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Influence of wind direction on the surface roughness of vineyards

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Abstract

Remote sensing-based models are the most viable means of collecting the high-resolution spatially distributed estimates of evaporative water loss needed to manage irrigation and ensure the effective use of limited water resources. However, due to the unique canopy structure and configuration of vineyards, these models may not be able to adequately describe the physical processes driving evapotranspiration from vineyards. Using data collected from 2014 to 2016 as a part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX), the twofold objective of this study was to (1) identify the relationship between the roughness parameters, zero-plane displacement height (do) and roughness length for momentum (zo), and local environmental conditions, specifically wind direction and vegetation density and (2) determine the effect of using these relationships on the ability of the remote sensing-based Two-Source Energy Balance (TSEB) model to estimate the sensible (H) and latent (λE) heat fluxes. Although little variation in do was identified during the growing season, a well-defined sigmoidal relationship was observed between zo and wind direction. When the output from a version of the TSEB model incorporating these relationships (TSEBVIN) was compared to output from the standard model (TSEBSTD), there were large changes to the roughness parameters, particularly zo, but only modest changes in the turbulent fluxes. When the output from TSEBVIN was compared to that of a version using a parameterization scheme representing open canopies (TSEBOPN), the mean absolute difference between the estimates of do and zo were 0.44 m and 0.25 m, respectively. While these values represent differences in excess of 45%, the turbulent fluxes differed by just 13 W m−2 or 10%, on average. The results suggest that the TSEB model is largely insensitive to changes in the roughness parameters for the range in roughness values evaluated in this study. This also suggests that the requirement for highly accurate roughness values has limited utility in the application of the TSEB model in vineyard systems. Since there is no significant advantage to using the more complex TSEBOPN and TSEBVIN models, it is recommended that the standard model be used.

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Notes

  1. The use of trade, firm, or corporation names in this article is for the information and convenience of the reader. Such use does not constitute official endorsement or approval by the US Department of Agriculture or the Agricultural Research Service of any product or service to the exclusion of others that may be suitable.

References

  • Acevedo-Opazo C, Ortega-Farias S, Fuentes S (2010) Effects of grapevine (Vitis vinifera L.) water status on water consumption, vegetative growth and grape quality: an irrigation scheduling application to achieve regulated deficit. Agric Water Manag 97:956–964

    Article  Google Scholar 

  • Alfieri JG, Kustas WP, Prueger JH, Hipps LE, Chavez JL, French AN, Evett SR (2011) Intercomparison of nine meteorological stations during the BEAREX08 field campaign. J Atmos Ocean Technol 28:1390–1406

    Article  Google Scholar 

  • Anderson MC, Norman JM, Diak GR, Kustas WP, Mecikalski JR (1997) A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens Environ 60:195–216

    Article  Google Scholar 

  • Anderson MC, Norman JM, Mecikalski JR, Torn RD, Kustas WP, Basara JB (2004) A multi-scale remote sensing model for disaggregating regional flues to micrometeorological scales. J Hydrometeorol 5:343–363

    Article  Google Scholar 

  • Anderson MC, Norman JM, Kustas WP, Li F, Prueger JH, Mecikalski JM (2005) Effects of vegetation clumping on two-source model estimates of surface energy fluxes from an agricultural landscape during SMACEX. J Hydrometeorol 6:892–909

    Article  Google Scholar 

  • Anderson MC, Norman JM, Kustas WP, Li F, Prueger JH, Mecikalski JR (2007) A climatological study of evapotranspiration and moisture stress across the continental United States: 1. Model formulation. J Geophys Res. https://doi.org/10.1029/2006JD007506

    Article  Google Scholar 

  • Arno J, Martınez-Casanovas J, Ribes-Dasi M, Rosell JR (2009) Review. Precision viticulture. Research topics, challenges and opportunities in site-specific vineyard management. Spanish J Agric Res 7:779–790

