Using wavelet analyses to identify temporal coherence in soil physical properties in a volcanic ash-derived soil

Lysimeters have been used for centuries to understand hydrological cycles. Nowadays, high-resolution weighing lysimeters allow precise determination of the water balance components. While major efforts have been focused on the definition of appropriate methodologies for data processing in order to obtain results with high accuracy, it is still unknown to what extent measurements registered by a lysimeter can reflect soil water dynamics and the transport phenomena in a defined agroecosystem. The aim of this work is to analyze temporally-coherent discrepancies in the estimation of soil parameters based on time series recorded inside and outside a lysimeter installed in a volcanic ash-derived soil. Continuous wavelet transforms and cross-wavelet analyses were used to understand temporal differences and similarities between time series, respectively. Inside and at a 2 m distance from the lysimeter, soil temperature, volumetric water content and matric potential were measured at different depths (10, 20 and 60 cm depth). Despite that the Pearson's correlation between the studied time series indicated good correlations (r² > 0.95), the wavelet analyses showed that coherence obtained inside the lysimeter can temporarily differ from those monitored in the field at specific times during the year. The latter was quantified using a Dissimilarity Index (DI), which showed high values at particular moments throughout the year. The wavelet analyses used here are a valuable tool to assess time series temporal variations which are unnoticed by commonly-used statistics, such as the Pearson's correlation. A better understanding of soil water and temperature temporal dynamics can enhance our ability to model and predict these processes in soils.