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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Earth Sci.</journal-id>
<journal-title>Frontiers in Earth Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Earth Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-6463</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">840250</article-id>
<article-id pub-id-type="doi">10.3389/feart.2022.840250</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Earth Science</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Actionable Information in Flood Risk Communications and the Potential for New Web-Based Tools for Long-Term Planning for Individuals and Community</article-title>
<alt-title alt-title-type="left-running-head">Mostafiz et&#x20;al.</alt-title>
<alt-title alt-title-type="right-running-head">Flood Risk Communications</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Mostafiz</surname>
<given-names>Rubayet Bin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1054058/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Rohli</surname>
<given-names>Robert V.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1125696/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Friedland</surname>
<given-names>Carol J.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/219306/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lee</surname>
<given-names>Yong-Cheol</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Oceanography and Coastal Sciences</institution>, <institution>College of the Coast and Environment</institution>, <institution>Louisiana State University</institution>, <addr-line>Baton Rouge</addr-line>, <addr-line>LA</addr-line>, <country>United&#x20;States</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Coastal Studies Institute</institution>, <institution>Louisiana State University</institution>, <addr-line>Baton Rouge</addr-line>, <addr-line>LA</addr-line>, <country>United&#x20;States</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Bert S. Turner Department of Construction Management</institution>, <institution>Louisiana State University</institution>, <addr-line>Baton Rouge</addr-line>, <addr-line>LA</addr-line>, <country>United&#x20;States</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1115785/overview">Anna Scolobig</ext-link>, Universit&#xe9; de Gen&#xe8;ve, Switzerland</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/865746/overview">Pingping Luo</ext-link>, Chang&#x2019;an University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/897647/overview">Matteo Convertino, DrEng</ext-link>, Tsinghua University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1064861/overview">Ashraf Dewan</ext-link>, Curtin University, Australia</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Rubayet Bin Mostafiz, <email>rbinmo1@lsu.edu</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Geohazards and Georisks, a section of the journal Frontiers in Earth Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>28</day>
<month>02</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>840250</elocation-id>
<history>
<date date-type="received">
<day>20</day>
<month>12</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>07</day>
<month>02</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Mostafiz, Rohli, Friedland and Lee.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Mostafiz, Rohli, Friedland and Lee</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these&#x20;terms.</p>
</license>
</permissions>
<abstract>
<p>Because of its ubiquitous nature and catastrophic impacts, flood information should be readily available and continually evaluated, to maximize utility for the public and professionals. Web-based tools can fill existing needs for actionable information to inform decisions regarding flood damage mitigation for new and existing structures. The goal of this research is to identify the current capabilities, gaps, and future demands of Web-based flood communication systems. To understand the current and potential niche of Web-based flood tools, a review of the literature concerning the effectiveness of mass media, grassroots-based &#x201c;citizen science&#x201d; efforts, and social media in communicating flood risk is conducted. Then, the strengths of 50 major, freely-available, Web-based flood information portals are reviewed. Results suggest that mass media often provide actionable information, especially for short-term benefit immediately before, during, and immediately after the flood for individuals and community leaders. Citizen science and grassroots efforts encourage planning strategies to prevent or mitigate flood. Social media is most beneficial in raising awareness of the flood hazard and communicating short- and long-term mitigation and adaptation strategies. However, while mass media, citizen science, and social media have revolutionized the way that people plan for, survive, and recover from floods, their utility is largely restricted to addressing short-term information needs at the meso-scale or broader and/or conveying information about singular events to scientists and/or other professional interests. Actionable information to inform long-term planning and mitigating flood, for both the public and community leaders, remains lacking. A particular need is for communication mechanisms that satisfy several criteria simultaneously: wide broadcast, appealing delivery method, and focus on enhancing decision-making for long-term needs rather than solely for short-term benefit. Particularly useful would be a new, webtool that provides sufficient functionality to enhance flood risk reduction decision making, considering both the costs and benefits of mitigation.</p>
</abstract>
<kwd-group>
<kwd>web-based tools</kwd>
<kwd>website</kwd>
<kwd>flood insurance and cost</kwd>
<kwd>flood forecasting and monitoring</kwd>
<kwd>flood zone</kwd>
<kwd>social media</kwd>
<kwd>mass media</kwd>
<kwd>citizen science</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction: Communication for Minimizing Flood Risk</title>
<p>Perennially the world&#x2019;s most ubiquitous and expensive natural hazard, flooding increases in notoriety as populations and economic investment in coastal and other flood-prone areas continue to climb sharply (<xref ref-type="bibr" rid="B34">Dewan et&#x20;al., 2006</xref>; <xref ref-type="bibr" rid="B19">Bushra et&#x20;al., 2021</xref>). One way to enhance flood risk preparedness is through improved flood risk communication (<xref ref-type="bibr" rid="B87">Maidl and Buchecker 2015</xref>), especially that which provides actionable information such as previous, current, and future flood damage (<xref ref-type="bibr" rid="B98">Mostafiz et&#x20;al., 2021a</xref>) and hazard risk, mitigation and adaptation approaches, and cost-benefit analysis. Actionable information enables informed decision making for disaster preparedness, mitigation, response, and recovery. Among the challenges in this regard are that judgments about whether a piece of information is actionable vary (<xref ref-type="bibr" rid="B167">Zade et&#x20;al., 2018</xref>) and that &#x201c;actionable&#x201d; information must be filtered from &#x201c;noise&#x201d; (<xref ref-type="bibr" rid="B62">He et&#x20;al., 2017</xref>), although automated categorization information based on actionability is possible to assist with these challenges (<xref ref-type="bibr" rid="B168">Zahera et&#x20;al., 2021</xref>). Technological advances and enhanced grassroots efforts have traditionally improved communications regarding the flood risk, before, during, and after flood disasters. Such endeavors <italic>via</italic> mass media, citizen science, and social media are helpful but continue to fall short in some ways, as evidenced by the fact that losses in flood-prone areas continue to increase (<xref ref-type="bibr" rid="B99">Mostafiz et&#x20;al., 2021b</xref>, <xref ref-type="bibr" rid="B169">2021c</xref>).</p>
<p>The overarching goal of this research is to identify the publicly available, actionable information on existing flood risk communication tools that might help to fill the communication gap regarding the flood hazard. To accomplish this goal, we address three questions about communicating the flood risk: 1) What information exists about the success (or lack thereof) of various vehicles for communicating the flood hazard and their effects on flood hazard mitigation? 2) What actionable information is available online and required for citizens and community leaders? 3) What is the functionality for the intended users of online tools to provide actionable information to aid flood risk reduction decision making?</p>
