Hybrid Physically Based and Deep Learning Modeling of a Snow Dominated, Mountainous, Karst Watershed-Reference-Cited by-同舟云学术

Hybrid Physically Based and Deep Learning Modeling of a Snow Dominated, Mountainous, Karst Watershed

Published:2022-03 Issue:3 Volume:58 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resources Research

Author:

Xu Tianfang¹²^ORCID,Longyang Qianqiu¹,Tyson Conor²³,Zeng Ruijie¹,Neilson Bethany T.²^ORCID

Affiliation:

1. School of Sustainable Engineering and the Built Environment Arizona State University Tempe AZ USA

2. Department of Civil and Environmental Engineering Utah Water Research Laboratory Utah State University Logan UT USA

3. Jordan Valley Water Conservancy District West Jordan UT USA

Funder

Division of Earth Sciences

U.S. Geological Survey

Utah Water Research Laboratory, Utah State University

Climate Program Office

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021WR030993

Reference114 articles.

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4. A processing–modeling routine to use SNOTEL hourly data in snowpack dynamic models

5. The effect of calibration data length on the performance of a conceptual hydrological model versus LSTM and GRU: A case study for six basins from the CAMELS dataset

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