Web‐based stakeholder collaboration in flood risk management

Almoradie, Adrian; Arevalo, Vivian Juliette Cortes; Jonoski, Andréja

doi:10.1111/jfr3.12076

Cited by 47 publications

(27 citation statements)

References 13 publications

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“…The revised maps were organized into an interactive, online, and publicly accessible geographical information system (GIS) that served as a flood hazard viewer (ArcGIS Online, ESRI, Redlands CA). Price and Vojinovic (2008) propose GIS as a focal point for coordinating FRM; Wilkinson et al (2015) present a cloud-based tool for information access and knowledge exchange on local flood risk; Mackay et al (2015) suggest that GIS enhances opportunities for knowledge exchange between scientists, policy makers, and local communities regarding a broad range of environmental issues; Almoradie et al (2015) present a web-based GIS to support stakeholder collaboration in FRM; and Stephens et al (2014Stephens et al ( , 2015 report on the elements of sea level rise viewers for effective communication with stakeholders.…”

Section: Training Sessions and Outreachmentioning

confidence: 99%

Collaborative Modeling With Fine‐Resolution Data Enhances Flood Awareness, Minimizes Differences in Flood Perception, and Produces Actionable Flood Maps

et al. 2020

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Existing needs to manage flood risk in the United States are underserved by available flood hazard information. This contributes to an alarming escalation of flood impacts amounting to hundreds of billions of dollars per year and countless disrupted lives and affected communities. Making information about flood hazards useful for the range of decisions that dictate the consequences of flooding poses many challenges. Here, we describe collaborative flood modeling, whereby researchers and end‐users at two coastal sites co‐develop fine‐resolution flood hazard models and maps responsive to decision‐making needs. We find, first of all, that resident perception and awareness of flooding are enhanced more by fine‐resolution depth contour maps than Federal Emergency Management Agency (FEMA) flood hazard classification maps and that viewing fine‐resolution depth contour maps helps to minimize differences in flood perception across subgroups within the community, generating a shared understanding. We also find that collaborative flood modeling supports the engagement of a wide range of end‐users in contemplating the risks of flooding and provides strong evidence that the co‐produced knowledge can be readily adopted and applied for Flood Risk Management (FRM). Overall, collaborative flood modeling advances FRM by providing multiple points of entry for diverse groups of end‐users to contemplate the spatial extent, intensity, timing, chance, and consequences of flooding, thus enabling the web of decision‐making related to flooding to be better informed with the best available science. This transdisciplinary approach emphasizes vulnerability reduction and is complementary to FEMA Flood Insurance Rate Maps used for flood insurance administration.

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Section: Training Sessions and Outreachmentioning

confidence: 99%

Collaborative Modeling With Fine‐Resolution Data Enhances Flood Awareness, Minimizes Differences in Flood Perception, and Produces Actionable Flood Maps

et al. 2020

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“…To be assigned the worst level, the aggregated Jonoski, 2015). As adopted here, an index is derived from Equation (1), according to the relative distances to the best and worst conditions.…”

Section: Rules To Identify Levels Of Functional Status Per Parametermentioning

confidence: 99%

Decision support method to systematically evaluate first-level inspections of the functional status of check dams

Arevalo

Sterlacchini

Bogaard

et al. 2016

Structure and Infrastructure Engineering

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First-level inspections could be provided by skilled volunteers or technicians to pre-screen the functional status of check dams. This paper discusses the design and testing of a support method in collaboration with the responsible technicians in evaluating inspection reports. Reports are based on linguistic rating scales that are systematically aggregated into indices by means of a multi-criteria TOPSIS method with fuzzy terms. The aggregation procedure is carried out for three parameters representing the structure's status while highlighting any lack of completeness of inspection reports. The method was evaluated using inspection reports collected during a workshop in the Fella basin in the Italian Alps. The method allows the responsible technicians to set rules to categorise the aggregated indices in one of three levels, each corresponding with a course of action. Rules were useful to categorise the aggregated indices according to the structure's status. Disagreements on rating defects suggest that a weighted aggregation procedure to calculate the indices might lead to overestimating or underestimating defects. Complementary data from historical inspections or remote sensing are required to initiate specific actions. The method can be applied to pre-screen different types of hydraulic structures after adaptation to the local conditions and functional requirements.

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“…These platforms enable simultaneous multi-user access that facilitate the collaborative modelling process that is perceived as joint learning process involving FRM experts, authorities and stakeholders, critically supported by models and modelling results [32].…”

Section: Figurementioning

confidence: 99%

Toward generalized decision support systems for flood risk management

Muste

Firoozfar

2016

E3S Web Conf.

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Abstract. Despite the emergence of a large number of specialized decision-support systems (DSS) in the last decades, currently there are fewer efforts made for integrating the flood risk management relevant sciences with information and communication technologies into generalized DSS. Such systems are expected to formulate decision options for prevention, mitigation, preparation, response, and recovery from flood impacts with consideration of climate change, socio-HFRQRPLF HYROXWLRQ DQG VWDNHKROGHUV ¶ LQSXW &XUUHQWO\ WKHUH LV QR XQLILHG YLVLRQ RQ WKH DUFKLWHFWXUH components, and the needed computer and communications technologies for attaining generic DSS for flood mitigation and resilience. Moreover, there is no guidance of what components should be developed first and in what order and how to efficiently include human-computer interfaces for efficient stakeholder engagement and consensus. This paper calls for the formation of a strategic global partnership for framing and subsequently assisting in the development of a generalized flood DSS (FLOODSS) that can overcome the current flood DSS limitations. The call is preceded by a review of the flood decision-support terminology and context. Subsequently, an initial vision on the FLOODSS is outlined and the steps for transitioning such a system from vision to practice are proposed.

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Web‐based stakeholder collaboration in flood risk management

Cited by 47 publications

References 13 publications

Collaborative Modeling With Fine‐Resolution Data Enhances Flood Awareness, Minimizes Differences in Flood Perception, and Produces Actionable Flood Maps

Collaborative Modeling With Fine‐Resolution Data Enhances Flood Awareness, Minimizes Differences in Flood Perception, and Produces Actionable Flood Maps

Decision support method to systematically evaluate first-level inspections of the functional status of check dams

Toward generalized decision support systems for flood risk management

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