The United Nations Office for Disaster Risk Reduction defines exposure as “a situation of people, infrastructure, housing, production capacities and other tangible human assets located in hazard-prone areas”<sup>47</sup> . To understand infrastructure network exposure to floods, the most widely used method in the literature is spatial overlay—a geospatial approach first proposed by Ian McHarg in his landmark book _Design with Nature_<sup>48</sup> . Many studies in the past used this method to understand flood exposure for different asset types at national and regional scales<sup>49</sup> . For example, Narayanan et al. leveraged the flood hazard layer provided by the Federal Emergency Management Agency (FEMA) to evaluate flood exposure across five infrastructure sectors including transportation in the contiguous United States<sup>50</sup> . Jongman et al. used a similar approach to measure long-term trends and changes in hazard exposure to river and coastal flooding at the global scale<sup>23</sup> . To achieve optimal outcomes with minimum errors in measurement, explicit and highresolution spatial data sets for infrastructure assets and well-established flood hazard zones or flood inundation maps are often required. In the past decades, increased computing power and precision of remote sensing data sets have led to the development of multiple high-resolution global flood models<sup>37,51</sup> . In addition, open-access road transportation network mapping and transportation data surveys (e.g., dualcondition General Transit Specification Survey) enable new research efforts that aim to understand direct transportation network exposure to floods across multiple temporal and spatial scales. For example, He et al. leveraged high-resolution flood maps for both pluvial and fluvial floods from Fathom and spatially overlaid on multimodal transportation network assets to evaluate flood exposure<sup>2</sup> .

## **Understanding vulnerability and resilience**

Early research on evaluating the vulnerability and resilience of transportation networks focuses on network topology<sup>52</sup> . When viewing the transportation system as a network of nodes and links, the vulnerability and resilience of the transportation systems can be measured by key topological features. Metrics that are used to understand vulnerability include network efficiency<sup>53</sup> , normalized average edge betweenness<sup>54</sup> , network autocorrelation<sup>55</sup> , cascading network failure proportion<sup>56</sup> , and average shortest path length<sup>57</sup> . Metrics that are used to understand resilience include the existence of giant connected component<sup>58</sup> , redundancy and fracture coefficient<sup>59</sup> , average degree, diameter, and cyclicity<sup>60</sup> . In recent years, more and more studies turned to mathematical models, simulation models, and data-driven models, namely, demand and supply models<sup>61–63</sup> , systems dynamic models, stochastic and optimization processes<sup>64</sup> , and data-driven approaches<sup>52</sup> , to understand the vulnerability and resilience of transportation networks<sup>65</sup> . Compared with traditional topology analysis, these models can more truly reflect the changes in system performance, which has attracted the attention of an increasing number of researchers. The mathematical models along with simulation and data-driven approaches are collectively referred to as system structure-based performance analysis. They mainly consider the impact of dynamic travel supply and demand on transportation network vulnerability and resilience<sup>52</sup> .

# **Methods**

To understand the impact of pluvial and fluvial floods of varying intensities on road transportation networks worldwide under multiple climate scenarios, we develop a framework with three main components: network boundary delineation and network model creation, global flood mapping, and travel simulation (Fig. 1). First, we extract the boundaries of settlement clusters around the world leveraging the global human settlement mapping effort by the European Commission. These boundaries delineate all human settlements, from hamlets and villages, to towns, cities, and metropolitan areas. The size of these clusters 4