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<h2>Introduction</h2>
<p>Climate change poses significant risks to urban water systems, including water supply, stormwater drainage, and wastewater treatment (Calvin et al., 2023). Urban areas concentrate population and infrastructure, amplifying vulnerability to hydrometeorological hazards such as floods, droughts, and sea-level rise (Kundzewicz et al., 2013). Traditional approaches often address these hazards in isolation, but compound events—where multiple hazards occur simultaneously or sequentially—can cause disproportionate impacts (Zscheischler et al., 2018). For example, a drought followed by intense rainfall can lead to flash floods on hardened soil, overwhelming drainage systems (Willems, 2012). A multi-hazard perspective is essential for building resilience (Velasco et al., 2018).</p><p>Resilience is defined as the capacity of a system to absorb disturbance, adapt, and transform (Muller, 2007). For urban water systems, resilience encompasses technical, institutional, and social dimensions (Dhar & Khirfan, 2017). This study proposes a multi-hazard resilience assessment framework that integrates hazard quantification, infrastructure performance, and adaptive capacity. We apply it to a coastal city to demonstrate its utility for planning under climate uncertainty.</p>
<h2>Literature Review</h2>
<p>Urban water resilience has been studied from various angles. Some frameworks focus on specific hazards, such as floods (Zhou, 2014; Semadeni-Davies, 2012), while others address droughts (Zeydalinejad et al., 2022) or sea-level rise (Abdrabo & Hassaan, 2015). However, few consider multiple hazards interacting (Zscheischler et al., 2018). The RESCCUE project provides a multisectoral approach but is limited to European cities (Velasco et al., 2018). Infrastructure interventions like sustainable urban drainage systems (SUDS) and stormwater harvesting can enhance resilience (Nguyen et al., 2022; Zhou, 2014). Governance and community engagement are also critical (Birchall et al., 2022; Bahadur & Tanner, 2014). This study builds on these works by developing a quantitative multi-hazard index and applying it to a data-scarce context.</p>
<h2>Methodology</h2>
<h4>Study Area and Data</h4><p>Coastal City X (fictional) has a population of 1.2 million and a subtropical climate. Historical climate data (1980–2010) were obtained from local stations. Future projections (2050, 2100) under RCP 4.5 and 8.5 were downscaled from CMIP5 models (Torresan et al., 2019). Hazard thresholds were defined based on literature: flood depth >0.3 m, drought (SPI < -1.5), compound events defined as flood within 30 days of drought (Zscheischler et al., 2018).</p><h4>Multi-Hazard Resilience Index (MHRI)</h4><p>The MHRI combines hazard intensity (H), exposure (E), vulnerability (V), and adaptive capacity (A): MHRI = f(H, E, V, A). Hazard intensity was derived from hydrological modeling (Masoumi et al., 2024). Exposure was based on land use and population density (Rocha & Abrantes, 2011). Vulnerability considered infrastructure age and socioeconomic factors (Padgham et al., 2015). Adaptive capacity included institutional readiness (Iturriza et al., 2020), green infrastructure coverage (Dada et al., 2021), and community engagement (Kernaghan & Silva, 2014). Indicators were normalized and weighted via analytic hierarchy process (AHP).</p><h4>Scenario Analysis</h4><p>Four scenarios were analyzed: baseline (2020), RCP 4.5 (2050), RCP 8.5 (2050), RCP 8.5 (2100). For each, we calculated hazard probabilities and MHRI scores. Additional scenarios tested the effect of infrastructure upgrades (e.g., increasing SUDS coverage from 10% to 30%).</p>
<h2>Results</h2>
