Displays

It is well accepted that warmer temperatures lead to greater moisture holding capacity for the atmosphere, resulting in bigger downpours, creating larger design precipitation intensities and possibly less secure flood infrastructure. It is also known that higher temperatures increase evaporation rates and hence dry soils quicker than before. This presentation discusses the role each of these controls plays in natural and urbanised catchments. It is shown that one of these two tends to dominate depending on a range of factors, including catchment attributes, as well as how extreme the design problem is. This presentation uses examples from four urban catchments spread across three continents as well as over 200 natural catchments representing various climatic zones in Australia to form its conclusions.

How to cite: Sharma, A.: The opposing factors controlling change in warming related future flood extremes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4277, https://doi.org/10.5194/egusphere-egu2020-4277, 2020.

Tropical Cyclones (TCs) represent a threat in several areas of the world, among which the Eastern/South-Eastern United States are one of the highly impacted regions. In addition to the frequently analyzed hazards related to the strong winds and storm surges associated with TCs, they are also responsible for heavy rainfall, which can affect areas located very far from the storm center. The accurate estimation of rainfall extremes is crucial in several TC-related impacts, such as engineering design of buildings and prevention/protection measures, flood mapping, risk estimation and mitigation, insurance and re-insurance purposes, policy-making support. Statistical approaches considering the physical drivers of hydrological phenomena, besides their conceptual relevance, can help reducing the estimation uncertainty of extremes. Under these premises, here we use the Metastatistical Extreme Value Distribution (MEVD), a recent approach that improves the estimation of high-return period values over the traditional Extreme Value Theory. We leverage the property of the MEVD to explicitly include in the statistical formulation different rainfall-generating phenomena and we examine the potential advantage of distinguishing TC-induced and non-TC rainfall events in the estimation of extremes. Hence, we apply the MEVD both in a single-component formulation (i.e., assuming that all rainfall events are generated by one single mechanism, so that they can be described by the same probability distribution) and a mixed-population formulation (i.e., separating non-TC and TC-induced rainfall events) to long time series of daily precipitation in six American metropolitan areas, historically known for being impacted by TCs. Moreover, due to the characteristic time scale of these mechanisms, which can significantly influence precipitation for several days, we focus also on aggregated values of rainfall on consecutive days. We find that the mixed approach is advantageous in some cases when looking at daily rainfall, especially when there is a rather uniform frequency of TC events over years. When considering cumulative rainfall on time windows of three days, we show that the reduction of the estimation error by the mixed MEVD is generally higher than in the case of daily rainfall and it is consistent for all the cases studied, except for Houston. A possible reason for the mixed MEVD not to outperform the single-component MEVD in this area is the presence of tornadic supercell convective mechanisms, which also generate heavy rainfall though concentrated in short time intervals.

How to cite: Miniussi, A., Marani, M., and Villarini, G.: Extreme rainfall from Tropical Cyclones described through the Metastatistical Extreme Value Distribution, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-752, https://doi.org/10.5194/egusphere-egu2020-752, 2020.

Damages from flooding in China account on average for 60-70% of the total Annual Losses derived from natural catastrophes. The extreme rainfall events responsible for these inundations can be broadly categorised in two well differentiated mechanisms: Tropical Cyclone (TC) induced, and non Tropical Cyclone induced (nonTC) precipitation. Between 2001 and 2015, inland nonTC rainfall flood events occurred roughly with double the frequency as TC events. While TC events can be highly destructive for coastal locations, over the entire China territory nonTC flooding accounted for more than half of the total economic flood loss for events with significant socio-economic impact, highlighting the importance of the nonTC flooding mechanism on the regional and national scale.

Large-scale modes of climate variability modulate in different ways TC and nonTC induced precipitation, both in the frequency and the magnitude of the events. In a stochastic rainfall generation framework, it becomes therefore useful to model these two mechanisms separately and include their differentiated long-term climatic influences in order to fully reproduce the overall observed rainfall variability. This work presents results on the effect of ENSO and Southern Oscillation Index (SOI) values on seasonal rainfall in China, and how to include this climatic variability in stochastic rainfall for flood catastrophe modelling.

How to cite: Salinas, J. L., Smith, R., Li, S., Nicotina, L., and Hilberts, A.: Including climatic variability in stochastic rainfall for flood catastrophe modelling – The effect of ENSO and SOI in China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20348, https://doi.org/10.5194/egusphere-egu2020-20348, 2020.

Pluvial flooding is getting increasing attention around the world, but there are very limited studies on how to estimate pluvial flood damage risk at a regional scale. In this paper, we evaluate the value of statistical methods for pluvial flood risk estimation. One objective is to assess if statistical methods can deliver significant relationships between precipitation indices, soil and landscape characteristics, and pluvial flood damage risk in agricultural areas. Additionally, we want to explore if the statistical methods could be a cost-efficient alternative to deterministic surface run-off models. The analyses are performed for agricultural landscapes in Upper Austria where flood damage location reports of the Austrian hail insurance are available for the 2007 to 2013 period. We assess the relative performances of a generalized linear model (GLM) and a random forest (RF) model to estimate pluvial flood occurrence based on presence/absence raster data set, where the imbalance of the binary target variable and multicollinearity of predictors pose specific challenges. The analysis reveal that within the study area the most severe agricultural damages were triggered by intense rain events, but in one case the damage was caused by longer lasting low intense rain. By means of log-linear models and random forests the relationships between the location characteristics and damage events are investigated. A specific focus is laid on comparing the skills of continuous versus classified parameters, and on methods for dealing with collinearity. We compare the performances of both models based on cross-validation statistics and the process-realism of results. We finally discuss how far the statistical methods appear appropriate for quantifying pluvial flood damage risk at a regional scale.

