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GeoPolicy: Bridging the gap between science and decision makers – a new tool for nuclear emergencies affecting food and agriculture

GeoPolicy: Bridging the gap between science and decision makers – a new tool for nuclear emergencies affecting food and agriculture

Amelia Lee Zhi Yi, the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture

The International Atomic Energy Agency (IAEA) has developed an online system to assist in improving the response capabilities of authorities in the event of an emergency caused by natural hazards. The Decision Support System for Nuclear Emergencies Affecting Food and Agriculture (DSS4NAFA), provides a clear overview of radioactive contamination of crops and agricultural lands through improved data management and visualisation, it also assists in decision support processes by suggesting management actions to decision makers. In this interview, we have the pleasure to introduce Ms Amelia Lee Zhi Yi, working at the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture to speak about DSS4NAFA.

Nuclear Emergency Response (NER) for food and agriculture – why is that important and what does it entail?

In the event of a nuclear or radiological emergency, the response should be swift in the interest of human health. After ensuring the well-being of the population, it is necessary to prioritise the assessment of possible radioactive contamination of crops and agricultural lands to avoid ingestion of radioactivity.

Proper data management, data visualisation and risk communication are essential for efficient response to a nuclear emergency. Factors that should be considered for such response include support for sampling and laboratory analysis, optimal allocation of manpower and analytical instruments, and integrated communication between stakeholders.

To make well-informed decisions on for instance planting and food restrictions, food safety authorities need to have a good understanding of the radiological conditions after a fallout event. This is accomplished through the collection of environmental samples such as soil and plants, and food products that are then analysed using consistent methods in qualified laboratories. Further, these data should be displayed in an intuitive manner so that authorities will be able to interpret the data under stressful, time-bound conditions. Finally, to reduce confusion and clearly communicate decisions made to the public, standardised communication protocols of the decisions made by policymakers need to be implemented.

How can technology assist us in this process? What is DSS4NAFA?

Innovative information technology (IT)-based methods can assist in optimising processes in NER. Some examples include streamlining data transfer using cloud-based platforms paired with mobile technologies, facilitating decision making using advanced visualisation tools, and communicating risk to the public using pre-defined correspondence templates.

The Decision Support System for Nuclear Emergencies Affecting Food and Agriculture (DSS4NAFA), is a cloud-based IT-DSS tool developed by the Soil and Water Management & Crop Nutrition Laboratory, under the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture. While it was originally developed as a system for nuclear emergency response management and communication, its ability to discern data quality, to provide user-friendly spatio-temporal visualisations for decision makers, and ease in creation of communication materials makes it a good candidate tool for usage in natural hazard risk mitigation.

The beta version of DSS4NAFA is planned to be released in August 2018 for testing by volunteer member states.

General overview of how DSS4NAFA works. After a nuclear or radiological fallout event affecting food and agriculture, the system assists decision makers by allocating samplers and laboratories according to proximity, allows for data to be input into a mobile device and sent to a cloud server immediately, and visualises data for intuitive decision making (Source FAO-IAEA).

How does DSS4NAFA support public authorities in emergencies?

DSS4NAFA contains modules which provide logistical support to decision makers in defining sampling location, sampler allocation and laboratory allocation. It also functions as a powerful visual interpretation tool that brings together multi-dimensional data usually handled to make decisions on planting and food restrictions in a nuclear emergency response situation.  Some of the functionalities of the modules are as below:

Data management:

  • Standardised data input with pre-determined data entry fields and format
  • Data housed within one server to ensure ease of data analysis
  • All data collected in the field using mobile devices and are sent directly to the server

Data visualisation:

  • GIS based visualisation for instinctive understanding of situation on the ground
  • “Logmap” for at-a-glance sampler and laboratory analyses status
  • Comprehensive information, such as current and historical decision actions, intuitively displayed on the Food Restriction Dashboard

Logistics and decision support:

  • Sampling assignments proposed based on crop calendar and land use type
  • Food and planting restrictions suggested based on the movable levels set by authorities
  • Public communication module

 

The Food Restriction Dashboard is a platform in DSS4NAFA whereby radioactivity information is collated considering the spatial distribution and time resolution of the accident, and suggests food and planting restrictions based on the level of risk and the specified tolerance levels (Source FAO-IAEA).

What feedback did you get from real users during the design/development of the DSS?

