Data supporting the study: Continuous Spatiotemporal Variations of Riverine Dissolved Organic Carbon in the Yangtze River Basin Revealed by A River-reach Scale Machine Learning-based Model

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Menghan Chen, Lei Cheng, Yue Wu, Mingshen Lu, Shiqiang Wu, Lu Zhang, Pan Liu
DOI: 10.5281/zenodo.18938601
Cited by: 0

Abstract

This database contains the R codes, input data, and output results supporting the study ‘Continuous Spatiotemporal Variations of Riverine Dissolved Organic Carbon in the Yangtze River Basin Revealed by A River-reach Scale Machine Learning-based Model’. The specific description of the code and data can be found in the file ‘ReadMe.docx’.

Fields of Study & Subjects

Soil and Water Nutrient Dynamics Hydrological Forecasting Using AI Water Quality and Pollution Assessment

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 March 2026
Language
EN
Document type
Dataset