Brief Communication: Inclusiveness in designing an early warning 1 system for flood resilience

Abstract

22 community-at-risk by engaging them in every stage of the decision-making process .  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  1 Introduction   51 The theme for World Meteorological Day 2022 (March 23) was 'Early Warning and Early Action -52 Hydrometeorological and Climate Information for Disaster Risk Reduction' which emphasises the vital 53 importance of information generation and sharing to minimize the risks from hydrometeorological extremes. 54 Further, the United Nations secretary-general announced a major initiative, to be delivered via COP 27 (UN 55 Climate Conference), for 'everyone on Earth should be protected by early warning systems against extreme 56 weather and climate change within the next five years.' These policy initiatives indicate the growing need for 57 new information and knowledge relating to risks arising directly from hazard but also from the complex 58 interactions with exposure and vulnerability (IPCC defined risk=hazard × exposure × vulnerability ÷ capacity 59 to cope, see details in Cardona et al., 2012). Although our understanding of hydrological extremes, such as 60 floods, has evolved in recent decades as we view them through the lens of hydro-complexity (Kosow et al.,61 2022). However, floods remain a "wicked" problem and are becoming more destructive with ecological, social 62 and economic impacts (i.e., source of water pollution, damages to wastewater and irrigation system, excessive 63 erosion damaging riverbank settlements, see details in Kosow et al., 2022;Hannah et al., 2020). In mountainous 64 regions floods are becoming more unpredictable and destructive in response to increasing climatic extremes. 65 This is exacerbated by anthropogenic pressures which have severely modified formerly pristine, high altitude 66 river catchments. Furthermore, increased encroachment of riverbanks, dumping of solid and sewer waste and 67 rapid urbanisation has increased the proportion of low-income communities living in flood-prone areas ( In this commentary, we assess potential approaches for facilitating inclusiveness in the design of a flood early 91 warning system by integrating social, cultural and political aspects, and identify preconditions and missing links. 92 2 Current approaches embedding inclusiveness in water and disaster research 93 In water and disaster research several approaches are emerging to provide concepts, tools and framings that can 94 be used to support inclusiveness and disciplinary convergence for actionable knowledge production. The 95 concept of knowledge co-production has emerged from science-society interaction under the umbrella of define the participatory convergence research as 'an approach to knowledge production and action that involves 113 diverse teams working together in novel ways-transcending disciplinary and organizational boundaries-to 114 address vexing social, economic, environmental, and technical challenges in an effort to reduce disaster losses 115 and promote collective well-being' (pp. 2). While this research approach has been identified as one of the best 116 ten big ideas in funding allocation and research direction by the National Science Foundation of USA (2016), 117 there has been little exploration on the framing (i.e., methods and ethics) to apply this in practice (Westerhoff ÷ ) suggest that reduction in risk is dependent not only on efficient forecasting 148 of hazard, but also on the understanding of associated exposure, vulnerability and capacity to cope by the 149 exposed community. Therefore, in Figure 1, we present three interdependent steps, i.e., collate data on risk 150 generate data and models to facilitate forecasting and disseminate that is necessary to develop a system that not 151 only produce flood alerts, but also provide risks information through monitoring exposure, vulnerability and 152 capacity of the community-at-risk. 153 154 3

.1 Mapping the risks through data collection and observation 155
In this step, it is crucial to collect as much information possible, to generate knowledge on the locality and the 156 community at risk to design a purposeful early warning system. The knowledge generated can also inform on 157 exposure, vulnerability and ability to cope if a disaster strikes and enables decision-makers to adjust or adapt 158 necessary precautionary measures to respond efficiently in a timely manner ( illegal settlement and therefore, will not engage. People might not engage also as they already lost their trust on 173 the governance system (i.e., did not receive compensation for their previous flood damage, recurring failed 174 commitments from the political parties to reduce flood vulnerability). Previous research partly discussed these 175 complexities ( and unrealistic expectation relating to the monitoring system. Therefore, it is crucial to make plausible 188 assumptions of risk behaviour relevant to flood exposure and vulnerability that can feed into designing the early 189 warning system including having more focused conversation with the community at risks, specifying the aim 190 and expected outcome of the flood monitoring system.