How to cite: Laaha, G. and Nocker, C.: How far can we estimate pluvial flood damage risk by statistical learning?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2056, https://doi.org/10.5194/egusphere-egu2020-2056, 2020.

Since its creation in the late 1990s, UNISDR has identified education and knowledge as priority factors for risk and disaster reduction, notably through Hyogo and Sendai frameworks for actions. More recently, the 2019 Assises Nationales des Risques Naturels (a major meeting event organized by the French Ministry of Ecology on the natural risks management) have pointed out the urgent need to develop a risk culture to improve the resilience of territories. One of the levers for developing this risk culture is to inform the population of the risks to which they are exposed. Preventive information can take a wide variety of forms: regulatory brochures, exhibitions, plays, etc. However, we can wonder about the impact of this information: is it effective? Does it reach its objectives? How to evaluate its influence?

In a geographical context where few natural disasters occur, questionnaire surveys can be a solution. However, several studies have shown that this method fails to put individuals in a situation of emergency and to project themselves into a potential event that they may have difficulties to imagine. This is why the I²PRI project proposes to go beyond these methods and develop innovative and immersive tools to assess the impact of preventive information on people's knowledge. The project developed both a video game and a play. The objective of these media is to immerse the respondents in a fictive but realistic disaster situation in order to evaluate their ability to mobilize their knowledge in the case of a real event. Those tools are based on a common scenario that aims at putting the respondents in a dilemma situation. They mobilize an artistic dimension and raise the question of how to transcribe natural events through sound and visual stimuli or through interactions with other characters. Each tool has an observation and a debriefing phase which allow not only to analyse the respondents reactions but also to assess the efficiency of the whole protocol.

Applied to two phenomena (fast kinetic floods and earthquakes), the survey has been carried out in six municipalities of the French Alps. Those municipalities are characterized by different geographical contexts (urban/rural, plain/mountain) and different preventive information contexts (old information, regulatory information, alternative information). The talk will present the two protocols and the first results of their deployment in the field: the results of the survey about the level of information of the population, the side effects of the protocols in terms of preventive action, and the action-based research process in terms of public action of preventive information.

How to cite: Beck, E., André-Poyaud, I., Arnaud, A., Borelly, A., Chionne, D., Duché, S., Gaïdatzis, C., Grancher, D., Jacquemet, E., Lutoff, C., Revol, C., Robinet, N., and Servet, P.: Evaluation of the impact of preventive information on natural risks with original immersion tools, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18491, https://doi.org/10.5194/egusphere-egu2020-18491, 2020.

Laymen’s awareness for the natural hazards and their perception of the associated risks at the local level have been acknowledged widely as key factor for the success of any risk mitigation initiative. It is therefore particularly beneficial to find out how people's risk perception is shaped in a multi-hazard environment, such as that of Eastern Mediterranean, and how it affects individual preparedness. To this end, we have conducted an online survey aimed at Greek citizens in order to better understand their risk perception among various hydro-meteorological hazards, including geophysical hazards for comparison, and to evaluate their coping capacity. The survey questionnaire received more than 2,300 responses from across Greece. The analysis of the questionnaire has been performed in the frame of the project “THESPIAN II – Development of synergistic and integrated methods and tools for monitoring, management and forecasting of Environmental parameters and pressures”.

Statistical results show that people consider hydro-meteorological hazards less worrying and dangerous than earthquakes. However, in contrast to earthquakes, it was found that increase in hydro-meteorological risks perception enhances preparedness i.e. the adoption of adequate protective measures, except of the private insurance coverage which was found to be purely a matter of economic criteria. Experience was found to have a significant impact on both risk perception and preparedness for all types of natural hazards. However, with respect to hydro-meteorological hazards, its effect decreases with time. Results also highlight the important role of a focused and coordinated effort by authorities and scientists to inform citizens and build a trustful relationship in motivating individual preparedness, as well as other interesting statistically significant relationships with participants demographics and other factors.

How to cite: Papagiannaki, K., Diakakis, M., Kotroni, V., Lagouvardos, K., and Andreadakis, E.: Hydro-meteorological risks perception and preparedness in a multi-hazard environment: The case of Greece, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2371, https://doi.org/10.5194/egusphere-egu2020-2371, 2020.

