Deep Learning Integrating Scale Conversion and Pedo‐Transfer Function to Avoid Potential Errors in Cross‐Scale Transfer

Deep Learning Integrating Scale Conversion and Pedo‐Transfer Function to Avoid Potential Errors in Cross‐Scale Transfer

Abstract Pedo‐transfer functions (PTFs) relate soil/landscape static properties to a wide range of model inputs (e.g., soil hydraulic parameters) that are essential to soil hydrological modeling. Combining PTFs and hydrological models is a powerful strategy allowing the use of soil/landscape static...

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Bibliographic Details
Main Authors: Peijun Li, Yuanyuan Zha, Yonggen Zhang, Chak‐Hau Michael Tso, Sabine Attinger, Luis Samaniego, Jian Peng
Format: Article
Language:English
Published: Wiley 2024-03-01
Series:Water Resources Research
Subjects:
soil moisture
pedo‐transfer function
soil hydraulic properties
convolutional neural network
scale conversion
data assimilation
Online Access:https://doi.org/10.1029/2023WR035543
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