Architecture of a pan-European framework for Integrated Soil Water Erosion Assessment

Soil erosion implications on future food security are gaining global attention because in many areas worldwide there is an imbalance between soil loss and its subsequent deposition. Soil erosion is a complex phenomenon affected by many factors such as climate, topography and land cover (in particular forest resources, natural vegetation and agriculture) while directly influencing water sediment transport, the quality of water resources and water storage loss. A modeling architecture, based on the Revised Universal Soil Loss Equation, is proposed and applied to evaluate and validate at regional scale potential and actual soil water erosion, enabling it to be linked to other involved natural resources. The methodology benefits from the array programming paradigm with semantic constraints (lightweight array behavioural contracts provided by the Mastrave library) to concisely implement models as composition of interoperable modules and to process heterogeneous data.JRC.H.3-Forest Resources and Climat

Architecture of Environmental Risk Modelling: for a faster and more robust response to natural disasters

Demands on the disaster response capacity of the European Union are likely to increase, as the impacts of disasters continue to grow both in size and frequency. This has resulted in intensive research on issues concerning spatially-explicit information and modelling and their multiple sources of uncertainty. Geospatial support is one of the forms of assistance frequently required by emergency response centres along with hazard forecast and event management assessment. Robust modelling of natural hazards requires dynamic simulations under an array of multiple inputs from different sources. Uncertainty is associated with meteorological forecast and calibration of the model parameters. Software uncertainty also derives from the data transformation models (D-TM) needed for predicting hazard behaviour and its consequences. On the other hand, social contributions have recently been recognized as valuable in raw-data collection and mapping efforts traditionally dominated by professional organizations. Here an architecture overview is proposed for adaptive and robust modelling of natural hazards, following the Semantic Array Programming paradigm to also include the distributed array of social contributors called Citizen Sensor in a semantically-enhanced strategy for D-TM modelling. The modelling architecture proposes a multicriteria approach for assessing the array of potential impacts with qualitative rapid assessment methods based on a Partial Open Loop Feedback Control (POLFC) schema and complementing more traditional and accurate a-posteriori assessment. We discuss the computational aspect of environmental risk modelling using array-based parallel paradigms on High Performance Computing (HPC) platforms, in order for the implications of urgency to be introduced into the systems (Urgent-HPC).Comment: 12 pages, 1 figure, 1 text box, presented at the 3rd Conference of Computational Interdisciplinary Sciences (CCIS 2014), Asuncion, Paragua

Toward Open Science at the European Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling

[Excerpt] Interfacing science and policy raises challenging issues when large spatial-scale (regional, continental, global) environmental problems need transdisciplinary integration within a context of modelling complexity and multiple sources of uncertainty. This is characteristic of science-based support for environmental policy at European scale, and key aspects have also long been investigated by European Commission transnational research. Approaches (either of computational science or of policy-making) suitable at a given domain-specific scale may not be appropriate for wide-scale transdisciplinary modelling for environment (WSTMe) and corresponding policy-making. In WSTMe, the characteristic heterogeneity of available spatial information and complexity of the required data-transformation modelling (D-TM) appeal for a paradigm shift in how computational science supports such peculiarly extensive integration processes. In particular, emerging wide-scale integration requirements of typical currently available domain-specific modelling strategies may include increased robustness and scalability along with enhanced transparency and reproducibility. This challenging shift toward open data and reproducible research (open science) is also strongly suggested by the potential - sometimes neglected - huge impact of cascading effects of errors within the impressively growing interconnection among domain-specific computational models and frameworks. Concise array-based mathematical formulation and implementation (with array programming tools) have proved helpful in supporting and mitigating the complexity of WSTMe when complemented with generalized modularization and terse array-oriented semantic constraints. This defines the paradigm of Semantic Array Programming (SemAP) where semantic transparency also implies free software use (although black-boxes - e.g. legacy code - might easily be semantically interfaced). A new approach for WSTMe has emerged by formalizing unorganized best practices and experience-driven informal patterns. The approach introduces a lightweight (non-intrusive) integration of SemAP and geospatial tools - called Geospatial Semantic Array Programming (GeoSemAP). GeoSemAP exploits the joint semantics provided by SemAP and geospatial tools to split a complex D-TM into logical blocks which are easier to check by means of mathematical array-based and geospatial constraints. Those constraints take the form of precondition, invariant and postcondition semantic checks. This way, even complex WSTMe may be described as the composition of simpler GeoSemAP blocks. GeoSemAP allows intermediate data and information layers to be more easily and formally semantically described so as to increase fault-tolerance, transparency and reproducibility of WSTMe. This might also help to better communicate part of the policy-relevant knowledge, often diffcult to transfer from technical WSTMe to the science-policy interface. [...

