Sap Flow & Modelling Surface Renewal ET Remotely Sensed ET

Flows, fluxes and flightpaths: Adventures in quantifying vine and vineyard water use

Andrew J. McElrone; ajmcelrone@ucdavis.edu

Precipitation (P) & Irrigation (I)

Vineyard Water Balance

Drainage (D)

Evaporation & Transpiration (ET)

Change in soil water = P + I – ET – D – R Gains Losses

Runoff (R)

ETc = Kc * ETo

Grapevine evapotranspiration Crop coefficient Reference ET(well-wateredmodel grass)

Kc = ETc / ETo

Obtained from vines in weighing lysimeter

Kearney Agricultural CenterUniv. of California- Parlier CA

California Irrigation Management Information

System (CIMIS)

“…assumes a disease-free plant

grown under optimum soil water

and nutrient conditions…”Doorenbos and Pruitt, 1977

Williams and Ayars (2005)

Scale or load cell

Irrigation supply tank

Concrete pad

Tank filled with soil

Datalogger

Schematic drawing of lysimeter

Thompson Seedless

grapevines

HRM-Downstream temp

CHPM & HRM-

Upstream temp

Heater probe

Bark Sapwood

Sap

flow X

X

Schematic of Dual Heat Pulse Sap Flow Sensors

HRM-

Ideal for low &

reverse flows

CHPM-

Ideal for high

flows

CHPM-Downstream temp

Thermocouples

Xu

Xd

6mm

18, 24 or

36mm

-6mm-6mm

Heartwood

Vh = (Xd + Xu)/2t0 * 3600

Compensation Heat Pulse Method (CHPM)

Vh = (k * ln(V1 / V2))/X * 3600

Heat Ratio Method (HRM)

T up = T down

Vh = heat pulse velocity; X = spacing distances; t0 = time to travel ½ way Vh = heat pulse velocity; k = thermal diffusivity; V = temp increases; X = spacing distance

Bleby et al. 2004

08 Sep 10 Sep 12 Sep 14 Sep

Sap

Flo

w (

L h

r-1)

0

2

4

6

8

10

ETc

HRM

CHPM 18 Field Weighing Lysimeter vs. Dual Sap Flow Method

2008 Field Season

y = 0.9898x

R2 = 0.896

Lysimeter

20 Jul 23 Jul 26 Jul 29 Jul 01 Aug 04 Aug 07 Aug

Sa

p F

low

Ve

loc

ity

(c

m h

r-1)

0

20

40

60

80

100

HRM

CHPM 18

CHPM 24

CHPM 36 Irrigation

events

Pearsall et al. 2014

Trunk

Green 1 year old shoot

2 year old shoot

Converting sap

velocity to volume

Grapevines are hydraulically sectored

Trunk

03-Oct 05-Oct 07-Oct 09-Oct 11-Oct 13-Oct

Sap

Flo

w V

elo

cit

y (

cm

hr-

1)

0

50

100

150

200

Sensor 1

Sensor 2

Sensor 3

Sensor 4

Sensor 5

Sensor 6

ET

o (m

m)

0.0

0.2

0.4

0.6

0.8

1.0

CIMIS ETo

Variability around the trunk

Pearsall et al. 2014 FPB

Vary from 50-200 cm hr-1

Sensor Installation

“Dye colouring of the xylem vessels revealed that even 21 year old

grapevines did not show any development of heartwood and that xylem

vessels of that age still have the capacity to transport water”

Braun and Schmid (1999)

Bouda et al. (in review)

MRI-flow FusionX-ray microCT

Actual vs. modelled flows on same stem

Flow = DY/ Hydraulic Resistance

Model predicted flow rates with single pressure value across whole segment

Bouda et al. (in review)

Bouda et al. 2019

Model predicted flow rates with separate pressure value for sets of vessels

Flow = DY/ Hydraulic Resistance

Well-watered

Severe stress

Different water content in same stem

5 cm hr-1 Flow, Fibers Water-Filled

Heat Propagation in Air-Filled vs. Water-Filled

Fiber Matrix

temp (K)

70% overestimation of sap flow velocity due to

air-filled fiber tissue

Surface Renewal

Paw U & collaborators 1989, 1991, 1995

Goal: inexpensive, site-specific measurement of actual crop water use

=Net

Radiation + +Ground

Heat Flux

Sensible Heat Flux

Latent Heat Flux

Surface Energy Balance: Partitioning of energy at the surface

Bird’s eye view

theoretical

actual

Surface Renewal- Theory vs. Reality

Successfully removed the need to calibrate against expensive research grade system (Shapland et al. 2012a,b, 2014)

Research Grade System~$10,000 New Commercial System from

joint patent between USDA & UC Davis

New Surface Renewal System: A reliable & automated ET measurement system

New Surface Renewal Method vs. Weighing Lysimeter

Proof of concept:

Kearney Agricultural CenterUniv. of California- Parlier CA

New Surface Renewal Method vs. Soil Water Budget

Proof of concept:

Kearney Agricultural CenterUniv. of California- Parlier CA

Refine and apply a multi-scale remote sensing ET toolkit for mapping crop water use and stress for improved irrigation management in CA

Grape Remote sensing Atmospheric Profile

& Evapotranspiration eXperiment

Anderson et al. 2016

Approach: During the 2013 to the 2016 growing seasons, micrometeorogical, biophysical and

remote sensing data from ground, airborne (including UAVs) and satellite platforms have

been collected in adjacent vineyards at different levels of maturity near Lodi. Expanded to

additional sites (near Cloverdale and Ripperdan) in 2017-2019.

Kustas et al. 2018

Parry et al. 2019

Kustas et al. 2018

Kustas et al. 2018

Utah State Aggie Air

Kustas et al. 2018

Knipper et al. 2019

Acknowledgements

• Mimar Alsina- E&J Gallo• Martha Anderson- USDA-ARS• Jim Ayars- USDA-ARS• Felipe Barrios Masias- UC Davis• Mark Battany- UC ANR• Daniel Bosch- Constellation Brands• Arturo Calderon- UC Davis• Sean Castorani- ARS Davis• Nick Dokoozlian- E&J Gallo• Ashley Eustis- USDA-ARS• Kevin Fort- UC Davis• Bill Kustas- USDA-ARS

• Jerry Lohr- Grower Cooperator• Kyaw Tha Paw U- UC Davis• Anji Perry- J Lohr V&W• Rod Scheaffer- Constellation Brands• Tom Shapland- UC Davis• Ruby Stahel- USDA-ARS• Rick Snyder- UC Davis• Gwen Tindula- UC ANR• Yannis Toutountzis- Constellation Vlade

Tudor- Tudor Farms• Andy Walker- UC Davis• Larry Williams- UC Davis• Andrew Zaninovich- Sunview Vineyards

• Funding Sources:– J. Lohr Vineyards and Wines

– American Vineyard Foundation

– National Grape and Wine Initiative

– NIFA-Specialty Crops Research Initiative

– USDA-ARS Sustainable Vit CRIS

– GRAPEX Team and E&J Gallo