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Spatio-Temporal Drought Risk Analysis Using GIS-Based Input Output Modeling

In: Advances in Spatial and Economic Modeling of Disaster Impacts

Author

Listed:
  • Sheree Pagsuyoin

    (University of Massachusetts-Lowell)

  • Joost Santos

    (George Washington University)

  • Gustavo Salcedo

    (University of Massachusetts-Lowell)

  • Christian Yip

    (George Washington University)

Abstract

Recent studies in the area of disaster risk management emphasize the increasing likelihood and adverse consequences of droughts. Droughts can have widespread severe impacts; for example, in 2016, the northeastern region of the United States experienced record levels of rainfall shortage, forcing regional government agencies to issue warnings and emergency advisories to the public. During drought events, the economic losses due to water shortage and government-mandated restriction measures create costly cascading effects due to the interconnected and interdependent nature of the economic sectors. Such sectors have different degrees of dependence on water, and often there is a lack of coordination in implementing sector-specific resilience measures, which makes the drought recovery management a complex and daunting task. Indeed, water is a critical resource and it is essential in producing a myriad number of goods and services in the economy. In the current chapter, the authors develop a new modeling framework for drought risk management by integrating spatial analysis and dynamic input-output modeling to better understand the direct and indirect effects of drought scenarios on interdependent sectors of a regional economy. A decision support tool that utilizes the geographic information systems (GIS) platform was also developed to perform the following functions: (1) model the time-varying impacts of drought scenarios on a regional economy, (2) simulate the responses of individual sectors throughout various stages of the drought recovery timeline, and (3) estimate the regional economic losses and potential benefits of implementing different categories of drought management policies. The utility of the integrated IO-GIS framework and decision support tool is demonstrated in a case study of the historic and widespread drought that occurred in the State of Massachusetts in 2016.

Suggested Citation

  • Sheree Pagsuyoin & Joost Santos & Gustavo Salcedo & Christian Yip, 2019. "Spatio-Temporal Drought Risk Analysis Using GIS-Based Input Output Modeling," Advances in Spatial Science, in: Yasuhide Okuyama & Adam Rose (ed.), Advances in Spatial and Economic Modeling of Disaster Impacts, chapter 0, pages 375-397, Springer.
    • Handle: RePEc:spr:adspcp:978-3-030-16237-5_15
    DOI: 10.1007/978-3-030-16237-5_15
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    Cited by:

    1. Yanqun Ren & Jinping Liu & Patrick Willems & Tie Liu & Quoc Bao Pham, 2023. "Detection and Assessment of Changing Drought Events in China in the Context of Climate Change Based on the Intensity–Area–Duration Algorithm," Land, MDPI, vol. 12(10), pages 1-18, September.
    2. Sass, Karina Simone & Haddad, Eduardo Amaral & Mendiondo, Eduardo Mario, 2023. "Impacts of Droughts on Economic Activities in The São Paulo Metropolitan Area," TD NEREUS 4-2023, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
    3. Sheree A Pagsuyoin & Joost R Santos, 2021. "Modeling regional impacts and resilience to water service disruptions in urban economies," Environment and Planning B, , vol. 48(5), pages 1058-1074, June.
    4. Kourtit, Karima & Nijkamp, Peter & Banica, Alexandru, 2023. "An analysis of natural disasters’ effects – A global comparative study of ‘Blessing in Disguise’," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).

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