Natural Hazards and Earth System Sciences
EISSN : 1684-9981
Published by: Copernicus GmbH (10.5194)
Total articles ≅ 3,454
Latest articles in this journal
Natural Hazards and Earth System Sciences, Volume 21, pp 2867-2880; https://doi.org/10.5194/nhess-21-2867-2021
Uncontrolled wildfires have a substantial impact on the environment, the economy and local populations. According to the European Forest Fire Information System (EFFIS), between 2000 and 2013 wildfires burned up to 740 000 ha of land annually in the south of Europe, Portugal being the country with the highest percentage of burned area per square kilometre. However, there is still a lack of knowledge regarding the impacts of the wildfire-related pollutants on the mortality of the country's population. All wildfires occurring during the fire season (June–July–August–September) from 2001 and 2016 were identified, and those with a burned area above 1000 ha (large fires) were considered for the study. During the studied period (2001–2016), more than 2 million ha of forest (929 766 ha from June to September alone) were burned in mainland Portugal. Although large fires only represent less than 1 % of the number of total fires, in terms of burned area their contribution is 46 % (53 % from June to September). To assess the spatial impact of the wildfires, burned areas in each region of Portugal were correlated with PM10 concentrations measured at nearby background air quality monitoring stations. Associations between PM10 and all-cause (excluding injuries, poisoning and external causes) and cause-specific mortality (circulatory and respiratory) were studied for the affected populations using Poisson regression models. A significant positive correlation between burned area and PM10 was found in some regions of Portugal, as well as a significant association between PM10 concentrations and mortality, these being apparently related to large wildfires in some of the regions. The north, centre and inland of Portugal are the most affected areas. The high temperatures and long episodes of drought expected in the future will increase the probabilities of extreme events and therefore the occurrence of wildfires.
Natural Hazards and Earth System Sciences, Volume 21, pp 2849-2865; https://doi.org/10.5194/nhess-21-2849-2021
Forecasting precipitation over the Mediterranean basin is still a challenge because of the complex orographic region that amplifies the need for local observation to correctly initialize the forecast. In this context, data assimilation techniques play a key role in improving the initial conditions and consequently the timing and position of the precipitation forecast. For the first time, the ability of a cycling 4D-Var to reproduce a heavy rain event in central Italy, as well as to provide a comparison with the largely used cycling 3D-Var, is evaluated in this study. The radar reflectivity measured by the Italian ground radar network is assimilated in the Weather Research and Forecasting (WRF) model to simulate an event that occurred on 3 May 2018 in central Italy. In order to evaluate the impact of data assimilation, several simulations are objectively compared by means of a fraction skill score (FSS), which is calculated for several threshold values, and a receiver operating characteristic (ROC) curve. The results suggest that both assimilation methods in the cycling mode improve the 1-, 3- and 6-hourly quantitative precipitation estimation. More specifically, the cycling 4D-Var with a warm start initialization shows the highest FSS values in the first hours of the simulation both with light and heavy precipitation. Finally, the ROC curve confirms the benefit of 4D-Var: the area under the curve is 0.91 compared to 0.88 for the control experiment without data assimilation.
Natural Hazards and Earth System Sciences, Volume 21, pp 2829-2847; https://doi.org/10.5194/nhess-21-2829-2021
There is now a wealth of data to calculate global flood exposure. Available datasets differ in detail and representation of both global population distribution and global flood hazard. Previous studies of global flood risk have used datasets interchangeably without addressing the impacts using different datasets could have on exposure estimates. By calculating flood exposure to different sized rivers using a model-independent geomorphological river flood susceptibility map (RFSM), we show that limits placed on the size of river represented in global flood models result in global flood exposure estimates that differ by more than a factor of 2. The choice of population dataset is found to be equally important and can have enormous impacts on national flood exposure estimates. Up-to-date, high-resolution population data are vital for accurately representing exposure to smaller rivers and will be key in improving the global flood risk picture. Our results inform the appropriate application of these datasets and where further development and research are needed.
Natural Hazards and Earth System Sciences, Volume 21, pp 2811-2828; https://doi.org/10.5194/nhess-21-2811-2021
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.