<p>To support the goal, this research addresses the gap in summarizing and synthesizing the existing literature. We analyze strengths and weaknesses in each of the traditional areas of mass media, citizen science and other outreach, and social media, vis-&#xe0;-vis flood risk communication. We then review online webtools that can address some of these existing gaps, with emphasis on analyzing the strengths and areas for improvement of existing Web-based portals, particularly as these relate to functionality for the intended user. Finally, we discuss the actionable information needed for laypeople and community officials to enhance long-term flood planning and mitigation strategies to build safer structures and reduce flood loss. This research provides a snapshot of the current state of flood risk communication, so that in future years when such websites are no longer available or are in greatly changed form, the scientific community will have a documentation of the state of the science and art in&#x20;2022.</p>
</sec>
<sec id="s2">
<title>Actionable Information</title>
<p>Actionable information as defined here refers to relevant data that span flood magnitude and occurrence, damage resulting from flood hazards, alternatives to minimize flood damage, and the associated cost of these alternatives. The time scale on which information can be &#x201c;actionable&#x201d; ranges, but a distinction can be considered here between short-term and long-term actionable information, with &#x201c;short-term&#x201d; referring to information that informs decisions in the immediate preparation and aftermath of the flood hazard, and &#x201c;long-term&#x201d; referring to that information that is useful for mitigating the impacts of the hazard, at the preparation or recovery stages. This distinction is important because short-term actionable information enhances the prospect of survival of the hazard, while long-term actionable information enhances resilience. In addition, both short- and long-term information can be characterized based on the primary intended audience of the message. Here we distinguish only between &#x201c;individual-&#x201d; and &#x201c;community-&#x201d; level audiences, with the former dominated by homeowners or prospective homeowners concerned about enhancing flood resilience for their investment and the latter consisting of elected officials, builders, and planners seeking to enhance the quality of life for their constituents. The present research directly considers the following as specific types of long-term actionable information, at both the individual- and community-level, against which the risk communication outlets are measured: hazard properties (i.e.,&#x20;flood frequency and magnitude), effects of hazards (i.e.,&#x20;flood damage and loss), mitigation options (e.g., flood barriers), structure resiliency (e.g., elevation, wet flood proofing), effectiveness of combinations of both hazard and building mitigation (e.g., sandbag plus elevated structure) customized for the individual&#x2019;s particular situation (e.g., livable area, presence of basement, number of stories, length of time that the user plans to use the structure, whether structure is insured and if so, amount of coverage and deductible), community information (e.g., community rating system (CRS) score and steps needed and benefits of enhancing the community&#x2019;s rating, existing community freeboard requirements), and economic parameters (e.g., interest and discount rates, mortgage period).</p>
</sec>
<sec id="s3">
<title>Mass Media Effectiveness</title>
<p>The wide audience of mass media allows it to provide critical information for short-term flood mitigation and response, particularly at the individual level, such as in broadcasting official forecasted flood warnings and in post-disaster relief distribution. <xref ref-type="bibr" rid="B6">Altinay et&#x20;al. (2021)</xref> reminded that mass media can also assist in long-term flood communication, particularly by informing risk perception (e.g., <xref ref-type="bibr" rid="B152">Wahlberg and Sjoberg 2000</xref>; <xref ref-type="bibr" rid="B48">Fleming et&#x20;al., 2006</xref>; <xref ref-type="bibr" rid="B166">You and Ju 2017</xref>; <xref ref-type="bibr" rid="B88">Martins et&#x20;al., 2019</xref>; <xref ref-type="bibr" rid="B63">Heidari et&#x20;al., 2021</xref>) and disaster preparedness (<xref ref-type="bibr" rid="B141">Tekeli-Ye&#x15f;il et&#x20;al., 2011</xref>). In general, consumers tend to feel that mass media provide more information about natural hazards that are experienced locally and frequently (<xref ref-type="bibr" rid="B73">Karanikola et&#x20;al., 2015</xref>). The demand for mass media-generated public information, including a widening scope of roles, increases during and after disaster events (<xref ref-type="bibr" rid="B96">Miller and Goidel 2009</xref>).</p>
<p>Sources of information broadcasted <italic>via</italic> mass media vary widely in degree of expertise, influence, and perceived credibility, including topical experts, community leaders, public eyewitnesses, and anecdotal comments from broadcasters or citizens. The extent to which expertise/influence of the source (<xref ref-type="bibr" rid="B139">Takahashi and Tandoc 2016</xref>) and the admission of uncertainty in broadcasted statements (<xref ref-type="bibr" rid="B58">Gustafson and Rice 2019</xref>) affect public credibility has been examined. However, differences in perceived trust of such sources regarding flood risk perception and actionability remain uninvestigated.</p>
<p>The mass media has been criticized for its coverage of local flood events, particularly in the last 2 decades. Using the example of the North Sea Flood of 1953, <xref ref-type="bibr" rid="B59">Hall (2011)</xref> suggested that catastrophic events in the infancy of instantaneous mass media were initially likely to have been presented as opportunities for community resilience and solidarity, but later gave way to opportunities for assigning blame and accountability. <xref ref-type="bibr" rid="B114">Perez-Lugo (2001)</xref> concluded that the media fell short in communicating warning due to a 1998 flood in Puerto Rico, but that even proper warnings of impending disaster are likely to be misinterpreted as merely nuisance. <xref ref-type="bibr" rid="B73">Karanikola et&#x20;al. (2015)</xref> cautioned that exaggerations of hazards by media sources in their own self-interests can be problematic. <xref ref-type="bibr" rid="B17">Bright and Bagley (2017)</xref> noticed that election cycles can impact the extent of coverage of media events. <xref ref-type="bibr" rid="B147">Valencio and Valencio (2018)</xref> somewhat apologetically highlighted the many dilemmas involved in mass media reporting of catastrophic events, with the need to balance different expectations, perspectives, and needs desired by mass media consumers, all amid various logistical and financial limitations, leading to possible reduction of trust in the mass media. Consumers have also perceived that mass media effectiveness is less than ideal (<xref ref-type="bibr" rid="B3">Ajaero et&#x20;al., 2016</xref>).</p>
<p>On the whole, <xref ref-type="bibr" rid="B151">Vyncke et&#x20;al. (2017)</xref> confirmed that mass media remain important, even in present times, particularly through elimination of misinformation and quelling of fears, perhaps as a counterbalance in an environment of escalating importance of social media. Information from mass media sources may contain actionable information, especially for short-term benefit immediately before, during, and in the direct aftermath of the disaster, and especially for laypeople. However, there remains a lack of actionable information for the long-term mitigation and decision-making process for individual homeowners and community officials (e.g., cost-benefit analysis of flood mitigation options). The utility and credibility of mass media-generated products could be improved by individual and local customization <italic>via</italic> Web-based data-sharing systems that would enhance awareness of long-term flood mitigation and adaptation options (e.g., as the wisdom of purchasing flood insurance, building outside of flood zone, and elevating new or existing homes).</p>
</sec>
<sec id="s4">
<title>Effectiveness of Citizen Science and Related Grassroots Efforts</title>
<p>While mass media information can be regarded as a &#x201c;top-down&#x201d; information flow, grassroots efforts are usually &#x201c;bottom-up&#x201d; flows. Grassroots efforts that include public information fairs, Earth Day events, peaceful rallies, educational programs, outreach programs, and other similar efforts are termed &#x201c;citizen science.&#x201d; Intended consumers can be both at the individual and community levels, for both short- and long-term benefit.</p>
