Hackathon 2025: Streamflow Forecasting and Water Resource Regulation
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://zenodo.org/record/14536610
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资源简介:
I. Data
The objective of this challenge is to develop a model to predict streamflow levels across different river basins, aiding in sustainable water management strategies. The provided dataset includes time-series observations of water flow at specific stations within the selected watersheds, with a prediction horizon of 4 weeks.
Spatial dimension:
Covers key French river basins (Adour-Garonne, Rhône-Mediterranean) and the Doce River basin in Brazil.
Data is available for 30 stations for training and 39 stations for evaluation for France and for Brazil we have 9 stations for training, 13 stations for evaluation.
Temporal dimension:
Training data spans from 1990 to 2003.
Evaluation/inference data spans from 2004 to 2009. The evaluation dataset consists of multiple time segments, including a 4-week historical period for streamflow and weather (temperature, ...), 1 week of weather forecast data, and a 4-week prediction horizon for streamflow.
Participants will have access to the following feature types:
Spatiotemporal Climate Variables:
Temperature at 2m above ground
Total precipitation
Evaporation rates
Soil moisture (volumetric soil water)
Geospatial Features:
Soil properties (bulk density, clay content, sand/silt ratio). Source: Soilgrids
Hydrological divisions (watersheds and sub-basins). Source: BD Carthage for France and SNIRH for Brazil
Altitude Digital Elevation Model (NASA SRTM). Source: NASA SRTM 30m
Dams positions in France. Source: Hydrographic nodes
All features are provided in formats suitable for direct analysis and integration. You can download all the data below.
For more details about the hackathon see Here --> https://www.codabench.org/competitions/4335/
创建时间:
2025-02-07



