Transcript Irrigation Scheduling and Soil Moisture Monitoring Steve A. Miller Biosystems and Agricultural Engineering Michigan State University [email protected] http://www.egr.msu.edu/bae/water/

Irrigation Scheduling and
Soil Moisture Monitoring
Steve A. Miller
Biosystems and Agricultural Engineering
Michigan State University
[email protected]
http://www.egr.msu.edu/bae/water/
Irrigation Scheduling
• Process of maintaining an optimum water
balance in the soil profile for crop growth and
production
• Irrigation decisions are based on an
accounting method on the water content in
the soil
Why Use Irrigation Scheduling?
• Prevent stress – health of plant; yield loss;
appearance
• Maximize water use efficiency – beneficial
use of resource
• Minimize leaching of nitrates or pesticides
http://www.miwwat.org/
Right to Farm GAAMPs
Irrigation Scheduling
• Irrigation scheduling for each unit or field is an
integral part of GAAMPs
• Irrigation scheduling is the process of
determining when it is necessary to irrigate
and how much water to apply
• Information from Record Keeping GAAMPs
can be inputs to irrigation scheduling
Irrigation Scheduling
Components
– Plant Growth and Water Use
– Soil Water Holding Capacity
– Rainfall / Irrigation
– RECORDKEEPING
Plant Growth and Water Use
Fundamentally crops use water to facilitate cell
growth, maintain turgor pressure, and for cooling.
Crop water use is driven by the evaporative demand
of the atmosphere.
Optimum crop growth and health occurs when the
soil moisture content is held between 50 – 80% of
the “plant available water”
http://www.egr.msu.edu/bae/water/
Irrigation Scheduling -- Primary Factors
(Irrigation GAAMPs)
• Know available soil water for each unit depth of soil
• Know depth of rooting for each crop
• Know allowable soil moisture depletion at each stage of
plant growth
• Use evapotranspiration data to estimate crop water use
• Measure rainfall in each field
• Know water retention and container capacity (volume)
used for nursery crops
Available Soil Water
• Soil absorbs and holds water in much the same way as a
sponge.
• A given texture and volume of soil will hold a given
amount of moisture.
• The intake rate of the soil will influence the rate at which
water can be applied.
• The ability of soil to hold moisture, and amount of
moisture it can hold, will greatly affect the irrigation
operational schedule
Soil Moisture
• Hygroscopic water is moisture that is held too tightly
in the soil to be used by plants.
• Capillary water is moisture that is held in the pore
spaces of the soil and can be used by plants.
• Gravitational water drains rapidly from the soil and
is not readily available to be used by plants.
Soil moisture
• The permanent wilting point represents the boundary
between capillary water and hygroscopic water.
• Because hygroscopic water is not usable by plants,
continuous soil moisture levels below the permanent
wilting point will result in damage to or death of the
plants.
• Field capacity represents the boundary between
gravitational water and capillary water. It is the upper
limit for soil moisture that is usable by plants.
1) Note that wilting coefficient
increases as texture
becomes finer.
2) Field capacity θv increases
as texture becomes finer
until silt loams, then
levels off.
3) Greatest plant-available
H2O capacity (PAWC) occurs
with medium- rather than
fine-textured soils.
Figure 5.25 General relationship between soil water characteristics and soil texture. Remember these are
representative curves & individual soils will likely have values different from those shown. (Brady and Weil, 2004, p. 157)
Importance of surface area/mass is
shown by the fact that it takes:
>85% sand to be a sand soil
>80% silt to be a silt soil, but only
~40% clay to be a clay soil
100%
90
80
Generally, the best soils for arable
crops are those that contain:
70
Clay (C)
10-20% clay
3% organic matter
equal % of sand & silt
60
50
40
30
Sandy
Clay (SC)
Clay Loam (CL)
Sandy Clay
Loam (SCL)
20
Sandy
Loam (SL)
10
Sand
(S)
Silty
Clay (SIC)
Loam
(L)
Loamy
Sand (LS)
Silty Clay
Loam (SICL)
Silt Loam
(SIL)
Silt
(SI)
Percent Sand
Figure 3.2 The textural triangle used to classify soil. (Scott, 2000, p. 39)
Plant Water Needs
• The amount of water a plant requires includes the water
lost by evaporation into the atmosphere from the soil
and the transpiration, which is the amount of water used
by the plant.
• The combination of these is evapotranspiration (ET).