Environmentally associated infectious diseases, including those driven by extreme weather events, represent a critical challenge for public health as their source and transmission are frequently sporadic and associated mechanisms often not well understood. Over the past decade, the Republic of Ireland (ROI) has persistently reported the highest incidence of confirmed verotoxigenic E. coli (VTEC) and cryptosporidiosis infection in the European Union. Moreover, recent climate projections indicate that the incidence, severity and timing of extreme rainfall events and flooding will increase dramatically over the next century, with Ireland forecast to be the second most affected European country with respect to the mean proportion of the population residing in flood-prone areas by 2100. This study aimed to assess the association(s) between potential flood risk exposure and the spatial occurrence of confirmed VTEC and cryptosporidiosis infection in Ireland over a 10-year period (2008-2017).

In 2012, the Irish Office of Public Works (OPW) initiated the National Catchment Flood Risk Assessment and Management (CFRAM) Programme within the framework of the Flood Directive (2007/60/CE), with high-resolution flood maps produced for coastal and fluvial risks and three risk scenarios based on calculated return periods (low, medium and high probability). Small area identifiers (national census area centroids) were used to attach anonymised spatially referenced case data to CFRAM polygons using Geographical Information Systems (GIS) to produce an anonymised dataframe of confirmed infection events linked to geographically explicit flood risk attributes. Generalised linear modelling with binary link functions (infection presence/absence) were used to calculate probabilistic odds ratios (OR) between flood risk (presence/absence and scenarios) and confirmed human infection.

Preliminary results indicate a clear relationship between both infections and hydrological risk. Over one third of all infection cases were reported within areas exposed to flood risk (VTEC 948/2755 cases; cryptosporidiosis 1548/4509 cases). Census areas categorised by a high (10-year Return Period) fluvial flood risk probability exhibited significantly higher incidence rates for both VTEC (OR: 1.83, P = 0.0003) and cryptosporidiosis (OR: 1.80, P = 0.0015). Similarly, areas characterised by low (1000-year Return Period) coastal flood risk probability were over twice as likely to report ≥1 confirmed case of cryptosporidiosis during the study period (OR: 2.2, P= 0.003). Space-time scan statistics (temporally-specific spatial autocorrelation) indicate an unseasonal peak of cryptosporidiosis cases occurring during April 2016, a majority of which took place within or adjacent to high flood risk areas (56% of total cases), revealing a potential relationship with the exceptional flooding events experienced during winter 2015-2016 (November-January). Further work will seek to identify the individual/combined flood risk (CFRAM) elements most significantly associated with the incidence of infections.

Flood risk assessment mapping may represent an innovative approach to assessing the human health impacts of flood risk exposure and climate change. The outcomes of this study will contribute to predictive modelling of VTEC and cryptosporidiosis in Ireland, thus aiding surveillance and control of these diseases in the future, and the causative nature of regional hydrology and climate.   

How to cite: Boudou, M., Cleary, E., Hynds, P., O'Dwyer, J., Garvey, P., ÓhAiseadha, C., and McKeown, P.: Climate Change, Flood Risk Prediction and Acute Gastrointestinal Infection in the Republic of Ireland, 2008-2017, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10162, https://doi.org/10.5194/egusphere-egu2020-10162, 2020.

Floods, which are considered as one of the most destructive extreme weather events, are being more severe issues with changing climate, and they are threatening both human life and property. To address flood hazard issues, this study evaluates the application of a hydro-meteorological model system as an early warning system approach. The Weather Research and Forecasting Hydrological model system (WRF-Hydro), a fully-distributed, multi-physics, multi-scale hydrologic model, has the capability of accurately capturing the flood hydrographs in terms of shape and peak time corresponding to storm precipitation. WRF-Hydro model system is implemented with meteorological forcing data obtained from the Weather Research and Forecasting (WRF) atmospheric model. WRF/WRF-Hydro model system is operated in uncoupled mode. The study area is the Oymapinar Basin in Southern Turkey has complex topographic characteristics, and in the upstream basin area, the river network originates from mountainous region. Five heavy rainfall events occurred between January 2015 and May 2015 in the basin selected to assess the model performance of simulating flood hydrograph. The model calibration process is performed by covering three heavy rainfall events, while two of them are used for validation of the model system. This study provides an initial evaluation for possible coupled atmospheric-hydrological model simulations between WRF and WRF-Hydro model systems for future applications.

How to cite: Kilicarslan, B. M., Duzenli, E., Pilatin, H., Yucel, I., and Yilmaz, M. T.: Evaluation of a Hydro-Meteorological Model System for Flood Forecasting of a Mediterranean Basin in Turkey, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-519, https://doi.org/10.5194/egusphere-egu2020-519, 2020.

Early warning systems are a critical element for flood risk reduction. If properly designed and disseminated, flood warnings can empower citizens and communities at risk by enhancing their preparedness and their response capacity during a flood event to reduce the possibility of personal injury or loss of life. Nevertheless, the reported situations where citizens did not react to warnings keep increasing, regardless if timely warnings were issued in the area. Receiving an official flood warning is not enough to guarantee appropriate proactive responses and self-protective behaviours from citizens during weather-related emergencies.

Flood warnings should aim to communicate clear and relevant local information on how floods might have an impact on citizens and what actions they can do to ensure their safety. Site-Specific Warnings (SSWs) are proposed as a step towards impact-based communication for citizens during weather-related emergencies.  The SSWs aim to translate meteorological and hydrological hazards into location-specific impacts and thus, propose appropriate local self-protection actions using local vulnerability and exposure information.

