A biophysical approach using water deficit factor for daily estimations of evapotranspiration and CO 2 uptake in Mediterranean environments

Abstract. Estimations of ecosystem-level evapotranspiration (ET) and CO2 uptake in water-limited environments are scarce and scaling up ground-level measurements is not straightforward. A biophysical approach using remote sensing (RS) and meteorological data (RS–Met) is adjusted to extreme high-energy water-limited Mediterranean ecosystems that suffer from continuous stress conditions to provide daily estimations of ET and CO2 uptake (measured as gross primary production, GPP) at a spatial resolution of 250 m. The RS–Met was adjusted using a seasonal water deficit factor (fWD) based on daily rainfall, temperature and radiation data. We validated our adjusted RS–Met with eddy covariance flux measurements using a newly developed mobile lab system and the single active FLUXNET station operating in this region (Yatir pine forest station) at a total of seven forest and non-forest sites across a climatic transect in Israel (280–770 mm yr−1). RS–Met was also compared to the satellite-borne MODIS-based ET and GPP products (MOD16 and MOD17, respectively) at these sites. Results show that the inclusion of the fWD significantly improved the model, with R =  0.64–0.91 for the ET-adjusted model (compared to 0.05–0.80 for the unadjusted model) and R =  0.72–0.92 for the adjusted GPP model (compared to R =  0.56–0.90 of the non-adjusted model). The RS–Met (with the fWD) successfully tracked observed changes in ET and GPP between dry and wet seasons across the sites. ET and GPP estimates from the adjusted RS–Met also agreed well with eddy covariance estimates on an annual timescale at the FLUXNET station of Yatir (266 ± 61 vs. 257 ± 58 mm yr−1 and 765 ± 112 vs. 748 ± 124 gC m−2 yr−1 for ET and GPP, respectively). Comparison with MODIS products showed consistently lower estimates from the MODIS-based models, particularly at the forest sites. Using the adjusted RS–Met, we show that afforestation significantly increased the water use efficiency (the ratio of carbon uptake to ET) in this region, with the positive effect decreasing when moving from dry to more humid environments, strengthening the importance of drylands afforestation. This simple yet robust biophysical approach shows promise for reliable ecosystem-level estimations of ET and CO2 uptake in extreme high-energy water-limited environments.

[1]  P. Nagler,et al.  Vegetation index‐based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems , 2011 .

[2]  D. Helman,et al.  Contrasting effects of two Acacia species on understorey growth in a drylands environment: interplay of canopy shading and litter interference , 2017 .

[3]  H. R. Haise,et al.  Estimating evapotranspiration from solar radiation , 1963 .

[4]  J. Monteith Climate and the efficiency of crop production in Britain , 1977 .

[5]  S. Running,et al.  Regional evaporation estimates from flux tower and MODIS satellite data , 2007 .

[6]  Y. Osem,et al.  Understory woody vegetation in manmade Mediterranean pine forests: variation in community structure along a rainfall gradient , 2012, European Journal of Forest Research.

[7]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[8]  Atul K. Jain,et al.  The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink , 2015, Science.

[9]  Naftali Lazarovitch,et al.  A review of approaches for evapotranspiration partitioning , 2014 .

[10]  David Helman,et al.  Land surface phenology: What do we really 'see' from space? , 2018, Science of the Total Environment.

[11]  Josep Peñuelas,et al.  Photosynthetic light use efficiency from satellite sensors: From global to Mediterranean vegetation , 2014 .

[12]  J. Peñuelas,et al.  The combined effects of a long‐term experimental drought and an extreme drought on the use of plant‐water sources in a Mediterranean forest , 2015, Global change biology.

[13]  A. Budovsky,et al.  The Effects of Long Time Conservation of Heavily Grazed Shrubland: A Case Study in the Northern Negev, Israel , 2014, Environmental Management.

[14]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[15]  Qiaoyun Xie,et al.  Improved estimation of light use efficiency by removal of canopy structural effect from the photochemical reflectance index (PRI) , 2015 .

[16]  J. Ogée,et al.  Resilience to seasonal heat wave episodes in a Mediterranean pine forest. , 2016, The New phytologist.

[17]  David Helman,et al.  Annual evapotranspiration retrieved from satellite vegetation indices for the eastern Mediterranean at 250 m spatial resolution , 2015 .

[18]  M. Mccabe,et al.  Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data , 2008 .

[19]  I. Lensky,et al.  Rehabilitating degraded drylands by creating woodland islets: Assessing long-term effects on aboveground productivity and soil fertility , 2014 .

[20]  S. Seneviratne,et al.  Climate extremes and the carbon cycle , 2013, Nature.

[21]  R. Myneni,et al.  On the relationship between FAPAR and NDVI , 1994 .

[22]  Piermaria Corona,et al.  Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems , 2009 .

[23]  David Helman,et al.  Detecting changes in biomass productivity in a different land management regimes in drylands using satellite‐derived vegetation index , 2014 .

[24]  Piermaria Corona,et al.  Use of remotely sensed and ancillary data for estimating forest gross primary productivity in Italy , 2006 .

[25]  I. Lensky,et al.  Forests growing under dry conditions have higher hydrological resilience to drought than do more humid forests , 2017, Global change biology.

