Published December 23, 2023 | Version v2
Dataset Open

Coupling deep learning and physically-based hydrological models for monthly streamflow predictions

Creators

  • 1. State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, 430072, China
  • 2. Hubei Provincial Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan, Hubei, 430072, China
  • 3. 1 State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, 430072, China 2 Hubei Provincial Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan, Hubei, 430072, China
  • 4. 3 UNESCO-IHE, Institute for Water Education, 2611AX, Delft, The Netherlands
  • 5. 4 Department of Geosciences, University of Oslo, P. O. Box 1047, Blindern, Oslo N-0316, Norway
  • 6. 5 USDA-ARS Oklahoma and Central Plains Agricultural Research Center, 7207 West Cheyenne St., El Reno, OK 73036, USA

Description

Revision in journal Water Resources Research, Paper # 2023WR035618R

Files

Daily meteorological variables including precipitation, maximum and minimum air temperatures_Hanjiang River basin.zip

Files (6.7 MB)