ET-Demands

Table of Contents:

Introduction

The ET-Demands model…

Acknowledgements

The basis for the ET Demands model is the dual crop coefficient method presented in FAO-56 (Allen et al., 1998). Original model code was developed by …

Model History

This methods used in this model were used to evaluate evapotranspiration and consumptive use irrigation water requirements for the state of Idaho (Allen and Robison, 2007) and the state of Nevada (Huntington and Allen, 2010). This approach has been used to quantify historical and future irrigation water requirements for selected irrigation projects operated by the Bureau of Reclamation (Reclamation, 2016). This approach has also been used to quantify historical and future irrigation water requirements in support of Reclamation’s WaterSMART Basin Studies Program.

Model Version History

v0.1.0

Initial model release

Model License

The software as originally published constitutes a work of the United States Government and is not subject to domestic copyright protection under 17 U.S.C. § 105. Subsequent contributions by members of the public, however, retain their original copyright.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Quick Start

Installing the Model

Model

Required Dependencies

Downloading Examples

Running Examples

Model Overview

Getting Started

Installation

Dependencies

Python

GDAL

Creating a Python Environment

Model Inputs

Model Control Files

Model Structure

Running the Model

Model Calibration

RefET

Thornton and Running Coefficients

CropET

Model Inputs

RefET

The RefET module calculates hourly or daily reference ET from meteorological data using the approach described in ASCE-NWRI (2005). If needed, the module will estimate solar radiation and dew point temperature, and gap fill meteorological data.

Meteorology Metadata

Meteorology Data

The RefET module requires hourly or daily meteorological data. If the calculated reference ET will be used in the CropET module, care should be taken to ensure this meteorological data is representative of agricultural conditions. Meteorological data can be obtained from agricultural weather networks, or adjustments reference ET can be made within the CropET module.

Timeseries Data

Daily Variables

• Date [in YYYY-MM-DD format]
• T_max = maximum daily air temperature
• T_min = minimum daily air temperature
• T_d = mean daily dew point temperature^a
• e_a = actual vapor pressure^a
• u_x = mean daily wind speed at known height^b
• R_n = calculated net radiation at the crop surface^c
• P_r = daily precipitation (optional)
• Q = specific humidity (optional)
• S_n = daily accumulated snow (optional)
• S_d = snow depth (optional)

^a One of these is required. If both T_d and e_a are not provided, mean monthly dew point depression, K₀, must be provided.

^b Wind measurement height in meters must be provided in the ini file.

^c If R_n is not provided it will be estimated using the approach described in Thornton and Running (1998). The three Thornton and Running coefficients must be provided in the ini file.

Hourly Variables

• Date [in YYYY-MM-DD HH:MM format]
• T_mean = mean hourly air temperature
• T_d = mean hourly dew point temperature^a
• u_x = mean hourly wind speed at known height^b
• R_n = calculated net radiation at the crop surface^c
• P_r = hourly precipitation (optional)
• Q = specific humidity (optional)
• S_n = hourly accumulated snow (optional)
• S_d = snow depth (optional)

^a One of these is required. If both T_d and e_a are not provided, mean monthly dew point depression, K₀, must be provided.

^b Wind measurement height in meters must be provided in the ini file.

^c If R_n is not provided it will be estimated using the approach described in Thornton and Running (1998). The three Thornton and Running coefficients must be provided in the ini file.

# HOW IS THE SNOW OR SNOW DEPTH USED?

File Format

RefET requires the timeseries weather data to be in delimited columns with header of column names. Column names and units are specified in the ini file. Files are allowed to have header rows, with the number of header rows specified in the ini file. The delimiter is also specified in the INI file.

