Articles | Volume 24, issue 10
https://doi.org/10.5194/nhess-24-3337-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-3337-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Sep 2024
Research article |
| 30 Sep 2024
| 30 Sep 2024
Improving fire severity prediction in south-eastern Australia using vegetation-specific information
Kang He
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269, USA
Eversource Energy Center, University of Connecticut, Storrs, CT 06269, USA
Xinyi Shen
School of Freshwater Sciences, University of Wisconsin, Milwaukee, Milwaukee, WI 53204, USA
Cory Merow
Eversource Energy Center, University of Connecticut, Storrs, CT 06269, USA
Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT 06269, USA
Efthymios Nikolopoulos
Department of Civil and Environmental Engineering, Rutgers University, Piscataway, NJ 08854, USA
Rachael V. Gallagher
Department of Biological Sciences, Macquarie University, North Ryde, NSW 2109, Australia
Feifei Yang
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269, USA
Eversource Energy Center, University of Connecticut, Storrs, CT 06269, USA
Emmanouil N. Anagnostou
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269, USA
Eversource Energy Center, University of Connecticut, Storrs, CT 06269, USA
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About 820 km2 of agricultural land was inundated in central Greece due to Storm Daniel. A detailed analysis revealed that the crop most affected by the flooding was cotton; the inundated area of more than 282 km2 comprised ~ 30 % of the total area planted with cotton in central Greece. In terms of livestock, we estimate that more than 14 000 ornithoids and 21 500 sheep and goats were affected. Consequences for agriculture and animal husbandry in Greece are expected to be severe.
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About 820 km2 of agricultural land was inundated in central Greece due to Storm Daniel. A detailed analysis revealed that the crop most affected by the flooding was cotton; the inundated area of more than 282 km2 comprised ~ 30 % of the total area planted with cotton in central Greece. In terms of livestock, we estimate that more than 14 000 ornithoids and 21 500 sheep and goats were affected. Consequences for agriculture and animal husbandry in Greece are expected to be severe.
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Efthymios I. Nikolopoulos, Elisa Destro, Md Abul Ehsan Bhuiyan, Marco Borga, and Emmanouil N. Anagnostou
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Debris flows, following wildfires, constitute a significant threat to downstream populations and infrastructure. Therefore, developing measures to reduce the vulnerability of local communities to debris flows is of paramount importance. This work proposes a new model for predicting post-fire debris flow occurrence on a regional scale and demonstrates that the proposed model has notably higher skill than the currently used approaches.
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H. Seyyedi, E. N. Anagnostou, E. Beighley, and J. McCollum
Hydrol. Earth Syst. Sci., 18, 5077–5091, https://doi.org/10.5194/hess-18-5077-2014, https://doi.org/10.5194/hess-18-5077-2014, 2014
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E. Picciotti, F. S. Marzano, E. N. Anagnostou, J. Kalogiros, Y. Fessas, A. Volpi, V. Cazac, R. Pace, G. Cinque, L. Bernardini, K. De Sanctis, S. Di Fabio, M. Montopoli, M. N. Anagnostou, A. Telleschi, E. Dimitriou, and J. Stella
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To release a slab avalanche, a crack in a weak snow layer beneath a cohesive slab has to propagate. Information on that is essential for assessing avalanche risk. In the field, information can be gathered with the propagation saw test (PST). However, there are different standards on how to cut the PST. In this study, we experimentally investigate the effect of these different column geometries and provide models to correct for imprecise field test geometry effects on the critical cut length.
Stephanie Bohlmann and Marko Laine
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Probabilistic ensemble forecasts of the Canadian Forest Fire Weather Index (FWI) can be used to estimate the possible wildfire risk but require post-processing to provide accurate and reliable predictions. This article presents a calibration method using non-homogeneous Gaussian regression to statistically post-process FWI forecasts up to 15 d. Calibration improves the forecast especially at short lead times and in regions with high fire risk.
Franz Kleine, Charlotte Bruland, Andreas Wüstefeld, Volker Oye, and Martin Landrø
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-202, https://doi.org/10.5194/nhess-2024-202, 2024
Revised manuscript accepted for NHESS
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We used a fiber optic cable along a road in western Norway to study snow avalanches signals. Our study shows that avalanches create distinct signals in the 20–50 Hz frequency range, with larger ones having weak early warning signals. However, road traffic interference complicates automatic detection. This research highlights the potential of using existing infrastructure for avalanche monitoring. Further improvements are needed for automated detection.
Amelie Fees, Alec van Herwijnen, Michael Lombardo, Jürg Schweizer, and Peter Lehmann
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Glide-snow avalanches release at the ground–snow interface, and their release process is poorly understood. To investigate the influence of spatial variability (snowpack and basal friction) on avalanche release, we developed a 3D, mechanical, threshold-based model that reproduces an observed release area distribution. A sensitivity analysis showed that the distribution was mostly influenced by the basal friction uniformity, while the variations in snowpack properties had little influence.
Greta Hoe Wells, Þorsteinn Sæmundsson, Finnur Pálsson, Guðfinna Aðalgeirsdóttir, Eyjólfur Magnússon, Reginald L. Hermanns, and Snævarr Guðmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2002, https://doi.org/10.5194/egusphere-2024-2002, 2024
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Glacier retreat elevates the risk of landslides released into proglacial lakes, which can trigger glacial lake outburst floods (GLOFs). This study maps proglacial lake evolution and GLOF hazard scenarios at Fjallsjökull glacier, Iceland. Lake volume increased from 1945–2021 and is estimated to triple over the next century. Three slopes are prone to landslides that may trigger GLOFs. Results will mitigate flood hazard at this popular tourism site and advance GLOF research in Iceland and globally.
Håvard B. Toft, Samuel V. Verplanck, and Markus Landrø
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This study investigates inconsistencies in impact force as part of extended column tests (ECTs). We measured force-time curves from 286 practitioners in Scandinavia, Central Europe, and North America. The results show a large variability in peak forces and loading rates across wrist, elbow, and shoulder taps, challenging the ECT's reliability.
Florian Herla, Pascal Haegeli, Simon Horton, and Patrick Mair
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Snowpack simulations are increasingly employed by avalanche warning services to inform about critical avalanche layers buried in the snowpack. However, validity concerns limit their operational value. We present methods that enable meaningful comparisons between snowpack simulations and regional assessments of avalanche forecasters to quantify the performance of the Canadian weather and snowpack model chain to represent thin critical avalanche layers on a large scale and in real time.
Philipp L. Rosendahl, Johannes Schneider, Grégoire Bobillier, Florian Rheinschmidt, Bastian Bergfeld, Alec van Herwijnen, and Philipp Weißgraeber
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-122, https://doi.org/10.5194/nhess-2024-122, 2024
Revised manuscript accepted for NHESS
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Our research investigates the role of anticracks in snowpacks and their impact on avalanche formation, focusing on anticracks due to weak layer collapse. We discovered that slab touchdown on the snow below the weak layer decreases the energy available for crack propagation, potentially leading to a stop of crack propagation. This underscores the importance of mechanical interactions in snowpack stability. Our work offers new insights for enhancing avalanche prediction and mitigation strategies.
