Andrés Cencerrado

Mitiga Solutions · Wildfire Research and Modelling

Social and mass media platforms (SMM) are essential tools for keeping people informed about health-promoting practices. However, the potential to spread misinformation or false rumors exists. These might influence preventive health behaviours and incite anxiety and/or fear among the population. A sample of 300 adults participated in a survey to und...

COVID-19 vaccines are essential to limit and eliminate the infectious disease. This research aims to identify strong vaccination resistance profiles and/or hesitation considering health, psychosocial, and COVID-related variables. A cross-sectional online survey (N = 300) was conducted in the context of strict COVID-related gathering and mobility re...

The transformation that COVID-19 has brought upon the world is unparalleled. The impact on mental health is equally unprecedented and yet unexplored in depth. An online-based survey was administered to 413 community-based adults during COVID-19 confinement to explore psychological impact and identify high risk profiles. Young females concerned abou...

Forest fires severally affect many ecosystems every year, leading to large environmental damages, casualties and economic losses. Established and emerging technologies are used to help wildfire analysts determine fire behavior and spread aiming at a more accurate prediction results and efficient use of resources in fire fighting. Natural hazards si...

Forest fires are a significant problem that every year causes important damages around the world. In order to efficiently tackle these hazards, one can rely on forest fire spread simulators. Any forest fire evolution model requires several input data parameters to describe the scenario where the fire spread is taking place, however, this data is us...

Predicting the propagation of forest fires is a crucial point to mitigate their effects. Therefore, several computational tools or simulators have been developed to predict the fire propagation. Such tools consider the scenario (topography, vegetation types, fire front situation), and the particular conditions where the fire is evolving (vegetation...

Many scientific works have focused on developing propagation models that predict forest fire behavior. These models require a precise knowledge of the environment where the fire is taking place. Geographical Information Systems allow us determining and building the different information layers that define the terrain and the fire. These data, along...

Forest fire propagation prediction is a crucial issue when fighting these hazards as efficiently as possible. Several propagation models have been developed and integrated in computer simulators. Such models require a set of input parameters that, in some cases, are difficult to know or even estimate precisely beforehand. Therefore, a calibration t...

The most important aspect that affects the reliability of environmental simulations is the un- certainty on the parameter settings describing the environmental conditions, which may involve important biases between simulation and reality. To relieve such arbitrariness, a two-stage pre- diction method was developed, based on the adjustment of the in...

Forest fires are a kind of natural hazard with a high number of occurrences in southern European countries. To avoid major damages and to improve forest fire management, one can use forest fire spread simulators to predict fire behavior. When providing forest fire predictions, there are two main considerations: accuracy and computation time. In the...

The EC-Earth climate model is a seamless Earth System Model (ESM) used to carry out climate research in 24 academic institutions and meteorological services from 11 countries in Europe. This model couples several components and it is continuously under development. In this work we present a study regarding the impact of the I/O and data management...

Southern European countries are severally affected by forest fires every year, which lead to very large environmental damages and great economic investments to recover affected areas. All affected countries invest lots of resources to minimize fire damages. Emerging technologies are used to help wildfire analysts determine fire behavior and spread...

A way to overcome data input uncertainty when simulating forest fire propagation, consists of calibrating inaccurate input data by applying computational-intensive methods. Genetic Algorithms (GA) are powerful and robust optimization techniques. However, their main drawback is their overall run time, which can easily become unacceptable, especially...

In this work we present the EC-Earth coupled climate model, which is a seamless Earth System Model (ESM) used to carry out climate research in 24 academic institutions and meteorological services from 11 countries in Europe. This model couples several components and it is continuously under development. As a coupled model, EC-Earth consists of seve...

This work details a framework developed to shorten the time needed to perform fire spread predictions. The methodology presented relies on a two-stage prediction strategy which introduces a calibration stage in order to relieve the effects of uncertainty on simulator input parameters. Early assessment of the response time and quality of the results...

Software simulators are developed to predict forest fire spread. Such simulators require several input parameters which usually are difficult to know accurately. The input data uncertainty can provoke a mismatch between the predicted forest fire spread and the actual evolution. To overcome this uncertainty a two stage prediction methodology is used...

The accurate prediction of forest fire propagation is a crucial issue to minimize its effects. Several models have been developed to determine the forest fire propagation. Simulators implementing such models require diverse input parameters to deliver predictions about fire propagation. However, the data describing the actual scenario where the fir...

This work presents a framework for assessing how the existing constraints at the time of attending an ongoing forest fire affect simulation results, both in terms of quality (accuracy) obtained and the time needed to make a decision. In the wildfire spread simulation and prediction area, it is essential to properly exploit the computational power o...

When an emergency occurs, hazard evolution simulators are a very helpful tool for the teams in charge of making decisions. These simulators need certain input data, which defines the characteristics of the environment where the emergency is taking place. This kind of data usually constitutes a big set of parameters, which have been previously recor...

A quick response becomes crucial in natural hazard management. When an emergency occurs, hazard evolution simulators are a very helpful tool for the teams in charge of making decisions. To perform the simulations, they rely on data which usually constitutes a big set of parameters, which have been previously recorded from observations, usually comi...

This work faces the problem of quality and prediction time assessment in a Dynamic Data Driven Application System (DDDAS) for predicting natural hazard evolution. Natural hazard management is undoubtedly a relevant area where systems modeling and numerical analysis take a great prominence. Modeling such systems is a very hard problem to tackle. Bes...

This work faces the problem of quality and prediction time assessment in a Dynamic Data Driven Application System (DDDAS) for predicting natural hazard evolution. In particular, we used forest fire spread prediction as acase study to show the applicability of the methodology. The improvement on the prediction quality when using a two-stage DDDAS pr...

Natural hazard management is undoubtedly a relevant application area in which Artificial Intelligence can play a very important role. In the field of physical systems modeling, there exist several tools for mitigating damages caused by this kind of phenomena, such as hazard evolution simulators. These simulators need certain input data, which define t...

Virtualization technologies provide flexible execution environments that could bring important benefits for computational problems with strong deadlines. Large Grid infrastructures are becoming available nowadays and they could be a suitable environment to run such on-demand computations that might be used in decision-making processes. For these co...

Execution of parallel and interactive applications on a Grid environment is a challenging problem that requires the cooperation of several middleware tools and services. In this paper, we present our experiences in the development of Cross-Broker, a job management service that provides transparent and reliable support for such types of applications...