Cooperation needed! The case of drought management in Austria

By Marlene Palka, research assistant in the IIASA Risk and Resilience Program

Marlene Palka discusses the work done by the IIASA FARM project, which has been investigating drought risk management in Austria for the past three years.

Future climate projections forecast an increase in both the frequency and severity of droughts, with the agricultural sector in particular being vulnerable to such extreme weather events. In contrast to most other climatic extremes, droughts can hit larger regions and often for extended periods – up to several months or even years. Like many other countries, Austria has been and is expected to be increasingly affected, making it necessary to devise a management strategy to mitigate drought damages and tackle related problems. The FARM project – a three year project financed by the Austrian Climate Research Program and run by the IIASA Risk and Resilience and Ecosystems Services and Management programs – kicked off in 2017 and has been investigating agricultural drought risk management both in a broad European context, and more specifically in Austria.

Young sunflowers on dry field © Werner Münzker | Dreamstime.com

Austria represents a good case study for agricultural drought risk management. Despite the agricultural sector’s rather small contribution to the country’s economic performance, it still has value and represents an important part of the country’s historical and cultural tradition. Around 80% of Austria’s total land area is used for agricultural and forestry activities. Equally important is its contribution to the preservation of landscapes, which is invaluable for many other sectors including tourism.

Globally, agricultural insurance is a widely used risk management instrument that is often heavily subsidized. Apart from the fact that the concept is increasingly being supported by European policymakers – the intention being that insurance should play a more prominent role in managing agricultural production risk – more and more voices from other sectors are calling for holistic management approaches in agriculture with the overall aim of increasing the resilience of the system.

There is a well-established mutual agricultural insurance company in Austria, which has high insurance penetration rates of up to 75% for arable land, and comparably high subsidies of up to 55% of insurance premiums. It is also encouraging to note that recent policy decisions support the timeliness of drought risk: in 2013, the Austrian government paid EUR 36 million in drought compensation to grassland farmers and in 2016, premium subsidies of 50% were expanded to other insurance products, including drought, while ad-hoc compensation due to drought was officially eliminated. In 2018, the subsidy rate was further increased to 55%. In light of these prospects, we investigated the management option space of the Austrian agricultural sector as part of the FARM project.

The 2018 Organisation for Economic Co-operation and Development (OECD) report on monitoring and evaluation of agricultural policies claims that efficient (drought) risk management in agriculture must consider the interactions and trade-offs between different on-farm measures, activities of the private sector, and government policies. The report further argues that holistic approaches on all management levels will be vital to the success of any agricultural management strategy.

In the course of our work, we found that agricultural drought risk management in Austria lacks decision making across levels. Although there is a range of drought management measures available at different levels, cooperation that includes farms, public and private businesses, and policy institutions is often missing. In addition, measures to primarily and exclusively deal with drought, such as insurance and irrigation, are not only limited, but (as we found) are also less frequently implemented.

As far as insurance is concerned, products are still being developed, and penetration rates are currently low. Drought risk is also highly uncertain, making it almost impossible to offer extensive drought insurance products. Irrigation is perceived as the most obvious drought management measure among non-agronomists. Simply increasing irrigation to deal with the consequences of drought could however lead to increased water demand at times when water is already in short supply, while also incurring tremendous financial and labor costs and additional stress to farmers. With that said, a large number of agricultural practices may also holistically prevent, cope with, or mitigate droughts. For example, reduced soil management practices are low in operating costs and prevent surface run-off, while simultaneously maintaining a soil structure that facilitates increased water holding capacity. Market futures might also stabilize farm income and therefore allow for future planning such as the purchase of irrigation equipment.

A workshop we held with experts from the Austrian agricultural sector further highlighted this gap. Thinking (not even yet acting) beyond the personal field of action was rare. The results of a survey we conducted showed that farmers were experiencing feelings of helplessness regarding their ability to manage the negative effects of droughts and other climatic extremes despite the implementation of a broad range of management solutions. One way to explain this could be a lack of cooperation across different management levels, meaning that existing efforts – although elaborate and well-proven – potentially reach their limit of effectiveness sooner rather than later.

