遇见数据集

A Compilation of Water Surface Elevation Time Series from Global Lake Gauges

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Zenodo2026-06-21 更新2026-06-28 收录
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Contacts: Mélanie Trudel (melanie.trudel@usherbrooke.ca), Jida Wang (jidaw@illinois.edu) Data overview and usage This dataset contains gauge measurements, primarily water surface elevation (WSE) time series, from more than 1,200 lake gauges across nine countries, compiled through an international collaborative effort (Table 1). Most records overlap at least part of the period from July 2023 to May 2025, and some records extend beyond this window. Temporal coverage, continuity, and sampling frequency vary among lakes and regions. This dataset was compiled to support validation of the Heuristic Adaptive Lake Filter (HALF) for SWOT vector lake products, as reported in Trudel et al. (2026, in review). It is released here as a companion dataset to the HALF code package and is intended to support the validation workflow implemented in half_v1_validation.py. The HALF code package is available through the GitHub repository at https://github.com/LARIC-jw/HALF, and the archived v1.0 code release is available through Zenodo at https://doi.org/10.5281/zenodo.20782248. Users may also use this gauge-data collection for other relevant research and applications, provided that the dataset is properly cited (see Citation) and that use complies with the terms and conditions of the original data sources. This release represents version 1.0 of the dataset. Detailed information on regions, countries, lake counts, temporal frequency, and data sources is summarized in Table 1. Overall, the included lakes span a wide range of sizes, from approximately 0.01 km2 to more than 57,000 km2. Additional details on data access, preprocessing, formatting, and source-specific considerations are provided in the log files within each regional data folder. Further processing and validation details are available in Trudel et al. (2026, in review). Table 1. Description of the collected lake gauge data Region Lake (PLD) count Temporal frequency Data sources Canada 282 Hourly Environment and Climate Change Canada (ECCC), Centre d'expertise hydrique du Québec (CEHQ), Hydro-Québec (HQ), and University of Sherbrooke US 284 Hourly U.S. Geological Survey (USGS) and U.S. Bureau of Reclamation (USBR) (Harlan et al., 2026) Norway 232 Hourly Norwegian Water Resources and Energy Directorate (Norges vassdrags-og energidirektorat (NVE)) Switzerland 29 Hourly Swiss Federal Office for the Environment (Bundesamt für Umwelt (BAFU)) China 38 Daily (inconsecutive) China Water and Rain Information website (http://xxfb.mwr.cn/sq_dxsk.html) Burkina Faso 1 Sub-hourly to hourly Specifically in situ set-up for SWOT cal/val (Girard et al. 2025) Niger 1 Sub-hourly to hourly Analyse Multidisciplinaire de la Mousson Africaine - Couplage de l’Atmosphère Tropicale et du Cycle Hydrologique (AMMA-CATCH) observatory (Girard et al. 2025) Amazonia, Brazil 6 Daily to hourly Instituto Mamirauá, Brazil Ceará, Brazil 8 Sub-hourly Ceará Institute of Meteorology and Water Resources (Funceme) Other Brazil 63 Daily Operador Nacional do Sistema Elétrico (ONS; https://www.ons.org.br) India 304 Daily (inconsecutive) Water Resources Information System of India (https://indiawris.gov.in/wris/#/), containing in situ data from multiple agencies (Central Water Commission (CWC), Andhra Pradesh Water Resources Information and Management System (APWRIMS), and Government of Gujarat (Gujarat)). Total 1,248 Citation Trudel, M., Wang, J., Biancamaria, S., Harlan, M.E., Shah, D., Gao, H., Collins, E., Getirana, A., Song, C., Reis Alencar Oliveira, R., Gosset, M., Rodrigues Martins, E.S., Fleischmann, A., Hymans, D., Grippa, M., Girard, F., Kergoat, L., Pottier, C., Fjørtoft, R., Oubanas, H., & Pavelsky, T.M. (2026). A Heuristic Adaptive Filter for SWOT Lake Vector Data Products. Geophysical Research Letters, in review.

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2026-06-21
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