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Estimating future short-duration extreme precipitation in mountainous regions is fundamental for risk management. High-resolution convection-permitting models (CPMs) represent the state of the art for these projections, as they resolve convective processes that are key to short-duration extremes. Recent observational studies reported a decrease in the intensity of extreme hourly precipitation with elevation. This “reverse orographic effect” could be related to processes which are subgrid even for CPMs. To quantify the reliability of future projections of extreme short-duration precipitation in mountainous regions, it is thus crucial to understand to what extent CPMs can reproduce this effect. Due to the computational demands however, CPM simulations are still too short for analyzing extremes using conventional methods. We use a non-asymptotic statistical approach (Simplified Metastatistical Extreme Value: SMEV) for the analysis of extremes from short time periods, such as the ones of CPM simulations. We analyze an ERA-Interim-driven Consortium for Small-Scale Modeling (COSMO-crCLIM, convection-resolving Climate Modelling) simulation (2000–2009; 2.2 km resolution), and we use hourly precipitation from 174 rain gauges in an orographically complex area in northeastern Italy as a benchmark. We investigate the ability of the model to simulate the orographic effect on short-duration precipitation extremes, as compared to observational data. We focus on extremes as high as the 20-year return levels. While overall good agreement is reported at daily and hourly duration, the CPM tends to increasingly overestimate hourly extremes with increasing elevation, implying that the reverse orographic effect is not fully captured. These findings suggest that CPM bias-correction approaches should account for orography. SMEV's capability of estimating reliable rare extremes from short periods promises further applications on short-time-period CPM projections and model ensembles.

Recent tracer-based studies using stable isotopes of hydrogen and oxygen showed that different methods for extracting water from plant tissues can return different isotopic compositions due to the presence of organic compounds and because they extract different plant water domains. One of the most used methods to extract plant water is the cryogenic vacuum distillation (CVD), which tends to extract total plant water. Conversely, the Scholander-type pressure chamber (SPC), which is commonly used by tree physiologists to measure water potential in plant tissues and determine plant water stress, is expected to extract only the more mobile plant water (i.e., xylem and inter-cellular water). However, only few studies reported the application of SPC to extract plant water for isotopic analyses, and therefore, inter-method comparisons between SPC and CVD are of great value. In this work, we analyzed the variability in the isotopic composition of plant water extracted by SPC and CVD, also considering the potential variability in the isotopic signature of the plant water extracted by CVD from various tissues (i.e., leaves, twig without bark, twig with bark, twig close to the trunk of the tree, and wood core) and from different plant species (i.e., alder, apple, chestnut, and beech). The extraction of plant water by SPC is simple, can be carried out in the field, and it does not require specific laboratory work as in the case of CVD. However, the main limitation of SPC is the very small water volume that can be extracted from the lignified twigs under water stress conditions compared to CVD. Our results indicated that plant water extracted by SPC and CVD were significantly different. The difference in the isotopic composition obtained by the two extraction methods was smaller in the beech samples compared to alder, apple, and chestnut samples. The isotopic signature of alder, apple, and chestnut plant water extracted by SPC was more enriched in δ2H and δ18O, respectively, than the samples obtained by CVD. We conclude that plant water extraction by SPC is not an alternative for CVD as SPC mostly extracts the mobile plant water, whereas CVD tends to retrieve all water stored in the sampled tissue from both living and dead cells. However, studies aiming to quantify the relative contribution of the soil water sources to transpiration should rely more on the isotopic composition of xylem water (which is theoretically sampled by SPC) than the isotopic composition of total plant water (sampled by CVD), which also contains a fraction of water that could be stored in plant tissues for a longer time.

Scholars have unravelled the complexities and underlying uncertainties in coupled human and water systems in various fields and disciplines. These complexities, however, are not always reflected in the way in which the dynamics of human–water systems are modelled. One reason is the lack of social data time series, which may be provided by longitudinal surveys. Here, we show the value of collecting longitudinal survey data to enrich sociohydrological modelling of flood risk. To illustrate, we compare and contrast two different approaches (repeated cross-sectional and panel) for collecting longitudinal data and explore changes in flood risk awareness and preparedness in a municipality hit by a flash flood in 2018. We found that risk awareness has not changed significantly in the timeframe under study (1 year). Perceived preparedness increased only among those respondents who suffered low damage during the flood event. We also found gender differences across both approaches for most of the variables explored. Lastly, we argue that results that are consistent across the two approaches can be used for the parametrisation of sociohydrological models. We posit that there is a need to enhance the representation of socio-demographic heterogeneity in modelling human–water systems in order to better support risk management.

