decision tree for the
selection of suitable sites starts with the occurrence and extent of
flooding events (regular flooding events with volumes less than
roughly 1 million m³), the morphology of the site (leveled with
groundwater levels below river water), and the hydrogeological
properties of the adjacent aquifers (ideally porous aquifers with high
specific yield and hydraulic conductivity). Further criteria are land
use (agriculture preferred), infrastructure (access to the site, no
subsurface installations), protection zones (groundwater, habitats,
...) and ecosystem services, and risk factors in the catchment
(hazardous substances, extended mobilization of soil during flooding,
...).  Three sites have been selected as pilot sites and will be

How to cite: Baumann, T., Augustin, L., and Dietmaier, A.: Smart-SWS: Combining flood protection and drought prevention -- Concept and site selection criteria, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5999, https://doi.org/10.5194/egusphere-egu23-5999, 2023.

Alexandra Amann, Sven F. Grantz, Katrin Brömme, Timo M. König, Oliver Buchholz, Paul Wagner, and Nicola Fohrer

The research project KliMaWerk has been launched in 2022 in the context of the “WaX” funding measure and is a part of the federal research program on water “Wasser: N”, which contributes to the strategy “Research for Sustainability (FONA)” of the BMBF (Federal Ministry of Education and Research, Germany).

The overall aim of the project is to develop strategies to increase the hydrological and ecological resilience of rivers against droughts and floods, two extremes, being elementary problems of climate change. The project follows a fully comprehensive and interdisciplinary approach by investigating the entire river basin (system), i.e. surface and subsurface water distribution in time, physico-chemical and ecological status, and competing water uses. Based on available data and additional field campaigns (biological and morphological mapping, groundwater and soil measurements), stakeholder involvement and the analyses of coupled surface/groundwater models on different scales, the project aims at the development of a toolbox as a modular planning instrument for the selection of management strategies and measures for both urban and rural areas. In addition, recommendations for dealing with droughts and low flow periods are being developed.

The present contribution will focus on the hydrological and hydrogeological modelling. First results are presented for selected case study regions located in the Lippe River Basin, North Rhine-Westphalia. The regions differ in terms of rural and urban catchment areas. Software packages being used are the groundwater simulation software SPRING (König 2022) and the hydrological models NASIM (Hydrotec 2022) and SWAT+ (Bieger et al. 2017). Whereas the SWAT+ model is used for computations of the entire region and upscaling, SPRING and NASIM will be deployed for detailed analysis of sub-basins. NASIM is strong in describing surface runoff processes and only roughly estimates flows to and from the groundwater. Vice versa, SPRING describes all processes relevant for subsurface flow in detail while surface runoff is simplified. Coupling between the different models will yield comprehensive hydrological models, which will significantly improve knowledge about the water balance development during the last decade, a prerequisite for scenario analysis.

A first project goal is the setup of the models based on hydrologic and geologic features. Calibration is carried out for the period 2011-2021 based on available groundwater level, streamflow measurements as well as water quality data (chemistry, temperature). In a next step, coupling of the models is done via parameters describing the interaction between surface and groundwater flow, like groundwater recharge and leakage rates. In the further course of the project, the developed models will be used to determine the effects of various measures and land management strategies for increasing resilience to climate-related extremes. The modelling results of the two focus sub-catchments are used to assess the potential for upscale to the whole Lippe catchment.


Bieger et al.  (2017): Introduction to SWAT+, A Completely Restructured Version of the Soil and Water Assessment Tool. In: JAWRA Journal of the American Water Resources Association 53 (1), S. 115–130.

Hydrotec (2022): NASIM 5.3.4 Benutzerdokumentation.

König et al. (2022): SPRING Benutzerhandbuch. ISBN 978-3-00-073433-5.

How to cite: Amann, A., Grantz, S. F., Brömme, K., König, T. M., Buchholz, O., Wagner, P., and Fohrer, N.: Hydrological Modelling of Droughts and Stormwater Events to Develop Climate Resilient Water Management Strategies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7573, https://doi.org/10.5194/egusphere-egu23-7573, 2023.

