Correlation between soil apparent electroconductivity and plant hyperspectral reflectance in a managed wetland

Abstract

The apparent electrical conductivity (σ_a) of soil is influenced by a complex combination of soil physical and chemical properties. For this reason, σ_a is proposed as an indicator of plant stress and potential community structure changes in an alkaline wetland setting. However, assessing soil σ_a is relatively laborious and difficult to accomplish over large wetland areas. This work examines the feasibility of using the hyperspectral reflectance of the vegetation canopy to characterize the σ_a of the underlying substrate in a study conducted in a Central California managed wetland. σ_a determined by electromagnetic (EM) inductance was tested for correlation with in-situ hyperspectral reflectance measurements, focusing on a key waterfowl forage species, swamp timothy (Crypsis schoenoides). Three typical hyperspectral indices, individual narrow-band reflectance, first-derivative reflectance and a narrow-band normalized difference spectral index (NDSI), were developed and related to soil σ_a using univariate regression models. The coefficient of determination (R ²) was used to determine optimal models for predicting σ_a, with the highest value of R ² at 2206 nm for the individual narrow bands (R ² = 0.56), 462 nm for the first-derivative reflectance (R ² = 0.59), and 1549 and 2205 nm for the narrow-band NDSI (R ² = 0.57). The root mean squared error (RMSE) and relative root mean squared error (RRMSE) were computed using leave-one-out cross-validation (LOOCV) for accuracy assessment. The results demonstrate that the three indices tested are valid for estimating σ_a, with the first-derivative reflectance performing better (RMSE = 30.3 mS m⁻¹, RRMSE = 16.1%) than the individual narrow-band reflectance (RMSE = 32.3 mS m⁻¹, RRMSE = 17.1%) and the narrow-band NDSI (RMSE = 31.5 mS m⁻¹, RRMSE = 16.7%). The results presented in this paper demonstrate the feasibility of linking plant–soil σ_a interactions using hyperspectral indices based on in-situ spectral measurements.

Acknowledgements

Funding for this work was provided by the State Water Resources Control Board (Grant no. 04-312-555-1), the University of California Salinity Drainage Program, the California Department of Water Resources, and the U.S. National Science Foundation (Awards EF 0410408 and CCF 0603903). The loan of the EM-38 instrument by Dr Nigel Quinn (Lawrence Berkeley National Laboratory and U.S. Bureau of Reclamation) and advice on its application in this setting are gratefully acknowledged. We also thank the reviewers for their constructive comments, which helped to strengthen the paper.