In this work, a prototype of SSWs has been developed for previously defined vulnerable points in the city of Blanes, Spain. As part of the first stage of implementation, a mobile app has been designed to serve as a risk communication platform during emergencies. The SSW app can inform users in real-time, the current warning level of vulnerable sites in the city on Blanes and the appropriate protective actions to be performed by citizens on each location to minimize consequences. Further components are the capability of users receiving official messages from authorities regarding a site risk level and the possibility of linking the SSW app to tailor-made multi-hazard early warning system platforms for operational authorities.

Finally, by moving towards warnings that can help citizens respond appropriately and effectively during a crisis, SSWs could play a central role in promoting a shift on how societies and authorities currently deal with weather-induced emergencies and their associated impacts.

How to cite: Landaverde, E., Sempere-Torres, D., and Berenguer, M.: Towards impact-based communication during emergencies: Development of site-specific warning services in Catalonia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1011, https://doi.org/10.5194/egusphere-egu2020-1011, 2020.

It is evident that changes in climate alter the incidence of hydro-climatic extreme events, specifically floods, which are likely to cause irreparable socio-economic and ecological damages. With a 7,516 km coastline that is prone to climate-mediated disturbances and cyclones, the eastern coast of the Indian subcontinent is comparatively more vulnerable to the changing climate and land use with higher incidences of extensive flooding. Therefore, the policy-makers and decision-making authorities are dependent on the scientific community to provide reliable estimates of hydro-meteorological variables for simulating extreme events under the impact of climate change. However, a comprehensive flood risk framework at a finer administrative level is not yet available under the Indian scenario that assesses the changing dynamics and complexities of different components of climatic risk (hazard, vulnerability, and exposure). The present study attempts to demonstrate a proposed framework of flood risk assessment for a highly flood-prone deltaic region of Mahanadi River Basin, India, under climate change scenarios for near-future (the 2040s) at present-day vulnerability and exposure status. It was noted that changes in future flood risk are highly influenced by the vulnerability and exposure status of the region. Lower vulnerability and exposure in coastal sub-districts reduces the overall risk even if a higher flood hazard is observed. Under both future scenarios, RCP 4.5 and 8.5, the number of villages under high hazard zones with greater flood magnitude has increased. Therefore, it thrusts upon the need to adopt stringent actions for devising better adaptation strategies and sustainable planning which can aid in lowering the vulnerability of the region to future floods.

How to cite: Gusain, A., Sudharsan, N., Karmakar, S., and Ghosh, S.: Flood Risk Characterization of Highly Flood-prone Data Scarce Region under Changing Climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1078, https://doi.org/10.5194/egusphere-egu2020-1078, 2020.

Risk associated with weather-induced hazards is worldwide continuously increasing due to the increase of urbanisation and exposed settlements in flood-prone areas. This asks for the implementation of more effective mitigation strategies, able at the same time to strengthen the community resilience at different territorial levels.

This study aims to propose an innovative methodology to better understand, study and analyse the vulnerability and capacity of exposed elements in order to improve the Italian Civil Protection (CP) Plans and consequently the public preparedness and the self-protective response at community level. This can support better mitigation strategies design and their relationship with decision making processes at local level.

The methodology assumes a reference scenario of a “flash flood” – that requires an immediate and efficient response of the civil protection system – and develops starting from the regulatory reference framework of the EU Floods Directive (2007/60/EC).

The main assumption of this study is that for CP purposes risk should be estimated by considering all its components of hazard, exposure, vulnerability and capacity; in addition, exposed elements must be characterised by reference to the local context through the active involvement of population, administrations and stakeholders.

In our methodology, the risk estimation has been enriched quantitative scale with information gained by the stakeholder involvement – both on hazard and on vulnerability and capacity of the considered exposed assets. These data constituted the input variables of the model for formalising the procedures and the actions to be undertaken, that by so doing are more suited to the territory.  

Thanks to the participative process, scientific analysis can be enriched with local knowledge, resulting in a detailed mapping and characterisation of elements to be considered in the definition of risk mitigation strategies, additionally strengthening coordination and collaboration between institutions and citizens and then community resilience.

A case study has been developed on the scholastic framework of Serra Riccò, a small municipality in the hinterland of Genoa.

The result was a detailed mapping of schools – based on accurate vulnerability and capacity data – which provides decisions support in actions, interventions and resources sorting thank to an actual and shared representation of the territory.

The process has helped the whole community to understand the importance of developing shared mitigation strategies. This constitutes the starting point for the development of a community vision on strategies to face with risk, ensuring the improvement in risk mitigation and management effectiveness, thus bolstering community resilience.

How to cite: Mortara, L., Ferraris, L., Morando, M., Giambelli, M., and Trasforini, E.: A methodology for flood risk mapping at the local scale for Civil Protection purposes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1842, https://doi.org/10.5194/egusphere-egu2020-1842, 2020.

