FLOOD-XML v.1.0 (Flood LOss and Observed Damage using eXplainable Machine Learning)

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FLOOD-XML v.1.0 (Flood LOss and Observed Damage using eXplainable Machine Learning)

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Type:	Resource
Storage:	The size of this resource is 3.1 MB
Created:	Jan 30, 2026 at 12:53 a.m. (UTC)
Last updated:	Feb 02, 2026 at 3:41 p.m. (UTC) (Metadata update)
Published date:	Feb 02, 2026 at 3:41 p.m. (UTC)
DOI:	10.4211/hs.43734306345c41358617d90800d12819
Citation:	See how to cite this resource
Content types:	Multidimensional Content CSV Content

Sharing Status:	Published
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Abstract

We introduce FLOOD-XML (Flood LOss and Observed Damage using eXplainable Machine Learning), a multi-model ensemble dataset that addresses this gap by developing data-driven flood damage functions and estimating event-level damages globally using a suite of machine learning (ML) models. Long-term flood event records from the Emergency Events Database (EM-DAT) since the 1980s have harmonized with event attributes (location, duration, fatalities, and affected area) to train ML models spanning tree-based methods, support vector regression, deep learning, and non-parametric approaches. Damage functions are calibrated using economic losses reported in U.S. dollars in EM-DAT and validated through leave-one-out and group K-fold cross-validation before being used to estimate flood damage for the Dartmouth Flood Observatory (DFO) dataset. Multiple evaluation metrics are used to assess model performance, and feature contributions are determined through explainable ML techniques.
The FLOOD-XML dataset provides globally consistent, explainable flood damage estimates, offering risk analysts, insurers, and policymakers a reproducible tool for impact-based flood hazard assessment and adaptation planning.

FLOOD-XML: https://github.com/nassernajibi/FLOOD-XML
FLOOD-XML Mapper: https://nassernajibi.github.io/FLOOD-XML-Mapper

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

North Latitude

90.0000°

East Longitude

-180.0000°

South Latitude

-90.0000°

West Longitude

180.0000°

Temporal

Start Date:
End Date:

Content

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Data Services

The following web services are available for data contained in this resource. Geospatial Feature and Raster data are made available via Open Geospatial Consortium Web Services. The provided links can be copied and pasted into GIS software to access these data. Multidimensional NetCDF data are made available via a THREDDS Data Server using remote data access protocols such as OPeNDAP. Other data services may be made available in the future to support additional data types.

THREDDS Data Service

https://thredds.hydroshare.org/thredds/catalog/hydroshare/resources/43734306345c41358617d90800d12819/data/contents/catalog.html

THREDDS Documentation OPeNDAP Documentation

How to Cite

Najibi, N. (2026). FLOOD-XML v.1.0 (Flood LOss and Observed Damage using eXplainable Machine Learning), HydroShare, https://doi.org/10.4211/hs.43734306345c41358617d90800d12819

This resource is shared under the Creative Commons Attribution-NoCommercial CC BY-NC.

http://creativecommons.org/licenses/by-nc/4.0/

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