Towards drought impact-based forecasting in a multi-hazard context

Boult, Victoria L.; Black, Emily; Abdillahi, Halima Saado; Bailey, Meghan; Harris, Clare; Kilavi, Mary; Kniveton, Dominic; MacLeod, David; Mwangi, Emmah; Otieno, George; Rees, Elizabeth; Rowhani, Pedram; Taylor, Olivia; Todd, Martin C.

doi:10.1016/j.crm.2022.100402

Cited by 8 publications

(11 citation statements)

References 13 publications

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“…This contrasts the widely used predefined forecast threshold triggers for preagreed actions. Being more reliable and transparent, this predefined option helps to avoid the real-time subjectivity and extra costs; however, even predefined systems can allow for flexible elements to be included to account for vulnerability dynamics (Boult et al, 2022). This is further reinforced by the latest GAR2021 report (UNDRR, 2021), which emphasizes that iterative learning is a must when modeling an action in response to a threat as complex as drought.…”

Section: Contextual Challenge: Account For Multi-sectoral Spatially H...mentioning

confidence: 99%

Advances and gaps in the science and practice of impact‐based forecasting of droughts

Shyrokaya,

Pappenberger,

Pechlivanidis

et al. 2023

WIREs Water

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Advances in impact modeling and numerical weather forecasting have allowed accurate drought monitoring and skilful forecasts that can drive decisions at the regional scale. State‐of‐the‐art drought early‐warning systems are currently based on statistical drought indicators, which do not account for dynamic regional vulnerabilities, and hence neglect the socio‐economic impact for initiating actions. The transition from conventional physical forecasts of droughts toward impact‐based forecasting (IbF) is a recent paradigm shift in early warning services, to ultimately bridge the gap between science and action. The demand to generate predictions of “what the weather will do” underpins the rising interest in drought IbF across all weather‐sensitive sectors. Despite the large expected socio‐economic benefits, migrating to this new paradigm presents myriad challenges. In this article, we provide a comprehensive overview of drought IbF, outlining the progress made in the field. Additionally, we present a road map highlighting current challenges and limitations in the science and practice of drought IbF and possible ways forward. We identify seven scientific and practical challenges/limitations: the contextual challenge (inadequate accounting for the spatio‐sectoral dynamics of vulnerability and exposure), the human‐water feedbacks challenge (neglecting how human activities influence the propagation of drought), the typology challenge (oversimplifying drought typology to meteorological), the model challenge (reliance on mainstream machine learning models), and the data challenge (mainly textual) with the linked sectoral and geographical limitations. Our vision is to facilitate the progress of drought IbF and its use in making informed and timely decisions on mitigation measures, thus minimizing the drought impacts globally.This article is categorized under: Science of Water > Water Extremes Science of Water > Methods Science of Water > Water and Environmental Change

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Section: Contextual Challenge: Account For Multi-sectoral Spatially H...mentioning

confidence: 99%

Advances and gaps in the science and practice of impact‐based forecasting of droughts

Shyrokaya,

Pappenberger,

Pechlivanidis

et al. 2023

WIREs Water

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“…It aims to directly forecast the impacts of extreme weather in order to allow for more targeted interventions (ARRCC et al., 2020). Impact‐based forecasting often depends on process‐based or machine learning approaches to anticipate impacts, but it is hindered by the poor availability of accurate impact data (Boult et al., 2022).…”

Section: Applying Fa In Conservationmentioning

confidence: 99%

“…Following the action‐based forecasting approach—determining the lead time required for each action (i.e., procurement and training may take several weeks, whereas canopies can be installed in a day) and the willingness to act in vain—may prove useful in conservation, particularly in cases for which sufficient monitoring and impact data are unavailable (Boult et al., 2022). Working together with forecasting experts and decision scientists to coproduce EAPs that carefully align anticipatory actions with forecast thresholds, accounting for uncertainties and potential conservation risks associated with intervention, will help realize FbA in conservation.…”

Section: Applying Fa In Conservationmentioning

confidence: 99%

Forecast‐based action for conservation

Boult

2023

Conservation Biology

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Extreme weather events pose an immediate threat to biodiversity, but existing conservation strategies have limitations. Advances in meteorological forecasting and innovation in the humanitarian sector provide a possible solution—forecast‐based action (FbA). The growth of ecological forecasting demonstrates the huge potential to anticipate conservation outcomes, but a lack of operational examples suggests a new approach is needed to translate forecasts into action. FbA provides such a framework, formalizing the use of meteorological forecasts to anticipate and mitigate the impacts of extreme weather. Based on experience from the humanitarian sector, I suggest how FbA could work in conservation, demonstrating key concepts using the theoretical example of heatwave impacts on sea turtle embryo mortality, and address likely challenges in realizing FbA for conservation, including establishing a financing mechanism, allocating funds to actions, and decision‐making under uncertainty. FbA will demand changes in conservation research, practice, and governance. Researchers must increase efforts to understand the impacts of extreme weather at more immediate and actionable timescales and should coproduce forecasts of such impacts with practitioners. International conservation funders should establish systems to fund anticipatory actions based on uncertain forecasts.

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“…Early warning systems can improve the detection of approaching natural disasters, inform the communities about the imminent threat, and advise people what actions they should take [21]. Also, they help in building resilient communities [22] And to better anticipate specific natural disasters, many humanitarian organizations (e.g., International Federation of the Red Cross [23]; START Network's Disaster Risk Financing Mechanisms [24]; the Famine Early Warning Network [25]) developed early warning systems [26]. Early warning systems can save lives and protect properties.…”

Section: A Disaster Preparedness and Multi-hazard Early Warning Systemsmentioning

confidence: 99%

A Baseline Assessment of the Multi-Hazard Early Warning Systems in the Province of Batangas, Philippines

Era¹,

Vallar²,

Osman³

et al. 2022

International Journal on Advanced Science, Engineering and Information Technology

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Batangas is a first-class province of the Philippines located on the southwestern part of Luzon in the CALABARZON region. Its capital is Batangas City and the provinces of Cavite and Laguna border it to the north and Quezon to the east. Across the Verde Island Passages to the south is the island of Mindoro and to the west lies the South China Sea. Geographically, Batangas is a combination of plains and mountains, including the world's smallest volcano, Mt. Taal, with an elevation of 600 meters, located in the middle of the Taal Lake. Other important peaks in Batangas include Mt. Makulot with an elevation of 830 m, Mt. Talamitan with 700 m, Mt. Pico de Loro with 664 m, Mt. Batulao with 811 m, Mt. Manabo with 830 m, and Mt. Daguldol with 672 m. The province has many beaches and is famous for its excellent diving spots. It has the second largest international seaport in the Philippines after Metro Manila. The city's identification as an industrial growth center in the region and the focal point of the CALABARZON program resulted in the increasing number of business establishments in the city's Central Business District (CBD) and numerous industries operating at the province's industrial parks. Given the geographical nature of the province and its current development, the present study was envisioned to assess its preparation for any forms of an imminent natural disaster. In particular, the study assessed the usage of multi-hazard early warning systems in the province using survey interviews with various stakeholders. The results of the 30 survey interviews showed that there is a limited multi-hazard early warning system in the province although the majority of the participants have experienced natural disasters in their respective areas.

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Towards drought impact-based forecasting in a multi-hazard context

Cited by 8 publications

References 13 publications

Advances and gaps in the science and practice of impact‐based forecasting of droughts

Advances and gaps in the science and practice of impact‐based forecasting of droughts

Forecast‐based action for conservation

A Baseline Assessment of the Multi-Hazard Early Warning Systems in the Province of Batangas, Philippines

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