Hydrogeological hazards are increasingly causing damage worldwide due to climatic and socio economic changes, making it crucial to build resilient communities to reduce potential losses. To this end, one of the first steps is to understand how people perceive potential threats around them. This study aims at exploring how risk awareness of and preparedness to face hydrological hazards changes over time. A cohort study was carried out in two villages in the North-eastern Italian Alps, Romagnano and Vermiglio, affected by debris flows in 2000 and 2002. Surveys were conducted in 2005 and 2018, and results compared. The survey data show that both awareness and preparedness decreased over time. We attribute this change to the fact that no event occurred in a long time and to a lack of proper risk communication strategies. Besides contributing to sociohydrological modelling by providing empirical data on human behaviour dynamics, the outcomes of this study are a valuable input for effective risk communication strategies.

How to cite: Mondino, E., Scolobig, A., Borga, M., Albrecht, F., Mård, J., Weyrich, P., and Di Baldassarre, G.: Exploring Changes in Hydrogeological Risk Awareness and Preparedness over Time: A Case Study in North-eastern Italy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2549, https://doi.org/10.5194/egusphere-egu2020-2549, 2020.

Riverine flooding associated with landfalling tropical cyclones (TCs) in the Western North Pacific basin is responsible for some of the most severe socioeconomic losses in East Asian countries. However, little is known about the spatial and temporal patterns of TC flooding and its synoptic controls, which constrain predictive understandings of flood risk in this highly populated region. In this study, we investigate hydrology, hydrometeorology, and hydroclimatology of riverine flooding over China induced by landfalling tropical cyclones, based on empirical analysis of dense networks of stream gauging and rainfall stations as well as downscaling simulations using the Weather Research and Forecasting (WRF) model driven by 20th Century Reanalysis fields. The most extreme floods in central and northeastern China are associated with TCs despite infrequent TC visits in these regions. Inter-annual variations in TC flooding demonstrate a mixture of climate controls tied to surface temperature anomalies in central tropical Pacific, western North Pacific and north Atlantic. We implement numerical modelling analysis of typhoon Nina (1975), typhoon Andy (1982) and typhoon Herb (1996) to further shed light on key hydro-meteorological features of landfalling TCs that are responsible for severe flooding over China. We highlight the important role of interactions of storm circulations with mid-latitude synoptic systems (e.g., upper-level trough) and complex terrains in producing extreme rain rates and flooding. Analytical framework developed in this study aims to explore utilization of hydro-meteorological approach in flood-control engineering designs by providing details on the key elements of flood-producing storms. We also highlight potential challenges of developing predictive tools of TC flood risk in east Asian countries.

How to cite: Yang, L., Liu, M., Wang, L., Ji, X., Li, X., and Hou, A.: Riverine Flooding and Landfalling Tropical Cyclones over China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3251, https://doi.org/10.5194/egusphere-egu2020-3251, 2020.

Cities are increasingly vulnerable to extreme hydro-meteorological disasters, like rainfall-generated flooding. The urban floods lead to devastating damage to property and loss of human life. Extreme storms, which is the major trigger of urban flooding, thus need to be carefully examined. Our previous studies have found an increase of large rainfall intensity and variability in Shanghai City, China. In this study, we will further explore: 1) the change of spatio-temporal heterogeneity and frequency of extreme storms over decades; 2) the association between urbanization and these changes. We first extract the extreme storm catalogs for various time scales. The characteristics of space-time structure of storms in these storm catalogs are examined by using spatial analysis methods. The interannual variation of rainfall space-time structure are investigated. By using the strategy of Stochastic Storm Transposition (SST), extreme storm frequencies are generated. Various storm frequencies with different storms catalogs are then compared to show the change of magnitude of extreme storms frequencies. The correlation between the process of urbanization and the change of extreme storms is analyzed from the statistical perspective. From these results, we will have a clearer understanding of urban extreme storms and provide important implementations for assessment of flood risks in urban areas.

How to cite: Zhou, Z., Zhuang, Q., and Liu, S.: The analysis of heterogeneity and frequency of extreme storms under urban settings: A case study in Shanghai City, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3301, https://doi.org/10.5194/egusphere-egu2020-3301, 2020.

Urban pluvial floods are increasingly recognized as a ubiquitous hazard. They are caused by short and intense rainfall, followed by rapid runoff concentration. But while flood hazard maps for rivers have been widely implemented under the EU Flood Directive, corresponding efforts for pluvial flooding are rare, yet: pluvial floods are not to the existence of a river channel. They could occur anywhere, subject to the existence of minimal areas for surface runoff generation and concentration. That concentration could be dominated by small features of urban landscapes, which makes identification of flow paths uncertain even with highly-resolved digital elevation models (DEM) and full hydrodynamic simulations (which are computationally expensive). At the same time, sub-surface sewer and drainage systems – an additional complication in an already complex environment – will typically be subject to overcharge for extremely heavy rainfall events. That, however, allows us to focus on the surface in order to assess the hazard from such events. In the present study, we present a low-(computational)-cost approach to identify areas at risk of pluvial flooding. Common GIS operations are used to detect flood-prone depressions from a high-resolution 1m x 1m DEM, identify contributing watersheds, and represent runoff concentration by a fill-spill-merge approach. The approach is applied to a study area in Berlin, which has been repeatedly subject to pluvial flooding in the past years.

