Article
Forestry
Adrian Cardil, Santiago Monedero, Phillip Selegue, Miguel Angel Navarrete, Sergio De-miguel, Scott Purdy, Geoff Marshall, Tim Chavez, Kristen Allison, Raul Quilez, Macarena Ortega, Carlos A. Silva, Joaquin Ramirez
Summary: This study assessed the performance of fire spread models used in California through analyzing the rate of spread (ROS) of 1853 wildfires. The models were found to accurately predict fire spread in operational environments, but still had biases in certain environmental variables.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2023)
Article
Mathematics, Applied
Jung-Chao Ban, Jyy- Hong, Yu-Liang Wu
Summary: This article compares the long-term behavior of a spread model before and after a type becomes frozen. It provides the spread rates of a 1-spread model with one frozen symbol and shows that this result holds for more general settings. Numerical experiments support the theory.
Article
Multidisciplinary Sciences
Anabelle W. Cardoso, Sally Archibald, William J. Bond, Corli Coetsee, Matthew Forrest, Navashni Govender, David Lehmann, Loic Makaga, Nokukhanya Mpanza, Josue Edzang Ndong, Aurelie Flore Koumba Pambo, Tercia Strydom, David Tilman, Peter D. Wragg, A. Carla Staver
Summary: This study demonstrates that an infection model captures the spreading pattern of individual fires better than competing models. The proportion of burned landscape can be described by measurements of grass biomass, fuel moisture, and vapor pressure deficit. Averaging across variability results in quasi-linear patterns regionally.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Mathematics, Interdisciplinary Applications
Jung-Chao Ban, Chih-Hung Chang, Jyy- Hong, Yu-Liang Wu
Summary: This paper presents a mathematical model to predict the spread of a pandemic, utilizing both random and deterministic models based on Markov processing. The deterministic model estimates the proportion of individuals in a specific generation given any initial condition, while the stochastic model has more empirical impact. The study establishes a transition model connecting stochastic and deterministic models, highlighting the relationship between different spread patterns during epidemic periods.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Forestry
Yunlin Zhang, Lingling Tian
Summary: This study evaluated the applicability of three methods, direct use of the Rothermel model, re-estimation of Rothermel parameters, and model reform, in predicting forest fire spread in Karst ecosystems. It found that the direct use of the Rothermel model is not practical, with relative errors as high as 50%. However, there were no significant differences between re-estimation of parameters and model reform, but the reform model showed advantages of simplicity and lower errors. The research proposes a new method for predicting fire spread rate in Karst ecosystems, which is significant for understanding and calculating the rate of forest fire spread in the region.
Article
Computer Science, Interdisciplinary Applications
K. C. Ujjwal, Jagannath Aryal, Saurabh Garg, James Hilton
Summary: Environmental models often involve inherent uncertainties, which can be quantified using global sensitivity analysis (GSA) methods such as Morris, Sobol, FAST, and PAWN. The choice of GSA method depends on the model complexity and computational constraints, with a trade-off between convergence and computational costs. Sobol method is recommended for detailed sensitivity information, while Morris or PAWN methods are preferred for balanced trade-off under computational constraints.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Multidisciplinary Sciences
Yang Chen, Stijn Hantson, Niels Andela, Shane R. Coffield, Casey A. Graff, Douglas C. Morton, Lesley E. Ott, Efi Foufoula-Georgiou, Padhraic Smyth, Michael L. Goulden, James T. Randerson
Summary: This study develops a novel object-based system to track individual wildfires using satellite data, improving our understanding and quantification of wildfire spread, behavior, and impacts. The system successfully mapped the history of California wildfires from 2012 to 2020.
Article
Mathematics, Applied
Jyy- Hong
Summary: In this paper, a spread model using multi-type branching processes is introduced to study the evolution of the population during a pandemic with different types of individuals. The study focuses on the growth rate and spread rate of the population under certain conditions of maximal eigenvalues and eigenvectors. Theoretical results are supported by numerical examples and simulations.
