Soil Moisture Measuring Techniques and Factors Affecting the Moisture Dynamics: A Comprehensive Review

Abstract

The amount of surface soil moisture (SSM) is a crucial ecohydrological natural resource that regulates important land surface processes. It affects critical land–atmospheric phenomena, including the division of energy and water (infiltration, runoff, and evaporation), that impacts the effectiveness of agricultural output (sensible and latent heat fluxes and surface air temperature). Despite its significance, there are several difficulties in making precise measurements, monitoring, and interpreting SSM at high spatial and temporal resolutions. The current study critically reviews the methods and procedures for calculating SSM and the variables influencing measurement accuracy and applicability under different fields, climates, and operational conditions. For laboratory and field measurements, this study divides SSM estimate strategies into (i) direct and (ii) indirect procedures. The accuracy and applicability of a technique depends on the environment and the resources at hand. Comparative research is geographically restricted, although precise and economical—direct measuring techniques like the gravimetric method are time-consuming and destructive. In contrast, indirect methods are more expensive and do not produce measurements at the spatial scale but produce precise data on a temporal scale. While measuring SSM across more significant regions, ground-penetrating radar and remote sensing methods are susceptible to errors caused by overlapping data and atmospheric factors. On the other hand, soft computing techniques like machine/deep learning are quite handy for estimating SSM without any technical or laborious procedures. We determine that factors, e.g., topography, soil type, vegetation, climate change, groundwater level, depth of soil, etc., primarily influence the SSM measurements. Different techniques have been put into practice for various practical situations, although comparisons between them are not available frequently in publications. Each method offers a unique set of potential advantages and disadvantages. The most accurate way of identifying the best soil moisture technique is the value selection method (VSM). The neutron probe is preferable to the FDR or TDR sensor for measuring soil moisture. Remote sensing techniques have filled the need for large-scale, highly spatiotemporal soil moisture monitoring. Through self-learning capabilities in data-scarce areas, machine/deep learning approaches facilitate soil moisture measurement and prediction.

Evaluation and Development of Pedotransfer Functions and Artificial Neural Networks to Saturation Moisture Content Estimation

“…This sensor measures the transmitted signal time from one end to the other [22,23]. However, in soils with high salt content, representativeness of the measurement can be lost, in addition to the fact that it requires a high initial investment [24].…”

Contactless estimation of soil moisture using leaky Rayleigh waves and a fully convolutional network

“…Several techniques have been developed to monitor soil moisture, including (i) gravimetric, (ii) tensiometer, (iii) electrical resistance, and (iv) frequency and time domain reflectometry techniques (Rasheed et al, 2022;Sharma, 2018). Except for the gravimetric method (direct soil moisture measurement), soil matric potential, electric signal, and attenuation of neutrons (indirect soil moisture measurements) are used as proxies to estimate soil moisture in the field.…”

“…Therefore, accurate measurement of soil moisture plays a vital role in Earth system science, ranging from estimating the molecular signatures of microbial decomposition to studying ecosystem responses to global warming (Songara & Patel, 2022). Several techniques have been developed to monitor soil moisture, including (i) gravimetric, (ii) tensiometer, (iii) electrical resistance, and (iv) frequency and time domain reflectometry techniques (Rasheed et al., 2022; Sharma, 2018). Except for the gravimetric method (direct soil moisture measurement), soil matric potential, electric signal, and attenuation of neutrons (indirect soil moisture measurements) are used as proxies to estimate soil moisture in the field.…”

Uniplanar multirod TDR probe for soil water content measurement over a larger spatial scale

“…Despite its significance in many practical fields, there are difficulties in making accurate measurements, monitoring and interpreting near-surface soil water at large spatial and temporal resolutions (Rasheed et al, 2022). The currently used probe types (time domain reflectometry [TDR], frequency domain reflectometry [FDR], resistance and capacitance sensors) in measuring soil water somewhat differ in terms of the methods involved, but they determine the soil water content of a limited sampling volume surrounding the probe (Raper, 2014).…”

“…Soil water data are essential for understanding many land surface processes, such as the water, energy and carbon cycles of the earth system (Bai et al, 2019; Fisher & Koven, 2020; Harmsen et al, 2021; Rasheed et al, 2022; Tavakol et al, 2021). It is an important ecohydrological parameter for many modelling applications related to energy balance, such as numerical weather forecasting, climate prediction, radiative transfer modelling, global change modelling and satellite data validation (Njoku et al, 2003; Owe et al, 2008; Zhang et al, 2022).…”