<p>Citizen science has been particularly useful in data collection about past, present, and future floods, for minimizing flood risk. Regarding understanding of past floods, <xref ref-type="bibr" rid="B146">Us&#xf3;n et&#x20;al. (2016)</xref> used participatory interviews to understand relationships among actors and agencies involved in the flood risk management in Santiago, Chile. <xref ref-type="bibr" rid="B53">Glas et&#x20;al. (2020)</xref> also used citizen science-based survey completion about floods in the past, but with a focus on Haiti. Citizen science has proven particularly useful in &#x201c;heat of the moment&#x201d; flood danger, such as storm surge monitoring (<xref ref-type="bibr" rid="B135">Spicer et&#x20;al., 2021</xref>), identifying flooded areas in real time (<xref ref-type="bibr" rid="B138">Sy et&#x20;al., 2019</xref>; <xref ref-type="bibr" rid="B162">Yang et&#x20;al., 2019</xref>), and recognizing spatial variability in urban flash floods (<xref ref-type="bibr" rid="B133">Smith and Rodriguez 2017</xref>). Efforts at understanding future risk have taken the form of clarification of flood scenarios (<xref ref-type="bibr" rid="B35">Dhiman et&#x20;al., 2019</xref>), improving spatial coverage of pluvial flood events (<xref ref-type="bibr" rid="B95">Michelson and Chang 2019</xref>), community mapping (<xref ref-type="bibr" rid="B115">Petersson et&#x20;al., 2020</xref>), and data collection in remote areas (<xref ref-type="bibr" rid="B109">Pandeya et&#x20;al., 2020</xref>).</p>
<p>Other citizen-science-based research has the potential to crosscut efforts to understand past, present, and future flood hazard mitigation. For example, cultural and linguistically diverse community leaders were found to serve as important gatekeepers in communicating flood details (<xref ref-type="bibr" rid="B131">Shepherd and van Vuuren 2014</xref>). <xref ref-type="bibr" rid="B60">Hamilton et&#x20;al. (2018)</xref>; <xref ref-type="bibr" rid="B74">Keech et&#x20;al. (2019)</xref> examined the role of public ad campaigns and informal communication, respectively, as a means of deterring the dangerous behavior of driving within floodwaters. Citizen engagement in implementing flood risk governance has proven to be successful and shows potential for future success in Europe (<xref ref-type="bibr" rid="B156">Wehn et&#x20;al., 2015a</xref>; <xref ref-type="bibr" rid="B157">Wehn et&#x20;al., 2015b</xref>; <xref ref-type="bibr" rid="B94">Mees et&#x20;al., 2016</xref>; <xref ref-type="bibr" rid="B93">Mees et&#x20;al., 2018</xref>) and elsewhere (<xref ref-type="bibr" rid="B89">Matczak and Hegger 2020</xref>), along with other &#x201c;bottom-up&#x201d; flood risk management initiatives (<xref ref-type="bibr" rid="B111">Paul et&#x20;al., 2018</xref>; <xref ref-type="bibr" rid="B128">Seebauer et&#x20;al., 2019</xref>).</p>
<p>The shortcomings of citizen science and related grassroots approaches have also been noted. A major disadvantage is data reliability (e.g., <xref ref-type="bibr" rid="B85">Lukyanenko et&#x20;al., 2016</xref>), particularly in evaluating flood risk (<xref ref-type="bibr" rid="B138">Sy et&#x20;al., 2019</xref>). <xref ref-type="bibr" rid="B7">Alves et&#x20;al. (2021)</xref> found that consuming messages from such grassroots efforts was associated with a low coping capacity even among those who had experienced flood. However, other recent work has shown that such uncertainties can be ameliorated to provide valuable information about the flood risk (<xref ref-type="bibr" rid="B143">Tian et&#x20;al., 2019</xref>). In summarizing the state of citizen science and related grassroots approaches regarding flood risk communication, <xref ref-type="bibr" rid="B24">Cheung and Feldman (2019)</xref> reaffirmed the importance while also calling for more collaboration between scientists and the lay public on applied problems using theoretical principles.</p>
<p>On the whole, citizen science appears to have an important and growing role in flood risk management. Its strengths are in enhancing public awareness of the necessity for long-term planning strategies to prevent or at least mitigate the flood hazard, thereby enhancing both individual- and community-level efforts. Toward this end, modern Internet capabilities allow for additional advances in citizen-science-based data collection for natural hazards (<xref ref-type="bibr" rid="B31">De Longueville et&#x20;al., 2010</xref>), including flood risk assessment. Likewise, modern communication tools such as Web apps (<xref ref-type="bibr" rid="B45">Ferri et&#x20;al., 2020</xref>) simultaneously across wide geographical areas (<xref ref-type="bibr" rid="B90">McCallum et&#x20;al., 2016</xref>; <xref ref-type="bibr" rid="B64">Hicks et&#x20;al., 2019</xref>) offers increased promise for citizen science as a means of mitigating the flood hazard. However, citizen science and grassroots efforts generally lack the provision of direct actionable information to individual homeowners or community officials at the micro-level, including cost-benefit analysis of mitigation options (e.g., elevated home, wet proofing, dry proofing, and sandbags).</p>
</sec>
<sec id="s5">
<title>Social Media Effectiveness</title>
<p>As social media share the advantage of mass media in reaching a wide audience quickly, it is not surprising that in recent years, flood information conveyed by social media has received increasing attention. The 2011 Bangkok flood may have been the first major flood event for which the role of social media was studied extensively, with the conclusion that flood losses were reduced by an average of 37 percent due to social media-acquired information (<xref ref-type="bibr" rid="B2">Allaire, 2016</xref>). Social media&#x2019;s role in mitigating the flood hazard has been praised, especially for its timeliness (<xref ref-type="bibr" rid="B81">Kwon and Kang, 2016</xref>), which provides short-term benefits.</p>
<p>In recent years, Twitter<sup>&#xae;</sup> has become a particularly important social media platform for flood communication and for analysis of its effectiveness in mitigating disaster risks, including that due to flood. <xref ref-type="bibr" rid="B106">Niles et&#x20;al. (2019)</xref> reported that use of Twitter varies by the various stages of disaster and by the type of disaster, with use in hurricane events peaking at the preparation stage and in flood and tornado events at the &#x201c;during&#x201d; or recovery stage. <xref ref-type="bibr" rid="B153">Wang et&#x20;al. (2021)</xref> found that Twitter use has a positive correlation with hurricane resiliency, suggesting that it can be a tool to enhance resilience. Machine learning techniques have revealed the temporal evolution of the various &#x201c;stages&#x201d; of Tweet applications in the context of a single disaster (<xref ref-type="bibr" rid="B6">Arapostathis, 2021</xref>), with other research calling for further integration of machine-learning-derived information in this regard (<xref ref-type="bibr" rid="B38">Dwarakanath et&#x20;al., 2021</xref>).</p>
<p>Social media-derived data can also be effective in managing long-term flood risk through enhancing scientific data availability. For example, social media are useful for identifying water height points (<xref ref-type="bibr" rid="B82">Li et&#x20;al., 2018</xref>) and areas likely to be submerged (<xref ref-type="bibr" rid="B134">Smith et&#x20;al., 2017</xref>), serving as a proxy for streamflow (<xref ref-type="bibr" rid="B120">Restrepo-Estrada et&#x20;al., 2018</xref>), and monitoring flood waters (<xref ref-type="bibr" rid="B125">Sattaru et&#x20;al., 2021</xref>), including mapping by use of images circulated on social media itself (<xref ref-type="bibr" rid="B116">Rajeshkannan and Kogilavani 2021</xref>). Bayesian statistical modeling has been conducted to consider data of various types (i.e.,&#x20;remotely sensed, high-resolution maps, and social media) in estimating flood inundation probability (<xref ref-type="bibr" rid="B121">Rosser et&#x20;al., 2017</xref>).</p>
<p>Social media can minimize flood risk during the human component of the disaster in both short and long terms through optimization of the quality and quantity of communication (<xref ref-type="bibr" rid="B84">Lovari and Bowen, 2020</xref>). At the planning stage, information planning and training possibilities gathered <italic>via</italic> social media are most effective on enhancing flood preparedness, and flood response and recovery (<xref ref-type="bibr" rid="B1">Abimbola et&#x20;al., 2020</xref>). During the flood, social media can disseminate news about sudden onset of the disaster (<xref ref-type="bibr" rid="B148">Vieweg et&#x20;al., 2014</xref>) to provide more effective warnings. The most effective niche for social media may be at the response stage (<xref ref-type="bibr" rid="B136">Stephenson et&#x20;al., 2018</xref>), though <xref ref-type="bibr" rid="B23">Cheng et&#x20;al. (2019)</xref> found that disaster response has been a largely underutilized tool in China. Social media has been found to be useful for immediate-post-disaster damage assessment (<xref ref-type="bibr" rid="B78">Kryvasheyeu et&#x20;al., 2016</xref>), relief and rescue attempts (<xref ref-type="bibr" rid="B13">Basu et&#x20;al., 2021</xref>), and recruiting and managing volunteers and gathering equipment in the flood aftermath (<xref ref-type="bibr" rid="B130">Sharp and Carter, 2020</xref>). At even longer time scales, the recovery process can benefit from greater investment in and more efficient information utilization from social media (<xref ref-type="bibr" rid="B163">Yeo et&#x20;al., 2020</xref>). <xref ref-type="bibr" rid="B8">Anderson (2020)</xref> noted that evidence of success during the recovery process can be derived from social media communications, in the form of a shift of pronouns from first person singular to first person plural (i.e.,&#x20;from &#x201c;I, me, my&#x201d; to &#x201c;we, us, our&#x201d;), as the former set of pronouns provides evidence of self-preservation (<xref ref-type="bibr" rid="B113">Pennebaker, 2013</xref>) while the latter signifies collectivity (<xref ref-type="bibr" rid="B112">Pavlidou, 2014</xref>).</p>
