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This proposal was forked from MOVE - Model for Vulnerability Evaluation for urban planning of smart cities in the contest Anticipating Climate Hazards 2017

Pitch

A tool to identify hotspots of climate vulnerabilities to foster collective decision-making and support strategies of communication


Description

Summary

In a developing country such as Brazil, resources are scarce for basic services such as health, education and housing, so prioritizing investments is a key part of public management and decision making. In this sense there is very little information on where, how and when to invest to adapt to climate change. In order to provide indicators that help answer essential questions for assertive decision making about adaptation, MOVE was created.

MOVE is an integrated cloud-based platform that uses spatial and statistical analysis to assess vulnerabilities associated with climate change, applicable to different thematic, on multiple scales and under different climate scenarios. The assessment enables the identification of the most vulnerable zones concerning climate risks, and enabling managers to find the best adaptation measures by a cost effectiveness analysis.

By diagnosing the future vulnerability of each zone concerning risks posed by climate change, it will provide information for prioritizing investments and set measures for adaptation. The results show vulnerability hotspots, which are the geographical and productive areas of priority. A detailing of hotspot features allows a better understanding of the causes of vulnerability and "how", "where", and "how much" to spend on interventions. In addition to empowering society by providing information that increase social resilience and allowing the population itself to assume an individual responsibility for social security.

The platform allows the compilation of data for the identification of climatic vulnerabilities. At present, it has been used to understand the vulnerability of mid-port cities in Brazil, identifying the priority points for investment as well as adaptation measures with best cost effectiveness in order to identify the convergence of interests among decision makers for public and private sectors justifying the targeting of resources.


Is this proposal for a practice or a project?

Project


What actions do you propose?

The main objective of the project is to provide a result that informs the priority areas for adaptive interventions. In this way, it allows the disaggregation of indicators that demonstrate which impact is most relevant and which is the main cause of this impact, whether due to infrastructure, environmental or socioeconomic sensitivity. This result is an essential tool to justify the needs for convergent actions between different actors and decision-making sectors by expanding resources and involvement in the implementation of the adaptive strategy.

The results also support and subsidize the discussion of climate change communication in society. So it is an extraordinary tool to more realistically approach the climatic risks of society. MOVE increases the conditions of society's response to the climate, being a very relevant support for the socioeducation and empowerment of the cause by the people.

A result obtained by the project for the city of Belo Horizonte, Brazil, assisted in the convergence of actions of municipal secretariats, the agency of basins and the concencionary of waters of the metropolitan region. These institutions joined forces from the rationale offered by MOVE that identified flood vulnerability hotspots and their relationship to the proliferation of mosquito vectors of tropical diseases. In addition, the resulting maps were used for socio-educational measures that demonstrated the contribution of inadequate waste disposal related to precipitation events, as conditioning factors for flooding and increased occurrence of Dengue. Thus, the impact communication strategy was based on the information generated by the map produced from MOVE. In the identified hotspots the strengthening of social engagement in combating climate change was prioritized by the city hall in order to increase the resilience of the most vulnerable population.

MOVE follows the methodology suggested by the Intergovernmental Panel on Climate Change (2007; 2014). The Vulnerability Index encompasses available information on exposure to changes in climate, socio-environmental sensitivity to these changes, and the system’s capability to deal with and adapt to new conditions. The calculation of each index and the choice of the most appropriate variables to characterize them relies strongly on the local context of social, economic and bio-geographical attributes, on the availability of quality data, and on the priorities decided on collaboratively by experts, society and public sector.

In that context, climate change vulnerability assessment at the city level is essential to indicate adaptive measures at appropriate scales, and as adaptation management tool runned by the cities' managers, can lead to effective planning. In general, there is significant delay in the decision to invest in city infrastructure that is capable to bear the acceleration of urban growth and the effects of climate change.

Analysis of vulnerability to natural hazards in the context of climate change and the need for adaptation have been carried out. Such studies have taken specificities of each city into consideration, plotting impacts related to fluvial and/or coastal flooding, landslides, forest fires, droughts and disease vectors into vulnerability maps. This type of analysis grants city authorities access to appropriate information for making decisions about the future development of urban and social infrastructure at city level for disaster risk prevention actions in the present.

