Floods are one of the most relevant natural hazards, causing significant socio-economic damage every year globally. They will likely continue to increase for various reasons: the climate and global changes, two relevant ones. More importantly, our still limited capability to predict river response to flooding and anticipate the consequences by designing proper and sustainable risk mitigation measures. A recent example was Europe's floods in July 2021, the highest recorded. They led to many casualties and economic losses (i.e., 180 fatalities and billions of Euros). Extreme long, high-intensity rainfall resulted in extreme flows, particularly in small tributaries, but this could not solely explain the devastating impacts. Geomorphological changes, bank erosion and channel widening, sediment erosion and transport, and uprooted and transported trees and instream large wood accumulated at bridges played a significant role. However, these cascade processes are rarely quantified or considered in flood hazard and risk analysis. This is the focus of this talk. Case studies showing a combination of modelling approaches will illustrate how quantifying the supply and transport of instream large wood is essential in river reaches crossing infrastructures like bridges to assess flood-related hazards and risks.

How to cite: Ruiz-Villanueva, V.: Cascading flood hazards: the role of large wood transport, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10255, https://doi.org/10.5194/egusphere-egu23-10255, 2023.

In the Northeastern U.S., the most costly damages from intense storm events were impacts to road-stream crossings.  In steep post-glacial terrain, erosion by floodwater and entrained sediment is the largest destructive force during intense storms, and the most likely driver of major morphological changes to riverbanks and channels.  Steam power analysis is a tool that can successfully quantify floodwater energy that caused damages, however, prediction of which reaches or watersheds may experience future impacts remains uncertain. Downstream, in urban areas, floodwaters increasingly occupy larger geographic extents that spill well beyond traditionally mapped flood and hazard zones. Limiting these maps are critical biases: Often more information is available for coastal and urban areas (missing steeper terrain geomorphic hazard zones), base functional assumptions (that flood risk is dominantly inundation risk from a specific depth of water, ignoring the force of moving water, sediment or erosion), their concentration around the highest-value infrastructure (lower-value and lower-density development or undeveloped areas have little or no map coverage) and how these maps are utilized for regulatory purposes (e.g. mortgage and insurance requirements). Compounding the physical destruction of flooding is the unequal distribution of these impacts on socially vulnerable populations that are least able to recover from them.  We strive to improve the co-generated mapping of social vulnerability and flood risk by (1) utilizing measures of social vulnerability with greater social and geographical insight and nuance, including self-organizing maps (SOM) that cluster overlapping metrics, (2) applying modified flood hazard maps that accurately represent fluvial geomorphic hazards, urban flooding hazards, and climate change considerations, and (3) overlapping these to understand what factors influence current maps and policy practice; what populations and places may be overlooked or under-resourced relative to vulnerability; and use this collective insight to help inform and develop improved map products and policy approaches.  Integration of this information directly with practitioners’ resources allows communities to prioritize and make land-use decisions and flood-response and preparedness decisions that are informed by the specific vulnerabilities of their populations as well as the fluvial geomorphic workings of the larger watershed, and that have powerful local implications.  Outreach and educational programs focused on social vulnerability and fluvial systems for river practitioners and politicians at all levels align communities’ attitudes about flooding and rivers can ultimately result in ecologically sound, socially just, and more flood resilient policies and practices.

How to cite: Hatch, C., Salap-Ayca, S., Guzman, C., and Vogel, E.: A just map: community and fluvial science working together for flood hazard vulnerability mapping in Massachusetts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17047, https://doi.org/10.5194/egusphere-egu23-17047, 2023.

Flood events are among the most damaging natural disasters, with billions of people being directly exposed to the risk of intense flooding worldwide. The economic and societal consequences of these events are expected to increase in the coming years. Flood societal risk can be determined by analyzing the relationship between the frequency of fatal flood events and the magnitude of the resulting consequences to the population (evaluated by the number of fatalities due to the event). Here, we test an approach previously proposed for landslides to estimate the flood societal risk in Italy, using historical sparse data on flood fatalities, available through national catalogues. Such an approach is based on the use of the Zipf distribution, which has previously been widely adopted for the modeling of societal risk for different natural hazards. The model allowed the evaluation of the spatial and temporal distribution of societal flood risk over the Italian territory over a regularly spaced grid. Different risk scenarios are presented and discussed.  