Delimiter	Model Notation
Comma	,
Tab	/t

• Format: .csv, .txt, .dat
• File Name: (DESCRIBE WILDCARDS)
• Structure:

Date	Tmax	Tmin	ux	Rn	Tdew
2017-10-01	9.34	3.70	3.95	120.93	3.21
2017-10-02	5.52	-2.12	7.54	59.10	-3.18
…	…	…	…	…	…

• Units

Class	Variables	Units	Model Notation
Temperature	Tmax, Tmin, Td	°C °F °K	c f k
Wind Speed	ux	m s-1 m d-1 mi d-1	m/s, mps m/d, m/day miles/d, miles/day, mpd
Solar Radiation	Rn	MJ m-2 d-1 W m-2 d-1 cal cm-2 d-1 langley	mj/m2, mj/m^2, mj/m2/d, mj/m^2/d, mj/m2/day, mj/m^2/day w/m2, w/m^2 cal/cm2’, cal/cm2, cal/cm2/d, cal/cm^2/d, cal/cm2/day, cal/cm^2/day langley
Precipitation	Pr	in d-1 mm d-1	in/d, in/day, inches/d, inches/day mm/d, mm/day
Humidity	Q	kg kg-1	kg/kg
Vapor Pressure	ea	kPa	kPa
Snow	Sn	in d-1 mm d-1	in/d, in/day, inches/d, inches/day mm/d, mm/day
Snow Depth	Sg	in mm	in, inches, in*100 mm

Mean Monthly Data

Mean monthly data are used to calculate a dew point temperature timeseries or gap fill the timeseries data if needed.

• T_max = mean monthly maximum daily air temperature
• T_min = mean monthly minimum daily air temperature
• u_x = mean monthly wind speed at known height
• K₀ = mean monthly dew point depression

File Format

• Delimiter:

See Timeseries Data - Delimiter

• Format: .csv, .txt, .dat
• Structure:

Met Node ID	Met Node Name	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
BFAM	Blackfeet, MT	2.6	3.0	7.3	11.6	16.8	21.5	28.3	23.5	17.9	13.6	7.3	1.7

T:sub:`max` example shown. File structure will be the same for T_min, u_x, and K₀. Individual files are provided for each variable.

• Units

See Timeseries Data - Units

Ancillary Data

• Thornton and Running Coefficients * TR_b0 * TR_b1 * TR_b2

Thornton and Running coefficients are used to estimate solar radiation from meteorological data. These coefficients are location-specific and should be calibrated using measured solar radiation data from a representative location. The calibration approach is described in detail here

• Wind Measurement Height (in meters)

CropET

Weather Data

Timeseries Data

The user must provide daily weather and reference ET data for each ET zone. This includes:

• Date [in YYYY-MM-DD format]
• T_max = maximum daily air temperature
• T_min = minimum daily air temperature
• T_d = mean daily dew point temperature^a
• u_x = mean daily or hourly wind speed at known height^b
• R_n = calculated net radiation at the crop surface^c
• Q = specific humidity (optional)
• S_n = daily accumulated snow (optional)
• S_d = snow depth (optional)

and one of two reference ET values:

• ASCEr - Daily reference ET from Penman–Monteith
• ASCEg - Daily reference ET from Penman–Monteith

File Format

• Format: .csv
• Structure:

Date	TMax	TMin	Precip	Snow	SDep	EstRs	EsWind	EsTDew	ETRef [ASCEr; ASCEg]
Units	[C]	[C]	[In]	[In]	[In]	[MJ/m2]	[m/s]	[C]	[mm/day]

Location Shapefile

A shapefile containing the locations of each weather station is also required and is used to generate the static input files. The shapefile must contain the following attributes:

• STATION_ID - Weather station ID
• ETZONE_ID - Zone ID. This can include HUC8, HUC10, COUNTRYNAME, OR GRIDMET_ID
• LAT - Weather station latitude
• LON - Weather station longitude
• [optional] ELEV [ELEV_FT; ELEV_M] - Weather station elevation in feet or meters. This field is optional and only required if running the RefET model to estimate reference ET.