The overall objective of MOVE is to perform an analysis of climate change vulnerability in the city, considering both the municipality’s current situation and projections for the future for the following impacts: flood, landslides, diseases and heat waves. This vulnerability assessment can be used as a basis for the Climate Change Adaptation Policy, in order to optimize investments and reduce costs in accordance with the priorities of the municipal government, as well to provide subsidies for socio-educational information and early alert systems as a solution for disaster risk reduction. That means that the application of MOVE is a systematic effort to analyses and manage the causal factors of disasters, including the exposure to hazards and considering vulnerable people and regions, leading to wise management of land and the environment, and improving the preparedness for adverse events (UNISDR, 2012).

A vulnerability index is calculated based on the available information on hazard, physical and environmental sensitivity to climate stimuli and their resilience. All the explanatory variables selected to represent climate change impacts and adaptability are geo-referenced and normalized to become spatially comparable and possible to be aggregated in a weighted average index. The choice of weights for each variable are based on the literature review and on results of the model calibration.

A survey of the values exposed to the impacts of climate change is carried out. The values are raised through population information, presence of infrastructural, cultural and production assets, as well as those presented by insurance premiums. With the information classified by the degree of importance of what can be lost, it adds up to the vulnerability to quantify the risk data of losses and damages.

With regard to sensitivity and adaptive capacity, calculation of each index and the choice of the most appropriate variables to characterize them relies on socio-economic and biogeographic attributes of the local context, data availability and priorities established by public data.

A spatial approach is adopted in order to identify the regions where climate change impacts are concentrated, pointing out vulnerability hotspots. As priority areas, their attributes are analyzed with a higher degree of detail. More specific information on the characteristics of hotspots ensure better understanding of the causes leading to high levels of vulnerability and provide answers to questions such as where and how to intervene, as well as how much to spend on adaptation and risk management.

As an example how to calculate an impact the method to obtain the risk of flooding is presented below:

- Information related to environmental sensitivity to flood occurrence are produced by crossing three indicators: Indicator of Morphometric Susceptibility to flooding; Predisposition to flood occurrence; and Urban Drainage Index, all of which quantify characteristics associated to the physical susceptibility to flooding.

The exposure analysis is carried out based on local observations about maximum historical rainfalls and the outputs of climate simulations. Statistical analysis of extreme events of rainfall in different areas of the municipality are performed for different return periods by building frequency-intensity-duration curves (FID curves), according to the distribution of extremes of Gumbel type.


Information on reference rainfall for macro drainage, when provided by the municipality, are properly treated. The resulting rainfall levels (mm) associated with emergency alerts for events with one hour of occurrence are then tabulated according to the sub-basins. Finally, information about return periods of rain and rainfall levels (mm) leading to emergency alerts for 1-hour-duration events are crossed. As a result, information on the probability of occurrence of flood events along the sub-basins are produced both for climatic simulation and for the historical period, thereby constituting the climate exposure maps.
Mapping of adaptive capacity are made for two time periods (actual and future) by crossing five indicators, properly treated and produced: population residing in slums in relation to total population of the sub-basin; low-income population; existence of rain alerts systems; presence of drainage infrastructure; and localization of reservoirs for flood control. Recent records of flood occurrences in the city are used to validate the model outputs.

For the quantification of losses and damages, the values of assets are marked by the tax on urban property and land, insurance premiums in addition to the density of people to know how many lives can be affected, in this way allows the best allocation of resources for disaster risk reduction. In this sense, MOVE collaborates for the DRR by allowing the implementation of low repentance measures, which are based on future climate change, but at the same time are aligned with present risk reduction needs.

Vulnerability analysis of Belo Horizonte - Brazil

As final result, the identification of vulnerability hotspots provide an interactive tool that can be displayed on a web-gis platform. Policy makers and public managers can use it as a guide to a data-driven urban planning, which takes into account climate change hazards. The expected direct impact is the smart implementation of adaptation measures on climate change. Those measures can be proactive or reactive; soft (non-infrastructural) or hard (infrastructure); green (natural infrastructure, i.e. revegetation) or gray (i.e. drainage).