Private risk reduction behaviours can significantly reduce the negative impacts of flooding and flash floods. Over the past decades, researchers have used various socio-cognitive models or threat and coping mechanisms to explain individual protective behaviours. However, these models ignore the fact that people are not equally ready to act upon a danger, and they (the models) give limited insights into the effectiveness of communication strategies to foster risk reduction behaviours. Therefore, we explored the current state of homeowners' readiness to undertake risk reduction behaviours in flood risk areas by applying a dynamic protection motivation framework. We conducted a survey in an Italian municipality that experienced severe flash flooding in September 2018. The results show that people are motivated by different factors in prompting risk reduction behaviour based on their chosen types of protective measures. For example, people that undertook structural or avoidance measures are more likely to be motivated to protect themselves by increased perceptions of vulnerability and response efficacy and are less worried about expected flood losses compared to people that undertook only basic emergency measures. In this paper, we argue how these new insights contribute to targeting flood risk communication strategies to groups of individuals characterized by different readiness stages and motivations to protect themselves.

Enhanced temperature-index distributed models for snowpack simulation, incorporating air temperature and a term for clear sky potential solar radiation, are increasingly used to simulate the spatial variability of the snow water equivalent. This paper presents a new snowpack model (termed TOPMELT) which integrates an enhanced temperature-index model into the ICHYMOD semi-distributed basin-scale hydrological model by exploiting a statistical representation of the distribution of clear sky potential solar radiation. This is obtained by discretizing the full spatial distribution of clear sky potential solar radiation into a number of radiation classes. The computation required to generate a spatially distributed water equivalent reduces to a single calculation for each radiation class. This turns into a potentially significant advantage when parameter sensitivity and uncertainty estimation procedures are carried out. The radiation index may be also averaged in time over given time periods. Thus, the model resembles a classical temperature-index model when only one radiation class for each elevation band and a temporal aggregation of 1 year is used, whereas it approximates a fully distributed model by increasing the number of the radiation classes and decreasing the temporal aggregation. TOPMELT is integrated within the semi-distributed ICHYMOD model and is applied at an hourly time step over the Aurino Basin (also known as the Ahr River) at San Giorgio (San Giorgio Aurino), a 614 km2 catchment in the Upper Adige River basin (eastern Alps, Italy) to examine the sensitivity of the snowpack and runoff model results to the spatial and temporal aggregation of the radiation fluxes. It is shown that the spatial simulation of the snow water equivalent is strongly affected by the aggregation scales. However, limited degradation of the snow simulations is achieved when using 10 radiation classes and 4 weeks as spatial and temporal aggregation scales respectively. Results highlight that the effects of space–time aggregation of the solar radiation patterns on the runoff response are scale dependent. They are minimal at the scale of the whole Aurino Basin, while considerable impact is seen at a basin scale of 5 km2.

This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as the EuroMedeFF database) include (i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, (ii) the high space–time resolution radar rainfall estimates, and (iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km2), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in France, Israel, Italy, Romania, Germany and Slovenia, and constitutes a sample of rainfall and flood discharge extremes in different climates. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the identification and analysis of the hydro-meteorological causative processes, evaluation of flash flood hydrological models and for hydro-meteorological forecast systems. The dataset also provides a template for the analysis of the space–time variability of flash flood triggering rainfall fields and of the effects of their estimation on the flood response modelling. The dataset is made available to the public with the following DOI: https://doi.org/10.6096/MISTRALS-HyMeX.1493.

One common approach to cope with floods is the implementation of structural flood protection measures, such as levees or flood-control reservoirs, which substantially reduce the probability of flooding at the time of implementation. Numerous scholars have problematized this approach. They have shown that increasing the levels of flood protection can attract more settlements and high-value assets in the areas protected by the new measures. Other studies have explored how structural measures can generate a sense of complacency, which can act to reduce preparedness. These paradoxical risk changes have been described as levee effect, safe development paradox or safety dilemma. In this commentary, we briefly review this phenomenon by critically analysing the intended benefits and unintended effects of structural flood protection, and then we propose an interdisciplinary research agenda to uncover these paradoxical dynamics of risk.

