five

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
下载链接
链接失效反馈
官方服务:
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
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作