Flood Analytics Information System (FAIS) Version 4.00 Manual

TL;DR

The Flood Analytics Information System (FAIS) Version 4.00 integrates big data, machine learning, and NLP of tweets to enhance flood risk assessment, providing real-time data visualization and flood frequency analysis for stakeholders.

Contribution

This paper introduces FAIS v4.00, a comprehensive system combining big data analytics, machine learning, and NLP for flood risk assessment and decision support.

Findings

FAIS enables real-time flood data visualization and analysis.

The system effectively integrates diverse data sources including IoT, imagery, and social media.

FAIS provides flood frequency analysis with uncertainty estimation.

Abstract

This project was the first attempt to use big data analytics approaches and machine learning along with Natural Language Processing (NLP) of tweets for flood risk assessment and decision making. Multiple Python packages were developed and integrated within the Flood Analytics Information System (FAIS). FAIS workflow includes the use of IoTs-APIs and various machine learning approaches for transmitting, processing, and loading big data through which the application gathers information from various data servers and replicates it to a data warehouse (IBM database service). Users are allowed to directly stream and download flood related images/videos from the US Geological Survey (USGS) and Department of Transportation (DOT) and save the data on a local storage. The outcome of the river measurement, imagery, and tabular data is displayed on a web based remote dashboard and the information can be plotted in real-time. FAIS proved to be a robust and user-friendly tool for flood data analysis at regional scale that could help stakeholders for rapid assessment of flood situation and damages. FAIS also provides flood frequency analysis (FFA) to estimate flood quantiles including the associated uncertainties that combine the elements of observational analysis, stochastic probability distribution and design return periods. FAIS is publicly available and deployed on the Clemson-IBM cloud service.