Natural Hazards and Earth System Sciences, Volume 21, pp 2791-2810; https://doi.org/10.5194/nhess-21-2791-2021
Detachments of large parts of low-angle mountain glaciers in recent years have raised great attention due to their threats to lives and properties downstream. While current studies have mainly focused on post-event analysis, a few opportunities have presented themselves to assess the potential hazards of a glacier prone to detachment. Here we present a comprehensive analysis of the dynamics and runout hazard of a low-angle (∼20∘) valley glacier, close to the Qinghai–Tibet railway and highway, in the East Kunlun Mountains on the Qinghai–Tibet Plateau. The changes in morphology, terminus position, and surface elevation of the glacier between 1975 and 2021 were characterized with a stereo-image pair from the historical KH-9 spy satellite, six digital elevation models (DEMs), and 11 high-resolution images from Planet Labs. The surface flow velocities of the glacier tongue between 2009 and 2020 were also tracked based on cross-correlation of Planet images. Our observations show that the glacier snout has been progressively advancing in the past 4 decades, with a stepwise increase in advance velocity from 4.55±0.46ma-1 between 1975 and 2009 to 30.88±2.36ma-1 between 2015 and 2020. DEM differencing confirms the glacial advance, with surface thinning in the source region and thickening in the tongue. The net volume loss over the glacier tongue was about 11.21±2.66×105 m3 during 1975–2018. Image cross-correlation reveals that the surface flow velocity of the glacier tongue has been increasing in recent years, with the mean velocity below 4800 m more than tripling from 6.3±1.8ma-1 during 2009–2010 to 22.3±3.2ma-1 during 2019–2020. With a combined analysis of the geomorphic, climatic, and hydrologic conditions of the glacier, we suggest that the flow of the glacier tongue is mainly controlled by the glacier geometry, while the presence of an ice-dammed lake and a supraglacial pond implies a hydrological influence as well. Taking the whole glacier and glacier tongue as two endmember avalanche sources, we assessed the potential runout distances of these two scenarios using the angle of reach and the Voellmy–Salm avalanche model. The assessments show that the avalanche of the whole glacier would easily travel a distance that would threaten the safety of the railway. In contrast, the detachment of the glacier tongue would threaten the railway only with a small angle of reach or when employing a low-friction parameter in the Voellmy–Salm modeling.
Natural Hazards and Earth System Sciences, Volume 21, pp 2773-2789; https://doi.org/10.5194/nhess-21-2773-2021
The prediction of debris flows is relevant because this type of natural hazard can pose a threat to humans and infrastructure. Debris-flow (and landslide) early warning systems often rely on rainfall intensity–duration (ID) thresholds. Multiple competing methods exist for the determination of such ID thresholds but have not been objectively and thoroughly compared at multiple scales, and a validation and uncertainty assessment is often missing in their formulation. As a consequence, updating, interpreting, generalizing and comparing rainfall thresholds is challenging. Using a 17-year record of rainfall and 67 debris flows in a Swiss Alpine catchment (Illgraben), we determined ID thresholds and associated uncertainties as a function of record duration. Furthermore, we compared two methods for rainfall definition based on linear regression and/or true-skill-statistic maximization. The main difference between these approaches and the well-known frequentist method is that non-triggering rainfall events were also considered for obtaining ID-threshold parameters. Depending on the method applied, the ID-threshold parameters and their uncertainties differed significantly. We found that 25 debris flows are sufficient to constrain uncertainties in ID-threshold parameters to ±30 % for our study site. We further demonstrated the change in predictive performance of the two methods if a regional landslide data set with a regional rainfall product was used instead of a local one with local rainfall measurements. Hence, an important finding is that the ideal method for ID-threshold determination depends on the available landslide and rainfall data sets. Furthermore, for the local data set we tested if the ID-threshold performance can be increased by considering other rainfall properties (e.g. antecedent rainfall, maximum intensity) in a multivariate statistical learning algorithm based on decision trees (random forest). The highest predictive power was reached when the peak 30 min rainfall intensity was added to the ID variables, while no improvement was achieved by considering antecedent rainfall for debris-flow predictions in Illgraben. Although the increase in predictive performance with the random forest model over the classical ID threshold was small, such a framework could be valuable for future studies if more predictors are available from measured or modelled data.
Natural Hazards and Earth System Sciences, Volume 21, pp 2753-2772; https://doi.org/10.5194/nhess-21-2753-2021
While optical remote sensing has demonstrated its capabilities for landslide detection and monitoring, spatial and temporal demands for landslide early warning systems (LEWSs) had not been met until recently. We introduce a novel conceptual approach to structure and quantitatively assess lead time for LEWSs. We analysed “time to warning” as a sequence: (i) time to collect, (ii) time to process and (iii) time to evaluate relevant optical data. The difference between the time to warning and “forecasting window” (i.e. time from hazard becoming predictable until event) is the lead time for reactive measures. We tested digital image correlation (DIC) of best-suited spatiotemporal techniques, i.e. 3 m resolution PlanetScope daily imagery and 0.16 m resolution unmanned aerial system (UAS)-derived orthophotos to reveal fast ground displacement and acceleration of a deep-seated, complex alpine mass movement leading to massive debris flow events. The time to warning for the UAS/PlanetScope totals 31/21 h and is comprised of time to (i) collect – 12/14 h, (ii) process – 17/5 h and (iii) evaluate – 2/2 h, which is well below the forecasting window for recent benchmarks and facilitates a lead time for reactive measures. We show optical remote sensing data can support LEWSs with a sufficiently fast processing time, demonstrating the feasibility of optical sensors for LEWSs.
