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Integrating Ecosystems in Risk Assessments: Lessons from Applying InVEST Models in Data-Deficient Countries

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Ecosystem-Based Disaster Risk Reduction and Adaptation in Practice

Part of the book series: Advances in Natural and Technological Hazards Research ((NTHR,volume 42))

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Abstract

The linkages between ecosystem conditions and disaster risk reduction have gained increasing international attention. Despite this growing awareness, national and local decision makers often lack the tools to visualize disaster risk under different ecosystem conditions. As a result, the importance of ecosystems continues to be under-appreciated in decision-making processes related to disaster risk reduction and climate change adaptation. While spatial models have commonly been applied in both ecological assessments and disaster management, there have been relatively few studies that merge these two applications. This chapter demonstrates applications of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) tool in data-deficient countries where the United Nations Environment Programme (UNEP) is currently implementing ecosystem-based field interventions to reduce disaster risk. InVEST software (developed by the Natural Capital Project) provides spatial tools for assessing ecosystems and disaster risk even when limited data is available. The first study presented in this chapter takes into consideration the role of coastal and marine ecosystems in reducing exposure to coastal hazards in a small municipality in the south of Haiti. It provides an example of a qualitative assessment of exposure to storm surges and coastal flooding under different ecosystem management scenarios. The second study examines realistic land use change scenarios such as reforestation and urbanization and their impacts on soil erosion and sedimentation in a river basin in the Democratic Republic of the Congo. Through detailed examination of the two case studies, this chapter aims to demonstrate how integrated models such as InVEST could function as decision-support tools for considering ecosystem-based solutions for disaster risk reduction and climate change adaptation. The limitations, challenges and areas for improvement of each model application, as well as implications for local decision-making and awareness-raising, are discussed.

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Notes

  1. 1.

    Spatial models are analytical procedures applied in geographic information systems (GIS) that simulate real-world conditions using spatial data.

  2. 2.

    InVEST is available for download at www.naturalcapitalproject.org

  3. 3.

    Lower tiers are qualitative and have minimal data requirements, while higher tiers can quantify ecosystem services through complex calculations and more intensive data requirements (Guerry et al. 2012). Tier 0/1 models such as Coastal Vulnerability and Sediment Retention are most suitable for identifying patterns of ecosystem services and supporting planning or priority setting exercises with limited data (Daily et al. 2011). If more data is available, more complex InVEST models can be applied, for example to quantify the protective value of ecosystems based on a particular hurricane (Guerry et al. 2012).

  4. 4.

    It should be noted that while InVEST CV model calculates exposure to coastal flooding and storm surges, it does not measure inland flooding from storm water.

  5. 5.

    For more information see: http://www.unep.org/disastersandconflicts/Introduction/DisasterRiskReduction/Countryactivities/tabid/104431/Default.aspx

  6. 6.

    We used version 3.0.0 of InVEST Sediment Retention model, which has D-infinity flow direction instead of D-8 and therefore offers a more accurate calculation of flow paths than previous versions of the model.

  7. 7.

    InVEST models can be applied in as little as one month, although depending on the location, scale of work and capacity of the team, it may take up to 24 months to gather data and run models (Eichelberger 2013).

  8. 8.

    Comprehensive risk assessments entail examination of vulnerability, quantitative potential damage over time and at various intensities of hazards, assessment of exposed economic resources and people.

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Acknowledgements

We would like to acknowledge Antoine Mfumu, Fils Makanzu, Souhail Elmdari, and Isavella Monioudi who helped us with parts of the analyses presented in this chapter. We are also grateful to the following organizations in Haiti and DR Congo that provided data: AUBR-L, METTELSAT, REGIDESO Kimwenza, CNIGS, CIAT and UNDP Haiti. And lastly, thanks are due to Greg Guannel, Marisol Estrella, Maximilien Pardo, Celine Jacmain, Adonis Velegrakis and two anonymous reviewers for their insightful comments.

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Authors and Affiliations

  1. United Nations Environment Programme, 11-15 Chemin des Anémones, Châtelaine, CH-1219, Geneva, Switzerland

    Niloufar Bayani

  2. SUZA, 146, Zanzibar, Tanzania

    Yves Barthélemy

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  1. Niloufar Bayani
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  2. Yves Barthélemy
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Correspondence to Niloufar Bayani .

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Editors and Affiliations

  1. Institute for Environment and Human Secu, United Nations University, Bonn, Nordrhein-Westfalen, Germany

    Fabrice G. Renaud

  2. Commission on Ecosystem Management, International Union for Conservation of Nature, Gland, Switzerland

    Karen Sudmeier-Rieux

  3. Post-Conflict and Disaster Management Branch, United Nations Environment Programme, Geneva, Switzerland

    Marisol Estrella

  4. Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), TH Köln, University of Applied Sciences, Köln, Germany

    Udo Nehren

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Bayani, N., Barthélemy, Y. (2016). Integrating Ecosystems in Risk Assessments: Lessons from Applying InVEST Models in Data-Deficient Countries. In: Renaud, F., Sudmeier-Rieux, K., Estrella, M., Nehren, U. (eds) Ecosystem-Based Disaster Risk Reduction and Adaptation in Practice. Advances in Natural and Technological Hazards Research, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-319-43633-3_10

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