Attribution of Urban Flood Hydrological Processes and Prioritisation of Nature‐Based Solutions Based in Pakistan Using Sentiment Analysis

Urban flooding is becoming increasingly prevalent worldwide due to climate change and rapid urbanisation, posing significant challenges for stormwater regulation, surface runoff management and drainage system effectiveness. Yet, despite the trend of recommending that nature‐based solutions (NBS) be deployed in flood mitigation efforts, information about the use of spatially resolved indicators of urban hydrological dysfunction is seldom used to inform their implementation. The paper makes contributions to the frontier of urban flood hydrology by proposing the concept of social sensing as an auxiliary observation layer that can be used to attribute processes related to flooding, such as surface runoff accumulation, drainage inefficiency and repetitive flooding. Based on the use of social media data in Pakistan, we combine sentiment analysis, topic modelling and spatial analysis to develop proxy variables for localised flood dynamics. Findings indicate a high degree of spatiotemporal alignment between clusters of negative sentiment and reported flood‐prone areas, suggesting that runoff pathways are highly concentrated and drainage is poor. Discourse analysis also links NBS‐related stories to key hydrological processes, such as runoff attenuation, increased infiltration and the moderation of flood peaks. The paper integrates social sensing and hydrological interpretation, forming a process‐based decision‐support system that can prioritise NBS interventions in urban flood‐prone environments. The results indicate that conventional hydrological data can be enhanced with crowd‐derived observations to capture the population‐level response to flood dynamics, thereby increasing situational awareness of urban runoff dynamics and drainage collapse. This social‐hydrological integration offers a versatile path to improving flexible flood management in data‐scarce, rapidly urbanising areas.