.2 Forecasting hazard risks and establish an alert system in real time 193
This step utilises information from the previous step to identify design specifications to build the early warning 194 system. For example, suitable sensor technology, identification of relevant variables (i.e., rainfall, water level), 195 suitable location(s) to install the components and transmit/receive data. In addition, decision-making on data 196 collection attributes, such as data transmission frequency, among others is critical because there will always be of what levels of technical details to share and which is the right time/phase to share with the community or the 234 state authority. This inadequate understanding to decide the right time or phase will risk of over-promising for 235 warning alert. 236 237

Communication and dissemination 238
After installation of the alert system, identification of the best possible modes of dissemination is critical to 239 further interact with the vulnerable communities and communicate the potential risks along with tentative 240 necessary actions to minimise the risks. While this has been the most critical part, it is also one of the most 241 interactive components in the entire scheme. New ICT technologies such as interactive dashboard visualisations, 242 give more flexibility in developing the visualisation to disseminate the EWS outputs in a way that can be easily 243 understood by the community is a major challenge (Mashi et  not only with the communities but also with the responsible state authorities and how they are supporting or 251 engaged in with the decision-making processes to respond in a timely manner. 252 253 4 A SMART way forward 254 We believe that through this commentary we have raised critical questions and identified missing links in the 255 context of disaster resilience and the development of tools to improve preparedness and response. The most 256 important include i) the absence of diverse contextual risk angle and community reactions; ii) a lack of 257 community trust in government agencies and technology focused forecasting; iii) significant data limitations to 258 ensure effective EWS operation and impact-based forecasting; and iv) a lack of effective communication 259 strategies. All these points need deeper exploration to ensure inclusive EWS are developed in data-scarce 260 mountainous regions or geographic regions similar in context. We acknowledge that many countries are 261 currently implementing EWS focusing on active community participation (please see reports links 1-5) 262 however, solutions to address these missing links are limited and thus ensuring inclusiveness and impact 263 remained challenging. We have highlighted the need for multiple lenses to establish and explore the complexity 264 of the risk portfolio and thus understand the architecture of the engaged stakeholders and their behaviour. This 265 is essential to ensure actionable knowledge is generated and bottom-up initiatives are strengthened and the 266 capacity to respond is improved. 267 268 Based on the above discussions of key questions, missing links and design needs, we propose the 'SMART 269 convergence participatory research' approach to support the EWS development phase and provide a checklist 270 of good practices. The SMART approach highlights crucial activity layers to incorporate into EWS 271 development which can help guide multi-disciplinary teams (e.g. disaster risk manager, hydrologist, engineer, 272 and social scientist) ( Figure 2). This will enable to incorporate diverse disciplinary lenses (i.e., social science 273 and meteorological data) along with risks diversity identify by the community-at-risk (illegal settlement beside 274 riverbank or slums) which mentioned earlier as missing-link. This will support to expose vulnerability and risks 275 from different socio-cultural, institutional and scientific context. Following a SMART approach will ensure 276 inclusiveness by helping to identify and connect missing components and linkages when designing an EWS. 277 278 The first step, S, represents 'Shared understanding of the risks' ensuring all stakeholder engagements are diverse 279 and representative (irrespective to their gender, sex, age, socio-economic status and physical abilities) and a 280 wide range of data forms and collection methods are utilised, as stated in EWS step-1 ( Figure 1). This knowledge 281 generated from the community will help the expert group to better understand context specific risks with more 282 focused exposure and vulnerability analysis. This further helps to identify common goals and anticipate damage 283 from the natural hazards and thus ensures impact though appropriate forecasting.

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Secondly, M representing 'Monitoring of the risks' aligned closely with establishing alert system and 286 forecasting hazard information as stated in step-2 ( Figure 1). This includes an intersection of generated 287 knowledge that will lead towards practicing collaborative activities, such as trust-building (which is key to 288 inclusive and impact-based forecasting), exchanging critical risk information to enrich data sets, feedbacks, 289 forming small groups for maintaining forecasting system.

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Thirdly, A, building Awareness (i.e., training and capacity development activities to embed understanding of 292 real time weather and alert information) is critical for this approach and is a continuous process throughout the 293 development and utilisation of early warning system, in particular focus to EWS step 3 to support effective 294 communication and dissemination and will further also support legacy and sustainability of the warning system 295 into the local context.

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Finally, RT indicating pre-planning Response actions on Time (i.e., comprehensive disaster management plan, 298 evacuation plan) based on the alert produced by the EWS and could be used to inform the effectiveness of the 299 overall EWS to minimize risks from the anticipated hazard. This will inform further the level of knowledge 300 produced through collaboration and how this can facilitate effective action by the community and responsible 301 agencies. 302 303 [ Figure 2] 304 305 We advocate the use of this SMART approach to facilitate bottom-up initiatives for developing an inclusive 306 and purposeful early warning system and to benefit the community-at-risk by engaging them every step of the 307 way along with including other stakeholders at multiple scales of operations (i.e., scientific and policy actors). 308 We advocate that the SMART convergence approach along with the dominant largely top-down initiatives will 309 contribute to developing capacity and redefining adaptation and resilience in the face of more extreme water 310 extremes (floods, droughts) and increased uncertainty under global change.