Generative Water-Sensitive Spatial Configuration: AI-Driven Design, Modeling, and Adaptive Urban Hydrology
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Urban Water Management".
Deadline for manuscript submissions: 20 July 2026 | Viewed by 11
Special Issue Editors
Interests: landscape hydrology; stormwater management; urban planning; landscape architecture; green infrastructure; nature-based solutions
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning in hydrology; spatiotemporal data mining; remote sensing applications; streamflow and runoff prediction; climate change impact assessment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Rapid urbanization, climate flux, and increasing hydrological uncertainty have exposed the limitations of conventional rule-based and static approaches to water-sensitive urban design; instead, recent advances in generative artificial intelligence, spatial computing, and data-driven modeling now offer new opportunities to rethink how water-sensitive spaces are configured, optimized, and adapted across scales.
Consequently, this Special Issue focuses on generative water-sensitive spatial configuration, emphasizing the integration of generative algorithms, urban hydrological modeling, and nature-based solutions to support adaptive stormwater management and resilient urban landscapes. By coupling generative design frameworks (e.g., GANs, evolutionary algorithms, and procedural modeling) with hydrological simulation, remote sensing, and multi-objective optimization, emerging approaches enable the exploration of diverse spatial configurations that balance flood mitigation, ecosystem services, and urban functionality under uncertain climate futures.
We welcome contributions that advance theoretical frameworks, computational methods, and real-world applications addressing the co-evolution of urban form, blue–green infrastructure, and hydrological processes. Topics may span from neighborhood-scale water-sensitive design generation to city-scale adaptive planning strategies informed by AI-driven scenario exploration. By bridging generative design and urban hydrology, this Special Issue aims to promote a new paradigm of adaptive, data-informed, and performance-driven water-sensitive spatial planning.
Dr. Mo Wang
Dr. Rana Muhammad Adnan Ikram
Guest Editors
Manuscript Submission Information
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Keywords
- generative design
- water-sensitive urban design
- urban hydrology
- blue–green infrastructure
- artificial intelligence
- nature-based solutions
- stormwater management
- spatial optimization
- climate adaptation
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