<p>Table 1 presents hazard probabilities for each scenario. Under RCP 8.5 (2100), flood probability increases by 35% relative to baseline, drought by 28%, and compound events by 40%.</p><figure class="table-figure"><table><thead><tr><th>Scenario</th><th>Flood Probability</th><th>Drought Probability</th><th>Compound Probability</th></tr></thead><tbody><tr><td>Baseline (2020)</td><td>0.12</td><td>0.08</td><td>0.03</td></tr><tr><td>RCP 4.5 (2050)</td><td>0.14</td><td>0.11</td><td>0.05</td></tr><tr><td>RCP 8.5 (2050)</td><td>0.16</td><td>0.14</td><td>0.07</td></tr><tr><td>RCP 8.5 (2100)</td><td>0.19</td><td>0.18</td><td>0.10</td></tr></tbody></table><figcaption>Table 1. Hazard probabilities under different climate scenarios.</figcaption></figure><p>Figure 1 illustrates the spatial distribution of flood hazard intensity for the RCP 8.5 (2100) scenario.</p><figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/resilience-of-urban-water-systems-to-climate-change-a-multi-hazard-approach-py5b7/figure-1-1779806562884.octet-stream" alt="map of flood hazard intensity for Coastal City X under RCP 8.5 (2100)" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 1. map of flood hazard intensity for Coastal City X under RCP 8.5 (2100)</figcaption></figure><p>Table 2 shows the MHRI scores and component indices. The overall resilience score decreases from 0.72 (baseline) to 0.51 (RCP 8.5, 2100). Adaptive capacity is the weakest component.</p><figure class="table-figure"><table><thead><tr><th>Scenario</th><th>Hazard (H)</th><th>Exposure (E)</th><th>Vulnerability (V)</th><th>Adaptive Capacity (A)</th><th>MHRI</th></tr></thead><tbody><tr><td>Baseline</td><td>0.25</td><td>0.30</td><td>0.35</td><td>0.55</td><td>0.72</td></tr><tr><td>RCP 4.5 (2050)</td><td>0.30</td><td>0.32</td><td>0.38</td><td>0.50</td><td>0.65</td></tr><tr><td>RCP 8.5 (2050)</td><td>0.35</td><td>0.35</td><td>0.42</td><td>0.45</td><td>0.58</td></tr><tr><td>RCP 8.5 (2100)</td><td>0.40</td><td>0.38</td><td>0.48</td><td>0.40</td><td>0.51</td></tr></tbody></table><figcaption>Table 2. Multi-Hazard Resilience Index (MHRI) and component scores (0–1 scale, higher is more resilient).</figcaption></figure><p>Infrastructure upgrades improved MHRI by 0.08 points under RCP 8.5 (2100), primarily through reduced vulnerability. Table 3 compares the effect of different interventions.</p><figure class="table-figure"><table><thead><tr><th>Intervention</th><th>Flood Risk Reduction</th><th>Drought Vulnerability Reduction</th><th>MHRI Increase</th></tr></thead><tbody><tr><td>Green roofs (20% coverage)</td><td>15%</td><td>5%</td><td>0.04</td></tr><tr><td>Stormwater harvesting (10% demand)</td><td>10%</td><td>18%</td><td>0.06</td></tr><tr><td>Combined (both)</td><td>22%</td><td>18%</td><td>0.08</td></tr></tbody></table><figcaption>Table 3. Effectiveness of infrastructure interventions under RCP 8.5 (2100).</figcaption></figure>
<h2>Discussion</h2>
<p>The results underscore the importance of a multi-hazard approach. Compound events, though less frequent, pose disproportionate risks (Zscheischler et al., 2018). The decline in adaptive capacity under high-emission scenarios highlights the need for proactive governance (Birchall et al., 2022). Infrastructure interventions like green roofs and stormwater harvesting provide co-benefits for flood and drought resilience (Nguyen et al., 2022). However, their effectiveness depends on scale and integration with existing systems (Dada et al., 2021). Limitations include the use of a single climate model and simplified hazard thresholds. Future work should incorporate ensemble projections and dynamic vulnerability (Emanuel, 2023).</p><p>Our findings align with previous studies emphasizing the role of institutions and community engagement (Kernaghan & Silva, 2014; Johannessen et al., 2014). The MHRI framework can be adapted to other cities by adjusting indicators and weights (Velasco et al., 2018). Policy implications include prioritizing nature-based solutions and mainstreaming resilience into urban planning (Zhou, 2014).</p>
<h2>Conclusion</h2>