Tandin Wangchuk and Ryota Tsubaki
Nat. Hazards Earth Syst. Sci., 24, 2523–2540, https://doi.org/10.5194/nhess-24-2523-2024, https://doi.org/10.5194/nhess-24-2523-2024, 2024
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A glacial lake outburst flood (GLOF) is a natural hazard in which water from a glacier-fed lake is swiftly discharged, causing serious harm to life, infrastructure, and communities. We used numerical models to predict the potential consequences of a GLOF originating from the Thorthomi glacial lake in Bhutan. We found that if a GLOF occurs, the lake could release massive flood water within 4 h, posing a considerable risk. Study findings help to mitigate the impacts of future GLOFs.
Håvard B. Toft, John Sykes, Andrew Schauer, Jordy Hendrikx, and Audun Hetland
Nat. Hazards Earth Syst. Sci., 24, 1779–1793, https://doi.org/10.5194/nhess-24-1779-2024, https://doi.org/10.5194/nhess-24-1779-2024, 2024
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Manual Avalanche Terrain Exposure Scale (ATES) mapping is time-consuming and inefficient for large-scale applications. The updated algorithm for automated ATES mapping overcomes previous limitations by including forest density data, improving the avalanche runout estimations in low-angle runout zones, accounting for overhead exposure and open-source software. Results show that the latest version has significantly improved its performance.
Paula Aguirre, Jorge León, Constanza González-Mathiesen, Randy Román, Manuela Penas, and Alonso Ogueda
Nat. Hazards Earth Syst. Sci., 24, 1521–1537, https://doi.org/10.5194/nhess-24-1521-2024, https://doi.org/10.5194/nhess-24-1521-2024, 2024
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Wildfires pose a significant risk to property located in the wildland–urban interface (WUI). To assess and mitigate this risk, we need to understand which characteristics of buildings and building arrangements make them more prone to damage. We used a combination of data collection and analysis methods to study the vulnerability of dwellings in the WUI for case studies in Chile and concluded that the spatial arrangement of houses has a substantial impact on their vulnerability to wildfires.
Martín Domínguez Durán, María Angélica Sandoval Garzón, and Carme Huguet
Nat. Hazards Earth Syst. Sci., 24, 1319–1339, https://doi.org/10.5194/nhess-24-1319-2024, https://doi.org/10.5194/nhess-24-1319-2024, 2024
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In this study we created a cost-effective alternative to bridge the baseline information gap on indoor radon (a highly carcinogenic gas) in regions where measurements are scarce. We model indoor radon concentrations to understand its spatial distribution and the potential influential factors. We evaluated the performance of this alternative using a small number of measurements taken in Bogotá, Colombia. Our results show that this alternative could help in the making of future studies and policy.
Julia Glaus, Katreen Wikstrom Jones, Perry Bartelt, Marc Christen, Lukas Stoffel, Johan Gaume, and Yves Bühler
EGUsphere, https://doi.org/10.5194/egusphere-2024-771, https://doi.org/10.5194/egusphere-2024-771, 2024
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This study assesses RAMMS::EXTENDED's predictive power in estimating avalanche run-out distances critical for mountain road safety. Leveraging meteorological data and sensitivity analysis, it offers meaningful predictions, aiding near real-time hazard assessments and future model refinement for improved decision-making.
Grégoire Bobillier, Bertil Trottet, Bastian Bergfeld, Ron Simenhois, Alec van Herwijnen, Jürg Schweizer, and Johan Gaume
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-70, https://doi.org/10.5194/nhess-2024-70, 2024
Revised manuscript accepted for NHESS
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Our study focuses on the initiation process of snow slab avalanches. By combining experimental data and numerical simulations, we show that on gentle slopes, a crack forms and propagates due to compression fracture within a weak layer, and on steep slopes, the crack velocity can increase dramatically after about 5 meters due to a fracture mode transition (compression to shear). Understanding these dynamics represents an essential additional piece in the dry-snow slab avalanche formation puzzle.
Monica Sund, Heidi A. Grønsten, and Siv Å. Seljesæter
Nat. Hazards Earth Syst. Sci., 24, 1185–1201, https://doi.org/10.5194/nhess-24-1185-2024, https://doi.org/10.5194/nhess-24-1185-2024, 2024
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Slushflows are rapid mass movements of water-saturated snow released in gently sloping terrain (< 30°), often unexpectedly. Early warning is crucial to prevent casualties and damage to infrastructure. A regional early warning for slushflow hazard was established in Norway in 2013–2014 and has been operational since. We present a methodology using the ratio between water supply and snow depth by snow type to assess slushflow hazard. This approach is useful for other areas with slushflow hazard.
Sophie Barthelemy, Bertrand Bonan, Jean-Christophe Calvet, Gilles Grandjean, David Moncoulon, Dorothée Kapsambelis, and Séverine Bernardie
Nat. Hazards Earth Syst. Sci., 24, 999–1016, https://doi.org/10.5194/nhess-24-999-2024, https://doi.org/10.5194/nhess-24-999-2024, 2024
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This work presents a drought index specifically adapted to subsidence, a seasonal phenomenon of soil shrinkage that occurs frequently in France and damages buildings. The index is computed from land surface model simulations and evaluated by a rank correlation test with insurance data. With its optimal configuration, the index is able to identify years of both zero and significant loss.
John Sykes, Håvard Toft, Pascal Haegeli, and Grant Statham
Nat. Hazards Earth Syst. Sci., 24, 947–971, https://doi.org/10.5194/nhess-24-947-2024, https://doi.org/10.5194/nhess-24-947-2024, 2024
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The research validates and optimizes an automated approach for creating classified snow avalanche terrain maps using open-source geospatial modeling tools. Validation is based on avalanche-expert-based maps for two study areas. Our results show that automated maps have an overall accuracy equivalent to the average accuracy of three human maps. Automated mapping requires a fraction of the time and cost of traditional methods and opens the door for large-scale mapping of mountainous terrain.
Conor Hackett, Rafael de Andrade Moral, Gourav Mishra, Tim McCarthy, and Charles Markham
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-27, https://doi.org/10.5194/nhess-2024-27, 2024
Revised manuscript accepted for NHESS
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This paper reviews existing wildfire propagation models and a comparison of different grid types including random grids to simulate wildfires. This paper finds that irregular grids simulate wildfires more efficiently than continuous models while still retaining a reasonable level of similarity. It also shows that irregular grids tend to retain greater similarity to continuous models than regular grids at the cost of slightly longer computational times.