File Format

• Format: .shp
• Attribute Table Structure:

STATION_ID

ZONE_ID [HUC8; HUC10; COUNTRYNAME; GRIDMET_ID]

LAT

LON

ELEV [ELEV_FT; ELEV_M]

Study Area

The user must provide a study area polygon shapefile with at least one feature. Each feature in the study area shapefile will become a separate ET cell/unit. Currently, only HUC8, HUC10, county, and gridmet cell shapefiles are fully supported by the prep tools.

Soils Data

Crop Type Data

Static Inputs

These files will be generated automatically by the CropETPrep module

CropCoefs

Crop coefficient curves for each crop. Generally, these values should not be modified. DESCRIBE CROP COEFFICIENTS -

CropParams

Crop parameters that can/should be modified during calibration.

• Format: .txt
• Structure:

ETCellsCrops

Flags controlling which crops to simulate. If using the prep workflow, the flags will initially be set based on the CDL acreage.

• Format: .txt
• Structure:

EToRatiosMon

Reference ET scale factors by month for each ET cell. This file could be used to account for a seasonal bias in the input weather data. This file is optional.

• Format: .txt
• Structure:

ETCellsProperties

Soil properties and weather station data for each ET cell. This file links the stations and the ET cells.

• Format: .txt
• Structure:

MeanCuttings

Sets the assumed number of alfalfa cuttings. This is important since the CropET module will use different crop coefficient curves for the first and last cutting.

• Format: .txt
• Structure:

Model Outputs

RefET

CropETPrep

CropET

AreaET

PostProcessing

Running the Model

RefET

CropETPrep

CropET

AreaET

PostProcessing

Model Description

The ET-Demands package

RefET

Reference evapotranspiration is calculated according to the ASCE Standardized Reference Evapotranspiration Equation (ASCE-EWRI, 2005).

Gap Filling and QA/QC

Missing Data

Missing values of maximum air temperature (T_max), minimum air temperature (T_min), and mean wind speed (u_x), up to six timesteps, are first filled through linear interpolation. Additional missing values not handled by the linear interpolation are filled using mean monthly values. Missing values of precipitation (P_r), snow, (S_n), and snow depth (S_d) are set to 0.

Maximum and Minimum Air Temperature

Maximum air temperature (T_max) values greater than 120°F are set to 120°F. Minimum air temperature (T_min) values greater than 90°F are set to 90°F. Maximum air temperature is checked against minimum air temperature at every time step. If minimum air temperature is greater than maximum air temperature, maximum air temperature is set to minimum air temperature.

ASCE Standardized Reference Evapotranspiration Equation

Daily Reference Evapotranspiration

where:

ET_sz = standardized reference crop evapotranspiration for short ET_os or tall ET_rs surfaces [mm d^-1 for daily time steps or mm h^-1 for hourly time steps]

R_n = calculated net radiation at the crop surface [MM m^-2 d^-1 for daily time steps or MM m^-2 h^-1 for hourly time steps]

G = soil heat flux density at the soil surface [MM m^-2 d^-1 for daily time steps or MM m^-2 h^-1 for hourly time steps]

T_mean = mean daily or hourly air temperature at 1.5 to 2.5-m height [°C]

u₂ = mean daily or hourly wind speed at 2-m height [m s^-1]

e_s = saturation vapor pressure at 1.5 to 2.5-m height [kPa]

e_a = mean actual vapor pressure at 1.5 to 2.5-m height [kPa]

Δ = slope of the saturation vapor pressure-temperature curve [kPa °C^-1]

γ = psychrometric constant [kPa °C^-1]

C_n = numerator constant that changes with reference type and calculation time step [K mm s³ Mg_-1 d^-1 for daily time steps or K mm s³ Mg_-1 h^-1 for hourly time steps]

C_d = denominator constant that changes with reference type and calculation time step [s m^-1]

For a grass reference surface (ET_o),

C_n = 900

C_d = 0.34

For an alfalfa reference surface (ET_r),

C_n = 1600

C_d = 0.38

As soil heat flux density is positive when the soil is warming and negative when the soil is cooling, over a day period it is relatively small compared to daily R_n. For daily calculations it is ignored,