How to cite: Seleem, O., Heistermann, M., and Bronstert, A.: Pluvial flooding in urban areas: Parsimonious hazard mapping for a case study in Berlin, Germany, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5322, https://doi.org/10.5194/egusphere-egu2020-5322, 2020.

Increasing water demand and climate change poses a great challenge in managing water resources availability. Reservoir operation during heavy rainfall events in an urbanized region is crucial in terms of decision making. The objective of this study is to assess the significance of reservoir operation during extreme rainfall events on flood mitigation and future domestic water supply. One of the major water supply reservoirs in Chennai city was chosen for this study. Rainfall record of recent four decades were analyzed and a major flood event occurred in 2015 was chosen. A combined model of hydrologic-hydraulic processes was carried out using Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) and a box model based on input-output parameters. These models were calibrated and validated with historical flood events with good performance indications. Four different scenarios were framed for the analysis by targeting reduction in outflow and higher storage in the end of the event. Reducing the reservoir storage in advance and releasing with its maximum capacity at the beginning of the event will reduce the outflow from 5 to 27% and increase the time to peak by 11 to 16 hours. Available hydraulic facilities for higher storage at the end of the event were analyzed. It reveals that with the available facilities, reducing the initial storage from 75 to 50% will help to store 27 to 40% of inflow at the end of the event. Whereas the available hydraulic facilities will not allow to have a 75% of the reservoir storage at the end of this event. New gates can be provided for the safe operation during extreme rainfall events associated with the higher initial storage in the reservoir. Increased storage capacity combined with additional provisions of gates will reduce the outflow by 30% and increase the time to peak by 20 hours with the actual condition. By adapting these reservoir operation strategies, flood mitigation and fresh water augmentation during extreme events can be achieved to a significant extent. The developed combined modelling approach can be used to simulate various combinations of reservoir operations to assess the significance of timely decision on release during extreme rainfall events.

Keywords: flood mitigation, reservoir operation strategies, urban water supply, modelling

How to cite: Panchanthan, A., La Rocca, M., and Lakshmanan, E.: Significance of reservoir operation during extreme rainfall event in flood mitigation and water demand management in a metropolitan city of India: a case study , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6409, https://doi.org/10.5194/egusphere-egu2020-6409, 2020.

Despite the recent advances in technology and infrastructure, extreme flood events continue to induce a significant number of fatalities across the globe, hurting particularly flash flood-prone and other vulnerable communities. The vulnerability of individuals to flooding has been studied in numerous previous works that examine various demographic and situational factors and their relation to the risk that floodwaters pose to individuals or more broadly, their association with flood mortality.

In an effort to provide a better understanding of how flood fatalities occur and how we can prevent them, this work focuses on the influence of the surrounding environment and victims’ behaviour during fatal incidents. The study exploits a database of flood fatalities for Greece (1960-2019) and examines statistical correlations between different elements, including the victims’ age and gender, their activity, the immediate surroundings and the environment that the incidents occur, as well as victims’ behaviour on the basis of their actions.

With respect to the surrounding environment, results indicate that particular characteristics of fatalities differ considerably depending on the setting. Outdoor, vehicle-related deaths are more abundant in rural settings, in which victims show mostly an active (risk-taking) behaviour towards floodwaters. Urban environments are characterized by larger numbers of indoor deaths (especially for the elderly) and a wider diversity of victim activities. Overall, analysis indicates that dangerous situations tend to develop differently between urban and rural settings.

With regard to victim behaviour, analysis of the database shows a great diversity of motivations behind their actions at the time of fatal incidents. A study of these motivations indicates that an overwhelming majority of flood victims come in contact with floodwaters deliberately, while they are in an initial position of safety. On the contrary, a smaller percentage of victims (close to one quarter) exhibits behaviours that can be characterized as passive, such as getting trapped inside buildings or being unable to flee danger, highlighting a population with particular vulnerability characteristics. Furthermore, victim behaviour was found to be strongly connected to victim demographics and surroundings, to an extent that it can be predicted with a high degree of certainty (i.e. close to 90%) by means of a statistical model.

The analysis provides insights useful to further understand the vulnerability of the population to flooding, in terms of how dangerous situations develop. The findings can be exploited in shaping policy and education programs that aim to mitigate risk of fatal incidents to specific population groups (e.g. vehicle-occupants, individuals with mobility impairment). Through better-targeted initiatives, these insights have the potential to enhance the overall resilience of communities, especially in flood-prone areas.

How to cite: Diakakis, M.: The role of victim’s behavior and surrounding environment in the vulnerability of individuals in flood fatality incidents. Findings from Greece, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8664, https://doi.org/10.5194/egusphere-egu2020-8664, 2020.

Recently, interested in LID and GI has been increasing for sustainable development. Rain water harvesting system is commonly used in various type as a form of low impact development. This study introduces a rain barrel sharing network, which is a connected system through water-sharing among individual RWHS users. In this study, we developed an evaluation procedure for the reliability, resiliency, and vulnerability of a RBSN based on a SRY relationship. The preliminary result shows that reliability and vulnerability increased with all the users connected. However, resiliency is degraded as the degree of sharing increases. Based on this, we analyzed the benefit from a RBSN with 73 observing data and RCP scenarios in South Korea and investigated the regional characteristics of benefits from the RBSN. The potential benefit from a RBSN implies the important role of social practices under water scarcity and extreme hydrologic events with climate change.