Jonas Mortelmans, Anne Felsberg, Gabriëlle J. M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, and Michel Bechtold
Nat. Hazards Earth Syst. Sci., 24, 445–464, https://doi.org/10.5194/nhess-24-445-2024, https://doi.org/10.5194/nhess-24-445-2024, 2024
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With global warming increasing the frequency and intensity of wildfires in the boreal region, accurate risk assessments are becoming more crucial than ever before. The Canadian Fire Weather Index (FWI) is a renowned system, yet its effectiveness in peatlands, where hydrology plays a key role, is limited. By incorporating groundwater data from numerical models and satellite observations, our modified FWI improves the accuracy of fire danger predictions, especially over summer.
Timothy W. Juliano, Fernando Szasdi-Bardales, Neil P. Lareau, Kasra Shamsaei, Branko Kosović, Negar Elhami-Khorasani, Eric P. James, and Hamed Ebrahimian
Nat. Hazards Earth Syst. Sci., 24, 47–52, https://doi.org/10.5194/nhess-24-47-2024, https://doi.org/10.5194/nhess-24-47-2024, 2024
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Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to understand the drivers of this devastating event. The simulation results show that extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making during wildfire events.
Stephanie Mayer, Frank Techel, Jürg Schweizer, and Alec van Herwijnen
Nat. Hazards Earth Syst. Sci., 23, 3445–3465, https://doi.org/10.5194/nhess-23-3445-2023, https://doi.org/10.5194/nhess-23-3445-2023, 2023
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We present statistical models to estimate the probability for natural dry-snow avalanche release and avalanche size based on the simulated layering of the snowpack. The benefit of these models is demonstrated in comparison with benchmark models based on the amount of new snow. From the validation with data sets of quality-controlled avalanche observations and danger levels, we conclude that these models may be valuable tools to support forecasting natural dry-snow avalanche activity.
Wei Yang, Zhongyan Wang, Baosheng An, Yingying Chen, Chuanxi Zhao, Chenhui Li, Yongjie Wang, Weicai Wang, Jiule Li, Guangjian Wu, Lin Bai, Fan Zhang, and Tandong Yao
Nat. Hazards Earth Syst. Sci., 23, 3015–3029, https://doi.org/10.5194/nhess-23-3015-2023, https://doi.org/10.5194/nhess-23-3015-2023, 2023
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We present the structure and performance of the early warning system (EWS) for glacier collapse and river blockages in the southeastern Tibetan Plateau. The EWS warned of three collapse–river blockage chain events and seven small-scale events. The volume and location of the collapses and the percentage of ice content influenced the velocities of debris flows. Such a study is helpful for understanding the mechanism of glacier hazards and for establishing similar EWSs in other high-risk regions.
Alba Marquez Torres, Giovanni Signorello, Sudeshna Kumar, Greta Adamo, Ferdinando Villa, and Stefano Balbi
Nat. Hazards Earth Syst. Sci., 23, 2937–2959, https://doi.org/10.5194/nhess-23-2937-2023, https://doi.org/10.5194/nhess-23-2937-2023, 2023
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Only by mapping fire risks can we manage forest and prevent fires under current and future climate conditions. We present a fire risk map based on k.LAB, artificial-intelligence-powered and open-source software integrating multidisciplinary knowledge in near real time. Through an easy-to-use web application, we model the hazard with 84 % accuracy for Sicily, a representative Mediterranean region. Fire risk analysis reveals 45 % of vulnerable areas face a high probability of danger in 2050.
Elisabeth D. Hafner, Frank Techel, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 23, 2895–2914, https://doi.org/10.5194/nhess-23-2895-2023, https://doi.org/10.5194/nhess-23-2895-2023, 2023
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Oftentimes when objective measurements are not possible, human estimates are used instead. In our study, we investigate the reproducibility of human judgement for size estimates, the mappings of avalanches from oblique photographs and remotely sensed imagery. The variability that we found in those estimates is worth considering as it may influence results and should be kept in mind for several applications.
Gerardo Romano, Marco Antonellini, Domenico Patella, Agata Siniscalchi, Andrea Tallarico, Simona Tripaldi, and Antonello Piombo
Nat. Hazards Earth Syst. Sci., 23, 2719–2735, https://doi.org/10.5194/nhess-23-2719-2023, https://doi.org/10.5194/nhess-23-2719-2023, 2023
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The Nirano Salse (northern Apennines, Italy) is characterized by several active mud vents and hosts thousands of visitors every year. New resistivity models describe the area down to 250 m, improving our geostructural knowledge of the area and giving useful indications for a better understanding of mud volcano dynamics and for the better planning of safer tourist access to the area.
Harry Podschwit, William Jolly, Ernesto Alvarado, Andrea Markos, Satyam Verma, Sebastian Barreto-Rivera, Catherine Tobón-Cruz, and Blanca Ponce-Vigo
Nat. Hazards Earth Syst. Sci., 23, 2607–2624, https://doi.org/10.5194/nhess-23-2607-2023, https://doi.org/10.5194/nhess-23-2607-2023, 2023
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We developed a model of fire spread that assumes that fire spreads in all directions at a constant speed and is extinguished at a constant rate. The model was fitted to 1003 fires in Peru between 2001 and 2020 using satellite burned area data from the GlobFire project. We fitted statistical models that predicted the spread and extinguish rates based on weather and land cover variables and found that these variables were good predictors of the spread and extinguish rates.
Anushilan Acharya, Jakob F. Steiner, Khwaja Momin Walizada, Salar Ali, Zakir Hussain Zakir, Arnaud Caiserman, and Teiji Watanabe
Nat. Hazards Earth Syst. Sci., 23, 2569–2592, https://doi.org/10.5194/nhess-23-2569-2023, https://doi.org/10.5194/nhess-23-2569-2023, 2023
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All accessible snow and ice avalanches together with previous scientific research, local knowledge, and existing or previously active adaptation and mitigation solutions were investigated in the high mountain Asia (HMA) region to have a detailed overview of the state of knowledge and identify gaps. A comprehensive avalanche database from 1972–2022 is generated, including 681 individual events. The database provides a basis for the forecasting of avalanche hazards in different parts of HMA.
Caili Zhong, Sibo Cheng, Matthew Kasoar, and Rossella Arcucci
Nat. Hazards Earth Syst. Sci., 23, 1755–1768, https://doi.org/10.5194/nhess-23-1755-2023, https://doi.org/10.5194/nhess-23-1755-2023, 2023
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This paper introduces a digital twin fire model using machine learning techniques to improve the efficiency of global wildfire predictions. The proposed model also manages to efficiently adjust the prediction results thanks to data assimilation techniques. The proposed digital twin runs 500 times faster than the current state-of-the-art physics-based model.
Abby Morgan, Pascal Haegeli, Henry Finn, and Patrick Mair
Nat. Hazards Earth Syst. Sci., 23, 1719–1742, https://doi.org/10.5194/nhess-23-1719-2023, https://doi.org/10.5194/nhess-23-1719-2023, 2023
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The avalanche danger scale is a critical component for communicating the severity of avalanche hazard conditions to the public. We examine how backcountry recreationists in North America understand and use the danger scale for planning trips into the backcountry. Our results provide an important user perspective on the strengths and weaknesses of the existing scale and highlight opportunities for future improvements.