[26]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[27]  P. Cox,et al.  Observing terrestrial ecosystems and the carbon cycle from space , 2015, Global change biology.

[28]  L. S. Pereira,et al.  A recommendation on standardized surface resistance for hourly calculation of reference ETo by the FAO56 Penman-Monteith method , 2006 .

[29]  Markus Reichstein,et al.  Climate and vegetation controls on the surface water balance: Synthesis of evapotranspiration measured across a global network of flux towers , 2012 .

[30]  W. Verstraeten,et al.  On temperature and water limitation of net ecosystem productivity: Implementation in the C-Fix model , 2006 .

[31]  J. Peñuelas,et al.  Remote estimation of carbon dioxide uptake by a Mediterranean forest , 2008 .

[32]  K. Pilegaard,et al.  How is water-use efficiency of terrestrial ecosystems distributed and changing on Earth? , 2014, Scientific Reports.

[33]  Josep Peñuelas,et al.  Photochemical reflectance index (PRI) and remote sensing of plant CO₂ uptake. , 2011, The New phytologist.

[34]  A. Schwartz,et al.  Physiology-phenology interactions in a productive semi-arid pine forest. , 2008, The New phytologist.

[35]  David Helman,et al.  A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series , 2015, Remote. Sens..

[36]  D. Baldocchi Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future , 2003 .

[37]  Michael Sprintsin,et al.  Long term and seasonal courses of leaf area index in a semi-arid forest plantation , 2011 .

[38]  C. Field,et al.  Relationships Between NDVI, Canopy Structure, and Photosynthesis in Three Californian Vegetation Types , 1995 .

[39]  A. Budovsky,et al.  Modeling herbaceous productivity considering tree-grass interactions in drylands savannah: the case study of Yatir farm in the Negev drylands. , 2016 .

[40]  Ü. Rannik,et al.  Estimates of the annual net carbon and water exchange of forests: the EUROFLUX methodology , 2000 .

[41]  I. Lensky,et al.  Relationships between climate, topography, water use and productivity in two key Mediterranean forest types with different water-use strategies , 2017 .

[42]  E. Rotenberg,et al.  Association between sap flow-derived and eddy covariance-derived measurements of forest canopy CO2 uptake. , 2016, The New phytologist.

[43]  P. Ciais,et al.  Europe-wide reduction in primary productivity caused by the heat and drought in 2003 , 2005, Nature.

[44]  T. A. Black,et al.  The use of remote sensing in light use efficiency based models of gross primary production: a review of current status and future requirements. , 2008, The Science of the total environment.

[45]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[46]  F. Veroustraete,et al.  Estimation of carbon mass fluxes over Europe using the C-Fix model and Euroflux data , 2002 .

[47]  F. Garbulskya,et al.  Photosynthetic light use efficiency from satellite sensors: From global to Mediterranean vegetation , 2014 .

[48]  Dario Papale,et al.  Operational monitoring of daily evapotranspiration by the combination of MODIS NDVI and ground meteorological data: Application and evaluation in Central Italy , 2014 .

[49]  S. Running,et al.  Global Terrestrial Gross and Net Primary Productivity from the Earth Observing System , 2000 .

[50]  W. Oechel,et al.  A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS , 2008 .

[51]  E. Rotenberg,et al.  Distinct patterns of changes in surface energy budget associated with forestation in the semiarid region , 2011 .

[52]  T. Vesala,et al.  On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm , 2005 .

[53]  Dan Yakir,et al.  Ecosystem photosynthesis inferred from measurements of carbonyl sulphide flux , 2013 .

[54]  S. Leavitt,et al.  Increase in water-use efficiency and underlying processes in pine forests across a precipitation gradient in the dry Mediterranean region over the past 30 years , 2011, Oecologia.

[55]  Dan Yakir,et al.  Dynamics of evapotranspiration partitioning in a semi-arid forest as affected by temporal rainfall patterns , 2012 .

[56]  S. Seneviratne,et al.  Recent decline in the global land evapotranspiration trend due to limited moisture supply , 2010, Nature.

[57]  Maosheng Zhao,et al.  Development of a global evapotranspiration algorithm based on MODIS and global meteorology data , 2007 .

[58]  Photosynthesis, stomatal conductance and terpene emission response to water availability in dry and mesic Mediterranean forests , 2016, Trees.

[59]  W. Cleveland Robust Locally Weighted Regression and Smoothing Scatterplots , 1979 .

[60]  Maosheng Zhao,et al.  Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 , 2010, Science.

[61]  S. G. Nelson,et al.  Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape , 2008, Sensors.

[62]  R. Oren,et al.  The space-time continuum: the effects of elevated CO2 and temperature on trees and the importance of scaling. , 2015, Plant, cell & environment.

[63]  C. Rao,et al.  Photosynthetically active components of global solar radiation: Measurements and model computations , 1984 .

[64]  P. Zhao,et al.  CO 2 uptake of a mature Acacia mangium plantation estimated from sap flow measurements and stable carbon isotope discrimination , 2013 .

[65]  Ramakrishna R. Nemani,et al.  Relating seasonal patterns of the AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates , 1988 .

[66]  A. Huete,et al.  Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing , 2010 .