Due to the more complex effects of any indirect/holistic drought management measure, we need tailored policies that take potential interdependencies and trade-offs into account. With evidence from the FARM project, my colleagues and I would like to emphasize an integrated risk management approach, not only at farm level but also in all relevant agencies of the agricultural sector in an economy. This will help to secure future production and minimize the need for additional public financial resources. Our findings not only contribute to ongoing high-level discussions, but also underpin the resulting claim for more holistic (drought) risk management with bottom-up data from our stakeholder work.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Enhancing urban resilience through nature-based solutions

By Luiza Toledo, IIASA Science Communication Fellow 2019

2019 YSSP participant Regina Buono investigates how the law can support or impede the use of nature-based solutions and help facilitate adaptation to climate change.

Recognizing the need for a systemic change is the first step to overcoming environmental challenges like climate change. In theory, governance systems can be designed and arranged to facilitate and embrace adaptation to climate change. Developing a legal framework that supports such an adaptation is, however, a big challenge. Learning how to manage the environmental crisis we currently find ourselves in while still being able to grow economically further complicates matters. According to Regina Buono, a participant in this year’s IIASA Young Scientist Summer Program (YSSP), nature-based solutions could be an alternative option that offers a multitude of benefits in terms of how this dual goal of economic growth and sustainability can be achieved. Buono’s research will contribute to IIASA as a partner in the EU Horizon 2020 project, PHUSICOS, which is demonstrating how nature-based solutions can reduce the risk of extreme weather events in rural mountain landscapes.

Outdoor green living wall, vertical garden on modern office building | © Josefkubes | Dreamstime.com

Nature-based solutions are actions to protect, manage, or restore natural ecosystems that address societal challenges, such as water security, pollution, or natural disasters – sometimes simultaneously. These solutions take advantage of the system processes found in nature – such as the water regulation function of wetlands, the allowance of natural space in floodplains to buffer flooding impacts, water storage in recharged aquifers, or carbon storage in prairies – to tackle environmental problems. This concept is now widely used to reframe policy debates on biodiversity conservation, climate change adaptation and mitigation strategies, urban resilience, as well as the sustainable use of natural resources.

As part of her research, Buono is exploring how the law can support or impede the use of nature-based solutions and considering how we can make legal systems more adaptive so they can help facilitate societal adaptation to a more uncertain world under ongoing and future climate change.

“My research is about using the law as a tool that works for us, rather than one that, because of its historic interest in stability, gets in the way,” she says.

Regina Buono, YSSP participant. | © Buono

Buono started her career as a lawyer based in the US. In her first job she was assigned to work with water issues and according to her, it was “love at first sight”. Following that first assignment, she continued to work on finding market-based solutions for issues related to endangered species. She decided to pursue a PhD in public policy in 2016, and soon after was asked to join the external advisory board to the Nature Insurance Value: Assessment and Demonstration (NAIAD) project in Europe. While attending the first meeting, she realized that there were no lawyers or legal scholars among the project researchers. As a lawyer, she could see that there was a gap in understanding how law and regulations would impact the uptake, development, and proliferation of nature-based solutions.

Working with NAIAD, she developed her PhD dissertation to address this gap and advance understanding around the role of the law in nature-based solutions, both in terms of governance in implementation and practice and the potential for governance innovation that better supports and promotes future adaptation.

“My YSSP project here at IIASA focuses on the city of Valladolid, Spain, and examines the legal context around the implementation of a collection of nature-based solution projects. I am trying to draw insights from these that could perhaps also be applied to other cases,” she explains.

Buono is doing a critical qualitative study that integrates analyses of interviews and policy documents using NVivo, a qualitative data analysis computer software package specifically designed to work with very rich text-based and/or multimedia information, together with legal analysis. She says that there is still a lot of work to be done to adapt to climate change and an interdisciplinary cross-sector effort will be necessary.