Adrián Cardíl, Victor M. Tapia, Santiago Monedero, Tomás Quiñones, Kerryn Little, Cathelijne R. Stoof, Joaquín Ramirez, and Sergio de-Miguel
Nat. Hazards Earth Syst. Sci., 23, 361–373, https://doi.org/10.5194/nhess-23-361-2023, https://doi.org/10.5194/nhess-23-361-2023, 2023
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This study aims to unravel large-fire behavior in northwest Europe, a temperate region with a projected increase in wildfire risk. We propose a new method to identify wildfire rate of spread from satellites because it is important to know periods of elevated fire risk for suppression methods and land management. Results indicate that there is a peak in the area burned and rate of spread in the months of March and April, and there are significant differences for forest-type land covers.
Liam S. Taylor, Duncan J. Quincey, and Mark W. Smith
Nat. Hazards Earth Syst. Sci., 23, 329–341, https://doi.org/10.5194/nhess-23-329-2023, https://doi.org/10.5194/nhess-23-329-2023, 2023
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Hazards from glaciers are becoming more likely as the climate warms, which poses a threat to communities living beneath them. We have developed a new camera system which can capture regular, high-quality 3D models to monitor small changes in glaciers which could be indicative of a future hazard. This system is far cheaper than more typical camera sensors yet produces very similar quality data. We suggest that deploying these cameras near glaciers could assist in warning communities of hazards.
Bastian Bergfeld, Alec van Herwijnen, Grégoire Bobillier, Philipp L. Rosendahl, Philipp Weißgraeber, Valentin Adam, Jürg Dual, and Jürg Schweizer
Nat. Hazards Earth Syst. Sci., 23, 293–315, https://doi.org/10.5194/nhess-23-293-2023, https://doi.org/10.5194/nhess-23-293-2023, 2023
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For a slab avalanche to release, the snowpack must facilitate crack propagation over large distances. Field measurements on crack propagation at this scale are very scarce. We performed a series of experiments, up to 10 m long, over a period of 10 weeks. Beside the temporal evolution of the mechanical properties of the snowpack, we found that crack speeds were highest for tests resulting in full propagation. Based on these findings, an index for self-sustained crack propagation is proposed.
Sigrid Jørgensen Bakke, Niko Wanders, Karin van der Wiel, and Lena Merete Tallaksen
Nat. Hazards Earth Syst. Sci., 23, 65–89, https://doi.org/10.5194/nhess-23-65-2023, https://doi.org/10.5194/nhess-23-65-2023, 2023
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In this study, we developed a machine learning model to identify dominant controls of wildfire in Fennoscandia and produce monthly fire danger probability maps. The dominant control was shallow-soil water anomaly, followed by air temperature and deep soil water. The model proved skilful with a similar performance as the existing Canadian Forest Fire Weather Index (FWI). We highlight the benefit of using data-driven models jointly with other fire models to improve fire monitoring and prediction.
Yi Victor Wang and Antonia Sebastian
Nat. Hazards Earth Syst. Sci., 22, 4103–4118, https://doi.org/10.5194/nhess-22-4103-2022, https://doi.org/10.5194/nhess-22-4103-2022, 2022
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In this article, we propose an equivalent hazard magnitude scale and a method to evaluate and compare the strengths of natural hazard events across different hazard types, including earthquakes, tsunamis, floods, droughts, forest fires, tornadoes, cold waves, heat waves, and tropical cyclones. With our method, we determine that both the February 2021 North American cold wave event and Hurricane Harvey in 2017 were equivalent to a magnitude 7.5 earthquake in hazard strength.
Michael A. Storey and Owen F. Price
Nat. Hazards Earth Syst. Sci., 22, 4039–4062, https://doi.org/10.5194/nhess-22-4039-2022, https://doi.org/10.5194/nhess-22-4039-2022, 2022
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Models are needed to understand and predict pollutant output from forest fires so fire agencies can reduce smoke-related risks to human health. We modelled air quality (PM2.5) based on fire area and weather variables. We found fire area and boundary layer height were influential on predictions, with distance, temperature, wind speed and relative humidity also important. The models predicted reasonably accurately in comparison to other existing methods but would benefit from further development.
Tomás Calheiros, Akli Benali, Mário Pereira, João Silva, and João Nunes
Nat. Hazards Earth Syst. Sci., 22, 4019–4037, https://doi.org/10.5194/nhess-22-4019-2022, https://doi.org/10.5194/nhess-22-4019-2022, 2022
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Fire weather indices are used to assess the effect of weather on wildfires. Fire weather risk was computed and combined with large wildfires in Portugal. Results revealed the influence of vegetation cover: municipalities with a prevalence of shrublands, located in eastern parts, burnt under less extreme conditions than those with higher forested areas, situated in coastal regions. These findings are a novelty for fire science in Portugal and should be considered for fire management.
Ana C. L. Sá, Bruno Aparicio, Akli Benali, Chiara Bruni, Michele Salis, Fábio Silva, Martinho Marta-Almeida, Susana Pereira, Alfredo Rocha, and José Pereira
Nat. Hazards Earth Syst. Sci., 22, 3917–3938, https://doi.org/10.5194/nhess-22-3917-2022, https://doi.org/10.5194/nhess-22-3917-2022, 2022
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Assessing landscape wildfire connectivity supported by wildfire spread simulations can improve fire hazard assessment and fuel management plans. Weather severity determines the degree of fuel patch connectivity and thus the potential to spread large and intense wildfires. Mapping highly connected patches in the landscape highlights patch candidates for prior fuel treatments, which ultimately will contribute to creating fire-resilient Mediterranean landscapes.
Simon K. Allen, Ashim Sattar, Owen King, Guoqing Zhang, Atanu Bhattacharya, Tandong Yao, and Tobias Bolch
Nat. Hazards Earth Syst. Sci., 22, 3765–3785, https://doi.org/10.5194/nhess-22-3765-2022, https://doi.org/10.5194/nhess-22-3765-2022, 2022
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This study demonstrates how the threat of a very large outburst from a future lake can be feasibly assessed alongside that from current lakes to inform disaster risk management within a transboundary basin between Tibet and Nepal. Results show that engineering measures and early warning systems would need to be coupled with effective land use zoning and programmes to strengthen local response capacities in order to effectively reduce the risk associated with current and future outburst events.