    Article  Google Scholar 

  • Arya P (2001) Introduction to micrometeorology. Academic Press, San Diego

    Google Scholar 

  • Baluja J, Diago MP, Balda P, Zorer R, Meggio F, Morales F, Tardaguila J (2012) Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). Irrig Sci 30:511–522

    Article  Google Scholar 

  • Bellvert J, Marsal J, Girona J, Zarco–Tejada PJ (2015) Seasonal evolution of crop water stress index in grapevine varieties determined with high-resolution remote sensing thermal imagery. Irrig Sci 33:81–93

    Article  Google Scholar 

  • Brunet Y, Finnigan JJ, Raupach MR (1994) A wind tunnel study of air flow in waving wheat: single-point velocity statistics. Bound Layer Meteorol 70:95–132

    Article  Google Scholar 

  • Brutsaert W (1982) Evaporation into the atmosphere. D Reidel Publishing Company, Dordrecht

    Book  Google Scholar 

  • California Department of Food and Agriculture (2017) California grape acreage report 2016. http://www.nass.usda.gov/ca. Accessed 21 Apr 2018

  • Campbell GS, Norman JM (1998) An introduction to environmental biophysics. Springer, New York

    Book  Google Scholar 

  • Campos I, Neale CMU, Calera A, Balbontin C, Gonzalez-Piqueras J (2010) Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.). Agric Water Manag 98:45–54

    Article  Google Scholar 

  • Chahine A, Dupont S, Sinfort C, Brunet Y (2014) Wind flow dynamics over a vineyard. Bound Layer Meteorol 151:557–577

    Article  Google Scholar 

  • Chapman DM, Roby G, Ebeler SE, Guinard JX, Matthews MA (2005) Sensory attributes of Cabernet Sauvignon wines made from vines with different water status. Aust J Grape Wine Res 11:339–347

    Article  CAS  Google Scholar 

  • Chaves MM, Santos TP, Souza CR, Ortun˜o MF, Rodrigues ML, Lopes CM, Maroco JP, Pereira JS (2007) Deficit irrigation in grapevine improves water-use efficiency while controlling vigour and production quality. Ann Appl Biol 150:237–252

    Article  Google Scholar 

  • Dyer AJ (1974) A review of flux profile relationships. Bound Layer Meteorol 7:363–372

    Article  Google Scholar 

  • Gao F, Anderson MC, Kustas WP, Wang Y (2012) A simple method for retrieving Leaf Area Index from Landsat using MODIS LAI products as reference. J Appl Remote Sens. https://doi.org/10.1117/.JRS.1116.063554

    Article  Google Scholar 

  • Goring DG, Nikora VI (2002) Despiking acoustic doppler velocimeter data. J Hydrol Eng 128:117–126

    Article  Google Scholar 

  • Goudriaan J (1977) Crop micrometeorology: a simulation study. Center for Agricultural Publications and Documentation, Wageningen

    Google Scholar 

  • Hicks BB (1973) Eddy fluxes over a vineyard. Agric Meteorol 12:203–215

    Article  Google Scholar 

  • John Dunham and Associates (2016) The 2015 economic impact study of the California wine industry. http://www.wineinstitute.org/resources/statistics. Accessed 6 Nov 2017

  • Jonsson P, Eklundh L (2004) TIMESAT—a program for analyzing time-series of satellite sensor data. Comput Geosci 30:833–845

    Article  Google Scholar 

  • Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows. Oxford University Press, Oxford

    Google Scholar 

  • Kustas WP, Norman JM (1997) A two-source approach for estimating turbulent fluxes using multiple angle thermal infrared observations. Water Resour Res 33:1495–1508

    Article  Google Scholar 

  • Kustas WP, Norman JM (1999) Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover. Agric For Meteorol 94:13–29

    Article  Google Scholar 

  • Kustas WP, Norman JM (2000) A two-source energy balance approach using directional radiometric temperature observations for sparse canopy covered surfaces. Agron J 92:847–854