How to cite: Kwon, Y. J. and Seo, Y.: Evaluation of a rain barrel sharing network for sustainable water management, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13300, https://doi.org/10.5194/egusphere-egu2020-13300, 2020.

Climate models have not achieved a consensus about the future trend of long-term average of precipitation. As well as, the future trend of extreme values (including both extreme, droughts and heavy events) has higher uncertainties, because are unusual events. The Colombian territory is permanently in risk due to precipitation climatic extremes: during El Niño years, the rain amounts are severely reduced, consequently the rivers flow and the water resource availability; nevertheless, during La Niña years, floods and landslides events are common, because the rain is excessive.

The precipitation extremes are affected due to long-term trends and the inter-annual variability represented by El Niño/La Niña cycle, then conduct this study is relevant. The selected study area is the Colombian territory. A Satellite Rainfall Estimate (SRE) was used to ensure a whole spatial coverage. The SRE has a daily temporary resolution, then it is suitable for building the selected Extreme Precipitation Indices (EPI). Statistical tests were carried out to verify the long-term change of EPI. The hydrological years were discriminated according to the ENSO, in order to perform a statistical test to probe the hypothesis that EPI, during these particular years (El Niño/La Niña), belong to probability distributions different from that distribution of EPI in “normal” years.

Mean annual precipitation in the Andean region drops in El Niño years, and it increases in La Niña years. In the Colombian Pacific basin, the number of wet days is reduced by the long-term trend, but the variable is not affected by the ENSO phenomena. However, in the Andean region and the eastern plains, El Niño has a high effect on reducing the number of wet days. Finally, extreme events are affected by both the long-term trend and the ENSO phenomena too; however, the change spatial distribution reveals a high impact on the Andean region.

How to cite: Giraldo-Osorio, J. D., Trujillo-Osorio, D. E., and Báez-Villanueva, O. M.: Changes and variability of extreme precipitation index in Colombia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18468, https://doi.org/10.5194/egusphere-egu2020-18468, 2020.

This study evaluates relative performances of different statistical algorithms to enhance radar-based quantitative precipitation estimation (QPE) accuracy using rain gauge network data. Initial investigations are implemented using observations obtained via 17 C-band radars located over different regions of Turkey. It was observed that there is an underestimation problem in radar estimations compared with the ground observations. According to the initial results, daily mean bias for radar estimations over different precipitation events is about -1.4 mm/day in average. Implemented statistical methodologies include Mean Field Bias (MFB), Local Multiplicative Bias (LMB), Local Additive Bias (LAB), Local Mixed Bias (LMIB), Multiple Linear Regression (MLR) adjustment, and Cumulative Distribution Function (CDF) Matching techniques. To test the performance of these algorithms, cross-validation methods have been used. In cross-validation, 50%, 25%, 12.5% of the station-based observations are excluded for validation while the remaining are used for the calibration in different experiments. Both the calibration and validation results obtained from all rainfall events of 2017 suggest that LMB and LAB adjustment methods perform better  both in terms of compensating the underestimation and decreasing the RMSE values. Primary results show that methods mentioned help reduce the underestimation problem by increasing the daily mean error from -1.4 mm up to -0.4 mm and decreasing the daily RMSE values from 6.2 mm/day to 0.80 mm/day in rainy days in average. Despite the fact that proposed time-independent MLR and CDF methods are shown to be compensating a large portion of radar precipitation underestimation (according to the initial results, from -1.4 mm/day into -0.5 mm/day in average), estimations obtained from these methods have higher uncertainties in estimating the precipitation amount especially in areas with higher probability of convective precipitation type (no significant increment in RMSE values). By utilizing the best methods among all bias adjustment methods, a high-resolution composite radar-based precipitation map of Turkey is currently being produced. For validating the final product, three independent networks of collocated rain-gauges will be used. Similar results are being expected from the final validation process. Nevertheless, the outputs of this validation process will help understand the relative performance of the bias correction algorithms in the areas with overlapping radar estimations.

Keywords — Merging, radar precipitation estimation, gauge adjustment

How to cite: Patakchi Yousefi, K., Yılmaz, M. T., Öztürk, K., Yücel, İ., and Yılmaz, K. K.: Production of a High-Resolution Improved Radar Precipitation Estimation Map Using Gauge Adjustment Bias Correction Methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18780, https://doi.org/10.5194/egusphere-egu2020-18780, 2020.

The Intensity-Duration-Frequency (IDF) curves are crucial for urban drainage design and to mitigate the impact of extreme precipitation events and floods. However, many regions lack a high-density network of rain gauges to adequately characterise the spatial distribution of precipitation events. In this work we compute IDF curves for the South-Central Chilean region (26-56°S) using the latest version of the Integrated Multi-satellitE Retrievals for GPM (IMERGv06B) for 2001-2018, with a spatial resolution of 0.10° and half-hourly temporal frequency.