How to cite: Yazdani, M., Salvati, P., Rossi, M., Bianchi, C., and Guzzetti, F.: Societal Flood Risk in Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7772, https://doi.org/10.5194/egusphere-egu23-7772, 2023.

Flood risk assessments are an important basis for risk management. For larger regions, these assessments are often based on small-scale modelling, which is subsequently compiled into a large-scale picture. However, this approach neglects spatial interactions, such as decreasing risk due to upstream dike breaches, and does not provide realistic risk statements for larger regions. This paper presents the ‘derived flood risk analysis’ as an alternative approach and its implementation for Germany. A model chain consisting of hydrological, hydraulic, and damage models simulates the occurrence of extreme runoff, inundation, and direct economic damages. This model chain is driven by a weather generator that provides spatially consistent fields of climate variables. The generation of very long (several thousand years) time series with daily resolution allows the estimation of extreme runoff and corresponding damages. The consideration of the spatial relations in all model components, from the weather generator to the damage model, is able to provide consistent large-scale risk statements. This avoids the significant overestimates typical of many large-scale flood risk assessments.

How to cite: Merz, B., Farrag, M., Guan, X., Guse, B., Han, L., Kreibich, H., Nguyen, D., Sairam, N., Schröter, K., and Vorogushyn, S.: Spatially consistent flood risk assessment for Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11966, https://doi.org/10.5194/egusphere-egu23-11966, 2023.

Characterizing the upper tail of flood peak distributions remains a challenge due to the elusive nature of extreme floods, particularly the key elements of flood-producing storms that are responsible for them. Here I examine the upper tail of flood peaks over China based on a comprehensive flood dataset that integrates systematic observations from 1759 stream gaging stations and 14,779 historical flood surveys. I show that flood peak distributions over China are associated with a mixture of rainfall-generation processes. The storms responsible for the upper-tail floods (with the recurrence intervals beyond 50 years) are characterized with anomalous moisture transport and/or synoptic configurations, with respect to those responsible for annual flood peaks. Anomalous moisture transport (in terms of intensity, pathways, and durations) dictates the space-time rainfall dynamics (relative to the drainage networks) that subsequently lead to anomalous basin-scale flood response. I provide physical insights into extreme flood processes based on downscaling simulations using the Weather Research and Forecasting model driven by the 20^th Century Reanalysis fields. Modeling analyses for a collective of extreme flood events highlight the role of interactions between complex terrain and large-scale environment in determining the spatial and temporal variability of extreme rainfall. My analyses contribute to improved understanding of the unprecedented flood hazards over China by establishing the nexus between atmospheric processes and basin-scale flood response. These knowledge gains can be potentially used to the upper tail of flood peak distributions.

How to cite: Yang, L.: Hydrometeorological processes and controls of the upper-tail floods over China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10453, https://doi.org/10.5194/egusphere-egu23-10453, 2023.

In a world of increasing global flood hazards, vulnerable populations (very young and elderly) are disproportionately affected by flooding due to their low self-reliance, weak political voice and insufficient inclusion in climate adaptation and emergency response plans. These individuals account for most flood casualties and often rely on emergency services due to flood-induced injuries, exacerbated medical conditions, and requiring evacuative assistance. However, emergency service demand often exceeds the potential capacity whilst flooded roads and short emergency response timeframes decrease accessibility, service area, and population coverage; but how does this compare across the globe and what will the future hold?

To answer this question, a global analytical framework has been created to determine the spatial, temporal, and demographic variability of emergency service provision during floods. This is based on global fluvial and coastal flooding (at 10-year and 100-year return periods), and present and future flood conditions (present-day and 2050, under RCP 4.5 and RCP 8.5 climate scenarios). The framework includes an accessibility analysis to identify emergency service accessibility to vulnerable populations based on restrictions of flood barriers and response-time frameworks, a vulnerability analysis to compare the difference in emergency service provision between key demographic groups, and a hotspot analysis to identify the extent and distribution of flood hazards and at-risk vulnerable populations.

