A Three-State Pecan-Almond Project: Help from Physiological Models, Remote Sensing, & Ground-Based...
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Transcript of A Three-State Pecan-Almond Project: Help from Physiological Models, Remote Sensing, & Ground-Based...
A Three-State Pecan-Almond Project: Help from Physiological Models, Remote Sensing, & Ground-Based Measurements
Vince Gutschick, Global Change Consulting Consortium, Inc.
Ted Sammis, Plant & Environmental Science, NMSU
Junming Wang, Plant & Environmental Science, NMSU
Manoj Shukla, Plant & Environmental Science, NMSU
Rolston St. Hilaire, Plant & Environmental Science, NMSU
ChallengesChallenges• Water shortages Water shortages deficit irrigation - what schedule is best? deficit irrigation - what schedule is best?• General resource management, including N General resource management, including N
Crafting plans and management tools• Optimal deficit irrigation – guidance from models <-> experiments
• Develop monitoring, particularly ET - large areas, near-real time
• Validate monitoring methods
• Develop simple management plan – distill the knowledge
• Validate the management plan
• Deliver practical tools
NMSU part:• Focus on pecans
• Development of framework applicable to other nut crops
Optimal deficit irrigation
• Maximal retention of yield and yield capacity
• Zillion risky expts.? No. Use models:
• To develop hypotheses
• Then to guide experimental design and interpretation
• Monitoring – cover large areas, in near-real time
• Satellite estimates of ET by energy balance
• Validate monitoring
• Eddy covariance, SWB, and physiological stress measures (optical…)
First three elements
• Develop a simple management plan
• Distill the response of yield to fraction of normal
water use (ET) – that is, yield as Y(E/E0)
• Validate optimal management results
• Deliver practical tools
• Monitoring of stress indicators, not just end yield
• Using simple, mostly automated tools
• Simpler is better - experience of DSSs, and
even simpler tools (nomograms,…)
• Novel satellite estimates of ET in near-real time
• Easily obtained ground data
Three more elements
Highlight: satellite estimates of ET by energy balance - a large-scale, rapid tool for monitoring stress and water use
• Modification of Surface Energy Balance Land (SEBAL) RSET
• Key problem avoided: low accuracy of surface temperature
• Including atmospheric effects, view angle (air mass) effects
• Remaining difficulty – disparity of aerodynamic resistance for
soil & canopy(2 sources)
• Some clues for future
• Even “as is” -for ag areas with good cover, not a big problem
• Automation a challenge
• Finding and processing scenes
• Locating hot and cold spots
• Including correction for differences in elevation, θ (VPT)
Overall scheme for using Overall scheme for using • satellite, • weather, and • ground data • satellite, • weather, and • ground data
Comparison of measured and Comparison of measured and remote sensing calculated ET remote sensing calculated ET
for a Pecan orchard at Las for a Pecan orchard at Las Cruces, NM. Cruces, NM.
0123456789
02/1
3/02
05/2
4/02
09/0
1/02
12/1
0/02
03/2
0/03
06/2
8/03
10/0
6/03
01/1
4/04
04/2
3/04
Time (day)
ET
(m
m/d
ay)
ObservationModel
Highlight: modelling plant responses to stress, for yield optimization
Where do we want to end up?
Whole-season water use and yield
Leafout (canopy leaf area, as a function of E/E0)
Nutfill (canopy photosynthesis, as a function of E/E0
Concurrent information: PS partitioning, leaf N dynamics
What we do know?
• What have physiological models given us over the years?
Decision support systems Erect leaf varieties ……
• Great detail needed in models great body of knowledge
• E.g., Ball-Berry, Farquhar et al., micromet, light interception… interception, LA phenology, Vcmax(stress), gs(stress - Tardieu…)
• Specific to pecans
• Our previous models
• Gas-exchange and stress data of David Johnson
What we don't know well enough & therefore need to measure
1. Seasonal patterns of stomatal control and WUE
What’s the unstressed Ball-Berry slope?
Does it really double from pre-monsoon to monsoon?
Evidence: gain in water-use rates
(Basis in ecology under natural conditions?)
26 June 03 Leyendecker
gs = 5.6296 IBB + 0.0182
R2 = 0.8668
0
0.05
0.1
0.15
0.2
0.25
-0.005 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035
IBB
gs
23 Aug 03 Leyendecker
gs = 11.74 IBB - 0.031
R2 = 0.8977
0
0.05
0.1
0.15
0.2
0.25
0.3
0 0.005 0.01 0.015 0.02 0.025 0.03
IBB
gs
Changing mBB; bBB=0.02
0
0.5
1
1.5
2
0 0.2 0.4 0.6 0.8 1
E/E0
WU
E/W
UE
0 28/0.3/1000
20/0.3/1000
28/0.5/1000
28/0.3/600
Change mBB; b=0.005
0
20
40
60
80
100
0 2 4 6 8 10
mBB
E/E
0
28/0.3/1000
20/0.3/1000
28/0.5/1000
28/0.3/600
How does the Ball-Berry slope respond to root or leaf water potential?
How much do we need to cut it to reduce E to 0.5 E0?
How does WUE change under stress?
2. Seasonal patterns of photosynthetic capacity (Vc,max25)
and relation to leaf N content (linear? intercept = ??)
Optimality
Distill the more detailed physiological and developmental
models of:
• Leaf area development – to a simple function of fraction of
unstressed ET (E/E0)
Basically, reset leaf area to a smaller fraction of normal,
reducing future ET demand
• Canopy photosynthesis – to a similarly simple function of E/E0)
See a gain in water-use efficiency that makes the cut in
season-total photosynthesis less than the cut in water use
• Find the combination of cuts in E/E0 in both stages that
leaves the greatest nut yield, for a given total water use
(a numerical solution)
Data needs for studies of stress responses and optimization
- under several stress levels (treatments and interplant/
microsite variation)
• Leaf gas exchange
• To eludicate the stomatal control program
• Aerial environment (2 fundamental parameters)
• Water stress (3rd fundamental parameter)
• To estimate photosynthetic capacity (Vc,max25) and its
relation to leaf N and light integral on the leaf
Concurrent measurements of leaf N and PAR levels
Determining seasonal trends in both
• Water stress quantification – soil water balance and
soil moisture release curve
• Measurements of growth, carbohydrate reserves, and nut yield