  • What are the most relevant impacts?

  • How can we avoid them?

  • Where should we invest?

  • When should we invest?

Those are questions that the Model for Vulnerability Evaluation (MOVE) can answer for us.

In the given example, identified vulnerability hotspots are formatted by an infrastructure composition and social sensitivity of undue occupation and low resilience. The drainage infrastructures of the city under analysis are deficient by the identified morphometry, with low permeability and little bulky canals. Likewise, the population at risk lives in low-quality housing in the flooded area and is in unattended areas and early warning systems. Thus, it is possible to identify the priority site for adaptation to the flood within the city.

MOVE anticipate climate hazards in a long term perspective, enabling urban planners to run actions to adapt and increase the absorbent capacity of cities, assuring the risk reduction by choosing the most effective adaptation measures. Reshaping the urban development, according to the answers that MOVE provides, is exactly deal with root causes of the vulnerabilities and assure that physical infraestructure will be ready to cope with climate change impacts. 

Find more here:

http://www.moveonadaptation.com/

https://www.youtube.com/watch?v=AaUNZYOomz0


Who will take these actions?

MOVE is a modelling platform designed as an private environmental consultancy tool, that must be operated by an expert team. It means that MOVE can be offered as a consultancy product for city managers and other regional policy makers to best make their decisions about urban planning, considering future climate change impacts.

MOVE can also be applied to the private sector, such as insurance companies that want to know the future hazards and risks on assets, to the construction sector, to better plan their future investments, or even to the real estate industry, to predict where will be the most valuated or depreciated areas within a city.

At the moment, the platform supports data acquisition and vulnerability modeling for medium-sized cities in Brazil. The platform is used by local government environmental experts to map vulnerability hotspots.


Where will these actions be taken?

These actions can be taken in every city or region that shares the same climate exposure database, regardless its size or location within South America. Cities that face climate change impacts nowadays and are aware that it is a big issue on their policies, are keener to use it.

For example, recently MOVE was applied on Belo Horizonte / Brazil - the country’s sixth largest city in number of inhabitants (2,502,557 inhabitants) (IBGE, 2015). The area of Belo Horizonte amounts to 331 km2. Belo Horizonte is the Brazilian leading city on implementing a climate change agenda. (link to download the complete study).


In addition, specify the country or countries where these actions will be taken.

Brazil


Country 2

No country selected


Country 3

No country selected


Country 4

No country selected


Country 5

No country selected


Impact/Benefits


What impact will these actions have on greenhouse gas emissions and/or adapting to climate change?

The proposal aims to promote a climate action for decision makers in Brazilian cities, according to local conditions. Adaptive measures are necessary, including a breakdown of associated risks and vulnerabilities. The cost of inaction may affect the various segments of Brazilian cities and may be greater at the cost of implementing preventive measures on climate change. For a study carried out by the European Commission (2013), the cost of inaction is six times higher than the cost of implementing an adaptation measure from vulnerability identification by 2050.


What are other key benefits?

One of the main gaps in the implementation of adaptation policies and projects is the lack of quantification of the costs related to climate vulnerability and the returns on investments in adaptation. Transforming a complex multidimensional concept, such as vulnerability, into a single dimension, which monetizes the damages, allows decision makers to better understand the results.

The cost of adaptation refers to the monetary measurement of the impacts, both positive and negative, associated with a particular adaptation action. In order to highlight the benefits associated with the implementation of an effective adaptation strategy, this cost is compared to a inaction scenario.

Considering that cities have a limited budget to spend, prioritization is a must when executing public policy. Through the use of MOVE, city managers can foresee where the investment on adaptation will be more effective to reduce the vulnerability, thus, optimizing the public expenditure.

 

 


Costs/Challenges


What are the proposal’s projected costs?

MOVE is a R&D project of WayCarbon, funded partially by ourselves and by FAPEMIGFinep and CNPq - three important innovation and applied research institutions of Brazil. Over this innovation project, since 2014, more than US$300,000.00 were invested.

