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Spatially and temporal explicit forecast model of broad front bird migration using radar surveillance data

English title Spatially and temporal explicit forecast model of broad front bird migration using radar surveillance data
Applicant Abhari Reza
Number 179053
Funding scheme Project funding (Div. I-III)
Research institution Institut für Energietechnik ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Other disciplines of Engineering Sciences
Start/End 01.05.2018 - 30.04.2019
Approved amount 64'046.00
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All Disciplines (2)

Discipline
Other disciplines of Engineering Sciences
Environmental Research

Keywords (6)

Large-scale bird migration ; Behaviour models; Mesoscale weather ; Radar data; Collision risk; Renewable energy

Lay Summary (German)

Lead
Kollisionen von Zugvögeln mit Windturbinen können reduziert werden, wenn bekannt ist wann und wo die Vögel unterwegs sind. Unser europaweites Vorhersage-Model soll unter Berücksichtigung der Wetterbedingungen und unter der Verwendung von aktuellen Radardaten ermöglichen das zeitliche und räumlichen Auftreten der nachts ziehenden Vögel vorherzusagen.
Lay summary

Das übergeordnete Ziel des Projekts ist es, die Komplexität des europaweiten Vogelzugs zu beschreiben, sowie Wechselwirkungen mit der Entwicklung sowie dem Betrieb erneuerbarer Energien zu analysieren. Da ein Zuwachs erneuerbarer Energien unverkennbar ist und diese einen negativen Einfluss auf Vogelpopulationen haben (z.B. durch Kollisionen von Vögeln mit Windturbinen), sollen Gebiete und Zeiträume mit hohem Kollisionsrisiko identifiziert werden. Dies soll zur Nachhaltigkeit erneuerbarer Energien beitragen. Ein seit Kurzem verfügbares europaweites Netz von Radardaten über die Anzahl und Flughöhe der Zugvögel ermöglicht es realistische Ausgangsbedingungen der Simulation zu definieren und die Simulationsresultate zu validieren. Die Resultate erlauben eine zeitliche und räumliche Quantifizierung des Vogelzuges und des damit verbundenen Kollisionsrisikos. Eine Verfeinerung der räumlichen Auflösung wird im Anschluss an das Projekt den praktischen Nutzen des Modells verbessern.

Das Projekt liefert Erkenntnisse zum generellen Verständnis von Biomassen-Verschiebungen über den europäischen Kontinent und schafft durch die Nutzung kostspielig erhobener Umweltdaten (Wetterradar-Netzwerk) einen gesellschaftlichen Mehrwert für diese Investitionen. Die Ergebnisse sind geeignet Massnahmen zu unterstützen um Kollisionen von Vögeln mit Windkraftanlagen, aber auch mit Flugzeugen möglichst effizient zu reduzieren.

Direct link to Lay Summary Last update: 18.04.2018

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Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
2019 conference of the British Ornithologists’ Union Talk given at a conference How environment affects bird migration patterns over Europe 27.03.2019 Warwick, Great Britain and Northern Ireland Aurbach Annika;


Associated projects

Number Title Start Funding scheme
153733 Combining Electricity Models (AFEM-MODEL) 01.11.2014 NRP 70 Energy Turnaround
154041 Technical evaluation of multi-energy-hub systems integration at neighbourhood scale IMES-TEC 01.11.2014 NRP 70 Energy Turnaround
184120 GloBAM - Towards monitoring, understanding and forecasting global biomass flows of aerial migrants 01.04.2019 BiodivERsA
167333 weObserve: Integrating Citizen Observers and High Throughput Sensing Devices for Big Data Collection, Integration, and Analysis 01.05.2017 NRP 75 Big Data
153774 Infrastructure for Future Electricity Markets (AFEM-INFRA) 01.01.2015 NRP 70 Energy Turnaround

Abstract

Every year about five billion birds migrate seasonally between Europe and Northern Africa, or even as far as sub-Saharan Africa, to escape harsh conditions by migrating to more favourable areas during the nonbreeding season. During this mass movement where birds cover distances of thousands of kilometres, mortality increases due to collisions with wind turbines. Current technologies like radar data and GPS-tracking devices can increase our understanding about individual behaviour and the parameters responsible for the spatial and temporal occurrence of birds in the aerosphere. This knowledge has to be incorporated into a forecast model for the broad front movement over large spatial scales in order to develop a risk assessment strategy for bird collisions with renewable energy power plants. One main task in the proposed work is to provide high-resolution Europe-wide simulations of the flow patterns of bird migration to first of all improve our understanding of spatial density distributions of birds during migration season and secondly to identify areas of high collision risk with renewable energy power plants. Over the last two years and in a cooperative project between the Laboratory for Energy Conversion, ETH Zurich and the Swiss Ornithological Institute, an agent-based bird migration simulation tool has been developed, validated and applied over the area of Switzerland. A mesoscale weather simulation model is used to provide accurate, high-resolution predictions of the spatially and temporally variable wind field. Wind flow has a major influence on the birds’ patterns of migration, as birds use the aerosphere to travel between breeding and overwintering areas. Wind strongly affects the temporal and spatial intensities of birds that are of high importance to predict collision risk with renewable power plants. Until now, the limited availability of radar data that provide information about the number and flight heights of migratory birds and that define the initial conditions of the simulation, limited the spatial extent of the simulation. Recently a Europe-wide network of radar data has become available. This newly available data allows application of the agent-based bird migration simulation tool to extend to larger areas, as well as requires that new models of bird behaviour be developed.As a next step, the PhD student shall perform Europe-wide bird migration simulations, as bird migration is a phenomenon that is influenced by weather dynamics from breeding grounds to overwintering areas. The PhD Student shall predict large-scale mass flow movement patterns to improve our general understanding of a bird’s movement behaviour and bird migration density patterns. The proposed study will also shed light on the wind flow that prevails during migration season and will point out environmental constraints birds have to cope with. The PhD Student shall identify the areas of high collision risk with renewable energy power plants, and provide recommendations regarding the operation and development of renewable energy power plants. Since 2009, the Laboratory for Energy Conversion, ETH Zurich has been developing EnerPol, a system-wide scenario-based assessment simulation tool for energy, transportation and urban infrastructures, and population dynamics. The proposed project shall benefit from this longstanding experience, as well as be able to assure the relevance of the outcomes from the proposed project. Thus, the knowledge acquired of the spatial and temporal mass flow patterns will have a significant overall impact in the field of renewable energy, as well as increase our understanding of landscape use by migratory birds.
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