Wolfgang Dorner, Andreas Weber, and Rajan Paudyal

The infiltration of surface water and excess water from floods requires numerous measures to prevent and avoid side effects in the groundwater. Besides all these physical measures, intensified monitoring will be necessary. As part of the project SmartSWS, a monitoring system as a set of local sensors for quantitative and qualitative parameters combined with remote sensing data from unmanned aerial systems will be developed, to monitor test installations of small stormwater storage with infiltration capacity (SmartSWS) in Southern Germany. While current monitoring strategies are based on a thinned-out network of stationary sensors, the infiltration of excess water runoff into the groundwater layer to compensate for drought effects requires dense monitoring. While local sensor installations can only provide punctual information but on a continuous basis, remote sensing data provides spatial information for time intersects. The idea of monitoring such a SmartSWS is based on sensor fusion of these spatially and temporarily covering data with a low-cost sensor network covering the industrial communication standards to allow installations in small rural catchments. The isolated location and environmental impacts of the SmartSWS require a high degree of reliability of the installed hardware in such environments. Reliable measurements are also required so that the installations can be monitored remotely, and the systems can operate autonomously most of the time. This will provide the basis for Big Data processing methods and data analytics to efficiently prepare the data for visualization to monitor the condition of the facility in real time so that interventions and the effectiveness of the concept can be shown.

How to cite: Dorner, W., Weber, A., and Paudyal, R.: Technical Monitoring of Smart Storm Water Storage Systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15637, https://doi.org/10.5194/egusphere-egu23-15637, 2023.

Mathias Jackel and Tobias Schuetz

Due to the climate change-related increase in extreme weather events and scenarios such as the flood disaster in Western and Central Europe in July 2021, an increased research effort is necessary in order to better predict the dynamics of such events and consequently create preventive measures. Due to a lack of water retention capacity and insufficient drainage structures, the vulnerability is high in and around of settlements where infrastructures are not sufficiently adapted for extreme precipitation. Since not only the sealed surfaces in urban areas contribute to the development of runoff processes, but the entire catchment area, the process dynamics of the outer areas of settlements must also be increasingly researched.

This study is part of the collaborative project “Urban Flood Resilience - Smart Tools (FloReST)”, which is funded by the German Federal Ministry of Education and Research and is dedicated to the exploration of measures to determine and increase the resilience of existing infrastructures.

Our scope is to analyze the effect of different flood prevention measures on an existing drainage infrastructure in the municipality of Filsch (Trier), which in the past could not fulfill the purpose of drainage and thus flood damage occurred frequently.

The connected runoff generating area is mainly used for agriculture. Despite an adapted cultivation method with the no tillage method and a 5-stage crop rotation that ensures a soil cover over the whole year several flooding events occurred due to surface runoff generation. Local farmers have reported that this slope does not always generate surface runoff throughout the year for similar heavy rainfall events. Hence, we hypothesize that not only the precipitation event, but also seasonal effects have an influence on runoff generation under heavy rainfalls. To quantify runoff generation and the causes of its occurrence, the study site will be analysed using the slope specific, physical, deterministic, hydrological model CATFLOW. Heavy rainfall simulations will be used to study the impact of current land use, alternative cultivation methods and decentralized water retention measures in order to understand potential water retention in the area. The simulation model will be calibrated using field studies such as soil sampling and irrigation tests on the study site and in addition on test fields with integrated water retention measures. Water retention measures also have the advantage of providing increased soil moisture during dry periods, thus enhancing agricultural land quality.

How to cite: Jackel, M. and Schuetz, T.: Hydrologic modelling of seasonal runoff generation during heavy rainfall: Effect of decentralized water retention measures at a flood-prone site in Trier (Germany) – A study concept, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-677, https://doi.org/10.5194/egusphere-egu23-677, 2023.

Udo Satzinger and Daniel Bachmann

The recent drought events (e.g. 2022) highlighted the impacts caused by hydrological drought and low-flow events to society and ecosystems. The consequences of low-flow events in recent years emphasizes the urgent need for a structured low-flow risk management. The DryRivers project aims to develop a software-based tool for an effective support of low-flow risk management. The low-flow risk analysis is the core of the supporting tool and will be described in detail in this work.

In the field of flood risk applications, scenario-based calculations are often performed. Due to a relative short duration of flood events between a few days to a few weeks and in general negligible hydrological interaction between temporal distant flood events, a clear distinction of such events is quite simple. However, for low-flow risk modelling, the definition of scenarios is considerably more complex due to their long-term development and occurrence. Thus, hydrological conditions from previous years can be essential for the development of a low-flow event. Due to this, the use of long-term continuous time series seems to be more suitable for low-flow risk modelling than a scenario-based approach. This continuous approach has been used in flood risk analysis by Sairam et. al. (2021). In this work it is adapted and extended for low-flow risk analysis.

