Abstract
Hydrologic/hydraulic models for flood risk assessment, forecasting and hindcasting have been greatly supported by the rising availability of increasingly accurate and high-resolution Earth Observation (EO) data. EO-based topographic and hydrologic open geo data are, nowadays, available on large scales. Data Assimilation (DA) models allow Early Warning Systems (EWS) to produce accurate and timely flood predictions. DA-based EWS generally use river flow real-time observations and 1D hydraulic models to identify potential inundation hot spots. Detailed high-resolution 2D hydraulic modeling is usually not used in EWS for the computational burden and the numerical complexity of injecting multiple spatially distributed sources of flow observations. In recent times, DEM-based hydrogeomorphic models demonstrated their ability in characterizing river basin hydrologic forcing and floodplain domains providing data-parsimonious opportunities for data-scarce regions. This work investigates the use of hydrogeomorphic floodplain terrain processing for optimizing the ability of DA-based EWSs in using diverse distributed flow observations. A flood forecasting framework with novel applications of hydrogeomorphic floodplain processing is conceptualized for empowering flood EWSs in preliminarily identifying the computational domain for hydraulic modeling, rapid flood detection using satellite images, and filtering geotagged crowdsourced data for flood monitoring. The proposed flood forecasting framework supports the development of an integrated geomorphic-hydrologic/hydraulic modeling chain for a DA that values multiple sources of observation. This work investigates the value of floodplain hydrogeomorphic models to tackle the major challenges of DA for EWS with specific regard to the computational efficiency issues and the lack of data in ungauged river basins towards an improved flood forecasting able to use advanced hydrodynamic modeling and to inject all available sources of observations including flood phenomena captures by citizens.
Highlights
DEM-based hydrogeomorphic models are fast and parsimonious tools aimed to identify floodplain boundaries
We propose a conceptual framework for integrating hydrogeomorphic modeling to: 1. Support fast hydrologic modeling for real-time identifying areas related to critical nodes of small basins whose stream network is not completely covered by the available standard flood maps; 2
This work conceptualizes the integration of a hydrogeomorphic floodplain delineation model GFPLAIN to improve flood forecasting at different spatial scales, for both small ungauged basins and large major rivers
Summary
DEM-based hydrogeomorphic models are fast and parsimonious tools aimed to identify floodplain boundaries. We propose the integration of the GFPLAIN model [3,5] in a DA framework to both bounding the physically-based flow propagation processes and masking geospatial information to be adopted as real-time observations for updating the flood forecasting model. We identified satellite-derived flood extensions and geotagged crowdsourced as examples of intermittent and spatially distributed observations that can be ingested for updating the flood forecasting model The aim of this methodology is to improve the responsiveness and enrich the set of information of the DA framework, reducing the computational time of both the physical hydraulic model and the algorithms aimed to retrieve intermittent and spatially distributed information for the model updating
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