The preliminary results from her YSSP research point to a number of constraints and facilitating factors related to law and regulation. She says that the lack of explicit legal authorization for nature-based solutions that she identified in her study, strict water quality regulations, and bureaucratic hurdles could be some of the factors that constrain the implementation of nature-based solutions. However, flexibility in the law and a polycentric governance structure was identified as facilitating factors that encourage local entities to opt for nature-based solutions.

Buono hopes that her research will help decision makers to assess and address legal components that guide, structure, or impede the use of nature-based solutions, and to consider how the law could be evolved to create a more enabling environment for more adaptive governance arrangements that would better support nature-based solutions.

“Our policies and infrastructure are going to have to change to be able to deal with the impacts that we are already experiencing. Nature-based solutions and a shift toward adaptive governance could help us navigate more gracefully in these important transitions,” she concludes.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Bringing some light into the dark

By Tobias Sieg, IIASA Young Scientists Summer Program alumnus

IIASA Young Scientists Summer Program alumnus Tobias Sieg explains how risk assessments considering uncertainties can substantially contribute to better risk management and consequently to the prevention of economic impacts.

© Topdeq | Dreamstime.com

According to the World Economic Forum’s Global Risk Landscape 2018, extreme weather events and natural disasters are ranked among the top three global risks. For many regions, hydro-meteorological risks – in other words, weather or water related events like cyclones or floods that pose a threat to populations or the environment – constitute the biggest threat. This calls for a comprehensive scientific risk assessment with a particular focus on large associated uncertainties.

Assessing the risk of hydro-meteorological hazards without considering these uncertainties, is like entering a pitch-dark labyrinth. You have no idea where you are and where you will end up. If you enter with a flashlight, you might still not immediately know exactly where you will end up, but at least you can assess your possibilities for finding a way out.

We should all care to see those possibilities and to identify uncertainties, since the consequences of hydro-meteorological hazards can have severe impacts on socioeconomic systems, and global- and climate change could favor the occurrence of floods. An increase in extreme weather events, such as heavy precipitation can be expected along with an increasingly warmer climate. In combination with uncontrolled socioeconomic development, these extreme weather events could potentially trigger more intense hazardous flood events in the future. Appropriate management of their consequences is therefore required, starting from today, while pro-actively thinking about the future. To that end, risk management policy and practice need reliable estimates of direct and indirect economic impacts.

The reliability of existing estimates is usually quite low and, what is maybe even worse, they are not communicated properly. This may signal a false sense of certainty regarding the prediction of future climate-related risks.

In two recent studies, my co-authors and I developed and applied a novel method, which specifically focuses on the communication of the reliability of economic impact estimates and the associated uncertainties. The proposed representation of uncertainties enables us to shed some light on the possibilities of how a specific event can affect economic systems. As a Young Scientists Summer Program (YSSP) participant with the IIASA Risk and Resilience Program, I applied the method together with my supervisors Thomas Schinko and Reinhard Mechler, to estimate the overall economic impacts of a major flood event in Germany in 2013.

The estimated overall economic impacts comprise both direct and indirect impacts. Direct impacts are usually caused by physical contact of the floodwater with buildings, while indirect impacts can also occur in regions that are not directly affected by a flood. For example, obstructions of the infrastructure can lead to delayed deliveries, in turn leading to negative impacts for the production of goods outside the flooded areas. The crucial novelty of this method is the integrated assessment of direct and indirect economic impacts. In particular, by considering how the uncertainties associated with the estimation of direct economic impacts propagate further into the estimates of indirect economic impacts.

Being able to reproduce what has happened in the past is essential to making credible predictions about what could potentially happen in the future. A comparison of reported direct economic impacts and model-based estimates reveals that the estimation technique already works quite reliably. The good news is that anyone can help to increase the predictive reliability even further. The method uses the crowdsourced OpenStreetMap dataset to identify affected buildings. The more detailed the given information about a building is, the more reliable the impact estimations can get.