Research findings include the identification that (based on the scenario of 2050 riverine flooding at a 100-yr return period under RCP8.5 and a 30-minute response time):

• Globally, 64% of schools are always accessible to the ambulance service and 56% of schools are always accessible to the fire service
• Globally, 29% of schools are never accessible to the ambulance service and 38% of schools are never accessible to the fire service.
• Globally, approximately 20% fewer people are accessible to emergency services than under non-flood conditions.
• Africa and Asia experience the greatest accessible population reductions (14-27% and 24-25%) whilst Europe experiences the least accessible population reductions (8-9%).
• Priority hotspot countries are primarily located in central North America (e.g., Belize), northern South America (e.g., Guyana) and west-central Africa (e.g., Liberia).

The highlighted geographical and temporal differences in emergency service provision globally and between regions, in addition to the framework itself, can be used by national and international organisations to inform strategic planning of emergency response operations and major investments of infrastructure, services, and facilities to maximise the benefit to the disproportionately affected vulnerable populations. This includes the production of more detailed flood hazard and evacuation maps that highlight vulnerability hotspots, the prioritisation of vulnerable population groups in emergency response plans to minimise geographic and population disparities of flood injuries and fatalities, and the allocation of emergency service hubs in regions of high vulnerability but low emergency response provision.

How to cite: Johnson, S., Wilby, R., Yu, D., and Matthews, T.: Global analysis of emergency service provision to vulnerable populations during floods of various magnitude under climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6689, https://doi.org/10.5194/egusphere-egu23-6689, 2023.

The concept of return period (recurrence interval) of extreme events is widely used in engineering practice and in the media. In engineering design and risk assessment, the concept of return period is used to determine the expected magnitude(s) of one or more extreme weather events – i.e., the expected magnitude of an event that, if occurred, might cause the failure of a structure. In the media, the concept of return period is used to communicate to the general public the severity of an event. For example, the 2021 summer flood in Northwestern Europe was reported in the news as a one-in-400-year event – an event expected on average once in 400 years. The strength of return period as a metric (in years) to describe the severity of events resides in the straightforward comparison between the average occurrence in years of an event with the average number of years a person can experience and recollect events.

Generally, the return period of a rare event and its magnitude (known as return level) is inferred from limited observations - often derived by extrapolating from a distribution function fitted to the available observations. The distribution is often greatly influenced by the length of observations. These factors make the concept of return period prone to misinterpretation as extreme events are rarely observed in existing records.

Here we provide a new perspective on the return period of extremes determined not only by its exceedance probability but also in relation to the observations used to describe the underlying distribution. Our method offers a straightforward metric, independent of the type of statistical distribution adopted, to quantify and communicate the likelihood of having observed the event of interest in the available observations, ranging from unlikely to very likely. This metric can provide a measure of confidence in the statistical inference of return periods based on the length of record used for inference. We argue that this additional information on likelihood offers important information for designers, planners, and decision-makers.

How to cite: Ragno, E. and AghaKouchak, A.: Communicating the return period of extremes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12932, https://doi.org/10.5194/egusphere-egu23-12932, 2023.

Flash droughts are generally considered a subset of seasonal drought events. In the present study, we have characterized the flash drought events based on soil moisture index (SMI) using daily ERA5 reanalysis data having a spatial resolution of 0.25⁰ * 0.25⁰ from 1960 till 2021. Flash drought events were identified when SMI drops below the 20^th percentile within less than 3 next pentads, and it terminates when SMI goes above the 20^th percentile and stays there for the next 2 pentads. Flash drought time series was prepared and the Mann-Kendall trend test was applied to investigate the evidence of the statistically significant trends. To assess the atmospheric drivers (precipitation, PET) of flash drought, standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI) were calculated during the occurrence of each flash drought event at each grid pixel. For calculating SPI and SPEI, ERA5 reanalysis data of precipitation and PET (potential evapotranspiration) was used. Seasonal analysis of results showed that the flash drought frequency observed during the pre-monsoon season (March-April-May) shows considerable variation when compared to the monsoon (July-August-September) and post-monsoon (October-November-December) seasons. Results of Mann-Kendall statistics show the increasing trend of flash drought over semi-arid regions like Marathwada and Vidarbha. Both SPI and SPEI shows spatially varying similarity with the flash drought events. When observed on a seasonal scale, it is observed that SPEI shows a higher degree of similarity with flash drought events during pre-monsoon season as compared to SPI as evaporative demand is high during this period.  

How to cite: Remesan, R. and Pachore, A.: Analysis of Spatio-temporal variability and atmospheric drivers of the flash drought over Godavari river basin., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15836, https://doi.org/10.5194/egusphere-egu23-15836, 2023.