G = 0

Hourly Reference Evapotranspiration

The equation for ET_sz is the same as daily, with

For a grass reference surface (ET_o),

C_n = 37.0

At night, when R_n < 0,

C_d = 0.96

G = 0.5

For an alfalfa reference surface (ET_r),

C_n = 66.0

At night, when R_n < 0,

C_d = 1.7

G = 0.2

# UNIT CONVERSION

Mean Air Temperature (T_mean)

ASCE-EWRI (2005) advises to use the mean of daily minimum and daily maximum temperature to calculate mean daily temperature as opposed to the mean of hourly temperatures.

where:

T_mean = mean daily air temperature [°C]

T_max = maximum daily air temperature [°C]

T_min = minimum daily air temperature [°C]

Ultimately, the ET_sz equation requires actual vapor pressure (e_a). This can be calculated from dew point temperature (T_d), specific humidity (q), or relative humidity (RH). If needed, dew point temperature can be calculated from minimum air temperature (T_min) and mean monthly dew point depression values (K₀).

Dew Point Temperature

where:

T_d = mean hourly or daily dew point temperature [°C]

T_min = mean hourly or daily minimum daily air temperature [°C]

K₀ = mean monthly dew point depression [°C]

Actual Vapor Pressure (e_a) from Dew Point Temperature (T_d)

where:

e_a = actual vapor pressure [kPa]

T_d = mean hourly or daily dew point temperature [°C]

# CALCULATE ACTUAL VAPOR PRESSURE FROM RELATIVE HUMIDITY

Actual Vapor Pressure (e_a) from Relative Humidity (RH)

where:

e_a = actual vapor pressure [kPa]

RH = relative humidity [%]

e_s = saturation vapor pressure [kPa]

Actual Vapor Pressure (e_a) from Specific Humidity (q)

where:

e_a = actual vapor pressure [kPa]

q = specific humidity [kg/kg]

P = mean atmospheric pressure at station elevation [kPa]

Atmospheric Pressure (P)

where:

P = mean atmospheric pressure at station elevation [kPa]

z = station elevation above mean sea level [m]

This equation differs slightly from ASCE 2005 as it reflects full precision per Dr. Allen (pers. comm.).

Psychrometric Constant (γ)

where:

γ = psychrometric constant [kPa °C^-1]

P = mean atmospheric pressure at station elevation [kPa]

Slope of the Saturation Vapor Pressure-Temperature Curve (Δ)

where:

Δ = slope of the saturation vapor pressure-temperature curve (kPa °C^-1]

T_mean = mean daily air temperature [°C]

Saturation Vapor Pressure (e_s)

where:

e_s = saturation vapor pressure

Tetens (1930)

Vapor Pressure Deficit (VPD)

where:

VPD = vapor pressure deficit [kPa]

e_s = saturation vapor pressure [kPa]

e_a = actual vapor pressure [kPa]

Extraterrestrial Radiation (R_a)

The calculations for hourly and daily extraterrestrial radiation (R_a) differ slightly as the hourly calculations require hourly solar time angles (ω) in addition to the sunset hour angle (ω_s) while the daily calculations just require the sunset hour angle.

Hourly and daily calculations require solar declination (δ), sunset hour angle (ω_s), and inverse square of the earth-sun distance (d_r).

Solar Declination (δ)

where:

δ = solar declination [radians]

DOY = day of year

Sunset Hour Angle (ω_s)

where:

ω_s = sunset hour angle [radians]

lat = Latitude [radians]

δ = solar declination [radians]

To calcuate the inverse quare of the earth-sun distance, the day-of-year fraction (DOY_frac) is needed

Day-of-Year Fraction (DOY_frac)

where:

DOY_frac = day-of-year fraction

DOY = day-of-year

Inverse Square of the Earth-Sun Distance (d_r)

where:

d_r = inverse square of the earth-sun distance [d^-2]

ω_s = sunset hour angle [radians]

lat = Latitude [radians]

δ = solar declination [radians]

Daily Extraterrestrial Radiation

where:

ω_s = sunset hour angle [radians]

lat = Latitude [radians]

R_a = daily extraterrestrial radiation [MJ m^-2 d^-1]

δ = solar declination [radians]

d_r = inverse square of the earth-sun distance [d^-2]

Hourly Extraterrestrial Radiation

Hourly calculations also require the calculation hourly solar time angles (ω), which requires the calculation of solar time (t_s).