Our study reveals that the potential of short-term indirect economic impacts (without considering recovery) are quite high. In fact, our results show that the indirect impacts can be as high as the direct economic impacts. Yet, this varies a lot for different economic sectors. The manufacturing sector, for instance, is much more affected by indirect economic impacts, since it is heavily dependent on well-functioning supply chains. This information can be used in emergency risk management where decisions have to be made about giving immediate help to companies of a specific sector to reduce high long-term indirect economic impacts.

We are now looking at different possibilities of how flood events could affect the economic system. Having a range of possibilities of the relation between these impacts makes them transferable between different regions with similar economic systems. Our results are therefore also relevant more broadly beyond the German case. This representation of uncertainties can help to get to a more credible and consistent risk assessment across all spatial scales. Thus, the method is able to potentially facilitate the fulfillment of some of the calls of the UN Sendai Framework for Disaster Risk Reduction.

Detailed risk assessments considering uncertainties can substantially contribute to better risk management and consequently to the prevention of economic impacts – direct and indirect, both now and in the future.

References:

[1] Sieg T, Schinko T, Vogel K, Mechler R, Merz B & Kreibich H (2019). Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification. PLoS ONE 14(4): e0212932. [pure.iiasa.ac.at/15833]

[2] Sieg T, Vogel K, Merz B & Kreibich H (2019). Seamless estimation of hydro-meteorological risk across spatial scales. Earth’s Future. https://doi.org/10.1029/2018EF001122

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Exploring risk in development indicators

By Junko Mochizuki, researcher with the IIASA Risk and Resilience Program

IIASA researcher Junko Mochizuki writes about her recent research in which she and other IIASA colleagues developed an indicator to help identify vulnerable countries that should be prioritized for human development and disaster risk reduction interventions.

© Yong Hian Lim | Dreamstime.com

Working as part of an interdisciplinary team at IIASA, it is not uncommon for researchers to uncover disciplinary blind spots that would otherwise have gone unnoticed. This usually leads to a conversation that goes something like, “If only we could learn from the other disciplines more often, we can create more effective theories, methods, and approaches.”

My recently published paper with Asjad Naqvi from the IIASA Advanced Systems Analysis Program titled Reflecting Risk in Development Indicators was the fruit of such an exchange. In one afternoon, our coffee conversation hypothesized various reasons as to why the disaster risk discipline continued to create one risk indicator after another while the development community remained silent on this disciplinary advancement and did not seem to be incorporating these indicators into ongoing research in their own field.

Global ambitions such as the Sustainable Development Goals (SDGs) and Sendai Framework for Disaster Risk Reduction call for disaster mainstreaming, in other words, that disaster risk be assessed and managed in combination with any development planning efforts. For various reasons, we however continue to measure development and disasters separately. We know that globally the poor are more exposed to risk and that disasters hurt development, but there was not a single effective measure that captured this interlinkage in an easy-to-grasp manner. Our aim was therefore to demonstrate how this could be done using the information on disasters and development that we already have at our disposal.

The Human Development Indicator (HDI) is a summary measure of average attainment in key dimensions of human development – education, life expectancy, and per capita income indicators – that are used to rank countries into four tiers of human development. Using the HDI as an example, Asjad and myself compiled global datasets on human development, disaster risk, and public expenditure, and developed a method to discount the HDI indicator for 131 countries globally – just as others have done to adjust for income– and gender-inequality. Discounting the HDI indicator for education, for instance, involves multiplying it by the annual economic value of the average loss in terms of education facilities, divided by the annual public expenditure on education. We did this for each dimension of the HDI.

Conceptually, the indicator development was an intriguing exercise as we and our reviewers asked interesting questions. These included questions about the non-linearity of disaster impact, especially in the health sector, such as how multiple critical lifeline failures may lead to high death tolls in the days, weeks, and even months following an initial disaster event. Other issues we examined were around possibilities for the so-called build-back-better approach, which offers an opportunity to create better societal outcomes following a disaster.

Our formulation of the proposed penalty function hardly captures these complexities, but it nevertheless provides a starting point to debate these possibilities, not just among disaster researchers, but also among others working in the development field.