<p>Among all stages of these uses of social media associated with the flood hazard, the analysis of consumer preferences is an important consideration (<xref ref-type="bibr" rid="B44">Feldman et&#x20;al., 2016</xref>). To that end, development of network structures of information dissemination among civilians has been characterized (<xref ref-type="bibr" rid="B142">Olanrewaju et&#x20;al., 2016</xref>), including use of agent-based modeling to identify structures (<xref ref-type="bibr" rid="B37">Du et&#x20;al., 2017</xref>). Perhaps chief among such structures are cultural groups that go beyond ethnicity to include faith-based groups, non-profits, and others, all of which may create both conduits and barriers for communication among victims (<xref ref-type="bibr" rid="B164">Yeo et&#x20;al., 2018</xref>). Perhaps the next development will be to characterize spatio-temporal response stages based on a large collection of events.</p>
<p>In general, social media is most beneficial in raising awareness of the flood hazard and communicating short- and long-term mitigation and adaptation strategies. It is the easiest and quickest way for local authorities to assimilate actionable information to the masses before, during, and after the flood event. However, reliance on social media for mitigating flood impacts has also taken criticism in some of the same ways as for other natural disasters, particularly for providing slowing rates of information diffusion as the crisis continues (<xref ref-type="bibr" rid="B165">Yoo et&#x20;al., 2016</xref>), for being a source of information overload during a stressful period of information processing (<xref ref-type="bibr" rid="B69">Imran et&#x20;al., 2020</xref>), and for the lack of identifiability of direct actionable information (<xref ref-type="bibr" rid="B91">McCreadie et&#x20;al., 2019</xref>), especially for long-term planning. One specific type of actionable information missing from social media sources is user-defined, point- or polygon-specific, flood mitigation cost-benefit analysis at the individual- and community-level.</p>
</sec>
<sec id="s6">
<title>Resources and Functionality of Webtools</title>
<p>Publicly-accessible webtools have become important for communicating and minimizing flood risk, especially as a means of addressing the shortcomings of the more traditional sources of flood information (i.e.,&#x20;mass media, citizen science, and social media). As hundreds of webtools provide information related to floods and search engines may point to some more readily than others, the inclusion criteria here emphasize the most popular webtools and those that provide the most valuable flood-related information, while excluding any that are non-English language. A review of the available resources reveals several categories based on the primary objective, with some overlapping functionality: Flood forecasting, flood zoning, flood insurance, historical flood analysis, flood monitoring, flood hazard risk and cost, water management, and general flood information. Although this research is not intended to include all of the existing webtools for flood risk communication, a review of the major attributes of 15 sampled online flood risk resources is shown in <xref ref-type="table" rid="T1">Table&#x20;1</xref> by objective. The resources included in <xref ref-type="table" rid="T1">Table&#x20;1</xref> and among the 50 sampled here were selected based on the authors&#x2019; pre-existing knowledge, along with the prominence of the tools as revealed in online searches by the authors.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Flood risk web resources sampled with major attributes.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Objective</th>
<th align="center">Web portal name</th>
<th align="center">Geographic coverage</th>
<th align="center">Analysis level</th>
<th align="center">Information types</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="4" align="left">Flood forecasting</td>
<td align="left">Global Flood Awareness System (GloFAS)</td>
<td align="left">Global</td>
<td align="left">Station</td>
<td align="left">Flood risk forecast</td>
</tr>
<tr>
<td align="left">Global Flood Monitoring System (GFMS)</td>
<td align="left">50&#xb0;N to 50&#xb0;S</td>
<td align="left">Regional basin</td>
<td align="left">Rainfall, streamflow, and flood detection/intensity</td>
</tr>
<tr>
<td align="left">Iowa Flood Information System (IFIS)</td>
<td align="left">U.S. State of iowa</td>
<td align="left">Community, watershed, and city</td>
<td align="left">Precipitation and flood forecast</td>
</tr>
<tr>
<td align="left">Flood Forecasting and Warning Centre (FFWC)</td>
<td align="left">Bangladesh</td>
<td align="left">Station</td>
<td align="left">Water level</td>
</tr>
<tr>
<td rowspan="2" align="left">Flood zoning (Digital Flood Insurance Rate Maps (DFIRMs))</td>
<td align="left">Georgia Flood Map Program</td>
<td align="left">U.S. State of Georgia</td>
<td align="left">Individual building</td>
<td align="left">Flood zones, 30-years flood risk probability, and flood depths</td>
</tr>
<tr>
<td align="left">Digital Flood Insurance Rate Map of City of Galveston</td>
<td align="left">City of Galveston, Texas</td>
<td align="left">Individual building</td>
<td align="left">Flood zones</td>
</tr>
<tr>
<td align="left">Flood insurance</td>
<td align="left">FloodSmart</td>
<td align="left">United&#x20;States.</td>
<td align="left">Individual</td>
<td align="left">Flood insurance importance, coverage, premium, andclaim.</td>
</tr>
<tr>
<td rowspan="3" align="left">Historical flood analysis</td>
<td align="left">U.S. Flood Inundation Map Repository (USFIMR)</td>
<td align="left">United&#x20;States.</td>
<td align="left">Historical flood event</td>
<td align="left">Historical flood inundation area</td>
</tr>
<tr>
<td align="left">Global Flood Inundation Map Repository (GloFIMR)</td>
<td align="left">Global</td>
<td align="left">Historical flood event</td>
<td align="left">Historical flood inundation area</td>
</tr>
<tr>
<td align="left">WaterWatch</td>
<td align="left">United&#x20;States.</td>
<td align="left">State or hydrologic unit</td>
<td align="left">Past flow/runoff, current streamflow, flood, drought</td>
</tr>
<tr>
<td rowspan="2" align="left">Flood monitoring</td>
<td align="left">Dartmouth Flood Observatory (DFO)</td>
<td align="left">Global</td>
<td align="left">Individual building</td>
<td align="left">Flooding status</td>
</tr>
<tr>
<td align="left">NRT Global Flood Mapping</td>
<td align="left">Global</td>
<td align="left">10 &#xd7; 10&#xb0; tiles</td>
<td align="left">Daily surface and flood water</td>
</tr>
<tr>
<td align="left">Flood hazard risk and cost</td>
<td align="left">Aqueduct Global Flood Analyzer</td>
<td align="left">Global</td>
<td align="left">Country, state, city, and river basin</td>
<td align="left">Flood-induced urban damage, affected GDP, and affected population</td>
</tr>
<tr>
<td align="left">Water management</td>
<td align="left">Corps Water Management System (CWMS)</td>
<td align="left">United&#x20;States.</td>
<td align="left">City, state, and zip code</td>
<td align="left">Current stage, flow, and daily change in storage</td>
</tr>
<tr>
<td align="left">General flood information</td>
<td align="left">Flood Victoria</td>
<td align="left">Province of Victoria, Australia</td>
<td align="left">Province</td>
<td align="left">Before, during, and after flood information</td>
</tr>
</tbody>
</table>
</table-wrap>
<sec id="s6-1">
<title>Flood Forecasting</title>
