Ecohydrological Model for Grassland Lacking Historical Measurements I: Downscaling Evaporation Data Based on Dynamic Sensitive Parameters and Deep Learning-Reference-Cited by-同舟云学术

Ecohydrological Model for Grassland Lacking Historical Measurements I: Downscaling Evaporation Data Based on Dynamic Sensitive Parameters and Deep Learning

Published:2021-08-02 Issue: Volume: Page:
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Author:

Li Mingyang¹^ORCID,Liu Tingxi¹^ORCID,Duan Limin²,Ma Long²,Wang Yixuan²,Wang Guoqiang³,Lei Huimin⁴,Wu Qiusheng⁵^ORCID,Singh Vijay⁶,Wang Sinan²

Affiliation:

1. Inner Mongolia Agricultural University

2. Water Conservancy and Civil Engineering College

3. Beijing Normal University

4. Tsinghua University

5. University of Tennessee

6. Texas A&M University

Publisher

Wiley

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4. On the contribution of dynamic leaf area index in simulating the African climate using a regional climate model (RegCM4);Anwar S. A.;Theoretical and Applied Climatology,2021

5. Ardabili S. Mosavi A. Dehghani M. & Várkonyi-Kóczy A. R. (2020). Deep Learning and Machine Learning in Hydrological Processes Climate Change and Earth Systems a Systematic Review Cham.

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