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Related Experiment Video

Updated: Jan 12, 2026

In Situ Soil Moisture Sensors in Undisturbed Soils

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

Persistence in Physical Systems: An Application to Soil Moisture Memory.

Madhusudan Ingale¹, Bhupendra Bahadur Singh¹, Milind Mujumdar¹

¹Indian Institute of Tropical Meteorology (Ministry of Earth Sciences), 1, Pune-411008, Maharashtra, India.

Physical Review Letters

|October 31, 2025

Summary

This summary is machine-generated.

This study introduces a new information theory method to accurately measure memory in complex time series. Soil moisture in India

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Area of Science:

Environmental Science
Data Science
Physics

Background:

Physical systems and fluid dynamics often display memory effects due to internal dynamics and external influences.
Existing methods for estimating memory timescales in nonlinear time series are often complex and prone to overestimation.

Purpose of the Study:

To develop a novel, model-free framework using information theory to accurately estimate memory timescales in stationary time series.
To apply this method to analyze soil moisture (SM) dynamics in India's core monsoon zone.

Main Methods:

Employed a nonparametric, information-theory-based approach with methodological modifications for estimating memory.
Validated the method using synthetic time series, showing agreement with known Markov orders.
Analyzed observational and reanalysis soil moisture datasets from India's core monsoon zone.

Main Results:

The proposed method demonstrated good agreement between estimated memory and known Markov orders for synthetic data.
Soil moisture time series in India's core monsoon zone were characterized as higher-order Markov processes.
A significant memory timescale of approximately 35 days was quantified for soil moisture in this region.

Conclusions:

The information theory framework provides a simple yet generalizable alternative to conventional linear methods for analyzing time series memory.
Soil moisture exhibits substantial memory, behaving as a higher-order Markov process, crucial for understanding monsoon dynamics.
The method offers improved accuracy and simplicity for quantifying memory effects in complex environmental systems.