Article
Thermodynamics
Zhenlin Li, Qiang Wang, Haihang Li, Fei Tang
Summary: This paper focused on studying the effect of sand on the spread radius and burning rate of spill fires. Through experiments and analysis, it was found that sand can reduce the spread of spill fires, enhance heat conduction feedback, and decrease heat loss. The results contribute to the understanding of the effectiveness of sand in impeding the spread of spill fires and provide a theoretical basis for extinguishing such fires.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2023)
Article
Forestry
Qingkuo Meng, Hao Lu, Yongjian Huai, Haifeng Xu, Siyu Yang
Summary: This study proposes a lightweight forest fire spread method based on cellular automata, which allows for simulating forest-scale fire propagation and analyzing the factors that affect forest fire spread. It also explores various forms of fire extinguishing methods in the virtual environment, enhancing the immersion and realism of the 3D forest fire scene.
Article
Construction & Building Technology
Jiaqiang Han, Fei Wang, Zihao Wang, Pengqiang Geng, Fang Liu, Miaocheng Weng
Summary: The study investigated the effects of elevated pool fires at different heights, revealing significant influences of fire height on burning rate and temperature. Different effects were observed under natural and longitudinal ventilation conditions, and smoke stratification was promoted by fire elevation.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Biology
Jung-Chao Ban, Jyy- Hong, Yu-Liang Wu
Summary: This paper focuses on analyzing the spread of two specific models, one from a deterministic perspective and the other from a random perspective. By using substitution dynamical systems and branching process, the spread rate of each pattern is discussed. Based on this, a comparison between the two spreading processes is made according to their models, and explanations are proposed for the higher frequency of a pattern in one model than the other. These results are supported by numerical evidence later in the article.
JOURNAL OF MATHEMATICAL BIOLOGY
(2023)
Article
Environmental Sciences
Gavin M. Schag, Douglas A. Stow, Philip J. Riggan, Atsushi Nara
Summary: The study evaluates the spatial sampling and statistical aspects of landscape-level wildfire rate of spread (ROS) estimates derived from airborne thermal infrared imagery. The findings reveal that the relationships between covariates and ROS estimates are substantially non-stationary on landscape scales. The study highlights the importance of directional slope as the most strongly associated covariate of ROS for the analyzed imagery sequences, regardless of the size of landscape sampling unit.
Article
Forestry
Daniel D. B. Perrakis, Miguel G. Cruz, Martin E. Alexander, Chelene C. Hanes, Dan K. Thompson, Stephen W. Taylor, Brian J. Stocks
Summary: This study aims to develop models for predicting crown fire occurrence based on the CFIS system approach and logistic regression analysis of fire environment variables. The final models achieved an accuracy of 92% and offer improved accuracy and flexibility.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2023)
Article
Engineering, Environmental
Haihang Li, Zhenlin Li, Qiang Wang, Yajun Huang, Fei Tang
Summary: A series of experiments were carried out to study the mechanism of ethanol spill fire on sand substrate. The results showed that sand affected the heat transfer process and steady burning rate of the fire by changing the proportion of heat transfer modes. The obstructive effect of sand on fuel spread was also analyzed.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Miguel G. Cruz, Martin E. Alexander, Andrew L. Sullivan, James S. Gould, Musa Kilinc
ENVIRONMENTAL MODELLING & SOFTWARE
(2018)
Article
Forestry
J. J. Hollis, W. L. McCaw, M. G. Cruz
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2018)
Article
Forestry
Miguel G. Cruz, Martin E. Alexander
ANNALS OF FOREST SCIENCE
(2019)
Letter
Engineering, Multidisciplinary
M. G. Cruz, M. E. Alexander
Article
Forestry
Martin E. Alexander, Miguel G. Cruz
FORESTRY CHRONICLE
(2020)
Article
Forestry
Francois Joseph Chatelon, Jacques Henri Balbi, Miguel G. Cruz, Dominique Morvan, Jean Louis Rossi, Carmen Awad, Nicolas Frangieh, Jacky Fayad, Thierry Marcelli
Summary: The 'Balbi model' is a simplified and computationally efficient model for simulating fire propagation accurately. It takes into account radiation and convection heat transfer processes to describe the steady-state spread rate of surface fires. The improved model, calibrated and tested with experimental data, demonstrates good predictive capability for outdoor fires with different fuel types and scales. Compared to older versions and empirical models, the improved Balbi model remains physics-based, faster than real time, and fully predictive.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2022)
