measuring consumptive use for alfalfa and grass hayfields ... · volumetric flow meter tailwater...
TRANSCRIPT
Photo: Orchard Mesa Research Center 08/04/2015
PROJECT PARTNERS
Dr. Perry Cabot │ Colorado State University
Photo: Orchard Mesa Research Center 03/28/2016
Measuring Consumptive Use for Alfalfa and Grass Hayfields Using Reflectance-Based Methods at Ground Surface
PROJECT PARTNERS
Measuring Consumptive Use for Alfalfa and Grass Hayfields Using Reflectance-Based Methods at Ground Surface
Dr. Perry Cabot │ Colorado State University
Photo: Orchard Mesa Research Center 08/06/2016Photo: Orchard Mesa Research Center 03/28/2016
Multi-Year / Multi-Site Study of Partial-Season Irrigation
Evapotranspiration Rates ?Conserved CU ?Forage Yields ?
Recovery after Stress Period ?
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 3
ECKERT, COLOMA, COIrrigated Acreage - Divisions 4, 5, 6, 7
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 4
The 1929 cut‐off is June 25, 1929, the effective date of the Boulder Canyon Project Act, which became the basis for the apportionment of the lower mainstem in Arizona v. California. The 1922 cut‐off is November 24, 1922, the date that the 1922 Compact was signed.
ECKERT, COLOMA, COWSLCU Requirement - Divisions 4, 5, 6, 7
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 5
MWH. 2012. Colorado River Water Bank Feasibility Study. Phase 1. Prepared for Colorado River Water Conservation District. 155 pp.
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 6
Grand Valley and Orchard Mesa
Uncompahgre and North Fork
Southwest
Upper Gunnison
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 7
Grand Valley and Orchard Mesa
Uncompahgre and North Fork
Southwest
Upper Gunnison
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 8
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 9
Research Outline
LOMA, COSoil Water Balance (IWB) Monitoring
Soil Water Content Reflectometers (CS655)
6”
18”
30”
Solar PanelCellular Antennae
1.5” Neutron Probe Access Tube ~ 8.0’ 1.0” Groundwater
Depth Well ~ 12.0’
Data Logger
∆ VWC = ETa (from root zone)
ET
SeametricsVolumetric Flow
Meter
Tailwater Flume with Pressure Transducer
2016 CWI Advisory Meeting │November 11, 2016 │ Denver, CO 10
Dc = Dp + ETa – P – Irr – U + SRO + DP“Actual ET”
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 11
Soil-Water Balance Monitoring (continued)
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 12
Soil-Water Balance Monitoring (continued)
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 13
Soil-Water Balance Monitoring (continued)
LOMA, CO Reference Evapotranspiration
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 14
CoAgMet collects local weather data in irrigated agricultural areas. Standardized instrumentation, dataloggers and telemetry deployed
through a network of stations. Temperature, Relative Humidity, Wind,
Solar Radiation, Precipitation ASCE evapotranspiration equation (ETr)
LOMA, COReference Evapotranspiration (continued)
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 15
http://www.coagmet.com/ over 100 stations
deployed in Colorado
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 16
Remote SensingSatellite Operating Period Revisit Sensor Band # Band Bandwidth (nm) GSD (m)
Landsat 7 Apr 1999 ‐ present 16 days ETM 12345678
BlueGreenRedNIR
SWIR‐1LWIRSWIR‐2Pan
450 – 520520 – 600630 – 690760 – 9001550 – 175010400 – 125002080 – 2350500 – 900
3030303030603015
Landsat 8 Mar 2013 ‐ present 16 days OLI 123456789
CoastalBlueGreenRedNIR
SWIR‐1SWIR‐2PanCirrus
433 – 453450 – 515525 – 600630 – 680845 – 8851560 – 16602100 – 2300500 – 6801360 – 1390
3030303030303015
Multi-Spectral Handheld Radiometer (MSR5) used to determine spectral signature of plants
MSR5 measures wavebands centered at blue (485 nm), green (560 nm), red (660 nm), near infrared (NIR, 830 nm), and short-wave infrared (SWIR, 1650 nm) similar to Landsat Thematic Mapper 5 satellite (ground-truth)
ECKERT, COLOMA, CORemote Sensing / Radiometer MeasurementsLANDSAT 7 / 8
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 17
LOMA, CO Spectral Signatures
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 18
LOMA, CO Spectral Signatures (continued)
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 19
Healthy plants are green because they contain chlorophyll. Chlorophyll absorbs light
in the red and blue regions of the visible light spectrum
Green light is not absorbed but reflected
Chlorophyll Absorption
LOMA, CO Spectral Signatures (continued)
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 20
Vegetation Index Abbrev Equation Reference
Simple Ratio SR (NIR/RED) Tucker, 1979
Normalized Difference Vegetation Index NDVI (NIR‐RED)/(NIR+RED) Tucker, 1979