<p>The Global Flood Awareness System (GloFAS; <xref ref-type="bibr" rid="B65">Hirpa et&#x20;al., 2018</xref>; <xref ref-type="bibr" rid="B22">Chen et&#x20;al., 2019</xref>; <xref ref-type="bibr" rid="B14">Baugh et&#x20;al., 2020</xref>; <xref ref-type="bibr" rid="B61">Harrigan et&#x20;al., 2020</xref>; <xref ref-type="bibr" rid="B110">Passerotti et&#x20;al., 2020</xref>; <xref ref-type="bibr" rid="B129">Senent-Aparicio et&#x20;al., 2021</xref>), produced by the Copernicus Emergency Management Service (CEMS), is an operational system for monitoring and forecasting floods globally. GloFAS consists of a hydrometeorological forecasting system that is connected to a monitoring system for providing forecasts out to the monthly and seasonal scales (<xref ref-type="bibr" rid="B4">Alfieri et&#x20;al., 2013</xref>). The system provides a quick overview of current and forecasted hydrometeorological events, including floods. GloFAS output can be used for streamflow forecasting and flood early warning (<xref ref-type="bibr" rid="B4">Alfieri et&#x20;al., 2013</xref>) at the macro-scale, but based on the information available, a user would be unlikely to be able to use the tool to mitigate long-term flood impacts at the micro-scale. Enhancing Flood Early Warning Services (<xref ref-type="bibr" rid="B39">EFEWS, 2022</xref>) increases flood forecast lead time with an operational 15-days flood forecast using GloFAS, thereby supporting flood resilience in the Hindu Kush Himalaya region. Likewise, the Flood Forecasting and Warning Centre (<xref ref-type="bibr" rid="B49">FFWC, 2022</xref>) provides flood forecast and flood warning information using GloFAS for Bangladesh.</p>
<p>The Global Flood Monitoring System (GFMS; <xref ref-type="bibr" rid="B160">Wu et&#x20;al., 2018</xref>), developed at the University of Maryland, inputs real-time precipitation data from the Tropical Rainfall Measuring Mission (TRMM; <xref ref-type="bibr" rid="B124">Santos et&#x20;al., 2019</xref>) Multi-satellite Precipitation Analysis (TMPA) and the Integrated Multi-SatellitE Retrievals for Global Precipitation Measurement (IMERG and GPM; <xref ref-type="bibr" rid="B77">Kidd and Huffman 2011</xref>; <xref ref-type="bibr" rid="B140">Tapiador et&#x20;al., 2012</xref>; <xref ref-type="bibr" rid="B57">Guo et&#x20;al., 2016</xref>; <xref ref-type="bibr" rid="B86">Mahmoud et&#x20;al., 2018</xref>) to produce hydrological runoff and routing model output, at a gridded spatial scale of 0.125&#xb0; from 50&#xb0;N to 50&#xb0;S. TRMM includes an array of international satellites that generate global observations of rain and snow by combining data from all passive-microwave instruments in the GPM suite (<xref ref-type="bibr" rid="B67">Huffman et&#x20;al., 2015</xref>). Flood detection/intensity forecasts are based on 13&#xa0;years of retrospective model runs with TMPA input, with flood thresholds derived for each grid point using surface water storage statistics (95th percentile plus parameters related to basin hydrologic characteristics). Streamflow, surface water storage, and inundation variables are also calculated at 1-km resolution (<xref ref-type="bibr" rid="B159">Wu et&#x20;al., 2014</xref>). The latest real-time GFMS couples the satellite-derived precipitation totals, runoff magnitude estimation and routing, and flood identification. <xref ref-type="bibr" rid="B161">Wu et&#x20;al. (2019)</xref> found that GFMS offers complementary information with the Soil Moisture Active Passive (SMAP) satellite data, available since 2015, to provide enhanced flood forecast information. GFMS data have been used for localized flood extent mapping, including in combination with U.S. Army Corps of Engineers (USACE) Hydrologic Engineering Center&#x2019;s River Analysis System (HEC-RAS; <xref ref-type="bibr" rid="B79">Kumar et&#x20;al., 2020</xref>). <xref ref-type="bibr" rid="B72">Kar et&#x20;al. (2020)</xref> integrated output from GloFAS and GFMS to classify flood severity at the drainage basin scale. The flood forecasting, based on precipitation forecasts and streamflow modeling, assists in short-term disaster preparedness by facilitating flood monitoring, including floods that can result from other hazards, such as tropical cyclones, and cause still other hazards, such as landslides. However, long-term actionable information is missing at the micro-scale for use by laypersons.</p>
<p>The iowa Flood Information System (IFIS; <xref ref-type="bibr" rid="B32">Demir and Krajewski 2013</xref>; <xref ref-type="bibr" rid="B33">Demir et&#x20;al., 2018</xref>) is a Google Maps&#xae;&#x2013;based Web platform developed by the iowa Flood Center (IFC) and represents one of the most comprehensive state-level resources of its kind. IFIS integrates and displays real-time meteorological, hydrological, and soil moisture conditions and forecasts by stream and watershed. This comprehensive data-driven system offers a flood hazard calculator tool with user-defined annual probabilities, to calculate the likelihood of a point flooding. One advantage is that IFIS helps to dispel the common misunderstanding that the flood return period determines the number of floods that can occur in a given return period. A shortcoming of IFIS is that even though it serves over 1,000 iowa communities, it has limited utility at scales more localized than the community&#x20;level.</p>
<p>National Oceanic and Atmospheric Administration (NOAA) has had a leading role in interactive hydrologic forecasting since the early 1990s (<xref ref-type="bibr" rid="B2">Adams, 2016</xref>). NOAA developed the Advanced Hydrologic Prediction Service (AHPS; <xref ref-type="bibr" rid="B92">McEnery et&#x20;al., 2005</xref>; <xref ref-type="bibr" rid="B103">National Research Council, 2006</xref>), an accurate, information-rich, Web-based forecast product. AHPS is particularly useful for generating extended probabilistic stream forecasts using ensemble precipitation and temperature forcing (<xref ref-type="bibr" rid="B100">Mullusky et&#x20;al., 2003</xref>; <xref ref-type="bibr" rid="B127">Schaake, 2003</xref>; <xref ref-type="bibr" rid="B126">Schaake et&#x20;al., 2004</xref>) to inform risk-based decisions (<xref ref-type="bibr" rid="B29">Connelly et&#x20;al., 1999</xref>). The most recent version of AHPS displays the magnitude and uncertainty of flood/drought events at time scales from hours to months, <italic>via</italic> user-friendly graphical products including hydrographs. Output includes flood forecast levels and time to crest, along with the likelihood of minor, moderate, or major flooding of a selected stream, the probability of stage exceeding a certain level, along with forecasted discharge during 90-day periods and an inundation map showing nearby infrastructure such as roads, railways, and landmarks relative to past floods. <xref ref-type="bibr" rid="B56">Gronewold et&#x20;al. (2011)</xref> used AHPS to characterize seasonal and inter-annual Great Lakes water levels but cautioned that AHPS dampens the variability relative to observed values. NOAA also produces the Automated Flood Warning System (AFWS; <xref ref-type="bibr" rid="B75">Keeney et&#x20;al., 2012</xref>), which uses gauge data from various sources including the U.S. National Weather Service (NWS), and other federal, state, and local agencies. AFWS data are incorporated not only into emergency planning, but also such routine and fundamental services as enhancing navigation and trade, evaluating water supply, treating wastewater, generating power, and enhancing structural integrity, often in&#x20;situations for which no other data are available (<xref ref-type="bibr" rid="B104">NWS, 2022</xref>).</p>
<p>Other flood forecasting tools are specifically designed for use at the regional scale outside the U.S.A. and particularly across political boundaries. For example, <xref ref-type="bibr" rid="B102">NOAA&#x2019;s (2022)</xref> Sea Level Rise Viewer shows the sea level rise and potential coastal flooding and inundation depth. Another useful webtool for flood forecasting is European Flood Awareness System (EFAS), provided by <xref ref-type="bibr" rid="B30">CEMS (2022)</xref>. EFAS emphasizes the large watersheds that cross national boundaries in Europe. In general, planning and decision-making regarding transboundary flooding issues are facilitated by <xref ref-type="bibr" rid="B54">Global Environment Facility (2022)</xref>, which sponsors an online tool for integrating present and future hydrometeorological scenarios including both flood and drought. The scenarios are useful even at the local (water utility) level. A notable example of a meso-(i.e.,&#x20;watershed-) level flood forecasting tool for the Global South is the Outil de Pr&#xe9;diction des Inondations dans la Delta Int&#xe9;rieur du Niger (<xref ref-type="bibr" rid="B107">OPIDIN. 2022</xref>), which forecasts flood inundation in the Inner Niger Delta.</p>