Markéta Součková, Roman Juras, Kryštof Dytrt, Vojtěch Moravec, Johanna Ruth Blöcher, and Martin Hanel
Nat. Hazards Earth Syst. Sci., 22, 3501–3525, https://doi.org/10.5194/nhess-22-3501-2022, https://doi.org/10.5194/nhess-22-3501-2022, 2022
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Avalanches are natural hazards that threaten people and infrastructure. With climate change, avalanche activity is changing. We analysed the change in frequency and size of avalanches in the Krkonoše Mountains, Czechia, and detected important variables with machine learning tools from 1979–2020. Wet avalanches in February and March have increased, and slab avalanches have decreased and become smaller. The identified variables and their threshold levels may help in avalanche decision-making.
Annalie Dorph, Erica Marshall, Kate A. Parkins, and Trent D. Penman
Nat. Hazards Earth Syst. Sci., 22, 3487–3499, https://doi.org/10.5194/nhess-22-3487-2022, https://doi.org/10.5194/nhess-22-3487-2022, 2022
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Wildfire spatial patterns are determined by fire ignition sources and vegetation fuel moisture. Fire ignitions can be mediated by humans (owing to proximity to human infrastructure) or caused by lightning (owing to fuel moisture, average annual rainfall and local weather). When moisture in dead vegetation is below 20 % the probability of a wildfire increases. The results of this research enable accurate spatial mapping of ignition probability to aid fire suppression efforts and future research.
John Sykes, Pascal Haegeli, and Yves Bühler
Nat. Hazards Earth Syst. Sci., 22, 3247–3270, https://doi.org/10.5194/nhess-22-3247-2022, https://doi.org/10.5194/nhess-22-3247-2022, 2022
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Automated snow avalanche terrain mapping provides an efficient method for large-scale assessment of avalanche hazards, which informs risk management decisions for transportation and recreation. This research reduces the cost of developing avalanche terrain maps by using satellite imagery and open-source software as well as improving performance in forested terrain. The research relies on local expertise to evaluate accuracy, so the methods are broadly applicable in mountainous regions worldwide.
Ivana Čavlina Tomašević, Kevin K. W. Cheung, Višnjica Vučetić, Paul Fox-Hughes, Kristian Horvath, Maja Telišman Prtenjak, Paul J. Beggs, Barbara Malečić, and Velimir Milić
Nat. Hazards Earth Syst. Sci., 22, 3143–3165, https://doi.org/10.5194/nhess-22-3143-2022, https://doi.org/10.5194/nhess-22-3143-2022, 2022
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One of the most severe and impactful urban wildfire events in Croatian history has been reconstructed and analyzed. The study identified some important meteorological influences related to the event: the synoptic conditions of the Azores anticyclone, cold front, and upper-level shortwave trough all led to the highest fire weather index in 2017. A low-level jet, locally known as bura wind that can be explained by hydraulic jump theory, was the dynamic trigger of the event.
Adam Emmer, Simon K. Allen, Mark Carey, Holger Frey, Christian Huggel, Oliver Korup, Martin Mergili, Ashim Sattar, Georg Veh, Thomas Y. Chen, Simon J. Cook, Mariana Correas-Gonzalez, Soumik Das, Alejandro Diaz Moreno, Fabian Drenkhan, Melanie Fischer, Walter W. Immerzeel, Eñaut Izagirre, Ramesh Chandra Joshi, Ioannis Kougkoulos, Riamsara Kuyakanon Knapp, Dongfeng Li, Ulfat Majeed, Stephanie Matti, Holly Moulton, Faezeh Nick, Valentine Piroton, Irfan Rashid, Masoom Reza, Anderson Ribeiro de Figueiredo, Christian Riveros, Finu Shrestha, Milan Shrestha, Jakob Steiner, Noah Walker-Crawford, Joanne L. Wood, and Jacob C. Yde
Nat. Hazards Earth Syst. Sci., 22, 3041–3061, https://doi.org/10.5194/nhess-22-3041-2022, https://doi.org/10.5194/nhess-22-3041-2022, 2022
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Glacial lake outburst floods (GLOFs) have attracted increased research attention recently. In this work, we review GLOF research papers published between 2017 and 2021 and complement the analysis with research community insights gained from the 2021 GLOF conference we organized. The transdisciplinary character of the conference together with broad geographical coverage allowed us to identify progress, trends and challenges in GLOF research and outline future research needs and directions.
Cited articles
Abatzoglou, J. T. and Kolden, C. A.: Climate change in western US deserts: potential for increased wildfire and invasive annual grasses, Rangeland Ecol. Manag., 64, 471–478, https://doi.org/10.2111/REM-D-09-00151.1, 2011.
Abatzoglou, J. T., Williams, A. P., and Barbero, R.: Global emergence of anthropogenic climate change in fire weather indices, Geophys. Res. Lett., 46, 326–336, https://doi.org/10.1029/2018GL080959, 2019.
Abram, N. J., Henley, B. J., Sen Gupta, A., Lippmann, T. J., Clarke, H., Dowdy, A. J., Sharples, J. J., Nolan, R. H., Zhang, T., Wooster, M. J., Wurtzel, J. B., Meissner, K. J., Pitman, A. J., Ukkola, A. M., Murphy, B. P., Tapper, N. J., and Boer, M. M.: Connections of climate change and variability to large and extreme forest fires in southeast Australia, Commun. Earth Environ., 2, 1–17, https://doi.org/10.1038/s43247-020-00065-8, 2021.
Agee, J. K.: The influence of forest structure on fire behavior, in: Proceedings of the 17th annual forest vegetation management conference, Redding, California, 16–18 January 1996, 52–68, https://ecoshare.info/wp-content/uploads/2021/02/Agee-1996-Conf-Proceedings.pdf (last access: 18 September 2022), 1996.
Alkhatib, A. A.: A review on forest fire detection techniques, Int. J. Distrib. Sens. N., 10, 597368, https://doi.org/10.1155/2014/597368, 2014.
Archibald, S., Lehmann, C. E., Gómez-Dans, J. L., and Bradstock, R. A.: Defining pyromes and global syndromes of fire regimes, P. Natl. Acad. Sci. USA, 110, 6442–6447, https://doi.org/10.1073/pnas.1211466110, 2013.
Barker, R., Price, O. F., Gill, A. M., and Bradstock, R. A.: Fire severity in a large wildfire is influenced by vegetation, terrain and weather, Landscape Ecol., 33, 1231–1247, https://doi.org/10.1007/s10980-018-0670-3, 2018.
Boby, L. A., Schuur, E. A., Mack, M. C., Verbyla, D., and Johnstone, J. F.: Quantifying fire severity, carbon, and nitrogen emissions in Alaska's boreal forest, Ecol. Appl., 20, 1633–1647, https://doi.org/10.1890/08-2295.1, 2010.
Bowman, D. M., Williamson, G. J., Gibson, R. K., Bradstock, R. A., and Keenan, R. J.: The severity and extent of the Australia 2019–20 Eucalyptus forest fires are not the legacy of forest management, Nat. Ecol. Evol., 5, 1003–1010, https://doi.org/10.1038/s41559-021-01464-6, 2021.