Free and Open Source Software underpinning the European Forest Data Centre

Worldwide, governments are growingly focusing on free and open source software (FOSS) as a move toward transparency and the freedom to run, copy, study, change and improve the software. The European Commission (EC) is also supporting the development of FOSS [...]. In addition to the financial savings, FOSS contributes to scientific knowledge freedom in computational science (CS) and is increasingly rewarded in the science-policy interface within the emerging paradigm of open science. Since complex computational science applications may be affected by software uncertainty, FOSS may help to mitigate part of the impact of software errors by CS community- driven open review, correction and evolution of scientific code. The continental scale of EC science-based policy support implies wide networks of scientific collaboration. Thematic information systems also may benefit from this approach within reproducible integrated modelling. This is supported by the EC strategy on FOSS: "for the development of new information systems, where deployment is foreseen by parties outside of the EC infrastructure, [F]OSS will be the preferred choice and in any case used whenever possible". The aim of this contribution is to highlight how a continental scale information system may exploit and integrate FOSS technologies within the transdisciplinary research underpinning such a complex system. A European example is discussed where FOSS innervates both the structure of the information system itself and the inherent transdisciplinary research for modelling the data and information which constitute the system content. [...

Semantic Array Programming for Environmental Modelling: Application of the Mastrave Library

Environmental datasets grow in size and specialization while models designed for local scale are often unsuitable at regional/continental scale. At regional scale, data are usually available as georeferenced collections of spatially distributed despite semantically atomic information. Complex data intrinsically impose modellers to manipulate nontrivial information structures. For example, multi-dimensional arrays of time series may be composed by slices of raster spatial matrices for each time step, whilst heterogeneous collections of uneven arrays are common when dealing with data analogous to precipitation events, and these structures may ask for integration at several spatial scales, projections and temporal extents. Interestingly, it might be far more difficult to practically implement such a complexity rather than conceptually describe it: a subset of modelling generalizations may deal more with abstraction rather than with the explosion of lines of code. Many environmental modelling algorithms are composed by chains of data-transformations or trees of domain specific sub-algorithms. Concisely expressing them without the need for paying attention on the enormous set of spatio-temporal details, is a highly recommendable practice in both mathematical formulation and implementation. The use of semantic array programming paradigm is here exemplified as a powerful conceptual and practical (with the free software library Mastrave) tool for easing scalability and semantic integration in environmental modelling. Array programming, AP, is widely used for its computational effectiveness but often underexploited in reducing the gap between mathematical notation and algorithm implementations, i.e. by promoting arrays (vectors, matrices, tensors) as atomic quantities with extremely compact manipulating operators. Coherent array-based mathematical description of models can simplify complex algorithm prototyping while moving mathematical reasoning directly into the source code – because of its substantial size reduction – where the mathematical description is actually expressed in a completely formalized and reproducible way. The proposed paradigm suggests to complement the characteristic AP weak typing with semantics, both by composing generalized modular sub-models and via array oriented – thus concise – constraints. The Mastrave library use is exemplified with a regional scale benchmark application to local-average invariant (LAI) downscaling of climate raster data. Unnecessary errors frequently introduced by non-LAI upsampling are shown to be easily detected and removed when the scientific modelling practice is terse enough to let mathematical reasoning and model coding merge together.JRC.H.3-Forest Resources and Climat

