AUTHOR=González-Sanchis María , García-Soro Juan M. , Molina Antonio J. , Lidón Antonio L. , Bautista Inmaculada , Rouzic Elie , Bogena Heye R. , Hendricks Franssen Harrie-JanHarrie , del Campo Antonio D. 

TITLE=Comparison of Soil Water Estimates From Cosmic-Ray Neutron and Capacity Sensors in a Semi-arid Pine Forest: Which Is Able to Better Assess the Role of Environmental Conditions and Thinning?

JOURNAL=Frontiers in Water

VOLUME=Volume 2 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/water/articles/10.3389/frwa.2020.552508

DOI=10.3389/frwa.2020.552508

ISSN=2624-9375

ABSTRACT=Water scarcity in semi-arid regions is expected to increase under climate change, which will significantly affect forest ecosystems by increasing fire risk, diminishing productivity and water provisioning. Eco-hydrological forest management is conceived here as an adequate strategy to buffer climate change effects and increase forest resilience. Under this context, soil water content (SWC) is a key variable to quantify the impacts of eco-hydrological forest management on forest-water relations. Cosmic-ray neutrons and capacitance probes are two different technics to register SWC, whose main differences are the spatial scale and the soil invasiveness. This study compares the capability of both methodologies in registering SWC as a key variable that reflects the effects of forest management in a semi-arid environment. To that end, two experimental plots were established in a post-fire regeneration Aleppo pine forest with high tree density. One plot was thinned (T) and the other remained as control (C). 9 capacitance probes and a CRS were installed at C and T plots, respectively. First, CRS was calibrated and validated, and subsequently, the performance of both techniques was analyzed by comparing SWC measures and its relationship with environmental variables and stand transpiration (Tr). The validation results confirmed the general reliability of CRS to obtain SWC under semi-arid conditions, with a Kling-Gupta efficiency coefficient (KGE) between 0.75 and 0.84, although this performance decreased significantly when dealing with extreme SWC (KGE: 0.02- -0.06). A significant effect of forest biomass and litter layer was also observed on CRS measures, which produced an overestimation of SWC. The performance of both methodologies was analyzed by partial correlations between SWC and environmental variables and Tr, as well as by applying Boosted Regression Trees to reproduce Tr with each SWC technic together with the environmental variables. Both methodologies were capable to reproduce tree transpiration affected by soil water content, environmental variables and thinning, although CRS probe always appeared as the most affected by atmospheric driving forces.