Article
Forestry
Miguel G. Cruz, N. Phillip Cheney, James S. Gould, W. Lachlan McCaw, Musa Kilinc, Andrew L. Sullivan
Summary: Developing a reliable and accurate model for the speed of wildfire propagation is crucial for timely prediction and devising suppression strategies. The empirical model derived in this study for eucalypt forests incorporates various environmental variables and shows mean absolute percentage errors between 35 and 46% against the data used for its development.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2022)
Article
Forestry
Miguel G. Cruz, Martin E. Alexander, Paulo M. Fernandes
Summary: The study suggests that there is a gradual diminishing effect of fuel characteristics on fire spread in certain forest ecosystem types, but this effect is not observable under extreme fire danger conditions. Empirical-based fire spread models often fail to adequately capture this effect.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2022)
Article
Forestry
Sadegh Khanmohammadi, Mehrdad Arashpour, Emadaldin Mohammadi Golafshani, Miguel G. G. Cruz, Abbas Rajabifard
Summary: This study aims to predict the onset of fire propagation and the type of fire behaviour in southern Australian semiarid shrublands using machine-learning methods. The results demonstrate that Support Vector Machine is the optimum machine learning classifier and accurately predicts fire spread sustainability and active crown fire propagation.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2023)
Article
Ecology
Miguel G. Cruz, Martin E. Alexander, Musa Kilinc
Summary: An analysis of wildfire data from southern Australia revealed a simple relationship between fire spread rate and wind speed, with the forward rate of fire spread being approximately 20% of the average 10-m open wind speed. The resulting rule of thumb performed comparably to established fire spread models under various burning conditions, making it a useful tool for estimating fire spread in grassland fuel conditions.
Article
Forestry
Martin E. Alexander, Miguel G. Cruz
Summary: This state-of-knowledge review examines the underlying assumptions and limitations associated with the inter-relationships among four widely used descriptors of surface fire behaviour and post-fire impacts in wildland fire science and management. The overwhelming tendency within the wildland fire community to regard certain fire behavior models as universal in nature has been challenged by research showing the strong influence of fuelbed structure on these relationships. Consideration of fuel complex specific-type models is necessary to accurately understand the linkages between fire behavior and post-fire impacts.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2021)
Article
Computer Science, Interdisciplinary Applications
Miguel G. Cruz, Martin E. Alexander, Paulo M. Fernandes, Musa Kilinc, Angelo Sil
ENVIRONMENTAL MODELLING & SOFTWARE
(2020)
Article
Forestry
Miguel G. Cruz, Andrew L. Sullivan, Rachel Bessell, James S. Gould
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2020)
Article
Forestry
Miguel G. Cruz, Richard J. Hurley, Rachel Bessell, Andrew L. Sullivan
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2020)
Article
Forestry
Miguel G. Cruz, Martin E. Alexander, Andrew L. Sullivan
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2018)
Article
Computer Science, Interdisciplinary Applications
Jeffrey Wade, Christa Kelleher, Barret L. Kurylyk
Summary: This study developed a physically-based water temperature model coupled with the National Water Model (NWM) to assess the potential for water temperature prediction to be incorporated into the NWM at the continental scale. By evaluating different model configurations of increasing complexity, the study successfully simulated hourly water temperatures in the forested headwaters of H.J. Andrews Experimental Forest in Oregon, USA, providing a basis for integrating water temperature simulation with predictions from the NWM.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Shaun SH. Kim, Lucy A. Marshall, Justin D. Hughes, Lynn Seo, Julien Lerat, Ashish Sharma, Jai Vaze
Summary: A major challenge in hydrologic modelling is producing reliable uncertainty estimates outside of calibration periods. This research addresses the challenge by improving model structures and error models to more reliably estimate uncertainty. The combination of the RBS model and SPUE produces statistically reliable predictions and shows better matching performance in tests.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Juan Pedro Carbonell-Rivera, Javier Estornell, Luis Angel Ruiz, Pablo Crespo-Peremarch, Jaime Almonacid-Caballer