Free and open source software underpinning the european forest data centre

Excerpt: Worldwide, governments are growingly focusing on free and open source software (FOSS) as a move toward transparency and the freedom to run, copy, study, change and improve the software. The European Commission (EC) is also supporting the development of FOSS [...]. In addition to the financial savings, FOSS contributes to scientific knowledge freedom in computational science (CS) and is increasingly rewarded in the science-policy interface within the emerging paradigm of open science. Since complex computational science applications may be affected by software uncertainty, FOSS may help to mitigate part of the impact of software errors by CS community- driven open review, correction and evolution of scientific code. The continental scale of EC science-based policy support implies wide networks of scientific collaboration. Thematic information systems also may benefit from this approach within reproducible integrated modelling. This is supported by the EC strategy on FOSS: "for the development of new information systems, where deployment is foreseen by parties outside of the EC infrastructure, [F]OSS will be the preferred choice and in any case used whenever possible". The aim of this contribution is to highlight how a continental scale information system may exploit and integrate FOSS technologies within the transdisciplinary research underpinning such a complex system. A European example is discussed where FOSS innervates both the structure of the information system itself and the inherent transdisciplinary research for modelling the data and information which constitute the system content. [...

Free and open source software underpinning the european forest data centre

Excerpt: Worldwide, governments are growingly focusing on free and open source software (FOSS) as a move toward transparency and the freedom to run, copy, study, change and improve the software. The European Commission (EC) is also supporting the development of FOSS [...]. In addition to the financial savings, FOSS contributes to scientific knowledge freedom in computational science (CS) and is increasingly rewarded in the science-policy interface within the emerging paradigm of open science. Since complex computational science applications may be affected by software uncertainty, FOSS may help to mitigate part of the impact of software errors by CS community- driven open review, correction and evolution of scientific code. The continental scale of EC science-based policy support implies wide networks of scientific collaboration. Thematic information systems also may benefit from this approach within reproducible integrated modelling. This is supported by the EC strategy on FOSS: "for the development of new information systems, where deployment is foreseen by parties outside of the EC infrastructure, [F]OSS will be the preferred choice and in any case used whenever possible". The aim of this contribution is to highlight how a continental scale information system may exploit and integrate FOSS technologies within the transdisciplinary research underpinning such a complex system. A European example is discussed where FOSS innervates both the structure of the information system itself and the inherent transdisciplinary research for modelling the data and information which constitute the system content. [...

Forest fire danger extremes in Europe under climate change: variability and uncertainty

Forests cover over a third of the total land area of Europe. In recent years, large forest fires have repeatedly affected Europe, in particular the Mediterranean countries. Fire danger is influenced by weather in the short term, and by climate when considering longer time intervals. In this work, the emphasis is on the direct influence on fire danger of weather and climate. For climate analysis at the continental scale, a daily high-emission scenario (RCP 8.5) was considered up to the end of the century, and a mitigation scenario that limits global warming to 2 °C was also assessed. To estimate fire danger, the Canadian Fire Weather Index (FWI) system was used. FWI provides a uniform numerical rating of relative fire potential, by combining the information from daily local temperature, wind speed, relative humidity, and precipitation values. The FWI is standardised to consider a reference fuel behaviour irrespective of other factors. It is thus well suited to support harmonised comparisons, to highlight the role of the varying climate in the component of fire danger that is driven by weather. RESULTS. Around the Mediterranean region, climate change will reduce fuel moisture levels from present values, increasing the weather-driven danger of forest fires. Furthermore, areas exhibiting low moisture will extend further northwards from the Mediterranean, and the current area of high fuel moisture surrounding the Alps will decrease in size. Projected declines in moisture for Mediterranean countries are smaller with mitigation that limits global warming to 2 °C, but a worsening is still predicted compared with present. There is a clear north-south pattern of deep fuel moisture variability across Europe in both climate change scenarios. Areas at moderate danger from forest fires are pushed north to central Europe by climate change. Relatively little change is expected in weather-driven fire danger across northern Europe. However, mountain systems show a fast pace of change. ADAPTATION OPTIONS. Key strategies to be considered may include vegetation management to reduce the likelihood of severe fires, as well as fuel treatments to mitigate fire hazard in dry forests. These measures should be adapted to the different forest ecosystems and conditions. Limited, preliminary knowledge covers specific but essential aspects. Evidence suggests that some areas protected for biodiversity conservation may be affected less by forest fires than unprotected areas, despite containing more combustible material. Specific typologies of old-growth forests may be associated with lower fire severity than densely stocked even-aged young stands, and some tree plantations might be more subject to severe fire compared with multi-aged forests. Particular ecosystems and vegetation associations may be better adapted for post-fire recovery, as long as the interval between fires is not too short. Therefore, deepening the understanding of resistance, resilience and habitat suitability of mixtures of forest tree species is recommended. Human activity (accidental, negligent or deliberate) is one of the most common causes of fire. For this reason, the main causes of fire should be minimized, which includes analysing the social and economic factors that lead people to start fires, increasing awareness of the danger, encouraging good behaviour and sanctioning offenders. LIMITATIONS. Bias correction of climate projections is known to be a potential noticeable source of uncertainty in the predicted bioclimatic anomalies to which vegetation is sensitive. In particular, the analysis of fire danger under climate change scenarios may be critically affected by climatic modelling uncertainty. This work did not explicitly model adaptation scenarios for forest fire danger because ecosystem resilience to fire is uneven and its assessment relies on factors that are difficult to model numerically. Furthermore, a component of the proposed climate-based characterization of future wildfire potential impacts may be linked to the current distribution of population, land cover and use in Europe. The future distribution of these factors is likely to be different from now.JRC.E.1-Disaster Risk Managemen