Seasonal Correction (sc)

where:

sc = seasonal correction [hours]

DOY = day-of-year

Solar Time (t:sub:`s`)

where:

t_s = solar time (i.e. noon is 0) [hours]

lon = Longitude [radians]

t = UTC time at the midpoint of the period [hours]

sc = seasonal correction [hours]

Solar Time Angle (ω)

where:

ω = solar hour angle [radians]

t_s = solar time (i.e. noon is 0) [hours]

Hourly Extraterrestrial Radiation

Checks on ω₁ and ω₂

where: ω₁ = solar time angle at the beginning of the period [radians]

ω₂ = solar time angle at the end of the period [radians]

ω = solar hour angle [radians]

t = UTC time at the midpoint of the period [hours]

ω_s = sunset hour angle [radians]

lat = Latitude [radians]

δ = solar declination [radians]

R_a = hourly extraterrestrial radiation [MJ m^-2 h^-1]

d_r = inverse square of the earth-sun distance [d^-2]

Clear-Sky Radiation (R_so)

Sin of the Angle of the Sun above the Horizon (sin:sub:`β24`)

where:

sin:sub:`β24`= sine of the angle of the sun above the horizon [radians]

lat = Latitude [radians]

DOY_frac = day-of-year fraction

Precipitable Water (w)

where:

w = precipitable water [mm]

P = mean atmospheric pressure at station elevation [kPa]

e_a = actual vapor pressure [kPa]

Clearness Index for Direct Beam Radiation (k:sub:`b`)

where:

k_b = clearness index for direct beam radiation

P = mean atmospheric pressure at station elevation [kPa]

sin:sub:`β24`= sine of the angle of the sun above the horizon [radians]

w = precipitable water [mm]

Transmissivity Index for Diffuse Radiation (k:sub:`d`)

where:

k_d = transmissivity index for diffuse radiation

k_b = clearness index for direct beam radiation

Daily Clear-Sky Radiation

where:

R_so = daily clear-sky radiation [MJ m^-2 d^-1]

R_a = daily extraterrestrial radiation [MJ m^-2 d^-1]

k_b = clearness index for direct beam radiation

k_d = transmissivity index for diffuse radiation

Hourly Clear-Sky Radiation

Several calculations, including the sin of the angle of the sun above the horizon (sin_β) and the clearness index for direct beam radiation (k_b) change when calculating hourly clear-sky radiation.

Sin of the Angle of the Sun above the Horizon (sin:sub:`β`)

where:

sin:sub:`β`= sine of the angle of the sun above the horizon [radians]

sin_{β,c`= sin:sub:`β} limited to 0.01 so that k_b does not go undefined

lat = Latitude [radians]

δ = solar declination [radians]

ω = solar hour angle [radians]

Clearness Index for Direct Beam Radiation (k:sub:`b`)

where:

k_t = atmospheric turbidity coefficient

k_b = clearness index for direct beam radiation

P = mean atmospheric pressure at station elevation [kPa]

sin:sub:`β,c`= sine of the angle of the sun above the horizon, limited to 0.01 [radians]

w = precipitable water [mm]

Transmissivity Index for Diffuse Radiation (k:sub:`d`)

where:

k_d = transmissivity index for diffuse radiation

k_b = clearness index for direct beam radiation

Hourly Clear-Sky Radiation

where:

R_so = hourly clear-sky radiation [MJ m^-2 h^-1]

R_a = hourly extraterrestrial radiation [MJ m^-2 h^-1]

k_b = clearness index for direct beam radiation

k_d = transmissivity index for diffuse radiation

Cloudiness Fraction (fcd)