The development of DSS4NAFA was highly iterative and findings from the process were invaluable. Some lessons learned during its development include the necessity for stakeholder involvement during the design process, the usage of a “one-house approach” for centralised data, and the importance of building a tool that is flexible enough to be used during emergency response and routine monitoring operations.

The system has generated a lot of interest when shown during several IAEA workshops and conferences such as at EGU, indicating the need for this type of system.

What do you think will be the main challenges in the application of the DSS4NAFA?

Two challenges are foreseen in the deployment of DSS4NAFA. The first is to explain the benefits of the system to countries with pre-existing Nuclear Emergency Response systems. We are confident that we can succeed as DSS4NAFA is modular, thus Member States can select and implement the components that suit their needs best.

Secondly, there could be some learning associated with the implementation of DSS4NAFA. To facilitate this process for governmental data analysts, user experience will be one of the major focus for improvement during the beta testing phase. We strive to develop DSS4NAFA such that the system will be intuitive for use to its fullest potential, even with minimal prior training.

The development of DSS4NAFA is part of the Joint FAO/IAEA Division Mandate in Preparedness and Response to Nuclear and Radiological Emergencies Affecting Food and Agriculture to promote the management of intra- and interagency emergency preparedness and response to nuclear accidents and radiological events affecting food and agriculture, including in the application of agricultural countermeasures.

by Jonathan Rizzi, Norwegian Institute of Bioeconomy Research

Jonathan Rizzi is the incoming ECS representative for the EGU’s Natural Hazard division. He has a bachelor in GIS and Remote Sensing and a master and a PhD in Environmental Sciences. He is a researcher at the Norwegian Institute of Bioeconomy Research and has worked in the field of climate change and risk assessment for the last several years.

Editor’s Note: This post first appeared on the EGU Natural Hazards (NH) Division blog. Read the original post here.

Imaggeo on Mondays: Digging out a glacier’s story

Imaggeo on Mondays: Digging out a glacier’s story

This photograph shows landforms on Coraholmen Island in Ekmanfjorden, one of the fjords found in the Norwegian archipelago, Svalbard. These geomorphic features were formed by Sefströmbreen, a tidewater glacier, when it surged in the 1880s.

Although all glaciers flow, some glaciers undergo cyclic changes in their flow. This is called surging, and glaciers that surge are called surging glaciers. During their active phase, surging glaciers speed up and advance. At this time, glaciers collect, transport and deposit large volumes of sediment. This active phase is then followed by a so-called quiescent phase, when glaciers slowdown and retreat. Sediment carried within the ice is then exposed. Often surge-type glaciers produce a characteristic set of landforms, like the red ridges featured here in this photograph.

Only a small proportion of the world’s glaciers surge. Svalbard is home to many of these surging glaciers, and the length of the surge cycle varies by region. A quiescent phase of surging glaciers in Svalbard can last between 10 and 100 years. An active phase is commonly between 1 and 10 years. Surging glaciers are enigmatic; we still do not fully understand all the processes that cause these glaciers to switch between active and quiescent phases.

When Sefströmbreen surged, it advanced over the fjord and overrode Coraholmen Island. The glacier deposited up to 0.2 km3 of sediment on the western side of the island. As a result, the island doubled in size. The red ridges in the foreground of the photograph were formed when sediment under the glacier was squeezed up into crevasses, large cracks in the ice. Once the ice melted, these crevasse-squeezed ridges were exposed. They contrast in colour with grey Kolosseum Mountain in the background.

Glaciers are useful indicators of past climate and they are used for climate reconstructions. However, surging glaciers are not suitable for such reconstructions. This is because glacier surging is not directly related to climate. When a surging glacier advances during its active phase, it does not mean that the climate is colder. This also holds true for the past. If a surging glacier was bigger at some point in the past, it is not because the climate at the time was colder. If we didn’t know that the glacier surged, we would make a wrong inference about climate. Therefore it is important to know which glaciers are surging-type glaciers.

To document surging behaviour of glaciers, we can use historical sources, glaciological observations and satellite images. If no such records exist or if we are interested in time period that precedes satellite observations, we rely on landforms to tell us the story. We can study these landforms, their appearance, shape, structure, and what they’re made of to learn about past behaviour of glaciers, their dynamics, and processes that go on underneath a glacier where it meets its bed.

The photograph was taken during a field cruise as part of the University Centre in Svalbard’s Arctic Glaciers and Landscapes course.