<p>These flood forecasting Web resources are designed for assessing flood risk and for promulgating real-time information regarding upcoming floods to professionals such as scientists, researchers, government officials, emergency managers, and media. While the webtools described above offer an important indirect service to the lay public <italic>via</italic> the mass media, they stop short of providing actionable information to enhance long-term individual or community resilience. For example, none of the tools described above make recommendations on the height to which particular buildings should be elevated.</p>
</sec>
<sec id="s6-2">
<title>Flood Zoning</title>
<p>Most U.S. counties provide online Flood Insurance Rate Maps (FIRMs) for the 100-years flood. For example, the <xref ref-type="bibr" rid="B52">Georgia Flood Map Program (2022)</xref> shows FIRMs for any property. A main advantage of such websites is a generally quick and easy determination of the flood zone, which fixes flood insurance rates and availability. A major disadvantage of such sites is that they generally lack interactivity and detailed information, especially on a near-real-time basis. Local or city-level products are also available for similar purposes to assist in flood zoning/insurance needs in the form of &#x201c;Digital FIRMs&#x201d; (DFIRMs). One example is that for the <xref ref-type="bibr" rid="B25">City of Galveston (2022)</xref>, which helps homeowners and prospective homeowners to identify their flood&#x20;zone.</p>
<p>Two Federal Emergency Management Agency (FEMA) products are also useful for flood zoning and other similar applications. The National Flood Hazard Layer (NFHL) viewer (<xref ref-type="bibr" rid="B42">FEMA, 2022a</xref>) depicts the current effective FIRM, flood zone, base flood elevation, levee location, and other information for the U.S., where maps have been modernized. NFHL compiles spatial data from the most recent FIRM database with Letters of Map Revision (LOMRs). The Flood Map Service Center (MSC; <xref ref-type="bibr" rid="B41">FEMA, 2022b</xref>) is the official public source for flood hazard information, including flood zones, produced in support of the National Flood Insurance Program (NFIP). MSC provides not only flood maps but also an array of other products useful for mitigating the flood hazard and communicating flood risk. The second product, <xref ref-type="bibr" rid="B40">FEMA (2022c)</xref> FloodMaps, provides new and preliminary FIRMs. The current flood map, FEMA standard flood hazard determination form, and FEMA&#x2019;s letter of map amendment are all available.</p>
<p>Another tool that falls into the category of flood zoning is the Virginia Flood Risk Information System (VFRIS; <xref ref-type="bibr" rid="B150">Virginia Department of Conservation and Recreation, 2022</xref>). VFRIS incorporates data from the NFIP, DFIRMs, NFHL, and other sources. Flood zone delineations, base flood elevation, sea level rise inundation areas, dam break inundation zones, 100-years return period flood depth, and parcel and building footprints are all depicted graphically. A similar product is available for Louisiana, called Louisiana&#x2019;s FloodMaps Portal (<xref ref-type="bibr" rid="B132">Skinner, 2022</xref>) that includes flood zone, ground elevation, effective FIRM, and historic FIRM data for that state at the individual building&#x20;level.</p>
<p>The primary advantage of such flood zoning Web resources is that the flood zone information is typically shown at the micro-scale or even at the individual building level. Such flood zone information alerts users to the need for purchasing flood insurance and other regulatory requirements. However, in general, like the tools or websites described above, these tend to provide little actionable information (e.g., the flood zone category for each building) for individual homeowners or community for long-term, flood-resilient construction.</p>
</sec>
<sec id="s6-3">
<title>Flood Insurance</title>
<p>Several useful tools are available for consumers to evaluate the economics of flood insurance for their properties. For example, <xref ref-type="bibr" rid="B43">FEMA&#x2019;s (2022d)</xref> &#x201c;FloodSmart&#x201d; provides details of flood insurance including its importance, types of flood insurance, coverage and premiums, insurance providers, and the process of purchasing insurance and filing claims. <xref ref-type="bibr" rid="B101">National Flood Services LLC&#x2019;s (2022)</xref> &#x201c;My Flood Quote&#x201d; also provides information regarding flood insurance (i.e.,&#x20;importance, cost, and process of purchase), claims, and assistance in the different stages of flood disaster. In general, these and similar sites are directed toward a lay public audience, but they also provide useful information for local-level community planning. For example, individual buildings where flood insurance is mandatory in the U.S. due to location within the 100-years flood zone are often identified. A shortcoming of flood insurance sites is that they typically lack quantitative information availability, such as the short- and long-term insurance premium savings for constructing above the minimum required elevation (i.e.,&#x20;freeboard).</p>
</sec>
<sec id="s6-4">
<title>Historical Flood Analysis</title>
<p>Archived information for historical flood events is available through the U.S. Flood Inundation Map Repository (USFIMR) project (<xref ref-type="bibr" rid="B71">Johnson et&#x20;al., 2019</xref>) housed at the University of Alabama. This product includes 10-30&#xa0;m-resolution satellite-based imagery of past U.S. flood events (<xref ref-type="bibr" rid="B27">Cohen et&#x20;al., 2018</xref>), with shapefiles available for download. Such information can be used as a basis of comparison for flood modeling and prediction. USFIMR does not attempt to integrate real-time meteorological or hydrological information. The extension of this project, known as the Global Flood Inundation Map Repository (GloFIMR), is also administered by the University of Alabama.</p>
<p>Similarly, U.S. Geological Survey (USGS) provides the WaterWatch (<xref ref-type="bibr" rid="B15">Beigi and Tsai, 2014</xref>; <xref ref-type="bibr" rid="B108">Oubeidillah et&#x20;al., 2014</xref>) service, which includes a Web-based map, graphs, and tables describing historical as well as near-real-time streamflow conditions in the U.S. at over 3,000&#x20;long-term USGS stream gauges. WaterWatch can also bundle streamflow output by hydrologic region, for daily, weekly, bi-weekly, or monthly mean periods for more precise analysis of hydrometeorological conditions back to 1901 (<xref ref-type="bibr" rid="B70">Jian et&#x20;al., 2008</xref>).</p>
<p>The United Nations Satellite Centre (UNOSAT) flood portal [United Nations Institute for Training and Research (<xref ref-type="bibr" rid="B144">UNITAR. 2022</xref>)] provides vectorized GIS files for satellite-derived historical flood data since 2007. Functionality includes the ability to import, incorporate, and analyze additional data to enhance decision-making for risk reduction.</p>
<p>All of the above historical flood webtools offer advantages for establishing precedents for flooding at the location of interest. Potential homeowners may use this information to build safe and stronger homes. However, the resources provide little other actionable information for the individual homeowner, such as the current and future probability of flooding, and damage and loss estimates from floods of various magnitudes.</p>
</sec>
<sec id="s6-5">
<title>Flood Monitoring</title>
<p>In addition to GloFAS and other tools described previously in the context of other objectives, Dartmouth Flood Observatory (DFO; <xref ref-type="bibr" rid="B83">Lin et&#x20;al., 2017</xref>) provides not only historical, but also near-real-time, maps of flooding globally, based on satellite imagery and data such as total precipitable water (i.e.,&#x20;precipitation that would fall if the entire column of water vapor above it condensed and precipitated), observed rainfall, and river and reservoir levels (<xref ref-type="bibr" rid="B76">Kettner et&#x20;al., 2021</xref>). <xref ref-type="bibr" rid="B80">Kundzewicz et&#x20;al. (2013)</xref> used this product to develop a flood climatology for Europe, and <xref ref-type="bibr" rid="B21">Chen et&#x20;al. (2020)</xref> did similar work for mainland Southeast&#x20;Asia.</p>
<p>Another useful product is from NASA Goddard Space Flight Center&#x2019;s (GSFC) Hydrology Laboratory, which operationalizes near-real-time global flood mapping using available satellite data resources. Currently, the system utilizes the twice-daily overpass of the Moderate-resolution Imaging Spectrometer (MODIS) instrument aboard the Terra and Aqua satellites. This system produces global daily surface and flood water maps at approximately 250-m resolution, in 10&#x20;&#xd7; 10&#xb0; tiles (<xref ref-type="bibr" rid="B105">Nigro et&#x20;al., 2014</xref>). <xref ref-type="bibr" rid="B16">Brakenridge and Anderson (2006)</xref> described early uses of MODIS in flood monitoring. Regional flood potential has been derived using terrestrial modeled water storage from the Gravity Recovery and Climate Experiment (GRACE) along with precipitation observations from the Global Precipitation Climatology Project (GPCP; <xref ref-type="bibr" rid="B118">Reager and Famiglietti,&#x20;2009</xref>.</p>