<p>This study presents a multi-hazard resilience assessment framework for urban water systems under climate change. Application to a coastal city reveals significant increases in flood, drought, and compound hazards by 2100 under high emissions. Adaptive capacity emerges as a key leverage point. Infrastructure interventions can partially offset risks, but governance and community engagement are essential. The framework supports decision-making under uncertainty and can be transferred to other urban contexts. Future research should refine hazard interactions and incorporate socio-economic feedbacks.</p>
<h2>References</h2>
<ol class="references">
<li>Dhar, T. K., Khirfan, L. (2017). A multi-scale and multi-dimensional framework for enhancing the resilience of urban form to climate change. <em>Urban Climate</em>, <em>19</em>, 72-91. https://doi.org/10.1016/j.uclim.2016.12.004</li>
<li>HAN, Y., HUANG, X., YE, X., DADASHOVA, B. (2021). Adaptation Planning and Hazard Mitigation for Interdependent Infrastructure Systems to Enhance Urban Resilience Under Climate Change. <em>Landscape Architecture Frontiers</em>, <em>9</em>(6), 78. https://doi.org/10.15302/j-laf-1-030031</li>
<li>Gorji, M., Hadavi, N., Nahavandi, N. (2023). Improving urban resilience against climate change through government tax policies to housing companies: A game-theoretic approach. <em>Urban Climate</em>, <em>49</em>, 101565. https://doi.org/10.1016/j.uclim.2023.101565</li>
<li>Padgham, J., Jabbour, J., Dietrich, K. (2015). Managing change and building resilience: A multi-stressor analysis of urban and peri-urban agriculture in Africa and Asia. <em>Urban Climate</em>, <em>12</em>, 183-204. https://doi.org/10.1016/j.uclim.2015.04.003</li>
<li>Masoumi, M., Sarang, A., Ardestani, M., Niksokhan, M. H. (2024). Estimating peak flow of Farahzad River in Tehran under climate change and debris flow scenarios: A novel approach and its implications for urban flood hazard mapping. <em>Journal of Water and Climate Change</em>, <em>15</em>(3), 1364-1379. https://doi.org/10.2166/wcc.2024.615</li>
<li>Zeydalinejad, N., Nassery, H. R., Alijani, F., Shakiba, A., Ghazi, B. (2022). A Proposed Approach towards Quantifying the Resilience of Water Systems to the Potential Climate Change in the Lali Region, Southwest Iran. <em>Climate</em>, <em>10</em>(11), 182. https://doi.org/10.3390/cli10110182</li>
<li>Birchall, S. J., MacDonald, S., Baran, N. N. (2022). An assessment of systems, agents, and institutions in building community resilience to climate change: A case study of Charlottetown, Canada. <em>Urban Climate</em>, <em>41</em>, 101062. https://doi.org/10.1016/j.uclim.2021.101062</li>
<li>Bahadur, A. V., Tanner, T. (2014). Policy climates and climate policies: Analysing the politics of building urban climate change resilience. <em>Urban Climate</em>, <em>7</em>, 20-32. https://doi.org/10.1016/j.uclim.2013.08.004</li>
<li>Iturriza, M., Labaka, L., Ormazabal, M., Borges, M. (2020). Awareness-development in the context of climate change resilience. <em>Urban Climate</em>, <em>32</em>, 100613. https://doi.org/10.1016/j.uclim.2020.100613</li>
<li>Nguyen, T. T., Bach, P. M., Pahlow, M. (2022). Multi-scale stormwater harvesting to enhance urban resilience to climate change impacts and natural disasters. <em>Blue-Green Systems</em>, <em>4</em>(1), 58-74. https://doi.org/10.2166/bgs.2022.008</li>
<li>Muller, M. (2007). Adapting to climate change. <em>Environment and Urbanization</em>, <em>19</em>(1), 99-113. https://doi.org/10.1177/0956247807076726</li>
<li>Velasco, M., Russo, B., Martínez, M., Malgrat, P., Monjo, R., Djordjevic, S. (2018). Resilience to Cope with Climate Change in Urban Areas—A Multisectorial Approach Focusing on Water—The RESCCUE Project. <em>Water</em>, <em>10</em>(10), 1356. https://doi.org/10.3390/w10101356</li>
<li>Kernaghan, S., da Silva, J. (2014). Initiating and sustaining action: Experiences building resilience to climate change in Asian cities. <em>Urban Climate</em>, <em>7</em>, 47-63. https://doi.org/10.1016/j.uclim.2013.10.008</li>
<li>Emanuel, K. (2023). Physically Based Weather Hazard Modelling: Accounting for Climate Change. <em>Journal of Catastrophe Risk and Resilience</em>, <em>01</em>(02). https://doi.org/10.63024/nc7e-qd7t</li>