Rainfall-induced debris flows in recently burned mountainous areas cause significant economic losses and human casualties. Currently, prediction of post-fire debris flows is widely based on the use of power-law thresholds and logistic regression models. While these procedures have served with certain success in existing operational warning systems, in this study we investigate the potential to improve the efficiency of current predictive models with machine-learning approaches. Specifically, the performance of a predictive model based on the random forest algorithm is compared with current techniques for the prediction of post-fire debris flow occurrence in the western United States. The analysis is based on a database of post-fire debris flows recently published by the United States Geological Survey. Results show that predictive models based on random forest exhibit systematic and considerably improved performance with respect to the other models examined. In addition, the random-forest-based models demonstrated improvement in performance with increasing training sample size, indicating a clear advantage regarding their ability to successfully assimilate new information. Complexity, in terms of variables required for developing the predictive models, is deemed important but the choice of model used is shown to have a greater impact on the overall performance.

Trying to obtain a more detailed understanding of the hydrological functioning of mountain catchments represents an important challenge in the effort of counteracting possible consequences of climate and land use change on water resources availability. Long-term ( 10 years) hydro-meteorological monitoring in small (typically 10 km2) experimental catchments constitutes a valuable tool to achieve these goal. One of these sites is the Rio Vauz Catchment (1.9 km2), in the Italian Dolomites, that represents an excellent example of long-term snowmelt-dominated catchment in Dolomitic regions. The strong elevation gradient of the Rio Vauz Catchment and the different physiographic properties of its nested subcatchments make this a unique site for investigating fundamental runoff generation mechanisms in mountain headwaters. In this work, we provide a review of physical processes that have been inferred from 12 years of hydrological monitoring in this catchment. We present the available dataset and summarize the main hydrological mechanisms that explain the internal functioning of the Rio Vauz Catchment, primarily focusing on three characterizing hydrological behaviours, namely thresholds, hysteresis and connectivity. The main control on surface and subsurface runoff threshold response is constituted by a combination of soil moisture antecedent conditions, rainfall amount and topography. Changes in hysteresis patterns (clockwise and anti-clockwise loops) between streamflow and soil moisture, water table depth and electrical conductivity were governed by distinct runoff generation processes and rainfall event characteristics. Hillslope-riparian-stream subsurface connectivity was controlled by antecedent wetness conditions and rainfall amount. The composition in environmental tracers (stable isotopes of water and electrical conductivity) in different water sources and the application of tracer-based mixing models helped to distinguish the geographical sources to runoff and to quantify the role of rainfall and snowmelt in streamflow. Finally, we define a perceptual model of runoff generation processes for dry and wet conditions that can be considered representative for many mountain headwater catchments in the world.

The systematic underestimation observed in debris flow early warning thresholds has been associated with the use of sparse rain gauge networks to represent highly non-stationary rainfall fields. Remote sensing products permit concurrent estimates of debris-flow-triggering rainfall for areas poorly covered by rain gauges, but the impact of using coarse spatial resolutions to represent such rainfall fields is still to be assessed. This study uses fine-resolution radar data for ∼  100 debris flows in the eastern Italian Alps to (i) quantify the effect of spatial aggregation (1–20 km grid size) on the estimation of debris-flow-triggering rainfall and on the identification of early warning thresholds and (ii) compare thresholds derived from aggregated estimates and rain gauge networks of different densities. The impact of spatial aggregation is influenced by the spatial organization of rainfall and by its dependence on the severity of the triggering rainfall. Thresholds from aggregated estimates show 8–21 % variation in the parameters whereas 10–25 % systematic variation results from the use of rain gauge networks, even for densities as high as 1∕10 km−2.

