Abstract
The Critical Zone Observatory (CZO) in the Alento River Catchment (ARC; southern Italy) has been collecting data for some decades and recently became part of the TERENO (TERrestrial ENvironmental Observatories) long-term ecosystem infrastructure network. In 2016, cosmic-ray neutron probes (CRNP, non-invasive proximal sensors) together with SoilNet wireless sensor networks (invasive ground-based sensors) were installed in two sub-catchments (MFC2 and GOR1), characterized by different weather, topographic, pedological, and land-use conditions. The SoilNet sensors are measuring soil apparent permittivity (converted into soil moisture), electrical conductivity, and temperature at two soil depths of 0.15 m and 0.30 m in 20 locations around the CRNP. The SoilNet sensor network includes also soil matric pressure potential sensors at the same soil depths and locations. A major aim of this study is to compare the hydrological response of the two experimental sites to climate forcings (rainfall minus potential evapotranspiration, hereby defined as rainfall deficit) through the use of the monthly Soil Moisture Index (SMI) computed from daily values of soil moisture measured by the CRNPs. For both sites, strong correlations are detected between monthly rainfall deficit and SMI, even if the cropland site (MFC2) is characterized by more extreme dry and wet conditions. For these two different sites, our investigations also aim at identifying the dominant controls governing the seasonal dynamics of spatial soil moisture patterns. The majority of the spatial variance in the cropland site is explained by terrain attributes, under both wet and dry conditions, whereas the second-order statistical moment of soil moisture in the forested site is mostly explained by topographic factors under wet conditions during the rainy season. For both sites, our data show that soil texture exerts a minimal impact on the spatial variations of soil moisture.
Highlights
Soil moisture (θ ) is an important state variable in environmental systems and can be inferred from ground-based devices, proximal sensors, and remote-sensing platforms enabling observations to be performed across different spatial and temporal scales
We found discrepancies in the data of the two sensor types related to the effects of the time-varying vertical measurement footprint of the cosmicray neutron probes (CRNPs), which induces a scale mismatch between CRNP-based soil moisture and the spatially averaged soil matric potential data measured at soil depths of 0.15 and 0.30 m
root mean squared error (RMSE) takes on very similar values for the four cases considered, the Schrön et al (2017) weighted procedure seems to provide a slightly better correlation than the unweighted one especially at the higher soil moisture contents, as evident from the fact that the scatter cloud tends to be closer to the identity line as θ increases
Summary
Soil moisture (θ ) is an important state variable in environmental systems and can be inferred from ground-based devices, proximal sensors, and remote-sensing platforms enabling observations to be performed across different spatial and temporal scales. Direct measurement based on the thermogravimetric technique (Topp and Ferré, 2002), can operationally provide reliable data in sparse locations and is commonly used during sporadic field campaigns This technique enables the soil water content distribution within the root zone to be measured occasionally and is destructive, timeconsuming, expensive, and unfeasible for large-scale applications (Entin et al, 2000; Romano, 2014). Unattended and automated in-situ monitoring networks for monitoring soil moisture are designed to overcome most of these drawbacks and comprise invasive ground-based instrumentation or noninvasive proximal sensors The former include point-scale sensors installed in multiple positions and soil depths, providing localized information about soil moisture dynamics in a field. Other proximal sensors are the thermal or spectral cameras carried by unmanned aerial systems (UASs), this relatively recent sensing technique can provide only sporadic measurements of soil moisture patterns
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