Over the past six years, Australia has experienced significant fluctuations in rainfall, including prolonged dry conditions and extensive bushfires, followed by two consecutive years of heavy rainfall in the east. Could such anomalies be predicted many years in advance is the question this study hopes to answer. A prediction framework that combines empirical and physically-based approaches using CMIP decadal prediction, and a novel spectral transformation approach is presented. When tested in a hindcast experiment, this framework shows significant prediction skill for rainfall up to five years in the future across all regions and climate zones in Australia. This framework was used to project from 2018 to 2022, covering the years of bushfires and extreme floods in Australia, as an added blindfolded validation of the prediction approach used. Following this, a blind projection of the precipitation anomalies over the continent for the coming five years is presented, to assess whether the anomalies for the past five years were, indeed, anomalies, or part of a pattern of what can be expected into the future. It is shown that this decadal framework has great potential for predicting whether the next few years will be wetter or drier, extending the predictive accuracy beyond a few months into the future. This can be valuable for managing water resources, prioritizing demands, protecting vulnerable systems, and reducing uncertainty in hydrological decision-making.

How to cite: Jiang, Z., Choudhury, D., and Sharma, A.: Could the 2019-20 Australia bushfires or 2020-22 floods be predicted using CMIP decadal prediction?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10096, https://doi.org/10.5194/egusphere-egu23-10096, 2023.

Five CMIP6 models were selected to project changes in rainfall erosivity of China for two future periods (the near-term in 2041-2065, the long-term in 2076-2100) under SSP1-RCP2.6 and SSP5-RCP8.5 scenarios. Models’ capacity in estimating two erosivity indices, annual average rainfall erosivity (R-factor) and the storm erosivity at 10-year return level (10-year storm EI) were evaluated by comparing the model derived indices for the historical period with the state-of-the-art reference erosivity maps of China interpolated with hourly observations. Results show that GFDL-ESM4, IPSL-CM6A-LR, and UKESM1-0-LL outperform the other two models with higher NSEs and better spatial correlation, especially in the water erosion regions. R-factor and 10-year storm EI estimated using MMEs (the arithmetic means of the aforementioned three models) for the historical period are generally underestimated, and the median biases are 0.80 and 0.66, respectively. Biases for each grid were determined as the bias-correction factors for future erosivity projection. Generally, most areas in eastern and central China are expected to experience larger rainfall erosivity. Under SSP1-RCP2.6 and SSP5-RCP8.5 scenarios, R-factor over mainland China is projected to increase by 18.9% and 19.8% for the near-term and 26.0% and 46.5% for the long-term, respectively; and 10-year storm EI is projected to increase by 14.2% and 17.4% for the near-term, and 14.9% and 45.0% for the long-term, respectively. The projected increases in rainfall erosivity are mainly due to the increasing probability of extreme precipitation. This implies that soil and water conservation measures in China need to be further strengthened to meet the challenges brought by the increasing number and magnitude of extreme events in the context of global warming.

How to cite: Wang, W., Yin, S., He, Z., Chen, D., Wang, H., and Klik, A.: Projection of future rainfall erosivity over China under global warming, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16630, https://doi.org/10.5194/egusphere-egu23-16630, 2023.

Evaluating the characteristics of long-term dry and wet climate changes under the background of global climate change is important for regional water resources security, ecosystem security and socio-economic development. Based on the daily meteorological data of 1680 meteorological stations in China from 1971 to 2019, the reference evapotranspiration (ET₀) was estimated with the FAO-56 Penman–Monteith equation. Based on which, the temporal and spatial variations of humidity index (HI), precipitation (P), reference evapotranspiration (ET₀) and the driving factors of which were further analyzed. Results showed that HI significantly increased in the northwest China of arid area, the northeast China of subhumid area and the Huang-Huai region of humid area, while it significantly decreased in the southwest and southeast China of humid areas. The change of HI can be mainly attributed to the change of ET₀ while no significant trends has been detected for P for most regions of China. During the past 50 years, the increasing rate of ET₀ was 3.76 mm/10a. But the temporal variation of ET₀ are different from regions, and the increasing and decreasing area were mainly dominated by climate different factors. For region of Huang-huai and northern Northeast China, ET₀ showed significant downward trend. Among factors that relating to ET₀, wind speed contributes most to the significant decrease of ET₀. For all rest regions of China, ET₀ showed significant upward trends, and relative humidity contribute most to the increase.