Understanding and modelling the dynamics of large wood (LW) in rivers during flood events has spurred a great deal of research in recent years. However, few studies have documented the effect of high-magnitude flash floods on LW recruitment, transport and deposition. On 25 October 2011, the Magra river basin (north-western Italy) was hit by an intense rainstorm, with hourly rainfall rates up to 130 mm h−1 and event rain accumulations up to 540 mm in 8 h. Such large rainfall intensities originated flash floods in the main river channels and in several tributaries, causing severe damages and loss of lives. Numerous bridges were partly or fully clogged by LW jams. A post-flood survey was carried out along the channels of two catchments that were severely and similarly affected by this event, the Gravegnola (34.3 km2) and Pogliaschina (25.1 km2). The analysis highlighted a very relevant channel widening in many channel reaches, which was more marked in the Gravegnola basin due to highly erodible material forming the slopes adjacent to the fluvial corridor. Large wood recruitment rates were very high, up to 1270 m3 km−1, and most of it (70–80 %) was eroded from the floodplains as a consequence of channel-widening processes, while the rest came from hillslopes processes. Overall, drainage area and channel slope are the most relevant controlling variables in explaining the reach-scale variability of LW recruitment, whereas LW deposition appears to be more complex, as correlation analysis did not evidence any statistically significant relationship with the tested controlling variables. Indeed, in-channel LW displacement during the flood has been mostly limited by the presence of bridges, given the relatively large width attained by channels after the event.

The current work addresses one of the key building blocks towards an improved understanding of flood processes and associated changes in flood characteristics and regimes in Europe: the development of a comprehensive, extensive European flood database. The presented work results from ongoing cross-border research collaborations initiated with data collection and joint interpretation in mind. A detailed account of the current state, characteristics and spatial and temporal coverage of the European Flood Database, is presented. At this stage, the hydrological data collection is still growing and consists at this time of annual maximum and daily mean discharge series, from over 7000 hydrometric stations of various data series lengths. Moreover, the database currently comprises data from over 50 different data sources. The time series have been obtained from different national and regional data sources in a collaborative effort of a joint European flood research agreement based on the exchange of data, models and expertise, and from existing international data collections and open source websites. These ongoing efforts are contributing to advancing the understanding of regional flood processes beyond individual country boundaries and to a more coherent flood research in Europe.

The work examines the seasonality and large-scale atmospheric circulation patterns associated with debris-flow occurrence in the Trentino–Alto Adige region (eastern Italian Alps). Analysis is based on classification algorithms applied to a uniquely dense archive of debris flows and hourly rain gauge precipitation series covering the period 2000–2009. Results highlight the seasonal and synoptic forcing patterns linked to debris flows in the study area. Summer and fall season account for 92% of the debris flows in the record, while atmospheric circulation characterized by zonal west, mixed and meridional south and southeast (SE–S) patterns account for 80%. Both seasonal and circulation patterns exhibit geographical preference. In the case of seasonality, there is a strong north–south separation of summer–fall dominance, while spatial distribution of dominant circulation patterns exhibits clustering, with both zonal west and mixed patterns prevailing in the northwest and central east part of the region, while the southern part relates to meridional south and southeast pattern. Seasonal and synoptic pattern dependence is pronounced also on the debris-flow-triggering rainfall properties. Examination of rainfall intensity–duration thresholds derived for different data classes (according to season and synoptic pattern) revealed a distinct variability in estimated thresholds. These findings imply a certain control on debris-flow events and can therefore be used to improve existing alert systems.

There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has traditionally been obtained through two alternative research approaches. The first approach is the data-based detection of changes in observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for nonlinear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities associated with flood change scenarios are discussed such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on long duration records and flood-rich and flood-poor periods rather than on short duration flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.

This work evaluates the predictive power of the quasi-dynamic shallow landslide model QD-SLaM to simulate shallow landslide locations in a small-scale Mediterranean landscape, namely, the lower portion (2.6 km2) of the Giampilieri catchment, located in Sicily (Italy). The catchment was impacted by a sequence of high-intensity storms over the years 2007–2009, resulting in widespread landsliding, with a total landslide initiation area amounting to 2.6% of the basin area. The effect of high-resolution digital terrain models (DTMs) on the quality of model predictions is tested by considering four DTM resolutions: 2, 4, 10 and 20 m. Moreover, the impact of the dense forest road network on the model performance is evaluated by separately considering road-related landslides and natural landslides. The landslide model does not incorporate the description of road-related failures and is applied without calibration of the model parameters. The model predictive power is shown to be DTM-resolution dependent. Use of coarser resolution has a smoothing effect on terrain attributes, with local slope angles decreasing and contributing areas becoming larger. The percentage of watershed area represented by the model as unconditionally unstable (i.e. failing even without the addition of water from precipitation) ranges between 6.3% at 20 m DTM and 13.8% at 2 m DTM, showing an overestimation of the mapped landslide area. We consider this prediction as an indication for likely failing sites in future storms rather than areas proved stable during previous storms. When assessed over the sample of mapped non-road-related landslides, better model performances are reported for 4 and 10 m DTM resolution, thus highlighting the fact that higher DTM resolution does not necessarily mean better model performances. Model performances over road-related failures are lower than for the natural cases, and slightly increase with decreasing DTM resolution. These findings indicate that to realize the full potential of high-resolution topography, more extensive work is needed aiming more specifically to identify the extent of the artificial structures and their impact on shallow landsliding processes.