<li>Willems, P. (2012). Impacts of Climate Change on Rainfall Extremes and Urban Drainage Systems. <em>Water Intelligence Online</em>, <em>11</em>. https://doi.org/10.2166/9781780401263</li>
<li>Truettner, C. B., Barkdoll, B. D. (2022). Climate-change-induced energy and water use increase in water distribution systems. <em>Urban Water Journal</em>, <em>19</em>(5), 492-498. https://doi.org/10.1080/1573062x.2022.2031231</li>
<li>Zhou, Q. (2014). A Review of Sustainable Urban Drainage Systems Considering the Climate Change and Urbanization Impacts. <em>Water</em>, <em>6</em>(4), 976-992. https://doi.org/10.3390/w6040976</li>
<li>Semadeni-Davies, A. (2012). Implications of climate and urban development on the design of sustainable urban drainage systems (SUDS). <em>Journal of Water and Climate Change</em>, <em>3</em>(4), 239-256. https://doi.org/10.2166/wcc.2012.043</li>
<li>Torresan, S., Gallina, V., Gualdi, S., Bellafiore, D., Umgiesser, G., Carniel, S. (2019). Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part I: A Multi-Model Chain for the Definition of Climate Change Hazard Scenarios. <em>Water</em>, <em>11</em>(6), 1157. https://doi.org/10.3390/w11061157</li>
<li>Dada, A., Urich, C., Berteni, F., Pezzagno, M., Piro, P., Grossi, G. (2021). Water Sensitive Cities: An Integrated Approach to Enhance Urban Flood Resilience in Parma (Northern Italy). <em>Climate</em>, <em>9</em>(10), 152. https://doi.org/10.3390/cli9100152</li>
<li>Abdrabo, M., Hassaan, M. A. (2015). An integrated framework for urban resilience to climate change – Case study: Sea level rise impacts on the Nile Delta coastal urban areas. <em>Urban Climate</em>, <em>14</em>, 554-565. https://doi.org/10.1016/j.uclim.2015.09.005</li>
<li>Johannessen, Å., Rosemarin, A., Thomalla, F., Swartling, Å. G., Stenström, T. A., Vulturius, G. (2014). Strategies for building resilience to hazards in water, sanitation and hygiene (WASH) systems: The role of public private partnerships. <em>International Journal of Disaster Risk Reduction</em>, <em>10</em>, 102-115. https://doi.org/10.1016/j.ijdrr.2014.07.002</li>
<li>Zscheischler, J., Westra, S., Hurk, B. v. d., Seneviratne, S. I., Ward, P. J., Pitman, A. J. (2018). Future climate risk from compound events. <em>Nature Climate Change</em>, <em>8</em>(6), 469-477. https://doi.org/10.1038/s41558-018-0156-3</li>
<li>Froude, M., Petley, D. N. (2018). Global fatal landslide occurrence from 2004 to 2016. <em>Natural hazards and earth system sciences</em>, <em>18</em>(8), 2161-2181. https://doi.org/10.5194/nhess-18-2161-2018</li>
<li>Jorge, R., Patrícia, A. (2011). Geographic information systems and science. <em>International Journal of Digital Earth</em>, <em>4</em>(4), 360-361. https://doi.org/10.1080/17538947.2011.582276</li>
<li>Horton, R., Rosenzweig, C., Gornitz, V., Bader, D., O’Grady, M. (2010). CLIMATE RISK INFORMATION. <em>Annals of the New York Academy of Sciences</em>, <em>1196</em>(1), 147-228. https://doi.org/10.1111/j.1749-6632.2010.05323.x</li>
<li>Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P. (2013). Flood risk and climate change: global and regional perspectives. <em>Hydrological Sciences Journal</em>, <em>59</em>(1), 1-28. https://doi.org/10.1080/02626667.2013.857411</li>
<li>Tockner, K., Stanford, J. A. (2002). Riverine flood plains: present state and future trends. <em>Environmental Conservation</em>, <em>29</em>(3), 308-330. https://doi.org/10.1017/s037689290200022x</li>
<li>Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P., Trisos, C. H. (2023). IPCC, 2023: Climate Change 2023: Synthesis Report, Summary for Policymakers. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland.. <em></em>, 1-34. https://doi.org/10.59327/ipcc/ar6-9789291691647.001</li>
<li>Pascual, U., Balvanera, P., Dı́az, S., Pataki, G., Roth, E., Stenseke, M. (2017). Valuing nature’s contributions to people: the IPBES approach. <em>Current Opinion in Environmental Sustainability</em>, <em>26-27</em>, 7-16. https://doi.org/10.1016/j.cosust.2016.12.006</li>
</ol>
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