Key words: Dry and wet climatic change, humidity index, reference evapotranspiration, contribution, climatic factors.

How to cite: Tang, J., Wang, W., and Xie, Y.: Dry and wet climatic change and its driving factors in China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16753, https://doi.org/10.5194/egusphere-egu23-16753, 2023.

In the hydraulic structures design against extreme events a proper estimate of the areal reduction factor (ARF) is required. Specifically, rainfall-runoff models widely used need to be fed with information on areal-average rainfall over a watershed surface, while rainfall data is typically available at a point scale. The ARF allows to convert rainfall data from point to areal scale.

In this work, a new fixed-area and deterministic approach for estimating the ARF is proposed; it involves ratios between observed annual maxima with specific duration of average rainfall occurring in a specific area and those referring to all the available point rainfalls in the same area. The approach was applied to the Umbria region in Central Italy where, using high-quality and validated rainfall data (with a temporal resolution of 1 minute), a parametric relation expressing ARFs as function of duration and area was found. The outcomes were then compared with those of the most widespread empirical approaches available in literature, often applied when rainfall data are lacking, obtaining substantial over- or underestimation of empirical ARFs. This confirms that the transposition of ARF relations from a geographic area to another could have not-negligible impacts on the design of hydraulic structures. In addition, indications aimed at selecting the most suitable method to be applied for ARF estimation are provided. Specifically, the proposed approach is suitable when a limited number of years of rainfall observations is available. In this regard, the robustness of the methodology was tested by varying the length of the rainfall observation period; a minimum number of about 6 years was found to make the derived empirical formulation sufficiently accurate in a specific area.

How to cite: Flammini, A., Dari, J., Saltalippi, C., and Morbidelli, R.: Areal reduction factor assessment for extreme rainfalls through a new empirical fixed-area formulation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7000, https://doi.org/10.5194/egusphere-egu23-7000, 2023.

Geo-hydrological hazards (landslides and floods) are often associated with significant damages on physical infrastructure like buildings and roads. Understanding the factors controlling the extent of damage is a prerequisite for quantitatively estimating risk and its spatial distribution, and advising on measures to reduce vulnerability. In this study we document the impact of 64 landslide and six flood events in four selected districts in western Uganda for the period May 2019 - March 2021 through extensive fieldwork. We quantify in economic value the physical damage of landslide and flood hazards on exposed buildings, roads and bridges. We then analyse the physical vulnerability based on damage ratios and determine the factors  (building material, hazard characteristics and age of the building) that control the degree of damage using fractional logistic regression. Out of the 91 buildings affected by landslides, 54% were totally destroyed, and only 10% not or minorly damaged, for an average damage cost of 3,179 USD/building. For the 212 documented buildings affected by floods, 35% were totally destroyed, 28% had severe to moderate damage and the rest were minorly or not affected, with an average damage costs of 1,755 USD/building. The physical vulnerability of buildings to landslides depends on the size of the landslide, age of the building, type of building wall material and the steepness of the slope cut to establish an artificial foundation platform. On the other hand, the physical vulnerability of buildings to flood hazards is largely controlled by the flood depth, the distance from the river channel, slope, size of flooded area and type of floor material. The physical vulnerability functions developed in this study are being used as a new inputs into a regional quantitative model of geo-hydrological risks. Combining the hazard estimates with the most accurate information on exposure of physical infrastructure, will facilitate the identification of the types of events and the locations that require most attention for risk reduction.

How to cite: Sekajugo, J., Kagoro-Rugunda, G., Mutyebere, R., Kabaseke, C., Mubiru, D., Namara, E., Kanyiginya, V., Bwambale, B., Jacobs, L. J., Dewitte, O., and Kervyn, M.: What controls physical vulnerability to geo-hydrological hazards? A contribution to quantitative assessment of landslide and flood risk in western Uganda, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4537, https://doi.org/10.5194/egusphere-egu23-4537, 2023.

