000888487 001__ 888487 000888487 005__ 20210628225835.0 000888487 0247_ $$2doi$$a10.3389/frwa.2020.552508 000888487 0247_ $$2Handle$$a2128/26395 000888487 0247_ $$2altmetric$$aaltmetric:94536140 000888487 0247_ $$2WOS$$aWOS:000659409100001 000888487 037__ $$aFZJ-2020-04951 000888487 082__ $$a333.7 000888487 1001_ $$0P:(DE-HGF)0$$aGonzález-Sanchis, María$$b0$$eCorresponding author 000888487 245__ $$aComparison of Soil Water Estimates From Cosmic-Ray Neutron and Capacity Sensors in a Semi-arid Pine Forest: Which Is Able to Better Assess the Role of Environmental Conditions and Thinning? 000888487 260__ $$aLausanne$$bFrontiers Media$$c2020 000888487 3367_ $$2DRIVER$$aarticle 000888487 3367_ $$2DataCite$$aOutput Types/Journal article 000888487 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1607418616_11439 000888487 3367_ $$2BibTeX$$aARTICLE 000888487 3367_ $$2ORCID$$aJOURNAL_ARTICLE 000888487 3367_ $$00$$2EndNote$$aJournal Article 000888487 520__ $$aWater 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 moisture is a key variable to quantify the impacts of eco-hydrological forest management on forest-water relations. Cosmic-ray neutron and capacitance probes are two different techniques for measuring soil moisture, which differ greatly in the spatial scale of the measurement support (i.e., few centimeters vs. several hectares). This study compares the capability of both methodologies in assessing soil water dynamics as a key variable that reflects the effects of forest management in a semi-arid environment. To this end, two experimental plots were established in Sierra Calderona in the province of Valencia in Spain in a post-fire regeneration Aleppo pine forest with high tree density. One plot was thinned (T) and the other remained as control (C). Nine capacitance probes and one Cosmic Ray Neutron Probe (CRNP) were installed in each plot. First, the CRNP was calibrated and validated, and subsequently, the performance of both techniques was analyzed by comparing soil moisture and its relationship with environmental variables and stand transpiration. The validation results confirmed the general reliability of CRNP to obtain soil moisture 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 soil moisture (KGE: −0.06–0.02). A significant effect of forest biomass and litter layer was also observed on CRNP-derived soil moisture, which produced an overestimation of soil moisture. The performance of both methodologies was analyzed by partial correlations between soil moisture and environmental variables and transpiration, as well as by applying Boosted Regression Trees to reproduce tree transpiration with each soil moisture measurement technique together with the environmental variables. Both methodologies were capable to reproduce tree transpiration affected by soil moisture, environmental variables and thinning, although CRNP always appeared as the most affected by atmospheric driving forces 000888487 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0 000888487 588__ $$aDataset connected to CrossRef 000888487 7001_ $$0P:(DE-HGF)0$$aGarcía-Soro, Juan M.$$b1 000888487 7001_ $$0P:(DE-HGF)0$$aMolina, Antonio J.$$b2 000888487 7001_ $$0P:(DE-HGF)0$$aLidón, Antonio L.$$b3 000888487 7001_ $$0P:(DE-HGF)0$$aBautista, Inmaculada$$b4 000888487 7001_ $$0P:(DE-HGF)0$$aRouzic, Elie$$b5 000888487 7001_ $$0P:(DE-Juel1)129440$$aBogena, Heye R.$$b6$$ufzj 000888487 7001_ $$0P:(DE-Juel1)138662$$aHendricks-Franssen, Harrie-Jan$$b7 000888487 7001_ $$0P:(DE-HGF)0$$adel Campo, Antonio D.$$b8 000888487 773__ $$0PERI:(DE-600)2986721-6$$a10.3389/frwa.2020.552508$$gVol. 2, p. 552508$$p552508$$tFrontiers in water$$v2$$x2624-9375$$y2020 000888487 8564_ $$uhttps://juser.fz-juelich.de/record/888487/files/FRWA_Gonz%C3%A1lez-Sanchis%20et%20al._2020.pdf$$yOpenAccess 000888487 909CO $$ooai:juser.fz-juelich.de:888487$$pVDB$$pVDB:Earth_Environment$$pdriver$$popen_access$$popenaire$$pdnbdelivery 000888487 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129440$$aForschungszentrum Jülich$$b6$$kFZJ 000888487 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)138662$$aForschungszentrum Jülich$$b7$$kFZJ 000888487 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0 000888487 9141_ $$y2020 000888487 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0 000888487 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2020-09-06 000888487 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2020-09-06 000888487 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 000888487 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Blind peer review$$d2020-09-06 000888487 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2020-09-06 000888487 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2020-09-06 000888487 920__ $$lyes 000888487 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0 000888487 980__ $$ajournal 000888487 980__ $$aVDB 000888487 980__ $$aUNRESTRICTED 000888487 980__ $$aI:(DE-Juel1)IBG-3-20101118 000888487 9801_ $$aFullTexts