SF2Bench Pump Station Monitoring Stations

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Authors: Xinyue Zheng, Chongjian Lin, Shigang Chen, Jian Liu, Dingbao Luo
Cited by: 0

Abstract

Time series data from 99 pump station monitoring stations (379 CSV files) in South Florida. Part of the SF2Bench dataset for compound flood forecasting research.This dataset contains 99 monitoring stations (379 CSV files) with time series data collected across South Florida (Miami-Dade, Broward, Palm Beach, Martin, St. Lucie counties). The data is part of the SF2Bench benchmark dataset for evaluating data-driven models in compound flood forecasting.SF2Bench Master CollectionThis dataset is a component of the SF2Bench benchmark. Cite the master collection for the full multi-factor archive:Master DOI: doi:10.34703/gzx1-9v95/GCVWG7Data Access:Pelican OSDF: osdf://envistor/compound-flood/PUMPArcGIS Online Feature Layer: https://services2.arcgis.com/FtJyXM7nBotS8g5t/arcgis/rest/services/sf2bench_pump_stations/FeatureServerAGOL Web Map: https://FIUGIS.maps.arcgis.com/home/item.html?id=fe3cd60e7f67423dae638f02aa062febTemporal Coverage: 1985-2023Spatial Coverage: South Florida region (Lon: -81.88 to -80.05, Lat: 25.20 to 28.80)Measurement Unit: RPMRelated Resources:Source Code: https://github.com/AslanDing/SFBench (Source code related to the paper)Paper: https://arxiv.org/abs/2506.04281Citation:Zheng, X., Lin, C., Chen, S., Chen, Z., Shi, J., Cheng, W., Obeysekera, J., Liu, J., & Luo, D. (2025). SF2Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida. arXiv:2506.04281. https://arxiv.org/abs/2506.04281

Fields of Study & Subjects

Flood Risk Assessment and Management Hydrological Forecasting Using AI Environmental Monitoring and Data Management

Publication details

Journal / source
FIU Research Data Portal
Publication date
5 March 2026
Language
EN
Document type
Dataset