By Monika Mendelova, University of Edinburgh (UK)

References

Boulton, G.S. et al. Till and moraine emplacement in a deforming bed surge — an example from a marine environment. QSR 15, 961-987. 1996

Evans, D.J.A., & Rea, B.R. Geomorphology and sedimentology of surging glaciers: a land-systems approach. Ann. Glaciol. 27, 75 – 82. 1999

Dowdeswell, J.A. et al. Mass balance change as a control on the frequency and occurrence of glacier surges in Svalbard, Norwegian High Arctic. Geophys. Res. Lett. 22, 2909-2912. 1995

Imaggeo is the EGU’s online open access geosciences image repository. All geoscientists (and others) can submit their photographs and videos to this repository and, since it is open access, these images can be used for free by scientists for their presentations or publications, by educators and the general public, and some images can even be used freely for commercial purposes. Photographers also retain full rights of use, as Imaggeo images are licensed and distributed by the EGU under a Creative Commons licence. Submit your photos at http://imaggeo.egu.eu/upload/.

Imaggeo on Mondays: Namibia’s mysterious fairy circles

Imaggeo on Mondays: Namibia’s mysterious fairy circles

The grassy Namibian desert is pock-marked with millions of circular patches of bare earth just like these shown in the picture between linear dunes.

Viewed from a balloon, they make the ground look like a moonscape. Commonly known as fairy circles, the patches range from two to 12 metres across and appear in a 2000 kilometre strip that stretches from Angola to South Africa.

For many decades, the fairy circles extending uniformly over vast areas in the landscape, have puzzled laymen and scientists alike. They are subject to a lively debate and contrary hypotheses on their origin exist. Some researchers claim fairy circles were caused by termites, others propose they are the result of vegetation self-organization.

Description by Hezi Yizhaq, as it first appeared on imaggeo.egu.eu.

Imaggeo is the EGU’s online open access geosciences image repository. All geoscientists (and others) can submit their photographs and videos to this repository and, since it is open access, these images can be used for free by scientists for their presentations or publications, by educators and the general public, and some images can even be used freely for commercial purposes. Photographers also retain full rights of use, as Imaggeo images are licensed and distributed by the EGU under a Creative Commons licence. Submit your photos at http://imaggeo.egu.eu/upload/.

Imaggeo on Mondays: Arctic cottongrass in Svalbard

Imaggeo on Mondays: Arctic cottongrass in Svalbard

In the High Arctic, where vegetation is limited in height, cottongrass stands out as some of the tallest plant species around.

This photo shows a wispy white patch of Arctic cottongrass growing amongst other tundra vegetation in the Advent river floodplain of Adventdalen, a valley on the Norwegian archipelago island Svalbard.

Svalbard is of particular scientific interest as it is a relatively warm region for its high latitude. This is due to the North Atlantic Ocean, which transports heat from lower latitudes to Svalbard’s shores.

The photo was taken in September 2014, towards the end of the region’s growing season. In the background, you can see that the season’s first snow had already blanketed the valley’s neighboring mountain tops.

Cottongrass generally loves wet conditions and scientists sometimes even use this plant genus (Eriophorum) as an indicator of the ground’s fluctuating water level, especially in areas that begin to develop peat, an accumulation of more of less decomposed plant material in wet environments. The waters feeding this region’s wetland come from melted snow and ice travelling down the adjacent mountains and floodwater from the Advent river, which is primarily meltwater fed.

Arctic cottongrass also can exchange gases with their underground environment through their roots and even have been shown to alter the local carbon budget of regions where they grow. It is therefore a very important species to account for when studying permafrost carbon dynamics.

Gunnar Mallon, currently a teaching fellow at the University of Sheffield (UK), took this photo while on a fieldwork expedition together with Andy Hodson, a glaciology professor at the University Centre in Svalbard, for the LowPerm project.

The LowPerm project aimed to understand how nutrients are transported within permafrost landscapes in Norway and Russia and how that may affect the production of greenhouse gases, such as carbon dioxide (CO2) and methane (CH4). The study brought together scientists from the UK, Norway, Denmark and Russia and results from the extensive field and laboratory work are currently being analysed and made ready for publication.

Imaggeo is the EGU’s online open access geosciences image repository. All geoscientists (and others) can submit their photographs and videos to this repository and, since it is open access, these images can be used for free by scientists for their presentations or publications, by educators and the general public, and some images can even be used freely for commercial purposes. Photographers also retain full rights of use, as Imaggeo images are licensed and distributed by the EGU under a Creative Commons licence. Submit your photos at http://imaggeo.egu.eu/upload/.