Topographic index-based hydrological models have gained wide use to describe the hydrological control on the triggering of rainfall-induced shallow landslides at the catchment scale. A common assumption in these models is that a spatially continuous water table occurs simultaneously across the catchment. However, during a rainfall event isolated patches of subsurface saturation form above an impeding layer and their hydrological connectivity is a necessary condition for lateral flow initiation at a point on the hillslope. Here, a new hydrological model is presented, which allows us to account for the concept of hydrological connectivity while keeping the simplicity of the topographic index approach. A dynamic topographic index is used to describe the transient lateral flow that is established at a hillslope element when the rainfall amount exceeds a threshold value allowing for (a) development of a perched water table above an impeding layer, and (b) hydrological connectivity between the hillslope element and its own upslope contributing area. A spatially variable soil depth is the main control of hydrological connectivity in the model. The hydrological model is coupled with the infinite slope stability model and with a scaling model for the rainfall frequency–duration relationship to determine the return period of the critical rainfall needed to cause instability on three catchments located in the Italian Alps, where a survey of soil depth spatial distribution is available. The model is compared with a quasi-dynamic model in which the dynamic nature of the hydrological connectivity is neglected. The results show a better performance of the new model in predicting observed shallow landslides, implying that soil depth spatial variability and connectivity bear a significant control on shallow landsliding.

This study evaluated between-sample memory in isotopic measurements of δ2H and δ18O in water samples by laser spectroscopy. Ten isotopically depleted water samples spanning a broad range of oxygen and hydrogen isotopic compositions were measured by three generations of off-axis integrated cavity output spectroscopy and cavity ring-down spectroscopy instruments. The analysis procedure encompassed small (less than 2‰ for δ2H and 1‰ for δ18O) and large (up to 201‰ for δ2H and 25‰ for δ18O) differences in isotopic compositions between adjacent sample vials. Samples were injected 18 times each, and the between-sample memory effect was quantified for each analysis run. Results showed that samples adversely affected by between-sample isotopic differences stabilised after seven–eight injections. The between-sample memory effect ranged from 14% and 9% for δ2H and δ18O measurements, respectively, but declined to negligible carryover (between 0.1% and 0.3% for both isotopes) when the first ten injections of each sample were discarded. The measurement variability (range and standard deviation) was strongly dependent on the isotopic difference between adjacent vials. Standard deviations were up to 7.5‰ for δ2H and 0.54‰ for δ18O when all injections were retained in the computation of the reportable δ-value, but a significant increase in measurement precision (standard deviation in the range 0.1‰–1.0‰ for δ2H and 0.05‰–0.17‰ for δ18O) was obtained when the first eight injections were discarded. In conclusion, this study provided a practical solution to mitigate between-sample memory effects in the isotopic analysis of water samples by laser spectroscopy.

The 2 June 2008 flood-producing storm on the Starzel river basin in South-West Germany is examined as a prototype for organized convective systems that dominate the upper tail of the precipitation frequency distribution and are likely responsible for the flash flood peaks in Central Europe. The availability of high-resolution rainfall estimates from radar observations and a rain gauge network, together with indirect peak discharge estimates from a detailed post-event survey, provided the opportunity to study in detail the hydrometeorological and hydrological mechanisms associated with this extreme storm and the ensuing flood. Radar-derived rainfall, streamgauge data and indirect estimates of peak discharges are used along with a distributed hydrologic model to reconstruct hydrographs at multiple locations. Observations and model results are combined to examine two main questions, (i) assessment of the distribution of the runoff ratio for the 2008 flash flood and how it compares with other less severe floods; and (ii) analysis of how the spatial and temporal distribution of the extreme rainfall, and more specifically storm motion, controls the flood response. It is shown that small runoff ratios (less than 20%) characterized the runoff response and that these values are in the range of other, less extreme, flood events. The influence of storm structure, evolution and motion on the modeled flood hydrograph is examined by using the "spatial moments of catchment rainfall". It is shown that downbasin storm motion (in the range of 0.7–0.9 m s−1) had a noticeable impact on flood response by increasing the modeled flood peak by 13%.