Bradstock, R. A., Hammill, K. A., Collins, L., and Price, O.: Effects of weather, fuel and terrain on fire severity in topographically diverse landscapes of south-eastern Australia, Landscape Ecol., 25, 607–619, https://doi.org/10.1007/s10980-009-9443-8, 2010.
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Castelli, M., Vanneschi, L., and Popovič, A.: Predicting burned areas of forest fires: an artificial intelligence approach, Fire Ecol., 11, 106–118, https://doi.org/10.4996/fireecology.1101106, 2015.
Chambers, J. M.: Software for data analysis: Programming with R, Springer, New York, Vol. 2, https://doi.org/10.1007/978-0-387-75936-4, 2008.
Chen, T. and Guestrin, C.: Xgboost: A scalable tree boosting system, in: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 13–17 August 2016, San Francisco, California, USA, Association for Computing Machinery, 785–794, https://doi.org/10.1145/2939672.2939785, 2016.
Chen, T., He, T., Benesty, M., Khotilovich, V., Tang, Y., Cho, H., Chen, K., Mitchell, R., Cano, I., and Zhou, T.: Xgboost: Extreme gradient boosting, R package version 0.4-2, https://cran.ms.unimelb.edu.au/web/packages/xgboost/vignettes/xgboost.pdf (last access: 27 February 2022), 2015.
Choat, B., Brodribb, T. J., Brodersen, C. R., Duursma, R. A., López, R., and Medlyn, B. E.: Triggers of tree mortality under drought, Nature, 558, 531–539, https://doi.org/10.1038/s41586-018-0240-x, 2018.
Clarke, H., Tran, B., Boer, M. M., Price, O., Kenny, B., and Bradstock, R.: Climate change effects on the frequency, seasonality and interannual variability of suitable prescribed burning weather conditions in south-eastern Australia, Agr. Forest Meteorol., 271, 148–157, https://doi.org/10.1016/j.agrformet.2019.03.005, 2019.
Clarke, P. J., Knox, K. J., Bradstock, R. A., Munoz-Robles, C., and Kumar, L.: Vegetation, terrain and fire history shape the impact of extreme weather on fire severity and ecosystem response, J. Veg. Sci., 25, 1033–1044, https://doi.org/10.1111/jvs.12166, 2014.
Collins, B. M., Kelly, M., Van Wagtendonk, J. W., and Stephens, S. L.: Spatial patterns of large natural fires in Sierra Nevada wilderness areas, Landscape Ecol., 22, 545–557, https://doi.org/10.1007/s10980-006-9047-5, 2007.
Collins, B. M., Miller, J. D., Thode, A. E., Kelly, M., and van Wagtendonk, J. W.: Interactions among wildland fires in a long-established Sierra Nevada natural fire area, Ecosystems, 12, 114–128, https://doi.org/10.1007/s10021-008-9211-7, 2009.
Collins, L., Bradstock, R. A., and Penman, T. D.: Can precipitation influence landscape controls on wildfire severity? A case study within temperate eucalypt forests of south-eastern Australia, Int. J. Wildland Fire, 23, 9–20, https://doi.org/10.1071/WF12184, 2013.
Collins, L., Griffioen, P., Newell, G., and Mellor, A.: The utility of Random Forests for wildfire severity mapping, Remote Sens. Environ., 216, 374–384, https://doi.org/10.1016/j.rse.2018.07.005, 2018.
Collins, L., Bennett, A. F., Leonard, S. W., and Penman, T. D.: Wildfire refugia in forests: Severe fire weather and drought mute the influence of topography and fuel age, Glob. Change Biol., 25, 3829–3843, https://doi.org/10.1111/gcb.14735, 2019.
Collins, L., Clarke, H., Clarke, M. F., McColl Gausden, S. C., Nolan, R. H., Penman, T., and Bradstock, R.: Warmer and drier conditions have increased the potential for large and severe fire seasons across south-eastern Australia, Global Ecol. Biogeogr., 31, 1933–1948, https://doi.org/10.1111/geb.13514, 2022.
Dixon, D. J., Callow, J. N., Duncan, J. M. A., Setterfield, S. A., and Pauli, N.: Regional-scale fire severity mapping of Eucalyptus forests with the Landsat archive, Remote Sens. Environ., 270, 112863, https://doi.org/10.1016/j.rse.2021.112863, 2022.
Dowdy, A. J., Mills, G. A., Finkele, K., and De Groot, W.: Australian fire weather as represented by the McArthur forest fire danger index and the Canadian forest fire weather index, Centre for Australian Weather and Climate Research, Melbourne, 91 pp., https://cawcr.gov.au/technical-reports/CTR_010.pdf (last access: 3 May 2022), 2009.
Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., Hofton, M., Hurtt, G., Kellner, J., Luthcke, S., and Armston, J.: The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth's forests and topography, Sci. Remote Sens., 1, 100002, https://doi.org/10.1016/j.srs.2020.100002, 2020.
Eidenshink, J., Schwind, B., Brewer, K., Zhu, Z. L., Quayle, B., and Howard, S.: A project for monitoring trends in burn severity, Fire Ecol., 3, 3–21, https://doi.org/10.4996/fireecology.0301003, 2007.
Enright, N. J., Fontaine, J. B., Bowman, D. M., Bradstock, R. A., and Williams, R. J.: Interval squeeze: Altered fire regimes and demographic responses interact to threaten woody species persistence as climate changes, Front. Ecol. Environ., 13, 265–272, https://doi.org/10.1890/140231, 2015.
Fang, L., Yang, J., Zu, J., Li, G., and Zhang, J.: Quantifying influences and relative importance of fire weather, topography, and vegetation on fire size and fire severity in a Chinese boreal forest landscape, Forest Ecol. Manag., 356, 2–12, https://doi.org/10.1016/j.foreco.2015.01.011, 2015.
Fang, L., Yang, J., White, M., and Liu, Z.: Predicting potential fire severity using vegetation, topography and surface moisture availability in a Eurasian boreal forest landscape, Forests, 9, 130, https://doi.org/10.3390/f9030130, 2018.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., and Seal, D.: The shuttle radar topography mission, Rev. Geophys., 45, RG2004, https://doi.org/10.1029/2005RG000183, 2007.
Fernández-Guisuraga, J. M., Suárez-Seoane, S., García-Llamas, P., and Calvo, L.: Vegetation structure parameters determine high burn severity likelihood in different ecosystem types: A case study in a burned Mediterranean landscape, J. Environ. Manage., 288, 112462, https://doi.org/10.1016/j.jenvman.2021.112462, 2021.
Gallagher, R. V., Allen, S., Mackenzie, B. D., Yates, C. J., Gosper, C. R., Keith, D. A., Merow, C., White, M. D., Wenk, E., Maitner, B. S., He, K., Adams, V. M., and Auld, T. D.: High fire frequency and the impact of the 2019–2020 megafires on Australian plant diversity, Divers. Distrib., 27, 1166–1179, https://doi.org/10.1111/ddi.13265, 2021.