The approach to low-flow risk analysis consists of four basic analyses. These include the meteorological-hydrological analysis, which generates synthetic long-term weather data - using, e.g., a stochastic weather generator - and transforms these weather data into long-term runoff time series. Therefore, a rainfall-runoff model is applied, considering the catchment-specific characteristics. The hydrodynamic analysis quantifies water levels, water temperatures and flow velocities along the river. Core of the analysis is a numerical 1D-river model, which calculates the hydraulic values using runoff time series and river characteristics (e.g., cross sections). The influence of the near-surface groundwater on the river by in-/exfiltration is considered via a bidirectionally coupled 2D-groundwater model. Water temperature is determined in a unidirectionally coupled temperature model. Weather data and hydraulic values are transformed into water temperature within the river. Based on the time series of the hydraulic values the consequences of low-flow are quantified as sum over the considered period within the analysis of consequences. Different categories of low-flow consequences are considered: socioeconomic consequences, e.g., for shipping or industrial water use, as well as ecological consequences for fish and macrozoobenthos. Threshold approaches for quantifying impacts are generally applied in both categories. Finally, in the risk analysis, the low-flow risk is calculated by dividing the damage sums per consequence category with the number of simulated years. This results in an annual low-flow risk, e.g., in €/a. The calculated low-flow risk is an essential basis for a transparent and objective decision support in low-flow risk management.

This research is funded within the research framework of WaX (Wasser-Extremereignisse) by the Federal Ministry of Education and Research of Germany.


Sairam, N., Brill, F., Sieg, T., Farrag, M., Kellermann, P. and Nguyen, V. D. (2021), Process‐Based Flood Risk Assessment for Germany, Earth's Future 9 (10), DOI: 10.1029/2021EF002259.

How to cite: Satzinger, U. and Bachmann, D.: Conceptual approach for a holistic low-flow risk analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5007, https://doi.org/10.5194/egusphere-egu23-5007, 2023.

Posters virtual: Mon, 24 Apr, 14:00–15:45 | vHall HS

Chairperson: Lea Augustin
Qingsong Xu, Yilei Shi, Jonathan Bamber, Chaojun Ouyang, and Xiao Xiang Zhu

Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to accurately forecast flood crests and issue time-critical hazard warnings. In this work, we build a fast, stable, accurate, resolution-invariant, and geometry-adaptative flood modeling and forecasting framework that can perform at scales from continental to global. We achieve this by combining continuous flow modeling of a geometry-adaptive physics-informed neural solver (GeoPINS) with the authenticity of Earth observation data. Specifically, the GeoPINS is proposed based on the advantages of no training data in physics-informed neural networks (PINNs), as well as possessing a fast, accurate, and resolution-invariant architecture through the implementation of Fourier neural operators (FNO). In particular, to adapt to complex and irregular geometries that exist in rivers, we reformulate PINNs in a geometry-adaptive space by taking full advantage of coordinate transformations and the efficiency of numerical methods in solving the spatial gradient. We validate our GeoPINS on popular partial differential equations on both regular and irregular domains, demonstrating fast, stable, and accurate performance, as well as resolution-invariant, geometry-adaptive properties. Next, due to a lack of large-scale ground truth data, time-series flood records are generated using freely available Sentinel-1 data and a SAR-based flood mapping algorithm. These flood records are used as boundary conditions and flood inundation extent verification of the proposed hydrodynamic model. Finally, we compare our GeoPINS results with a 30 m resolution, SAR-based flood record, and measured discharge from gauging stations, obtaining good agreement among the three. The experimental results for the Pakistan flood in 2022 indicate that the proposed method can maintain high-precision large-scale flood dynamics solutions at different resolutions and flood hazards can be forecast in real-time with the aid of reliable precipitation data.

How to cite: Xu, Q., Shi, Y., Bamber, J., Ouyang, C., and Zhu, X. X.: A large-scale flood modeling using geometry-adaptive physics-informed neural solver and Earth observation data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3276, https://doi.org/10.5194/egusphere-egu23-3276, 2023.