This work analyses the prominent characteristics of flash flood regimes in two Mediterranean areas: the North-Western Mediterranean region, which includes Catalonia, France and Northern Italy, and the South-Eastern Mediterranean region, which includes Israel. The two regions are characterized by similarities in the hydro-meteorological monitoring infrastructure, which permits us to ensure homogeneity in the data collection procedures. The analysis is articulated into two parts. The first part is based on use of flood peak data, catchment area and occurrence date for 99 events (69 from the North-Western region and 30 from the South-Eastern region). Analysis is carried out in terms of relationship of flood peaks with catchment area and seasonality. Results show that the envelope curve for the South-Eastern region exhibits a more pronounced decreasing with catchment size with respect to the curve of the North-Western region. The differences between the two relationships reflect changes in the effects of storm coverage and hydrological characteristics between the two regions. Seasonality analysis shows that the events in the North-Western region tend to occur between August and November, whereas those in the South-Eastern area tend to occur in the period between October and May, reflecting the relevant patterns in the synoptic conditions leading to the intense precipitation events. In the second part, the focus is on the rainfall-runoff relationships for 13 selected major flash flood events (8 from the North-Western area and 5 from the South-Eastern area) for which rainfall and runoff properties are available. These flash floods are characterised in terms of climatic features of the impacted catchments, duration and amount of the generating rainfall, and runoff ratio. Results show that the rainfall duration is shorter and the rainfall depth lower in the South-Eastern region. The runoff ratios are rather low in both regions, whereas they are more variable in the South-Eastern area. No clear relationship between runoff ratio and rainfall depth is observed in the sample of floods, showing the major influence of rainfall intensity and the initial wetness condition in the runoff generation for these events.

This paper describes a set of spatial rainfall statistics (termed "spatial moments of catchment rainfall") quantifying the dependence existing between spatial rainfall organisation, basin morphology and runoff response. These statistics describe the spatial rainfall organisation in terms of concentration and dispersion statistics as a function of the distance measured along the flow routing coordinate. The introduction of these statistics permits derivation of a simple relationship for the quantification of catchment-scale storm velocity. The concept of the catchment-scale storm velocity takes into account the role of relative catchment orientation and morphology with respect to storm motion and kinematics. The paper illustrates the derivation of the statistics from an analytical framework recently proposed in literature and explains the conceptual meaning of the statistics by applying them to five extreme flash floods occurred in various European regions in the period 2002–2007. High resolution radar rainfall fields and a distributed hydrologic model are employed to examine how effective are these statistics in describing the degree of spatial rainfall organisation which is important for runoff modelling. This is obtained by quantifying the effects of neglecting the spatial rainfall variability on flood modelling, with a focus on runoff timing. The size of the study catchments ranges between 36 to 982 km2. The analysis reported here shows that the spatial moments of catchment rainfall can be effectively employed to isolate and describe the features of rainfall spatial organization which have significant impact on runoff simulation. These statistics provide useful information on what space-time scales rainfall has to be monitored, given certain catchment and flood characteristics, and what are the effects of space-time aggregation on flood response modeling.

This study investigates the role of soil moisture on the threshold runoff response in a small headwater catchment in the Italian Alps that is characterised by steep hillslopes and a distinct riparian zone. This study focuses on: (i) the threshold soil moisture-runoff relationship and the influence of catchment topography on this relation; (ii) the temporal dynamics of soil moisture, streamflow and groundwater that characterize the catchment's response to rainfall during dry and wet periods; and (iii) the combined effect of antecedent wetness conditions and rainfall amount on hillslope and riparian runoff. Our results highlight the strong control exerted by soil moisture on runoff in this catchment: a sharp threshold exists in the relationship between soil water content and runoff coefficient, streamflow, and hillslope-averaged depth to water table. Low runoff ratios were likely related to the response of the riparian zone, which was almost always close to saturation. High runoff ratios occurred during wet antecedent conditions, when the soil moisture threshold was exceeded. In these cases, subsurface flow was activated on hillslopes, which became a major contributor to runoff. Antecedent wetness conditions also controlled the catchment's response time: during dry periods, streamflow reacted and peaked prior to hillslope soil moisture whereas during wet conditions the opposite occurred. This difference resulted in a hysteretic behaviour in the soil moisture-streamflow relationship. Finally, the influence of antecedent moisture conditions on runoff was also evident in the relation between cumulative rainfall and total stormflow. Small storms during dry conditions produced low stormflow amounts, likely mainly from overland flow from the near saturated riparian zone. Conversely, for rainfall events during wet conditions, higher stormflow values were observed and hillslopes must have contributed to streamflow.