Gallagher, R. V., Allen, S. P., Mackenzie, B. D., Keith, D. A., Nolan, R. H., Rumpff, L., Nolan R. H., Rumpff L., Gosper C. R., Pegg G., van Leeuwen S., Ooi M. K. J., Yates C. J., Merow C., Williams R. J., Nikolopoulos E. I., Beaumont L. J., and Auld, T. D.: An integrated approach to assessing abiotic and biotic threats to post-fire plant species recovery: Lessons from the 2019–2020 Australian fire season, Global Ecol. Biogeogr., 31, 2056–2069, https://doi.org/10.1111/geb.13478, 2022.
García, M. L. and Caselles, V.: Mapping burns and natural reforestation using Thematic Mapper data, Geocarto Int., 6, 31–37, https://doi.org/10.1080/10106049109354290, 1991.
Giglio, L., Randerson, J. T., and van der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res.-Biogeo., 115, 317–328, https://doi.org/10.1002/jgrg.20042, 2010.
Gill, A. M.: Fire and the Australian flora: A review, Aust. Forestry, 38, 4–25, https://doi.org/10.1080/00049158.1975.10675584, 1975.
Gómez, C., White, J. C., and Wulder, M. A.: Optical remotely sensed time series data for land cover classification: A review, ISPRS J. Photogramm., 116, 55–72, https://doi.org/10.1016/j.isprsjprs.2016.03.011, 2015.
Gorokhovich, Y. and Voustianiouk, A.: Accuracy assessment of the processed SRTM-based elevation data by CGIAR using field data from USA and Thailand and its relation to the terrain characteristics, Remote Sens. Environ., 104, 409–415, https://doi.org/10.1016/j.rse.2006.05.012, 2006.
Harris, L. and Taylor, A. H.: Topography, fuels, and fire exclusion drive fire severity of the Rim Fire in an old-growth mixed-conifer forest, Yosemite National Park, USA, Ecosystems, 18, 1192–1208, https://doi.org/10.1007/s10021-015-9890-9, 2015.
Hawker, L., Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C., and Neal, J.: A 30 m global map of elevation with forests and buildings removed, Environ. Res. Lett., 17, 024016, https://doi.org/10.1088/1748-9326/ac4d4f, 2022.
Hennessy, K., Lucas, C., Nicholls, N., Bathols, J., Suppiah, R., and Ricketts, J.: Climate change impacts on fire-weather in south-east Australia, Climate Impacts Group, CSIRO Atmospheric Research and the Australian Government Bureau of Meteorology, Aspendale, https://www.researchgate.net/profile/James-Ricketts-3/publication/252471836_Climate_Change_Impacts_on_Fire-Weather_in_South-East_Australia/links/54a86d870cf257a6360bdfea/Climate-Change-Impacts-on-Fire-Weather-in-South-East-Australia.pdf (last access: 19 September 2022), 2005.
Holden, Z. A., Morgan, P., and Evans, J. S.: A predictive model of burn severity based on 20 year satellite-inferred burn severity data in a large southwestern US wilderness area, Forest Ecol. Manag., 258, 2399–2406, https://doi.org/10.1016/j.foreco.2009.08.017, 2009.
Holden, Z. A., Swanson, A., Luce, C. H., Jolly, W. M., Maneta, M., Oyler, J. W., Warren, D. A., Parsons, R., and Affleck, D.: Decreasing fire season precipitation increased recent western US forest wildfire activity, P. Natl. Acad. Sci. USA, 115, E8349–E8357, https://doi.org/10.1073/pnas.1802316115, 2018.
Howe, A. A., Parks, S. A., Harvey, B. J., Saberi, S. J., Lutz, J. A., and Yocom, L. L.: Comparing Sentinel-2 and Landsat 8 for burn severity mapping in Western North America, Remote Sens.-Basel, 14, 5249, https://doi.org/10.3390/rs14205249, 2022.
Hudak, A. T., Strand, E. K., Vierling, L. A., Byrne, J. C., Eitel, J. U., and Martinuzzi, S.: Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys, Remote Sens. Environ., 123, 25–40, https://doi.org/10.1016/j.rse.2012.02.023, 2012.
Hudak, A. T., Ottmar, R. D., Vihnanek, R. E., Brewer, N. W., Smith, A. M., and Morgan, P.: The relationship of post-fire white ash cover to surface fuel consumption, Int. J. Wildland Fire, 22, 780–785, https://doi.org/10.1071/WF12150, 2013.
Jolly, W. M., Cochrane, M. A., Freeborn, P. H., Holden, Z. A., Brown, T. J., Williamson, G. J., and Bowman, D. M. J. S.: Climate-induced variations in global wildfire danger from 1979 to 2013, Nat. Commun., 6, 7537, https://doi.org/10.1038/ncomms8537, 2015.
Keeley, J. E.: Fire intensity, fire severity and burn severity: a brief review and suggested usage, Int. J. Wildland Fire, 18, 116–126, https://doi.org/10.1071/WF07049, 2009.
Keeley, J. E., Bond, W. J., Bradstock, R. A., Pausas, J. G., and Rundel, P. W.: Fire in Mediterranean ecosystems: Ecology, evolution and management, Cambridge University Press, https://doi.org/10.1017/CBO9781139033091, 2009
Keetch, J. J. and Byram, G. M.: A drought index for forest fire control, USDA Forest Service Research Paper SE-38, Asheville, NC, https://research.fs.usda.gov/treesearch/40 (last access: 26 April 2022), 1968.
Keith, D. A.: Ocean shores to desert dunes: the native vegetation of New South Wales and the ACT, Department of Environment and Conservation (NSW), ISBN 10: 0731367804, 2004.
Keith, D. A., Allen, S. P., Gallagher, R. V., Mackenzie, B. D., Auld, T. D., Barrett, S.,Buchan, A., English, V., Gosper, C., Kelly, D., McIllwee, A., Melrose, R. T., Miller, B. P., Neldner, V. J., Simpson, C. C., Tolsma, A. D., Rogers, D., van Leeuwen, S., White, M. D., Yates, C. J., and Tozer, M. G.: Fire-related threats and transformational change in Australian ecosystems, Global Ecol. Biogeogr., 31, 2070–2084, https://doi.org/10.1111/geb.13500, 2022.
Key, C. H. and Benson, N. C.: Landscape assessment (LA), FIREMON: Fire effects monitoring and inventory system, 164, LA-1, https://research.fs.usda.gov/treesearch/24066 (last access: 23 June 2022), 2006.
Lentile, L. B., Holden, Z. A., Smith, A. M., Falkowski, M. J., Hudak, A. T., Morgan, P., Lewis, S. A., Gessler, P. E., and Benson, N. C.: Remote sensing techniques to assess active fire characteristics and post-fire effects, Int. J. Wildland Fire, 15, 319–345, https://doi.org/10.1071/WF05097, 2006.