For those familiar with the global analysis of disaster risk, the results of our analysis may not be surprising: disasters, unlike other development issues (such as income- and gender inequalities for which HDI have been reformulated), have a small group of countries that stand out in terms of their relative burdens. These are small island states such as Belize, Fiji, and Vanuatu, as well as highly exposed low and lower-middle income countries like Honduras, Madagascar, and the Philippines, which were identified as hotspots in terms of risk-adjustments to HDI. Simply put, this means that these countries will have to divert public and private funds to pay for response and recovery efforts in the event of disasters, where these expenses are sizeable relative to the resources they have in advancing the three dimensions of the HDI indicator. Despite their high relative risk, the latter countries also receive less external support measured in terms of per capita aid-flow.

Our study shows that global efforts to promote disaster risk reduction like the Sendai Framework should be aware of this heterogeneity and that more attention in the form of policy support and resource allocation may be needed to support groups of outliers. Finally, although the cost of most disasters that occur globally are small relative to the size of most countries’ national economies, further sub-national analysis will help identify highly vulnerable areas within countries that should be prioritized for development and disaster risk reduction interventions.

Reference:

Mochizuki J & Naqvi A (2019). Reflecting Disaster Risk in Development Indicators. Sustainability 11 (4): e996 [pure.iiasa.ac.at/15757]

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Reimagining the workforce of the future

© SasinTipchai | Shutterstock

By Sandra Ortellado, 2018 Science Communication Fellow

Science fiction depicts the future with a combination of fascination and fear. While artificial intelligence (AI) could take us beyond the limits of human error, dystopic scenes of world domination reveal our greatest fear: that humans are no match for machines, especially in the job market. But in the so-called fourth industrial revolution, often known as Industry 4.0, the line between future and fiction is a thread of reality.

Over the next 13 years, impending automation could force as many as 70 million workers in the US to find another way to make money. The role of technology is not only growing but also demanding a completely new way of thinking about the work we do and our impact on society because of it.

Rather than focusing on which jobs will disappear because of technological disruption, we could be identifying the most resilient tasks within jobs, says J. Luke Irwin, 2018 YSSP participant. His research in the IIASA World Population program uses a role- and task-based analysis to investigate professions that will be most resilient to technological disruption, with the hope of guiding workforce development policy and training programs.

“We are getting better and better at programming algorithms for machines to do things that we thought were really only in the realm of humans,” says Irwin. “The amount of disruption that’s going to happen to the work industry in the next ten years is really going to impact everyone.”

However, the fear and instability created by the potential disruption elicit chaos, and the response is hard to organize into constructive action. While the resources remain untapped, creativity and imagination are wasted on speculation instead of preparation.

“I couldn’t stand that there’s all this great evidence-based work out there about how we can improve people’s lives and no one is using it,” said Irwin, “I’m trying to align a lot of research and put it in a place where you can compare it and make it more useful and more transferable between the people who would be talking about this: educators, policymakers, employers, and anybody in the workforce.”

Using a German dataset with vocational training as well as time and task information, Irwin will break down jobs into the specific cognitive and physical skills involved and rank the durability of each skill.

Based on the identified jobs and skills, Irwin will go on to draw connections between labor-force capabilities and education policies. His goal is to scale the findings of the most resilient skills to the German labor system so that policymakers and academic institutions can retrain currently displaced workforces and reimagine the future of human work.

After all, while about half the duties workers currently handle could be automated, Mckinsey Global Institute suggests that less than 5% of occupations could be entirely taken over by computers. The future of predictable, repetitive, and purely quantitative work may be threatened, but automation could also open the door for occupations we can’t even imagine yet.

“I think people are amazing and that they have a lot more potential than we are currently capable of fulfilling,” says Irwin.

The World Economic Forum estimates that 65% of children today will end up in careers that don’t even exist yet. For now, an increasingly self-employed millennial generation works insecure, unprotected jobs. The new gig economy, characterized by temporary contracted positions, offers independence but also instability in the labor market.