First, we evaluated the performance of IMERGv06B against 344 rain gauge stations at daily, monthly and annual temporal scales using a point-to-pixel approach. The modified Kling-Gupta efficiency (KGE’) and its components (linear correlation, bias, and variability ratio) were selected as continuous indices of performance. Secondly, we fit maximum precipitation intensities from 14 long-term rain gauge stations to three probability density functions (Gumbel, Log-Pearson Type III, and GEV II) to evaluate: i) the impact of using 15-year rainfall time series in the computation of IDF curves instead of using the typical long-term periods (~ 30 years); and ii) to select the best distribution function for the study area. The Gumbel distribution was selected to obtain the maximum annual intensities for each grid-cell within the study area for 12 durations (0.5, 1, 2, 4, 6, 8, 10, 12, 18, 24, 48, and 72 h) and 6 return periods (T=2, 5, 10, 25, 50, and 100 years).

The application of the Wilcoxon Mann-Whitney test indicates that differences between IDF curves obtained from 15 years of records at the 14 long-term rain gauges and those derived from 25 years of record (or more) are not statistically significant, and therefore, 15 years of record are enough (although not optimal) to compute the IDF curves. Also, our results show that IMERGv06B is able to represent the spatial distribution of precipitation at daily, monthly and annual temporal scales over the study area. Moreover, the obtained precipitation intensities showed high spatial variability, mainly over the Near North (26.0-32.2°S) and the Far South (43.7-56.0°S). Additionally, the intensities from Central Chile (32.2-36.4°S) to the Near South (36.4-43.7°S) were systematically higher compared to the intensities described in older official governmental reports, suggesting an increase in precipitation intensities during recent decades.

How to cite: Zambrano-Bigiarini, M., Soto Escobar, C., and Baez-Villanueva, O. M.: Spatially-distributed IDF curves for Center-Southern Chile using IMERG, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21091, https://doi.org/10.5194/egusphere-egu2020-21091, 2020.

Flood risk in Italy is a wide-spread and never-ending issue. Traditional flood defense focused on making the river system “resistant” to flood events, possibly by flood-control structures including floodwalls, levees, dams and channels. These actions reduce the frequency of inundations, but they do not affect flooding effects, and associated impacts once the flood plain is inundated. In facts, structural flood defenses are designed and operated to accommodate floods not exceeding a given magnitude, as fixed by the original design. Thus, these engineering works are highly inefficient to cope with capacity-exceeding floods, the magnitude of which was fixed many years ago using poor data sets, and it is expected to increase with climate changes.

FLORIMAP (Smart FLOod RIsk MAnagement Policies), a project funded by Fondazione CARIPLO aims to revalue extreme floods distribution in the different homogeneous areas of northern Italy using regional approaches based upon recent data form the last three decades.

FLORIMAP will first cover open issues associated with the quantification of flood hazard and inundation risk, then it will assess human exposure and vulnerability, and combine these issues with strategies of communication and risk management, because risk communication is an important activity that can influence the flood risk management. Communication is the bridge between the technical and professional community, decision makers, elected officials, funding sources, and the public at large. The literature on risk communication and perception has highlighted that the understanding of the psychological perception of environmental risk is a crucial factor in order to foster the community resilience and to promote adaptive attitudes and behaviors.

Here, we present a preliminary assessment of updated extreme values distribution for the case study of Northern Italy hydrologically homogeneous regions. The results will be then compared against those obtained with previous dataset dating until 1970, to study the evolution of flood hazard and inundation risk under recent climate change. We then provide application of flood hazard, and risk for a case study area, and demonstrate modified hazard under recent climate change.

We then discuss implications for risk communication in the target areas, and provide suggestions for prosecution of the FLORIMAP project. 

How to cite: Galizzi, M., Rosso, R., and Bocchiola, D.: Extreme floods value distributions under recent global warming in Northern Italy, and new risk management policies. The project FLORIMAP, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22352, https://doi.org/10.5194/egusphere-egu2020-22352, 2020.

Many physically based models aiming to quantify the vulnerability and risk of hydrologic and geomorphic hazards need as input or forcing time series of processes such as precipitation, temperature, humidity, etc. The reliability of their output depends on how realistic the inputs are. CoSMoS is a multi-platform software that generates reliable time series from hydroclimatic variables (precipitation, temperature, wind, relative humidity, streamflow, etc.). It is developed in R (version 2.0) as well as in other platforms (Matlab, Mathematica, Excel). It can be used to generate univariate and multivariate time series at any time scale by reproducing the marginal distributions and the linear correlation structures (including intermittency) of the process under investigation. CoSMoS implements a unified stochastic modelling scheme that expands and enhances a generic modelling approach based on the transformation of “parent” Gaussian time series. By design it aims to offer a simple and easy-to-apply solution to the user requesting minimal information, such as the target marginal distribution and the correlation structure. The software is accompanied by a complete users’ manual.

How to cite: Papalexiou, S. M., Strnad, F., Markonis, Y., Serinaldi, F., Rajulapati, C. R., Hobbi, S., and Hanel, M.: CoSMoS v2.0: Making Time Series Generation Simple, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22357, https://doi.org/10.5194/egusphere-egu2020-22357, 2020.