    Article  Google Scholar 

  • Kustas WP, Alfieri JG, Anderson MC, Colaizzi PD, Prueger JH, Evett SR, Neale CM, French AN, Hipps LE, Chávez JL, Copeland KS, Howell TA (2012) Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area. Adv Water Resour 50:120–133

    Article  Google Scholar 

  • Legates DR, McCabe GR (1999) Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour Res 35:233–241

    Article  Google Scholar 

  • Lindroth A (1993) Aerodynamic and canopy resistance of short-rotation forest in relationship to leaf area index and climate. Bound Layer Meteorol 66:265–279

    Article  Google Scholar 

  • Liu H, Peters G, Foken T (2001) New equations for sonic temperature variance and buoyancy heat flux with an omnidirectional sonic anemometer. Bound Layer Meteorol 100:459–468

    Article  Google Scholar 

  • Lobell DB, Cahill KN, Field CB (2007) Historical effects of temperature and precipitation on California crop yields. Clim Change 81:187–203

    Article  Google Scholar 

  • Massman WJ (2000) A simple method for estimating frequency response corrections for eddy covariance systems. Agric For Meteorol 104:185–198

    Article  Google Scholar 

  • Massman WJ, Lee X (2002) Eddy covariance flux corrections and uncertainties in long term studies of carbon and energy exchanges. Agric For Meteorol 113:121–144

    Article  Google Scholar 

  • Maurer KD, Hardiman BS, Vogel CS, Bohrer G (2013) Canopy-structure effects on surface roughness parameters: observations in a Great Lakes mixed-deciduous forest. Agric For Meteorol 177:24–34

    Article  Google Scholar 

  • Maurer KD, Bohrer G, Kenny WT, Ivanov VY (2015) Large-eddy simulations of surface roughness parameter sensitivity to canopy-structure characteristics. Biogeosciences 12:2533–2548

    Article  Google Scholar 

  • MFK Research (2007) The impact of wine, grapes, and grape products on the American economy. https://www.wineinstitute.org/files/mfk_us_econ_report07.pdf. Accessed 6 Nov 2017

  • Nieto H, Kustas WP, Torres-Rúa A, Alfieri JG, Gao F, Anderson MC, White WA, Song L, del Mar Alsina M, Prueger JH, McKee M, Elarab M, McKee LG (2018a) Evaluation of TSEB turbulent fluxes using different methods for the retrieval of soil and canopy component temperatures from UAV thermal and multispectral imagery. Irrig Sci. https://doi.org/10.1007/s00271-018-0585-9

    Article  PubMed  Google Scholar 

  • Nieto H, Kustas WP, Alfieri JG et al (2018b) Impact of different within-canopy wind attenuation formulations on modelling sensible heat flux using TSEB. Irrig Sci. https://doi.org/10.1007/s00271-018-0611-y

    Article  PubMed  Google Scholar 

  • Norman JM, Kustas WP, Humes KS (1995) A two-source approach for estimating soil and vegetation energy fluxes from observations of directional radiometric surface temperature. Agric For Meteorol 77:263–293

    Article  Google Scholar 

  • Ojeda H, Andary C, Kraeva E, Carbonneau A, Deloire A (2002) Influence of pre and postveraison water deficit on synthesis and concentration of skin phenolic compounds during berry growth of Vitis vinifera cv. Shiraz. Am J Enol Vitic 53:261–267

    CAS  Google Scholar 

  • Padro J, Massman WJ, Den Hartog G, Neumann HH (1994) Dry deposition velocity of O3 over a vineyard obtained from models and observations: the 1991 California ozone deposition experiment. Water Air Soil Pollut 75:307–323

    Article  CAS  Google Scholar 

  • Pagay V (2016) Effects of irrigation regime on canopy water use and dry matter production of ‘Tempranillo’ grapevines in the semi-arid climate of Southern Oregon, USA. Agric Water Manag 178:271–280

