FIMserv v.1.0: A tool for streamlining Flood Inundation Mapping (FIM) using the United States operational hydrological forecasting framework

In the United States, the National Oceanic and Atmospheric Administration-Office of Water Prediction (NOAA-OWP) utilizes the National Water Model (NWM) for operational hydrological forecasting. Its Flood Inundation Mapping (FIM) framework translates NWM discharge to inundation extent using the Height Above the Nearest Drainage (HAND) approach. The simplicity of the OWP HAND-FIM framework enables rapid, large-scale FIM predictions across the U.S., fostering a growing user and developer community beyond NOAA. In this paper, we introduce “FIM as a Service (FIMserv)”, an open-source toolset that streamlines OWP HAND-FIM predictions with enhanced functionalities: (1) FIM generation from retrospective and forecasted NWM discharge, (2) Simultaneous simulations of multiple watersheds for various flood events, (3) FIM from Group on Earth Observations Global Water Sustainability (GeoGLOWS) discharge, (4) evaluation of NWM and GeoGLOWS discharge against USGS observations. FIMserv operates as a standalone notebook on local/cloud systems and as a Community Resource within the CIROH cloud cyberinfrastructure. • A user-friendly Python package is developed for generating Flood Inundation Maps (FIM) using the United States Operational hydrological model. • Execute seamlessly on local systems and cloud platforms like Google Colab and 2i2c interactive computing. • Integrates National Water Model (retrospective and forecast) and GeoGLOWS discharge in FIM generation.

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Publication Details

Journal
Environmental Modelling & Software
Published
2025-06-17
DOI
https://doi.org/10.1016/j.envsoft.2025.106581
Citations
8
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
8.84
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article

FIMserv v.1.0: A tool for streamlining Flood Inundation Mapping (FIM) using the United States operational hydrological forecasting framework

Sagy Cohen, Christopher Watts, Dipsikha Devi, Thanh‐Nhan Tran et al.
8 citations
Environmental Modelling & Software
Flood Risk Assessment and Management
8.84
article

FIMserv v.1.0: A tool for streamlining Flood Inundation Mapping (FIM) using the United States operational hydrological forecasting framework

Sagy Cohen, Christopher Watts, Dipsikha Devi, Thanh‐Nhan Tran, Yixian Chen, Carson Pruitt, Supath Dhital, Hesham Elhaddad, Anupal Baruah
article en
8 citations

Abstract

In the United States, the National Oceanic and Atmospheric Administration-Office of Water Prediction (NOAA-OWP) utilizes the National Water Model (NWM) for operational hydrological forecasting. Its Flood Inundation Mapping (FIM) framework translates NWM discharge to inundation extent using the Height Above the Nearest Drainage (HAND) approach. The simplicity of the OWP HAND-FIM framework enables rapid, large-scale FIM predictions across the U.S., fostering a growing user and developer community beyond NOAA. In this paper, we introduce “FIM as a Service (FIMserv)”, an open-source toolset that streamlines OWP HAND-FIM predictions with enhanced functionalities: (1) FIM generation from retrospective and forecasted NWM discharge, (2) Simultaneous simulations of multiple watersheds for various flood events, (3) FIM from Group on Earth Observations Global Water Sustainability (GeoGLOWS) discharge, (4) evaluation of NWM and GeoGLOWS discharge against USGS observations. FIMserv operates as a standalone notebook on local/cloud systems and as a Community Resource within the CIROH cloud cyberinfrastructure. • A user-friendly Python package is developed for generating Flood Inundation Maps (FIM) using the United States Operational hydrological model. • Execute seamlessly on local systems and cloud platforms like Google Colab and 2i2c interactive computing. • Integrates National Water Model (retrospective and forecast) and GeoGLOWS discharge in FIM generation.

Environmental Modelling & SoftwareVol. 192
National Oceanic and Atmospheric Administration (US), Western Michigan University (US), University of Alabama (US), University of Massachusetts Amherst (US), NOAA Oceanic and Atmospheric Research (US), University of Virginia (US)
Climate action
Openalex Percentile: Top 2%
Flood Risk Assessment and Management
8.84
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