Regarding to direct cost for contracting one study for a specific city, we estimate US$20,000 to US$50,000, depending on the city size and complexity.

 

 


Timeline

Project development time line: In 2012 the concept idea of the project was conceived, and since 2014 the project has been developed as a R&D project. Concrete results can be seen in studies delivered through the MOVE platform (Belo Horizonte Vulnerability Analisys, 2016; Climate Change Impact Assessment in the Atlantic Forest Regions and 3 conservation units within the framework of Biodiversity and Climate Change Program, GIZ, 2016; Economic assessment of food security vulnerability to climate change in Brazil – UN-ECLAC, 2014; Climate Vulnerability Mapping of municipality of Goiânia - IADB ESCI, 2012).

Project application time line: Once MOVE has been contracted, we estimate 4 to 6 months to deliver the final result.

Adaptation effects time line: After the results are delivered to a city or region, we consider that the effects, if any adaptation measure is adopted, can be noticed in short, medium to long term. The climate scenarios used as exposure input are able to estimate nowcast up to 100 year forecast.  


About the author(s)

Henrique Pereira: With a multidisciplinary background, Henrique holds a BSc. in International Relations from the Catholic University of Minas Gerais (PUC Minas), a graduate degree in Environmental Technologies from the Engineering College of the Federal University of Minas Gerais (UFMG) and a MSc. in Environment and Development from the London School of Economics and Political Science (LSE). He is the co-founder of WayCarbon, which provides climate change advisory services to the private and public sector. 

Leonardo Santiago: Bachelor degree in Environmental Engineering from the FUMEC University and developed his Master Studies in Environmental Studies at the Natural Environment Analysis, at the Autonomous University of Barcelona (UAB). Leonardo has extensive experience in GIS and its applications in environmental studies; development of studies related to conservation; and the development of risk assessment, uncertainties and environmental constraints for future projects.

Marco Follador: PhD in environmental engineer (Italy) and Geography (France) and Post-PHD in land use modeling (Brazil), with 11 years of experience in natural resources management, modeling and climate issues. He has been working for years at Climate Change and Risk Management Unit of European Commission, with a focus on integrated assessment of adaptation policies in rural areas.

Melina Amoni: Master Degree in Geography and PhD in Treatment of Spatial Information from the Catholic University of Minas Gerais. She has experience in Geoprocessing, Spatial Analysis, Climatology and Hydrometeorology. She has worked as climatology consultant in the area of climatology, climate change, hydrology and geoprocessing.

Virgílio Pereira: Biologist (UFMG) and have a masters in Agroecology and Rural Development (UFSCar). He has developed researches in agro climatic risk and diseases vector occurrence due climate change.


Related Proposals


References

IBGE, 2015. Estimativas da população residente para os municípios e para as unidades da federação brasileira com data de referência em 1º de julho de 2015.


IPCC, 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, P.J., Hanson, C.E. (Eds.)].Cambridge University Press, Cambridge, UK, 976 pp.

IPCC, 2012. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change [Field, C.B., Barros, V., Stocker, T.F., Qin, D., Dokken, D.J., Ebi, K.L., Mastrandrea, M.D., Mach, K.J., Plattner, G.-K., Allen, S.K., Tignor, M., Midgley, P.M. (Eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA, 582 pp.

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Marengo, J., Chou, S.C., Kay, G., Alves, L.M., Pesquero, J.F., Soares, W.R., Santos, D.C., Lyra, A., Sueiro, G., Betts, R., Chagas, D.J., Gomes, J., Bustamente, J.F., Tavares, P., 2012. Development of region future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and region analyses for the Amazon, Sao Francisco and the Parana River basins. ClimDyn 38: pp 1829-1848.

Montgomery, M. R., 2008. The Urban Transformation of the Developing World. Science, 319(5864), 761–764.http://doi.org/10.1126/science.1153012

UNISDR (2012) How to Make Cities More Resilient - A Handbook for Mayors and Local Government Leaders. Geneva, Switzerland: United Nations International Strategy for Disaster Reduction