Lutes, D. C., Keane, R. E., Caratti, J. F., Key, C. H., Benson, N. C., Sutherland, S., and Gangi, L. J.: FIREMON: Fire effects monitoring and inventory system, Gen. Tech. Rep. RMRS-GTR-164, US Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO, https://research.fs.usda.gov/treesearch/24042 (last access: 24 June 2022), 2006.
Mallinis, G., Mitsopoulos, I., and Chrysafi, I.: Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece, GIsci. Remote Sens., 55, 1–18, https://doi.org/10.1080/15481603.2017.1354803, 2018.
McArthur, A. G.: Fire behaviour in eucalypt forests, Commonwealth of Australia, Forest and Timber Bureau Leaflet 107, Canberra, ACT, Australia, https://www.cabidigitallibrary.org/doi/full/10.5555/19670604037 (last access: 1 July 2022), 1967.
Miller, J. D., Knapp, E. E., Key, C. H., Skinner, C. N., Isbell, C. J., Creasy, R. M., and Sherlock, J. W.: Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA, Remote Sens. Environ., 113, 645–656, https://doi.org/10.1016/j.rse.2008.11.009, 2009.
Morgan, P., Keane, R. E., Dillon, G. K., Jain, T. B., Hudak, A. T., Karau, E. C., Sikkink, P. G., Holden, Z. A., and Strand, E. K.: Challenges of assessing fire and burn severity using field measures, remote sensing and modelling, Int. J. Wildland Fire, 23, 1045–1060, https://doi.org/10.1071/WF13058, 2014.
Muñoz Sabater, J.: ERA5-Land hourly data from 1950 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.e2161bac, 2019.
Nolan, R. H., Boer, M. M., Collins, L., Resco de Dios, V., Clarke, H. G., Jenkins, M., Kenny, B., and Bradstock, R. A.: Causes and consequences of eastern Australia's 2019–20 season of mega-fires, Glob. Change Biol., 26, 1039–1041, https://doi.org/10.1111/gcb.14987, 2020.
Nolan, R. H., Collins, L., Leigh, A., Ooi, M. K., Curran, T. J., Fairman, T. A., Resco de Dios, V., and Bradstock, R.: Limits to post-fire vegetation recovery under climate change, Plant Cell Environ., 44, 3471–3489, https://doi.org/10.1111/pce.14176, 2021.
NSW Department of Climate Change, Energy, the Environment and Water: NPWS Fire History - Wildfires and Prescribed Burns, SEED [data set], https://datasets.seed.nsw.gov.au/dataset/1d05e145-80cb-4275-af9b-327a1536798d (last access: 8 June 2022), 2010.
Pausas, J. G. and Fernández-Muñoz, S.: Fire regime changes in the Western Mediterranean Basin: from fuel-limited to drought-driven fire regime, Climatic Change, 110, 215–226, https://doi.org/10.1007/s10584-011-0060-6, 2012.
Shine, J.: Statement regarding Australian bushfires, https://www.science.org.au/news-and-events/news-and-media-releases/australian-bushfires-why-they-are-unprecedented, last access: 4 February 2020.
Shortridge, A. and Messina, J.: Spatial structure and landscape associations of SRTM error, Remote Sens. Environ., 115, 1576–1587, https://doi.org/10.1016/j.rse.2011.02.017, 2011.
Soverel, N. O., Perrakis, D. D., and Coops, N. C.: Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada, Remote Sens. Environ., 114, 1896–1909, https://doi.org/10.1016/j.rse.2010.03.013, 2010.
Speer, M. S., Wiles, P., and Pepler, A.: Low pressure systems off the New South Wales coast and associated hazardous weather: establishment of a database, Aust. Meteorol. Ocean., 58, 29, https://doi.org/10.22499/2.5801.004, 2009.
Takeuchi, W., Darmawan, S., Shofiyati, R., Khiem, M. V., Oo, K. S., Pimple, U., and Heng, S.: Near-real time meteorological drought monitoring and early warning system for croplands in Asia, in: Asian Conference on Remote Sensing 2015: Fostering Resilient Growth in Asia, Quezon City, Metro Manila, Philippines, 24–28 October 2015, Vol. 1, 171–178, https://www.researchgate.net/profile/Uday-Pimple/publication/313647536_NEAR-REAL_TIME_
METEOROLOGICAL_DROUGHT_MONITORING_AND_
EARLY_WARNING_SYSTEM_FOR_CROPLANDS_IN_
ASIA/links/58a1675592851c7fb4bf51d3/NEAR-REAL-TIME-
METEOROLOGICAL-DROUGHT-MONITORING-AND-
EARLY-WARNING-SYSTEM-FOR-CROPLANDS-IN-ASIA.pdf (last access: 3 May 2022), 2015.
METEOROLOGICAL_DROUGHT_MONITORING_AND_
EARLY_WARNING_SYSTEM_FOR_CROPLANDS_IN_
ASIA/links/58a1675592851c7fb4bf51d3/NEAR-REAL-TIME-
METEOROLOGICAL-DROUGHT-MONITORING-AND-
EARLY-WARNING-SYSTEM-FOR-CROPLANDS-IN-ASIA.pdf (last access: 3 May 2022), 2015.
Tran, B. N., Tanase, M. A., Bennett, L. T., and Aponte, C.: Evaluation of spectral indices for assessing fire severity in Australian temperate forests, Remote Sens.-Basel, 10, 1680, https://doi.org/10.3390/rs10111680, 2018.
Ukkola, A. M., De Kauwe, M. G., Roderick, M. L., Abramowitz, G., and Pitman, A. J.: Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation, Geophys. Res. Lett., 47, e2020GL087820, https://doi.org/10.1029/2020GL087820, 2020.
Wang, C. and Glenn, N. F.: Estimation of fire severity using pre-and post-fire LiDAR data in sagebrush steppe rangelands, Int. J. Wildland Fire, 18, 848–856, https://doi.org/10.1071/WF08173, 2009.
Weiss, A.: Topographic position and landforms analysis, in: Poster presentation, ESRI user conference, San Diego, CA, USA, 9–13 July 2001, Vol. 200, https://www.jennessent.com/downloads/TPI-poster-TNC_18x22.pdf (last access: 4 April 2022), 2001.
Zheng, D., Jiang, Y., and Cheng, T.: UAV-based remote sensing technology in the rapid monitoring of forest fires, Int. J. Remote Sens., 40, 4257–4275, https://doi.org/10.11834/jrs.20210351, 2019.
Short summary
A framework combining a fire severity classification with a regression model to predict an indicator of fire severity derived from Landsat imagery (difference normalized burning ratio, dNBR) is proposed. The results show that the proposed predictive technique is capable of providing robust fire severity prediction information, which can be used for forecasting seasonal fire severity and, subsequently, impacts on biodiversity and ecosystems under projected future climate conditions.
A framework combining a fire severity classification with a regression model to predict an...
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