Reference Evapotranspiration
• ETo, or potential evapotanspiration, represents a well
watered, fully developed plant such as grass
• Reference evapotranspiration is multiplied by a crop
coefficient to obtain the ET rate for a specific crop
• The crop coefficient varies throughout the growing
season
Estimates of ET
•
•
•
•
•
•
“Max” and “min” temperatures
Relative humidity
Wind
Net radiation
Modified Penman to estimate ETo
Enviro-weather
www.enviroweather.msu.edu/
For Annual Crops
• Depth of root zone increases during the growing season
• Allowable soil moisture depletion varies with each stage
of plant growth
Depth of Rooting
CORN
2.5 to 4 feet
POTATOES
1.5 to 2 feet
SOYBEANS
1.5 to 2 feet
DRYBEANS
1 to 2 feet
TURFGRASS
0.5 to 1.5 feet
Ref. Vitosh, Irrigation Guide, CES, MSU
Rainfall Measurement
• Measure in each field
• Should be read each day that a rain event occurs
• Record the time when the reading is taken – should
be consistent
• Keep Clean
• Install away from obstructions
• Basic gauges must not be allowed to freeze
• http://www.enviro-weather.msu.edu/
Rain Gauges
• Basic unit – 2 inch opening
• Cost -- less than $10.00 ea
• 1-800-647-5368
• http://www.forestrysuppliers.com/product_pages/vie
w_catalog_page.asp?id=5479
Estimating ET for Different Crops
• Combining a “Crop Coefficient Curve” with the
reference ET.
• Crop Curve is a relationship between the
specific plants’ growth characteristics and its
water use relationship to the reference crop.
Crop Curve
http://enviroweather.msu.edu/
Checkbook Register
Minnesota Data
Michigan Data
Max
Temp
50 - 59
60 - 69
70 - 79
80 - 89
90 +
Eto
0.07
0.12
0.15
0.17
0.21
1
2
3
4
5
6
7
0.25
0.02
0.03
0.04
0.04
0.05
0.25
0.02
0.03
0.04
0.04
0.05
0.25
0.02
0.03
0.04
0.04
0.05
0.38
0.03
0.05
0.06
0.06
0.08
0.57
0.04
0.07
0.09
0.10
0.12
0.75
0.05
0.09
0.11
0.13
0.16
0.94
0.07
0.11
0.14
0.16
0.20
Weeks from Emergence
8
9
10
11
1.12
0.08
0.13
0.17
0.19
0.24
1.2
0.08
0.14
0.18
0.20
0.25
1.2
0.08
0.14
0.18
0.20
0.25
1.2
0.08
0.14
0.18
0.20
0.25
12
13
14
15
16
17
1.2
0.08
0.14
0.18
0.20
0.25
1.1
0.08
0.13
0.17
0.19
0.23
0.86
0.06
0.10
0.13
0.15
0.18
0.62
0.04
0.07
0.09
0.11
0.13
0.41
0.03
0.05
0.06
0.07
0.09
0.63
0.04
0.08
0.09
0.11
0.13
www.agry.purdue.edu/irrigation/IrrDown.htm
Relative diameters of a 0.002 mm clay particle, a 0.02 mm
silt particle, and a 0.15 mm fine sand grain enlarged 1000 times.
Slide from Lee Jacobs
1) Note that wilting coefficient
increases as texture
becomes finer.
2) Field capacity θv increases
as texture becomes finer
until silt loams, then
levels off.
3) Greatest plant-available
H2O capacity (PAWC) occurs
with medium- rather than
fine-textured soils.
Figure 5.25 General relationship between soil water characteristics and soil texture. Remember these are representative
curves & individual soils will likely have values different from those shown. (Brady and Weil, 2004, p. 157)
http://websoilsurvey.nrcs.usda.gov/app/
Resistance
Slide from Ron Goldy
Tensiometers and Watermarks
http://www.specmeters.com/Soil_Moisture/
Granular Matrix Sensor – Watermark Block
Time Domain
Reflectometry
Time domain reflectometry. The speed of an electromagnetic signal
passing through a material varies with the dielectric of the material.
http://www.campbellsci.com.au/hydrosense
Time Domain Reflectometry (TDR)
Decatur Table 3 2013 6-1-2013 to 9-30-2013
0.2
V
o
l 0.18
u
m
e 0.16
m
e
0.14
t
r
i
0.12
c
2
VW1
1.8
VW2
Rainfall and Irrigation
1.6
1.4
1.2
%
W 0.1
a
t
e 0.08
r
1
0.8
0.06
C
o
n 0.04
t
e
n 0.02
t
0.6
0
5/31/2013 0:00
0
0.4
0.2
6/20/2013 0:00
7/10/2013 0:00
7/30/2013 0:00
8/19/2013 0:00
9/8/2013 0:00
9/28/2013 0:00
June 19 2013 to September 30 2013 – Potatoes
Sandy Soils
Data from Dr. Goldy
John Deere Connect 2013 – Sandy Loam - Sum
Frequency Domain Reflectometry (FDR)
John Deere Connect 2013 – Fine Sand
Frequency Domain Reflectometry (FDR)
Water Patterns by Treatment
Slide from N.L. Rothwell, NWMHRS
1 GPH Emitter
X
X = tree
X
Microsprinklers
X
X
6”
18”
30”
Double RAM
Single RAM
X
X
X
6”
18”
30”
X
Questions and Discussions