The lack of a quantitative model that links multiple

The gap

Evidence profile

Sourced from the limitations and limitations section and stated research gap and abstract of the source papers, classified as general, spanning 3 journals.

Supporting evidence — 4 representative gaps

• Analysis of influencing factors and prediction model of resistivity in unsaturated loess (2026) · Bulletin of Engineering Geology and the Environment · doi

  The empirical model proposed in this study describes the relationship between soil resistivity and temperature (0 ~ 30℃), moisture content (5 ~ 30%), and dry density (1.24 ~ 1.62 g/cm3) and enables rapid estimation and pre- liminary field assessment. However, several limitations remain for practical application. Firstly, we did not take into account the changes in the test frequency. Secondly, the temperature range of the soil is limited, and soil resistivity can exhibit abrupt changes near 0℃. When the soil tem- perature falls below 0℃, moisture may freeze, leading to a sharp increase in resistivity. Furthermore, during measure- ments we neglected the influence of soil mineral composi- tion (Rashid et al. 2018), as well as the composition and concentration of saline ions (Zohra et al. 2019; Zhang et al. 2018), the plasticity index of the soil (Memon et al. 2024), and organic matter content (Liu et al. 2025). These factors limit the model’s extrapolation capability. Additionally, when preparing the samples, we first ensured their dry den- sity and water content. Then, we adjusted the temperature in the oven. However, during the temperature adjustment pro- cess, some moisture deposition inevitably occurred, which increased the inaccuracy of the measurement. With the development of electrical resistivity tomogra- phy (ERT) technology, many researchers have utilized resis- tivity to invert various soil physical properties (Vivaldi et al. 2024; Alam et al. 2025). However, a single resistivity Bulletin of Engineering Geology and the Environment (2026) 85:347 1 3  347 Page 12 of 14 value may correspond to different combinations of param- eters, complicating the accurate inversion of soil proper- ties. To reliably infer soil physical properties, it is essential to elucidate the relationships between each parameter and soil resistivity. The relationship between soil resistivity and parameters is often nonlinear, and the diversity of soil types and field conditions further increases the difficulty of prediction. In comparison, machine learning has dem- onstrated strong accuracy in handling nonlinear regression problems (Kundu et al. 2024). Consequently, future work should focus on integrating these variable factors to develop a more comprehensive soil resistivity model (Sangprasat et al. 2025), or on employing machine-learning approaches to construct interpretable regression models, thereby enhanc- ing the practical engineering applications of soil resistivity.

  generallimitationsevidence 5/5
  Keywords: soil resistivity temperature model moisture content relationship field practical changes factors physical properties engineering nonlinear
• Robust automated processing of continuous electrical resistivity measurements for soil texture mapping in support of optimized precision farming (2026) · Precision Agriculture · doi

  Soil moisture strongly affects resistivity, which may influence observed resistivity patterns. The measurements were conducted in October, when natural variations in moisture may be present. Further investigation may be necessary to confirm the overall quality of the data.

  generallimitations sectionevidence 5/5
  Keywords: soil moisture strongly affects resistivity influence observed patterns
• Analysis of influencing factors and prediction model of resistivity in unsaturated loess (2026) · Bulletin of Engineering Geology and the Environment · doi

  The lack of a quantitative model that links multiple factors to soil resistivity. The need for a predictive model that can accurately estimate soil resistivity in unsaturated loess.

  generalstated research gapevidence 5/5
  Keywords: lack quantitative model links multiple factors soil resistivity
• Exploring spatial variability in the physical and chemical properties of urban soils using electrical resistivity tomography (2026) · Frontiers in Soil Science · doi

  However, except in highly polluted industrial sites, the relationship between soil resistivity and physico-chemical properties, organic matter composition, and contaminants remains poorly documented.

  generalabstractevidence 4/5
  Keywords: except highly polluted industrial sites relationship soil resistivity physico chemical properties organic matter composition contaminants

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