Investigating the impact of meteorological parameters on daily soil temperature changes using machine learning models

Investigating the impact of meteorological parameters on daily soil temperature changes using machine learning models

Abstract Soil temperature (ST) is one of the critical parameters in agricultural meteorology and significantly influences physical, chemical, and biological activities in the soil environment. One of the major challenges in agricultural studies is the limited number of synoptic stations for measurin...

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Bibliographic Details
Main Authors: Farrokh Asadzadeh, Somayeh Emami, Ahmed Elbeltagi, Muhammed Ernur Akiner, Vahid Rezaverdinejad, Farshid Taran, Ali Salem
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Reports
Subjects:
Artificial neural network (ANN)
Soil temperature (ST)
Seasonal ARIMA (SARIMA)
Meteorological parameters
Predictive modeling
Soil depth
Online Access:https://doi.org/10.1038/s41598-025-04605-0
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