    Article  Google Scholar 

  • Paulson CA (1970) The mathematical representation of wind speed and temperature profiles in the unstable atmospheric boundary layer. J Appl Meteorol 9:857–861

    Article  Google Scholar 

  • Pellegrino A, Lebon E, Simonneau T, Wery J (2005) Towards a simple indicator of water stress in grapevine (Vitis vinifera L.) based on the differential sensitivities of vegetative growth components. Aust J Grape Wine Res 11:306–315

    Article  Google Scholar 

  • Pitman AJ (1994) Assessing the sensitivity of a land-surface scheme to the parameter values using a single column model. J Clim 7:1856–1869

    Article  Google Scholar 

  • Priestley CHB, Taylor RJ (1972) On the assessment of surface heat flux and evaporation using large-scale parameters. Mon Weather Rev 100:81–92

    Article  Google Scholar 

  • Raupach M (1992) Drag and drag partition on rough surfaces. Bound Layer Meteorol 60:375–395

    Article  Google Scholar 

  • Raupach M (1994) Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index. Bound Layer Meteorol 71:211–216

    Article  Google Scholar 

  • Riou C, Pieri P, Valancogne C (1987) Variation de la vitesse du vent a l’interieur et au-dessus d’une vigne. Agric For Meteorol 39:143–154

    Article  Google Scholar 

  • Santanello JA, Friedl MA (2003) Diurnal variation in soil heat flux and net radiation. J Appl Meteorol 42:851–862

    Article  Google Scholar 

  • Sauer TJ, Norman JM, Tanner CB, Wilson TB (1995) Measurement of heat and vapor transfer at the soil surface beneath a maize canopy using source plates. Agric For Meteorol 75:161–189

    Article  Google Scholar 

  • Schaudt KJ, Dickinson RE (2000) An approach to deriving roughness length and zero-plane displacement height from satellite data, prototyped with BOREAS data. Agric For Meteorol 104:143–155

    Article  Google Scholar 

  • Semmens KA, Anderson MC, Kustas WP, Gao F, Alfieri JG, McKee L, Prueger JH, Hain CR, Cammalleri C, Yang Y, Xia T, Sanchez L, Alsina MM, Velez M (2016) Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach. Remote Sens Environ 185:155–170

    Article  Google Scholar 

  • Sene KJ (1994) Parameterisations for energy transfers from a sparse vine crop. Agric For Meteorol 71:1–18

    Article  Google Scholar 

  • Shaw RH, Pereira A (1982) Aerodynamic roughness of a plant canopy: a numerical experiment. Agric Meteorol 26:51–65

    Article  Google Scholar 

  • Stull R (1988) Introduction to boundary layer meteorology. Kluwer Academic Publishers, Dordrecht

    Book  Google Scholar 

  • Sun L, Gao F, Anderson MC, Kustas WP, Alsina M, Sanchez L, Sams B, McKee LG, Dulaney WP, White A, Alfieri JG, Prueger JH, Melton H, Post K (2017) Daily mapping of 30 m LAI, NDVI for grape yield prediction in California vineyard. Remote Sens 9:317

    Article  Google Scholar 

  • Tanner CB, Thurtell G (1969) Anemoclinometer measurements of Reynolds stress and heat transport in the atmospheric surface layer. Research and Development Technical Report to US Army Electronic Command, ECOM 66-G22-F. Department of Soil Sciences, University of Wisconsin

  • Timmermans WJ, Kustas WP, Anderson MC, French AN (2007) An intercomparison of the surface energy balance algorithm for land (SEBAL) and the two-source energy balance (TSEB) modeling schemes. Remote Sens Environ 108:369–384

    Article  Google Scholar 

  • US Department of the Treasury, Alcohol and Tobacco Tax and Trade Bureau (2017) Statistical report—wine. https://www.ttb.gov/wine/wine-stats.shtml. Accessed 21 Apr 2018