<p>The Automated Disaster Analysis and Mapping system (ADAM; <xref ref-type="bibr" rid="B158">World Food Programme (WFP) 2022</xref>) provides current flood alerts, events, and monitoring information globally. ADAM also tracks longer-term flood events that could have catastrophic consequences for human health, food security, and/or transportation.</p>
<p>Many websites, such as that of the <xref ref-type="bibr" rid="B12">Australian Government Bureau of Meteorology (2022a)</xref>, monitor floods at the national level. Likewise, the <xref ref-type="bibr" rid="B55">Government of Canada (2022)</xref> monitors the water level and discharge data at the Canadian province and territory level. Pakistan (<xref ref-type="bibr" rid="B50">Flood Forecasting Division, 2022</xref>), France (<xref ref-type="bibr" rid="B149">Vigicrues, 2022</xref>), and Germany (<xref ref-type="bibr" rid="B18">Bundesanstalt f&#xfc;r Gew&#xe4;sserkunde, 2022</xref>) are other examples of nations with similar offerings. These flood monitoring websites and webtools provide actionable information for the individual and community officials to prepare for imminent disaster. However, they generally lack information for long-term planning to promote resilient site selection and construction.</p>
</sec>
<sec id="s6-6">
<title>Flood Hazard Risk and Cost</title>
<p>
<xref ref-type="bibr" rid="B123">Samu and Kentel (2018)</xref> recently produced a comprehensive economic analysis of flood in Zimbabwe, but similar micro-scale analyses are difficult and lacking. In a useful overview of the advantages and limitations of global flood risk models (GFIRMs), <xref ref-type="bibr" rid="B155">Ward et&#x20;al. (2015)</xref> cautioned that GFIRMs are often mismatched to their intended uses, especially at the local level. The Aqueduct Global Flood Analyzer (AGFA; <xref ref-type="bibr" rid="B68">Iceland, 2015</xref>; <xref ref-type="bibr" rid="B137">Sutanudjaja et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B154">Ward, 2017</xref>) represents a zoomable, meso-resolution offering for determining riverine or coastal flood risk and cost-benefit analysis for either an &#x201c;optimistic&#x201d; or &#x201c;pessimistic&#x201d; scenario, for 2030, 2050, or 2080, according to the user-defined projection model. The tool provides a customizable, expected, annual urban damage and potential avoided loss by flood protection mechanisms (e.g., levee, dam; <xref ref-type="bibr" rid="B155">Ward et&#x20;al., 2015</xref>). <xref ref-type="bibr" rid="B119">Samu and Ak&#x131;ntu&#x11f; (2020)</xref> used AGFA successfully to assess economic risk of flood and drought in Zimbabwe. Nevertheless, as with many other systems described above, AGFA does not offer analysis at scales more localized than the watershed&#x20;level.</p>
<p>
<xref ref-type="bibr" rid="B145">USGS (2022)</xref> provides the Flood Inundation Mapper (FIM), which shows flood locations and potential loss estimates interactively, based on user-selected stream conditions. Historical flood information is also available. The &#x201c;what if&#x201d; flood scenarios available through FIM provide useful risk assessments and flood planning tools at the community&#x20;level.</p>
<p>The main limitation of existing flood hazard risk and cost webtools or websites is that the analysis is typically at city-to-global level instead of at the micro&#x2013;level, which limits the utility for decision making by individuals before constructing or purchasing a home. Flood Factor<sup>&#xae;</sup>, produced by <xref ref-type="bibr" rid="B46">First Street Foundation (2020a)</xref>, addresses such shortcomings by offering a micro-scale (i.e.,&#x20;individual building-level) analytic approach to understanding the flood risk for homes and other structures. <xref ref-type="bibr" rid="B47">First Street Foundation (2020b)</xref> also produces a national-level flood risk assessment from these data, which is now being used in as a tool for other research, such as that by <xref ref-type="bibr" rid="B10">Armal et&#x20;al. (2020)</xref>, who used Flood Factor to quantify past and future economic impacts due to&#x20;flood.</p>
</sec>
<sec id="s6-7">
<title>Water Management</title>
<p>One useful tool for water management is USACE&#x2019;s Corps Water Management System (CWMS; <xref ref-type="bibr" rid="B66">Hu et&#x20;al., 2006</xref>), which is an information system that integrates data management and short-term modeling tools. CWMS collects, validates, and stores information such as precipitation, river stage, and floodgate settings, on a real-time basis from platforms <italic>via</italic> Geostationary Operational Environmental Satellite, NWS Advanced Weather Interactive Processing System, and other sources. The values are then disseminated to users primarily through Web technology and are used to calibrate hydrologic and hydraulic models to represent current conditions. Stage and runoff forecasting is done using several engineering models. The control and visualization interface (CAVI) provides user functionality, such as in executing model runs, visualizing data, and selecting outputs (<xref ref-type="bibr" rid="B20">Charley and Luna, 2007</xref>). Agriculturalists can benefit greatly from such water management websites, not only because of information needed to inform planning regarding irrigation water availability, but also for harvest scheduling, reservoir water supply budgeting, and flooding following opening of dam reservoir gates. The constraint of such resources is that the utility is for a limited audience of agriculturalists. However, flood forecasting from water management websites may have untapped potential for assisting communities in flood preparation.</p>
</sec>
<sec id="s6-8">
<title>General Flood Information</title>
<p>Many websites provide general flood information for education and public awareness of flood impacts. For example, the <xref ref-type="bibr" rid="B11">Australian Government Bureau of Meteorology (2022b)</xref> includes flood warning services and text regarding flood preparation and understanding floods. Such information was useful to Australians before, during, and after Flood Victoria (<xref ref-type="bibr" rid="B97">Molino, 2009</xref>). In addition to its use for flood insurance described previously, <xref ref-type="bibr" rid="B43">FEMA&#x2019;s (2022d)</xref> &#x201c;FloodSmart&#x201d; includes more general information regarding cost of flooding and flood maps. <xref ref-type="bibr" rid="B117">Ready (2022)</xref>, an official website of the U.S. government, provides useful information for the preparation, action, and recovery stages of flood. <xref ref-type="bibr" rid="B28">Colorado Division of Homeland Security and Emergency Management Department of Safety (2022)</xref> includes basic flood information along with similar guidelines on what should be done before, during, and after a flood. Another example is <xref ref-type="bibr" rid="B26">City of New Orleans (2022)</xref>, which offers information on flood insurance, flood risk reduction, and flood resilience for new construction. These and similar websites serve the public in an education/outreach capacity regarding the short-term actions that should be taken to reduce the flood impact, but they offer limited actionable information for long-term planning, such as location specific comparative cost-benefit analyses under different mitigation options.</p>
</sec>
<sec id="s6-9">
<title>Overall Assessment of Webtools</title>
<p>Comprehensive assessment of the relative usefulness of the webtools is difficult. While data regarding use statistics and the types of data that users felt were most and least helpful would provide valuable information for webtool comparison, such data would likely be biased toward the webtools that serve areas that have the highest population density and experienced the most flooding. Few would use even the most comprehensive webtool if no ominous flood event exists in the region that it covers, and many would use even the least comprehensive webtool if there is an ominous flood event in the region that it covers. Similarly, the variety of scales covered across the webtools is also likely to bias any assessment of usefulness based on &#x201c;hit&#x201d; statistics. Moreover, while assessing what the users gain from the webtools would be useful, such an analysis would be most appropriate for an interview or questionnaire format on the webtool itself, but such data are unavailable to the authors.</p>