In many mountain valleys, communities and infrastructure are exposed to high risks of damage due to debris fan aggradation. To assess such risks, two questions must be addressed: (1) What will be the extent and thickness of deposition over the fan for a given volume of debris delivered from the upstream catchment? (2) How large could debris flow volumes be for a single event or a sequence of events? In this contribution, we propose a methodology to address both questions. Its first component is a simplified model of debris fan morphology, based on assuming a fan-slope-distance relationship along paths affected by topographic obstacles like steep valley sides. Using a computationally efficient algorithm, this model can be used to reconstruct past fan volumes from terrace remnants resolved on high resolution DEM topography, and to simulate large numbers of possible future events. Its second component is a stochastic model for the evolution of fan volume framed as a form of random walk. To take into account the episodicity of debris delivery, we model this random walk as a gamma-subordinated Wiener process aka a variance-gamma process. To calibrate the model parameters, we exploit both short-term and long-term data: for the slope-distance relationship, topographic data from recent and Holocene debris-fan remnants; for the stochastic process parameters, reconstructed fan-volume changes associated with recent flood events and with older radiocarbon-dated fan surfaces. We illustrate the approach with an application to the Laonong River in southern Taiwan. In this valley, an important roadway link has been repeatedly damaged by debris-flow aggradation. To guide road and bridge reconstruction, it is essential to assess fan aggradation risk for different design alternatives on a decadal time scale or more. The model provides a basis for optimizing the layout and height of such infrastructure.

How to cite: Chiu, Y.-H., Stark, C. P., and Capart, H.: Modeling risk to infrastructure due to episodic debris fan aggradation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3734, https://doi.org/10.5194/egusphere-egu23-3734, 2023.

The Campania region, in Southern Italy, is affected by hundreds of wildfires every year, mainly during the summer season. Starting from the month of September, mountain watersheds including those hit by wildfires are impacted by even more frequent intense rainstorms. In such conditions, the high sediment availability, lack of recovered vegetation and a likely stronger soil water repellency increase the likelihood of surface runoff and soil erosion, leading to potential post-fire debris flows downstream.

This work provides information on more than 100 post-fire debris flows (PFDFs) that occurred in Campania between 2001 and 2021, with a particular focus on the triggering rainfall conditions. Rainfall measurements at a high temporal resolution (10 min) were gathered from a dense rain gauge network, with an average distance between sensors and PFDFs initiation areas of 2.6 km. Information on the occurrence of PFDFs was obtained from web news, social networks, and reports produced by the Fire Brigades. The collection of accurate information related to the debris flow timing and location allowed retrieving and analyzing properties of the triggering rainfall inputs, by identifying the minimum triggering conditions with rainfall thresholds. Moreover, to evaluate the temporal structure and type of the storms associated with the PFDFs (e.g., convective or frontal systems), the standardized rainfall profiles of the triggering events were defined. The return times of the peak cumulative rainfall of the bursts in 10, 20, and 30 minutes were also calculated.

Results show that the triggering rainfall events are very short (37 minutes on average), with high average intensity (73.2 mm/h and 49 mm/h in 10 and 30 minutes, respectively), and mostly associated with severe convective systems (i.e., thunderstorms). The estimated return times are quite low, with 75° percentiles of the related distribution ranging from 2.7 to 3.2 years, indicating that these rainfall events are neither rare nor extreme, as also observed by other authors worldwide. Differences are observed in return times and the spatial distribution of the events that occurred in July-September (higher rainfall magnitudes and longer return times) rather than in October-December. The time window in which PFDFs are more likely to occur in the study area has an extension of four months, from September to December. According to the defined triggering rainfall threshold, a rainfall of 11.4 mm in 30 minutes (corresponding to an average intensity of 22.8 mm/h) is likely sufficient to trigger a PFDF in the study area.

These research outcomes provide reliable and effective support to inform decision-makers engaged in hazard assessment and risk management, in order to implement suitable countermeasures in terms of monitoring and early warning systems. It is worth noting that PFDFs often occur in small-scale watersheds characterized by very short concentration times, in response to intense bursts of less than 60 minutes. This means insufficient lead time to fully develop an effective emergency response. This and other criticalities represent serious challenges requiring additional work.

How to cite: Gariano, S. L., Esposito, G., Masi, R., Alfano, S., and Giannatiempo, G.: Triggering rainfall conditions of post-fire debris flows in Campania, Southern Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1542, https://doi.org/10.5194/egusphere-egu23-1542, 2023.