Natural Hazards and Earth System Sciences, Volume 21, pp 2643-2678; https://doi.org/10.5194/nhess-21-2643-2021
The city of Venice and the surrounding lagoonal ecosystem are highly vulnerable to variations in relative sea level. In the past ∼150 years, this was characterized by an average rate of relative sea-level rise of about 2.5 mm/year resulting from the combined contributions of vertical land movement and sea-level rise. This literature review reassesses and synthesizes the progress achieved in quantification, understanding and prediction of the individual contributions to local relative sea level, with a focus on the most recent studies. Subsidence contributed to about half of the historical relative sea-level rise in Venice. The current best estimate of the average rate of sea-level rise during the observational period from 1872 to 2019 based on tide-gauge data after removal of subsidence effects is 1.23 ± 0.13 mm/year. A higher – but more uncertain – rate of sea-level rise is observed for more recent years. Between 1993 and 2019, an average change of about +2.76 ± 1.75 mm/year is estimated from tide-gauge data after removal of subsidence. Unfortunately, satellite altimetry does not provide reliable sea-level data within the Venice Lagoon. Local sea-level changes in Venice closely depend on sea-level variations in the Adriatic Sea, which in turn are linked to sea-level variations in the Mediterranean Sea. Water mass exchange through the Strait of Gibraltar and its drivers currently constitute a source of substantial uncertainty for estimating future deviations of the Mediterranean mean sea-level trend from the global-mean value. Regional atmospheric and oceanic processes will likely contribute significant interannual and interdecadal future variability in Venetian sea level with a magnitude comparable to that observed in the past. On the basis of regional projections of sea-level rise and an understanding of the local and regional processes affecting relative sea-level trends in Venice, the likely range of atmospherically corrected relative sea-level rise in Venice by 2100 ranges between 32 and 62 cm for the RCP2.6 scenario and between 58 and 110 cm for the RCP8.5 scenario, respectively. A plausible but unlikely high-end scenario linked to strong ice-sheet melting yields about 180 cm of relative sea-level rise in Venice by 2100. Projections of human-induced vertical land motions are currently not available, but historical evidence demonstrates that they have the potential to produce a significant contribution to the relative sea-level rise in Venice, exacerbating the hazard posed by climatically induced sea-level changes.
Natural Hazards and Earth System Sciences, Volume 21, pp 2633-2641; https://doi.org/10.5194/nhess-21-2633-2021
Venice is an iconic place and a paradigm of huge historical and cultural values at risk. The frequency of the flooding of the city centre has dramatically increased in recent decades, and this threat is expected to continue to grow – and even accelerate – through this century. This special issue is a collection of three review articles addressing different and complementary aspects of the hazards causing the floods of Venice, namely (1) the relative sea level rise, (2) the occurrence of extreme water heights, and (3) the prediction of extreme water heights and floods. It emerges that the effect of compound events poses critical challenges to the forecast of floods, particularly from the perspective of effectively operating the new mobile barriers (Modulo Sperimentale Elettromeccanico – MoSE) in Venice and that the relative sea level rise is the key factor determining the future growth of the flood hazard, so that the present defence strategy is likely to become inadequate within this century under a high-emission scenario. Two strands of research are needed in the future. First, there is a need to better understand and reduce the uncertainty of the future evolution of the relative sea level and its extremes at Venice. However, this uncertainty might not be substantially reduced in the near future, reflecting the uncertain anthropogenic emissions and structural model features. Hence, complementary adaptive planning strategies appropriate for conditions of uncertainty should be explored and developed in the future.
Natural Hazards and Earth System Sciences, Volume 21, pp 2679-2704; https://doi.org/10.5194/nhess-21-2679-2021
This paper reviews the state of the art in storm surge forecasting and its particular application in the northern Adriatic Sea. The city of Venice already depends on operational storm surge forecasting systems to warn the population and economy of imminent flood threats, as well as help to protect the extensive cultural heritage. This will be more important in the future, with the new mobile barriers called MOSE (MOdulo Sperimentale Elettromeccanico, Experimental Electromechanical Module) that will be completed by 2021. The barriers will depend on accurate storm surge forecasting to control their operation. In this paper, the physics behind the flooding of Venice is discussed, and the state of the art of storm surge forecasting in Europe is reviewed. The challenges for the surge forecasting systems are analyzed, especially in view of uncertainty. This includes consideration of selected historic extreme events that were particularly difficult to forecast. Four potential improvements are identified: (1) improve meteorological forecasts, (2) develop ensemble forecasting, (3) assimilation of water level measurements and (4) develop a multimodel approach.