The aim of this study was to analyse the reproducibility of off-axis integrated cavity output spectroscopy (OA-ICOS)-derived δ2H and δ18O measurements on a set of 35 water samples by comparing the performance of four laser spectroscopes with the performance of a conventional mass spectrometer under typical laboratory conditions. All samples were analysed using three different schemes of standard/sample combinations and related data processing to assess the improvement of results compared with mass spectrometry. The repeatability of the four OA-ICOS instruments was further investigated by multiple analyses of a sample subset to evaluate the stability of δ2H and δ18O measurements. Results demonstrated an overall agreement between OA-ICOS-based and mass spectrometry-based measurements for the entire dataset. However, a certain degree of variability existed in precision and accuracy between the four instruments. There was no evident bias or systematic deviations from the mass spectrometer values, but random errors, which were apparently not related to external factors, significantly affected the final results. Our investigation revealed that analytical precision ranged ±from ±0.56‰ to ±1.80‰ for δ2H and from ±0.10‰ to ±0.27‰ for δ18O measurements, with a marked variability among the four instruments. The overall capability of laser instruments to reproduce stable results with repeated measurements of the same sample was acceptable, and there were general differences within the range of the analytical precision for each spectroscope. Hence, averaging the measurements of three identical samples led to a higher degree of accuracy and eliminated the potential for random deviations.

This article is dedicated to radar rainfall estimation for the post-event analysis of a flash flood that occurred on 18 September 2007 in Slovenia. The utility of the Mountain Reference Technique is demonstrated to quantify rain attenuation effects that affect C-band radar measurements in heavy rain. Maximum path-integrated attenuation between 15 and 20 dB were estimated thanks to mountain returns for path-averaged rain rates between 10 and 15 mm h−1 over a 120-km path. Assuming the reflectivity-attenuation relationship to be known, the proposed technique allows for estimating an effective radar calibration correction factor to be accounted for in the parameterization of the attenuation correction. Screening effects are quantified using a geometrical calculation based on a digitized terrain model of the region. The vertical structure of the reflectivity is modeled with a normalized apparent vertical profile of reflectivity. Implementation of the radar data processing indicates that: (1) the combined correction for radar calibration and attenuation effects allows for obtaining satisfactory radar rain estimates (Nash criterion of 0.8 at the event time scale); (2) due to the attenuation equation instability, it is however compulsory to limit the maximum path-integrated attenuation to be corrected to about 10 dB; (3) the results also prove to be sensitive on the parameterization of reflectivity-attenuation-rainrate relationships.

High resolution radar rainfall fields and a distributed hydrologic model are used to evaluate the sensitivity of flash flood simulations to spatial aggregation of rainfall at catchment scales ranging from 10.5 km2 to 623 km2. The case study focuses on the extreme flash flood occurred on 29 August 2003 on the eastern Italian Alps. Four rainfall spatial resolutions are considered, with grid size equal to 1-, 4-, 8- and 16-km. The influence of rainfall spatial aggregation is examined by using the flow distance as a spatial coordinate, hence emphasising the role of river network in the averaging of space-time rainfall. Effects of rainfall spatial aggregation are quantified by using a dimensionless parameter, represented by the ratio of rainfall resolution (Lr) to the characteristic basin length (Lw), taken as the square root of the watershed area. Increasing the Lr/Lw parameter induces large errors on the simulated peak discharge, with values of the peak discharge error up to 0.33 for Lr/Lw equal to 1.0. An important error source related to spatial rainfall aggregation is the rainfall volume error caused by incorrectly smoothing the rainfall volume either inside or outside of of the watershed. It is found that for Lr/Lw 1.0, around 50% of the peak discharge error is due to the rainfall volume error. Remaining errors are due to both the distortion of the rainfall spatial distribution, measured with respect to the river network, and to the reduced spatial variability of the rainfield. Further investigations are required to isolate and examine the effect of river network geometry on the averaging of space-time rainfall at various aggregation lengths and on simulated peak discharges.

No abstract available.