Without stable work, people lose a sense of security, and that can be dangerous for a policy system that isn’t built to handle uncertainty.

The last industrial revolution caused two or three generations of people to be thrown into poverty and lose everything they had because it was all tied into their job, recalls Irwin.

“Everything gets bad when things are uncertain,” says Irwin, “And this is a very uncertain time. We need to have a better idea of what’s coming so we can actually make some change.”

Irwin, who earned his Master’s in Public Health in 2014, wants his work to have a preventative focus, trying to find those things that not enough people are talking about, but have the potential to make a huge impact on public well-being.

“Especially in the United States, where I live, we’re so tied up with our jobs—it seems like it’s over half our identity,” says Irwin, “We live to work in America.”

In a place like the US, where a job is not only a source of income, but also an identity and a health factor, Irwin’s research offers hope that technological disruption can foster opportunity instead of chaos.

Note: This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Estimating risk across Africa

by Melina Filzinger, IIASA Science Communication Fellow

Having just finished tenth grade, Lillian Petersen from New Mexico, USA is currently spending the summer at IIASA, working with researchers from both the Ecosystems Services and Management (ESM), and Risk and Resilience (RISK) programs on developing risk models for all African countries.

At a talk Petersen gave at the Los Alamos Nature Center/Pajarito Environmental Education Center, her method for predicting food shortages in Africa from satellite images caught the attention of Molly Jahn from the University of Wisconsin-Madison. Jahn, who is collaborating with the ESM and RISK programs at IIASA, was so impressed with Petersen’s work that she added her to her research group and connected her to IIASA researchers for a joint project.

One of the indicators used to estimate poverty in Nigeria. © Lillian Petersen | IIASA

Knowing which areas are at risk for disasters like conflict, disease outbreak, or famine is often an important first step for preventing their occurrence. In developed countries, there is already a lot of work being done to estimate these risks. In developing countries, however, a lack of data often hinders risk modeling, even though these countries are often most at risk for disasters.

Many humanitarian crises, like famine, are closely connected to poverty. However, high resolution poverty estimates are only available for a few African countries. This is why Petersen and her colleagues are developing methods to obtain those poverty estimates for all of Africa using freely available data, like maps showing major roads and cities, as well as high-resolution satellite images. Information about poverty in a certain region can be extracted from this data by considering several indicators. For example, areas that are close to major roads or cities, or those that have a large amount of lighting at night, meaning that electricity is available, are usually less poor than those without these features. The researchers are also analyzing the trading potential with neighboring countries, the land cover type, and distance to major shipping routes, such as waterways.

As no single one of these indicators can perfectly predict poverty, the scientists combine them. They “train” their model using the countries for which poverty data exists: A comparison of the model’s output and the real data helps to reveal which combination of indicators gives a reliable estimate of poverty. Following this, they plan to apply that knowledge in order to accurately predict poverty with high spatial resolution over the entire African continent.

Poverty data for Nigeria in 2010 (left) and poverty estimates based on five different indicators (right). © Lillian Petersen | IIASA

Once these estimates exist, Petersen and her colleagues will apply risk models to find out which areas are particularly vulnerable to disease outbreaks, famine, and conflicts. “I hope that this research will inform policymakers about which populations are most at risk for humanitarian crises, so that they can target these populations systematically in aid programs,” says Petersen, adding that preventing a disaster is generally cheaper than dealing with its aftermath.

The skills Petersen is using for her research are largely self-taught. After learning computer programming with the help of a book when she was in fifth grade, Petersen conducted her first research project on the effect of El Nino on the winter weather in the US when she was in seventh grade. “It was a small project, but I was pretty excited to obtain scientific results from raw data,” she says. After this first success she has been building up her skills every year, by competing at science fairs across the US with her research projects.

Her internship at IIASA gives Petersen access to the resources she needs to take her research to the next level. “Getting feedback from some of the top scientists in the field here at IIASA is definitely improving my work,’’ she says. Petersen is hoping to publish a paper about her project next year, and wants to major in applied mathematics after she finishes high school.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.