  • Verhoef A, McNaughton KG, Jacobs AFG (1997) A parameterization of momentum roughness length and displacement height for a wide range of canopy densities. Hydrol Earth Sys Sci 1:81–91

    Article  Google Scholar 

  • Webb EK, Pearman GL, Leuning R (1980) Correction measurements for density effects due to heat and water vapour transfer. Q J R Meteorol Soc 106:85–100

    Article  Google Scholar 

  • Webb LB, Whetton PH, Barlow EWR (2007) Modelled impact of future climate change on the phenology of winegrapes in Australia. Aust J Grape Wine Res 13:165–175

    Article  Google Scholar 

  • Weiss A, Allen LH (1976) Vertical and horizontal air flow above rows of a vineyard. Agric Meteorol 17:433–452

    Article  Google Scholar 

  • Willmott CJ (1982) Some comments on the evaluation of model performance. Bull Am Meteorol Soc 63:1309–1313

    Article  Google Scholar 

  • Willmott C, Matsuura K (2005) Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res 30:79–82

    Article  Google Scholar 

  • Willmott C, Robeson SM, Matsuura K (2012) A refined index of model performance. Int J Climatol 321:2088–2094

    Article  Google Scholar 

  • Xia T, Kustas WP, Anderson MC, Alfieri JG, Gao F, McKee L, Prueger JH, Geli HME, Neale CMU, Sanchez L, Alsina MM, Wang Z (2016) Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes. Hydrol Earth Syst Sci 20:1523–1545

    Article  Google Scholar 

  • Zarrouka O, Francisco R, Pinto-Marijuan M, Brossa R, Santos RR, Pinheiro C, Costa JM, Lopes C, Chaves MM (2012) Impact of irrigation regime on berry development and flavonoids composition in Aragonez (Syn. Tempranillo) grapevine. Agric Water Manag 114:18–29

    Article  Google Scholar 

  • Zeng X, Wang A (2007) Consistent parameterization of roughness length and displacement height for sparse and dense canopies in land models. J Hydrometeorol 8:730–737

    Article  Google Scholar 

  • Zhan X, Kustas WP, Humes KS (1996) An Intercomparison study on models of sensible heat flux over partial canopy surfaces with remotely sensed surface temperature. Remote Sens Environ 58:242–256

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the many researchers within the USDA and other governmental agencies, university collaborators, and industry partners who have contributed to the GRAPEX project. Specifically, the authors would like to thank E.&J. Gallo Winery for financial and logistical support and the staff of Viticulture, Chemistry, and Enology Division of E.&J. Gallo Winery for their assistance with data collection. The authors would also like to thank Mr. Ernie Dosio of Pacific Agri Lands Management and the vineyard staff at the Borden/McMannis Vineyard for their cooperation and support of this research. Finally, the authors would like to acknowledge financial support for this research from NASA (NNH16ZDA001N-WATER). USDA is an equal opportunity provider and employer.

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Authors and Affiliations

  1. Hydrology and Remote Sensing Laboratory, USDA ARS, Beltsville, MD, 20705-2350, USA

    Joseph G. Alfieri, William P. Kustas, Lynn G. McKee & Feng Gao

  2. Institute for Food and Agricultural Research and Technology, Parc de Gardeny, Edifici Fruitcentre, 25003, Lleida, Spain

    Hector Nieto

  3. National Laboratory for Agriculture and the Environment, USDA ARS, Ames, IA, 50011, USA

    John H. Prueger

  4. Plants, Soils and Climate Department, Utah State University, Logan, UT, 84322-4820, USA

    Lawrence E. Hipps & Sebastian Los

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  1. Joseph G. Alfieri
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  2. William P. Kustas
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  3. Hector Nieto
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Correspondence to Joseph G. Alfieri.

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Communicated by Nurit Agam.

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Alfieri, J.G., Kustas, W.P., Nieto, H. et al. Influence of wind direction on the surface roughness of vineyards. Irrig Sci 37, 359–373 (2019). https://doi.org/10.1007/s00271-018-0610-z

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