Transformed Vegetation Index TVI (NDVI + 0.5)0.5 Tucker, 1979
Infrared Percentage Vegetation Index IPVI NIR/(NIR+RED) Crippen, 1990
Soil Adjusted Vegetation Index SAVI [(NIR‐RED) /(NIR+RED+L)] ×(1+L) Huete, 1988
Modified Soil Adjusted Vegetation Index MSAVI (2NIR+1‐[(2NIR+1)2‐8(NIR‐RED)]0.5)/2 Qi et al., 1994
Difference Vegetation Index DVI NIR‐RED Roujean and Breon,1995
Renormalized Difference Vegetation Index RDVI (NDVI×DVI)0.5 Roujean and Breon,1995
Optimized Soil Adjusted Vegetation Index OSAVI 1.16×(NIR‐RED)/(NIR+RED+0.16) Rondeaux et al., 1996
Green Normalized Difference Veg Index GNDVI (NIR‐GREEN)/(NIR+GREEN) Gitelson and Merzlyak, 1998
Normalized Difference Water Index NDWI (NIR‐SWIR)/(NIR+SWIR) Gao, 1996
Normalized Difference Vegetation Index
MSR5 Measurements
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 21
LOMA, CODeveloping a Spectral Signature ModelStudy Study Area Crop Type ModelNeale et al. (1989) Colorado (Fruita)
Colorado (Greeley)CornCorn
Kc = 1.092NDVI – 0.053Kc = 1.181NDVI – 0.026
Bausch et al. (1993) Colorado Corn Kcb = 1.416savi + 0.017
Singh & Irmak (2009) Nebraska CornSoybeanSorghumAlfalfa
Kc = 1.31NDVI + 0.027Kc = 1.22NDVI + 0.033Kc = 1.34NDVI – 0.056Kc = 0.981NDVI + 0.113
Johnson et al. (2012) California GarlicPepperBroccoliLettuce
Kcb = ‐0.985fc2+1.759fc+0.272Kcb = ‐0.078fc2+1.124fc+0.142Kcb = ‐0.933fc2+1.756fc+0.181Kcb = ‐0.985fc2+1.759fc+0.209
Kamble et al. (2013) NebraskaSouth Dakota
MaizeGrassSoybean
Kc = 1.457NDVI ‐ 0.1725
Vashisht (2016) Western Colorado Grass Kc = 1.195NDVI – 0.057
Alam et al. (2018) NSW, Australia Grass Kc = (1.84 ± 0.41) × NDVI2 ‐ (1.03 ± 0.48) × NDVI + (0.42 ± 0.14)Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 22
Developing a Spectral Signature Model
Reflectance‐based crop coefficient approachRequires multispectral bands, weather data
Crop ET is directly related to crop coefficients (Kc) and Vegetation Index (e.g., NDVI)
Kcr = a x NDVI +b
Radiometric Kc values have the advantages of capturing vegetation growth as affected by climate as well soil moisture stress
ETa = Kcr x ETrefWater Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 23
ET June 28, 2016 (mm)Field boundary
High : 10
Low : 0
±
Uncompahgre Valley Irrigated AcreageDelta alfalfa
Montrose grass hay
Radiometer Measurements as an additional ground truth
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 24
Kruthaupt Ranch
ET June 5, 2016 (mm)Field boundary
High : 10
Low : 0
±
Upper Gunnison Irrigated Acreage
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 25
LOMA, CODeveloping a Spectral Signature Model
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 26
ETa is obtained using Soil Water Balance ETr is obtained using ASCE Standardized Equation Using these values together, we calculate a crop coefficient (Kca) defined as the ratio of ETa and ETr (Allen et al., 1998)
Kca = ETa/Etr
By comparing Kca at equivalent times as the VI, we can evaluate a relationship between Kca and the spectral signature of the field
LOMA, CODeveloping a Spectral Signature Model
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 27
VIKCA = A × (VI) + B
A B R² RMSE MBE NSCESR 0.06 0.04 0.78 0.10 ‐0.001 0.78
NDVI 1.12 ‐0.08 0.87 0.08 0.004 0.87TVI 2.35 ‐1.85 0.86 0.08 0.007 0.86IPVI 2.30 ‐1.24 0.87 0.08 0.001 0.87SAVI 1.46 0.02 0.80 0.10 ‐0.004 0.80MSAVI 1.27 0.11 0.78 0.11 0.002 0.78DVI 2.06 0.08 0.69 0.12 0.004 0.69RDVI 1.54 ‐0.02 0.71 0.11 0.005 0.71OSAVI 1.45 ‐0.02 0.82 0.08 0.002 0.82GNDVI 1.83 ‐0.52 0.87 0.09 0.004 0.87NDWI 0.95 0.41 0.80 0.09 0.003 0.80
LOMA, CONDVI Model for grass canopy (Gautam et al., 2018)
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 28
y = 1.12x - 0.08R² = 0.87
0.00
0.20
0.40
0.60
0.80
1.00
0.00 0.20 0.40 0.60 0.80 1.00
Kca
NDVI
LOMA, CO Conclusion and General Procedure
Water Bank Workgroup│ November 2, 2018 │ Grand Junction, CO 29
Regular measurement of spectral signatures using a combination of handheld (MSR5) or satellite instrumentation (LANDSAT) spatio-temporal scales need to be considered!!
Daily recording of ETr using meterological data (CoAgMet) Use reflectance-based model to identify “canopy coefficient” Kca = 1.12 x NDVI – 0.08 (Gautam et al., 2018)
Calculate ETa (for specific field conditions on given days) ETa = 1.12 x ETr
http://eeflux-level1.appspot.com
Discussion and Conclusions
2016 CWI Advisory Meeting │November 11, 2016 │ Denver, CO 30
Kilic, A. and R. Allen (2015)METRIC‐EFFLUX ON Google Earth Engine platform: http://eeflux‐level1.appspot.com
2016 CWI Advisory Meeting │November 11, 2016 │ Denver, CO 31
Kilic, A. and R. Allen (2015)METRIC‐EFFLUX ON Google Earth Engine platform: http://eeflux‐level1.appspot.com
End