<p>Nevertheless, it is clear that the existing tools provide some actionable information for enhancing resilience, but with much room for improvement (<xref ref-type="table" rid="T2">Table&#x20;2</xref>). A major shortcoming is that, with the notable exception of Flood Factor, they tend to be useful only at the meso-scale or broader, and most tend to be geared toward short-term flood danger mitigation. While progress made in webtool development in recent years to mitigate the flood hazard, especially with applications such as Flood Factor, represents impressive advancement of science communication, there remains an absence of tools that optimize freeboard benefit-to-cost ratio at the individual building scale, for both new and existing residence owners, renters, developers, engineers, architects, and planners, in a bottom-up approach. Such a flood risk communication webtool is urgent so that individuals and community leaders can make decisions based on quantitative, long-term actionable information. However, as <xref ref-type="bibr" rid="B122">Salvati et&#x20;al. (2016)</xref> cautioned, such a development should not come at the expense of advances in other forms of flood communication designed for the layperson.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Types of long-term actionable information at the micro-scale in selected existing web resources.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left"/>
<th colspan="17" align="center">Long-term actionable information at micro-scale (for individuals and community)</th>
</tr>
<tr>
<th rowspan="2" align="left">Category</th>
<th colspan="3" align="center">Flood properties</th>
<th align="center">Effects of flood</th>
<th colspan="3" align="center">Mitigation options</th>
<th colspan="5" align="center">User customization information</th>
<th colspan="2" align="center">Community information</th>
<th colspan="3" align="center">Financial parameters</th>
</tr>
<tr>
<th align="center">Inundation area</th>
<th align="center">Depth</th>
<th align="center">Zone</th>
<th align="center">Flood damage and loss</th>
<th align="center">Hazard</th>
<th align="center">Structure</th>
<th align="center">Combined</th>
<th align="center">Basement</th>
<th align="center">&#x23; Of stories</th>
<th align="center">Livable area</th>
<th align="center">Time frame</th>
<th align="center">Insurance</th>
<th align="center">CRS</th>
<th align="center">Freeboard</th>
<th align="center">Interest rate</th>
<th align="center">Discount rate</th>
<th align="center">Mortgage period</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Iowa Flood Information System</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Georgia Flood Map Program</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Louisiana FloodMaps Portal</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Flood Factor</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Aqueduct Global Flood Analyzer</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">U.S. Flood Inundation Map Repository</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Global Flood Inundation Map Repository</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Global Flood Awareness System</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Global Flood Monitoring System</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Dartmouth Flood Observatory</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Corps Water Management System</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">WaterWatch</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Advanced Hydrologic Prediction Service</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Automated Flood Warning System</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">FEMA Flood Maps</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Flood and Dought Portal</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
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</tr>
<tr>
<td align="left">UNOSAT Flood Portal</td>
<td align="center">&#x2212;</td>
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<td align="center">&#x2212;</td>
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</tr>
<tr>
<td align="left">National Flood Hazard Layer</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x221a;</td>
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<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">FloodSmart</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">My Flood Quote</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Flood Victoria</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Flood Inundation Mapper</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Virginia Flood Risk Information System</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Digital Flood Insurance Rate Map of City of Galveston</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x221a;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Ready</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
<tr>
<td align="left">Flood Forecasting and Warning Centre</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
<td align="center">&#x2212;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>&#x201c;&#x221a;&#x201d; represents availability of long-term, actionable information at the micro-scale, while &#x201c;&#x2212;&#x201d; represents unavailability of such information.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Recently, researchers at Louisiana State University and University of New Orleans began developing the <xref ref-type="bibr" rid="B51">Flood Safe Home (2022)</xref> webtool to assist individual homeowners in the decision-making process based on life-cycle cost-benefit analysis (<xref ref-type="bibr" rid="B36">Dong and Frangopol, 2017</xref>). Available information will include the optimal elevation above ground level for the residence, for deriving the maximum benefit from not only avoiding flood loss but also from savings on insurance premiums. Such tools seem to be the next step in the provision of actionable information regarding flood hazard mitigation.</p>
</sec>
</sec>
<sec id="s7">
<title>Summary and Conclusion</title>
<p>Results of this analysis suggest that while mass media, citizen science, and social media have revolutionized the way that people plan for, survive, and recover from floods, their utility is largely restricted to addressing short-term needs for information and/or conveying information about singular events to scientists. More robust applications of these well-established forms of media might include broadcast of more specific, actionable information based on sound science from trusted voices to enhance long-term planning. However, availability of such actionable information to both community leaders and the lay public to satisfy needs for long-term planning for and mitigation of the flood hazard remains limited. A particular area of need is media that satisfy several criteria simultaneously: a delivery method that reaches the most people and that people find most appealing, while enhancing decision-making for long-term needs rather than for short-term gain. The most likely solution is a webtool that builds on Flood Factor by providing additional functionality to support improved flood risk reduction decision making, especially one that considers both the costs and benefits of mitigation. Such a tool would enhance resilience to the world&#x2019;s most widespread and impactful hazard.</p>
</sec>
</body>
<back>
<sec id="s8">
<title>Author Contributions</title>
<p>RM developed the detailed methodology, collected and analyzed the data, and developed the initial text. RR helped in the literature review, and edited early and late drafts of the text. CF helped to organize the paper and tables, and revised the text. Y-CL provided oversight on analysis and edited the&#x20;text.</p>
</sec>
<sec id="s9">
<title>Funding</title>
<p>This was funded by the Louisiana Sea Grant College Program (Omnibus cycle 2020&#x2013;2022; Award Number: NA18OAR4170098; Project Number: R/CH-03), the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine under the Grant Agreement number: 200010880 &#x201c;The New First Line of Defense: Building Community Resilience through Residential Risk Disclosure,&#x201d; and the U.S. Department of Housing and Urban Development (HUD; 2019&#x2013;2022; Award No. H21679CA, Subaward No. S01227-1). Any opinions, findings, conclusions, and recommendations expressed in this manuscript are those of the author and do not necessarily reflect the official policy or position of the funders. Publication of this article was subsidized by the Performance Contractors Professorship in the College of Engineering at LSU.</p>
</sec>
<sec sec-type="COI-statement" id="s10">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s11">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, orclaim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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