Summary: This study presents Class3Dp, a software for classifying vegetation species in colored point clouds. The software utilizes geometric, spectral, and neighborhood features along with machine learning methods to classify the point cloud, allowing for the recognition of species composition in an ecosystem.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhi Li, Daniel Caviedes-Voullieme, Ilhan Oezgen-Xian, Simin Jiang, Na Zheng
Summary: The optimal strategy for solving the Richards equation numerically depends on the specific problem, particularly when using GPUs. This study investigates the parallel performance of four numerical schemes on both CPUs and GPUs. The results show that the scaling of Richards solvers on GPUs is influenced by various factors. Compared to CPUs, parallel simulations on GPUs exhibit significant variation in scaling across different code sections, with poorly-scaled components potentially impacting overall performance. Nonetheless, using GPUs can greatly enhance computational speed, especially for large-scale problems.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ludovic Cassan, Leo Pujol, Paul Lonca, Romain Guibert, Helene Roux, Olivier Mercier, Dominique Courret, Sylvain Richard, Pierre Horgue
Summary: Methods and algorithms for measuring stream surface velocities have been continuously developed over the past five years to adapt to specific flow typologies. The free software ANDROMEDE allows easy use and comparison of these methods with image processing capabilities designed for measurements in natural environments and with unmanned aerial vehicles. The validation of the integrated algorithms is presented on three case studies that represent the targeted applications: the study of currents for eco-hydraulics, the measurement of low water flows and the diagnosis of hydraulic structures. The field measurements are in very good agreement with the optical measurements and demonstrate the usefulness of the tool for rapid flow diagnosis for all the intended applications.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Mariia Kozlova, Robert J. Moss, Julian Scott Yeomans, Jef Caers
Summary: This paper introduces a framework for quantitative sensitivity analysis using the SimDec visualization method, and tests its effectiveness on decision-making problems. The framework captures critical information in the presence of heterogeneous effects, and enhances its practicality by introducing a formal definition and classification of heterogeneous effects.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Chad R. Palmer, Denis Valle, Edward V. Camp, Wendy-Lin Bartels, Martha C. Monroe
Summary: Simulation games have been used in natural resource management for education and communication purposes, but not for data collection. This research introduces a new design process which involves stakeholders and emphasizes usability, relevance, and credibility testing criteria. The result is a finalized simulation game for future research.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Tao Wang, Chenming Zhang, Ye Ma, Harald Hofmann, Congrui Li, Zicheng Zhao
Summary: This study used numerical modeling to investigate the formation process of iron curtains under different freshwater and seawater conditions. It was found that Fe(OH)3 accumulates on the freshwater side, while the precipitation is inhibited on the seaward side due to high H+ concentrations. These findings enhance our understanding of iron transformation and distribution in subterranean estuaries.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Grant Hutchings, James Gattiker, Braden Scherting, Rodman R. Linn
Summary: Computational models for understanding and predicting fire in wildland and managed lands are becoming increasingly impactful. This paper addresses the characterization and population of mid-story fuels, which are not easily observable through traditional survey or remote sensing. The authors present a methodology to populate the mid-story using a generative model for fuel placement, which can be calibrated based on limited observation datasets or expert guidance. The connection of terrestrial LiDAR as the observations used to calibrate the generative model is emphasized. Code for the methods in this paper is provided.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Saswata Nandi, Pratiman Patel, Sabyasachi Swain
Summary: IMDLIB is an open-source Python library that simplifies the retrieval and processing of gridded meteorological data from IMD, enhancing data accessibility and facilitating hydro-climatic research and analysis.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Pengfei Wu, Jintao Liu, Meiyan Feng, Hu Liu
Summary: In this paper, a new flow distance algorithm called D infinity-TLI is proposed, which accurately estimates flow distance and width function using a two-segment-distance strategy and triangulation with linear interpolation method. The evaluation results show that D infinity-TLI outperforms existing algorithms and has a low mean absolute relative error.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)