Integrating real-time rainfall intensity and duration

The gap

Evidence profile

Sourced from the future-work section and limitations section and stated challenges and abstract of the source papers, classified as general, spanning 5 journals. Those papers have been cited 1 times in total.

Supporting evidence — 6 representative gaps

• Predictive Modeling of Flash Floods: Investigating Hydrology and Land Cover Dynamics through Remote Sensing Data (2026) · Journal of Earth Observation and Geospatial Applications · doi

  Integrating real-time rainfall intensity and duration data into the model. Addressing the resolution gap between different datasets. Expanding the model to other regions and exploring its applicability to different types of floods.

  generalfuture-work section
  Keywords: integrating real-time rainfall intensity duration data model addressing
• Assessing financial risk to property portfolios from physical rainfall extremes (2026) · Natural hazards and earth system sciences · doi

  The method has limitations, including the simplified modelling of rainfall–flood relationships and the omission of potential future changes to floodplains. The absolute values of Expected Annual Damage should be interpreted with caution due to modelling caveats. No bias correction is applied to the rainfall data used in this analysis.

  generallimitations section
  Keywords: method has limitations including simplified modelling rainfall flood
• Assessing financial risk to property portfolios from physical rainfall extremes (2026) · Natural hazards and earth system sciences · doi

  The challenge of assessing physical climate risk from extreme rainfall is a key technical challenge. The complexity of modelling rainfall–flood relationships is also a challenge. The need for more advanced models and methods for assessing physical climate risk is a domain challenge.

  generalstated challenges
  Keywords: challenge assessing physical climate risk extreme rainfall key
• Balancing Accuracy and Efficiency for Sustainable Flood Adaptation: Multi-Resolution LiDAR DEM Sensitivity Analysis of Urban Pluvial Flooding in the Gumi Industrial Complex (2026) · Sustainability · cited 1× · doi

  Urban pluvial flood risk in industrial zones is intensifying under climate change, yet the joint influence of digital elevation model (DEM) resolution, surface roughness heterogeneity, and infiltration capacity on simulation accuracy remains insufficiently characterized.

  generalabstractevidence 5/5
  Keywords: urban pluvial flood risk industrial zones intensifying climate change joint influence digital elevation model resolution
• A GeoAI framework for coastal flood risk assessment: integrating remote sensing and socioeconomic data (2026) · Frontiers in Climate · doi

  The study uses a limited dataset and may not be generalizable to other areas. The study does not account for other factors that may affect flood risk, such as land use change. The study uses a simplified approach to predict flood risk and may not capture complex interactions between variables.

  generallimitations sectionevidence 5/5
  Keywords: study uses limited dataset generalizable other areas does
• Beyond the 100-year flood: probabilistic flood hazard assessment for King and Pierce Counties under future climate scenarios (2026) · Natural Hazards and Earth System Sciences · doi

  Future research should focus on improving the accuracy of the SFINCS model for complex bathymetric features and variable atmospheric conditions. The EAFA should be further developed and validated for use in flood risk management and planning. The impact of climate change on flood risk should be further studied using the SFINCS model.

  generalfuture-work sectionevidence 5/5
  Keywords: future research focus improving accuracy sfincs model complex

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