DOI: 10.3990/1.9789036538961
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Tree-water interactions at varying spatiotemporal scales in a water limited environment

Abstract: This dissertation is approved by: prof. dr. Z. Su (promotor) dr. ir. Maciek W. Lubczynski (co-promotor) I want to extend my gratitude to all the people that directly and/or indirectly supported all the stages of my PhD experience. To my supervisor, Dr. Ir. Maciek Lubczynski, for his patience, involvement, passion, vision and guidance during all these years. To Prof. Bob Su, for his active and timely support in my PhD project. To Dr. J. Martínez Fernández at the Universidad de Salamanca, and all the members of … Show more

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Cited by 5 publications
(13 citation statements)
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References 175 publications
(530 reference statements)
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“…The novelty of that conceptualization involves partitioning and sourcing of subsurface evapotranspiration, in which transpiration, in contrast to evaporation, is water table depth independent and driven mainly by the climatic conditions, while contributions of water sources (saturated or unsaturated zone) are dependent on water potential schematized by set of lumped parameters. The appropriate performance of MARMITES-MODFLOW was confirmed on the La Mata hard rock study case (Chapter 5) and validated against independent studies (van der Tol, 2012;Balugani et al, 2015;Reyes-Acosta, 2015) and states variables measured in the field (soil moisture and hydraulic heads). The capability of MARMITES-MODFLOW in integrating MRS method in the model calibration was also tested in the Carrizal sedimentary rock study case.…”
Section: Discussionmentioning
confidence: 92%
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“…The novelty of that conceptualization involves partitioning and sourcing of subsurface evapotranspiration, in which transpiration, in contrast to evaporation, is water table depth independent and driven mainly by the climatic conditions, while contributions of water sources (saturated or unsaturated zone) are dependent on water potential schematized by set of lumped parameters. The appropriate performance of MARMITES-MODFLOW was confirmed on the La Mata hard rock study case (Chapter 5) and validated against independent studies (van der Tol, 2012;Balugani et al, 2015;Reyes-Acosta, 2015) and states variables measured in the field (soil moisture and hydraulic heads). The capability of MARMITES-MODFLOW in integrating MRS method in the model calibration was also tested in the Carrizal sedimentary rock study case.…”
Section: Discussionmentioning
confidence: 92%
“…As recent studies focused on the assessment of these components individually (e.g. Shah et al, 2007;Balugani et al, 2014;Reyes-Acosta, 2015), such research created an opportunity to generate tools to integrate these fluxes separately in coupled hydrological models, allowing this way to retrieve a detailed and complete water balance at the catchment scale.…”
Section: I S S E R T a T I O Nmentioning
confidence: 99%
“…To assess the sources of water transpired by trees ( or ), we applied the methodology described by Lubczynski (2009) to experimental data described in Reyes-Acosta et al (2015). Constant doses of deuterated water were injected during 24 h into the groundwater using a network of piezometers drilled around the trees, following Brooks et al (2002).…”
Section: Tree Transpiration Estimated With Sap Flowmentioning
confidence: 99%
“…This setup maximized the plume shape and the chemical dispersion through the soil. During and after the deuterated water injection, we used sap flow sensors to monitor and collected xylem water, soil water and groundwater samples to assess the sources' contributions to (Reyes-Acosta et al, 2015). To upscale the transpiration estimates for the MF area we: (i) established the upscaling functions for each tree species using the procedure explained in Reyes and Lubczynski (2013) after digital mapping of the trees in the study area using a QuickBird image as reference; (ii) upscaled the 30 min sap flow measurements into whole-tree scale and to the investigated footprint area; (iii) extrapolated the results of the sap flow measurement campaign temporally into the whole dry summer period applying an artificial neural network model (Liu et al, 2009); and (iv) sourced sap flow into and using deuterium tracing experiments (Reyes-Acosta and Reyes-Acosta et al, 2015) for the whole dry summer period (according to the measurements, performed during dry summer campaigns of 2009 and 2010, Reyes-Acosta and Lubczynski, 2011).…”
Section: Tree Transpiration Estimated With Sap Flowmentioning
confidence: 99%
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