Robust modelling of the impacts of climate change on the habitat suitability of forest tree species

In Europe, forests play a strategic multifunctional role, serving economic, social and environmental purposes. However, forests are among the most complex systems and their interaction with the ongoing climate change – and the multifaceted chain of potential cascading consequences for European biodiversity, environment, society and economy – is not yet well understood. The JRC PESETA project series proposes a consistent multi-sectoral assessment of the impacts of climate change in Europe. Within the PESETA II project, a robust methodology is introduced for modelling the habitat suitability of forest tree species (2071-2100 time horizon). Abies alba (the silver fir) is selected as a case study: a main European tree species often distributed in bioclimatically complex areas, spanning over various forest types and with multiple populations adapted to different conditions. The modular modelling architecture is based on relative distance similarity (RDS) estimates which link field observations with bioclimatic patterns, projecting their change under climate scenarios into the expected potential change of suitable habitat for tree species. Robust management of uncertainty is also examined. Both technical and interpretation core aspects are presented in an integrated overview. The semantics of the array of quantities under focus and the uneven sources of uncertainty at the continental scale are discussed (following the semantic array programming paradigm), with an effort to offer some minimal guidance on terminology, meaning and methodological limitations not only of the proposed approach, but also of the broad available literature – whose heterogeneity and partial ambiguity might potentially reverberate at the science-policy interface. ► How to cite: ◄ de Rigo, D., Caudullo, G., San-Miguel-Ayanz, J, Barredo, J.I., 2017. Robust modelling of the impacts of climate change on the habitat suitability of forest tree species. Publication Office of the European Union, Luxembourg. 58 pp. ISBN:978-92-79-66704-6 , https://doi.org/10.2760/29650

Architecture of a pan-European framework for Integrated Soil Water Erosion Assessment

Soil erosion implications on future food security are gaining global attention because in many areas worldwide there is an imbalance between soil loss and its subsequent deposition. Soil erosion is a complex phenomenon affected by many factors such as climate, topography and land cover (in\ud particular forest resources, natural vegetation and agriculture) while directly influencing water sediment transport, the quality of water resources and water storage loss. A modeling architecture, based on the Revised Universal Soil Loss Equation, is proposed and applied to evaluate and validate at regional scale potential and actual soil water erosion, enabling it to be linked to other involved natural resources. The methodology benefits from the array programming paradigm with semantic constraints (lightweight array behavioural contracts provided by the Mastrave library) to concisely implement models as composition of interoperable modules and to process heterogeneous data.\u