Daily Cloudiness Fraction

where:

fcd = daily cloudiness fraction

R_s = measured solar radiation [MJ m^-2 d^-1]

R_so = clear sky solar radiation [MJ m^-2 d^-1]

R_s / R_so is limited to 0.3 < R_s / R_so ≤ 1.0

Hourly Cloudiness Fraction

At low sun angles (β), cloudiness fraction (fcd) is set to 1.

where:

β = angle of the sun above the horizon [radians]

lat = Latitude [radians]

δ = solar declination [radians]

ω = solar hour angle [radians]

fcd = hourly cloudiness fraction

R_s = measured solar radiation [MJ m^-2 h^-1]

R_so = clear sky solar radiation [MJ m^-2 h^-1]

Net Longwave Radiation (R_nl)

Daily Net Longwave Radiation

where:

R_nl = daily net longwave radiation [MJ m^-2 d^-1]

fcd = daily cloudiness fraction

e_a = actual vapor pressure [kPa]

T_max = maximum daily air temperature [°C]

T_min = minimum daily air temperature [°C]

Hourly Net Longwave Radiation

where:

R_nl = hourly net longwave radiation [MJ m^-2 h^-1]

fcd = daily cloudiness fraction

e_a = actual vapor pressure [kPa]

T_mean = mean hourly air temperature [°C]

Net Radiation (R_n)

Daily Net Radiation

where:

R_n = daily net radiation [MJ m^-2 d^-1]

R_nl = daily net longwave radiation [MJ m^-2 d^-1]

R_s = measured solar radiation [MJ m^-2 d^-1]

Hourly Net Radiation

where:

R_n = hourly net radiation [MJ m^-2 h^-1]

R_nl = hourly net longwave radiation [MJ m^-2 h^-1]

R_s = measured solar radiation [MJ m^-2 h^-1]

Windspeed Adjustment

The standardized reference crop evapotranspiration equation assumes a 2-m height windspeed. Windspeed measured at different heights can be approximated as

where:

u₂ = wind speed at 2 m above ground surface [m s^-1]

u_z = measured wind speed at z_w m above ground surface [m s^-1]

z_w = height of wind measurement about ground surface [m]

## CACLULATE MIN AND MAX MONTHLY MEAN TEMPERATURES

Thornton and Running Solar Radiation Estimate

If measured solar radiation (R_s) is not provided, it can be estimated using the approach described in Thorton and Running (1999). This approach requires three calibrated coefficients [LINK TO PAGE ON HOW TO DO THIS].

System Message: WARNING/2 (T_{diff} = T_{max} - T_{min} T_{mon,diff} = T_{mon,max} - T_{mon,min} B_{TR} = TR_{b0} + TR_{b1} \cdot \exp{(TR_{b2} \cdot{T_{mon,diff}}) R_{s} = R_{so} \cdot (1 - 0.9 \exp{(-B_{TR} \cdot T_{diff}^{1.5})}))

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where:

T_diff = temperature difference [°C]

T_max = maximum daily air temperature [°C]

T_min = minimum daily air temperature [°C]

T_mon,diff = mean monthly temperature difference [°C]

T_mon,max = mean monthly maximum air temperature [°C]

T_mon,min = mean monthly minimum air temperature [°C]

TR_b0 = Thornton and Running b₀ coefficient

TR_b1 = Thornton and Running b₁ coefficient

TR_b2 = Thornton and Running b₂ coefficient

B_TR = Thorton and Running parameter

R_s = calculated solar radiation [MJ m^-2 d^-1]

R_so = clear sky solar radiation [MJ m^-2 d^-1]

For arid stations, [REFERENCE FOR THESE COEFFICIENTS]

TR_b0 = 0.023

TR_b1 = 0.1

TR_b2 = 0.2

[DISCUSSION OF THESE PARAMETERS, AND HOW TO GET THEM]

Other Potential ET Estimates

The RefET module code can also calculate potential evapotranspiration using several different approaches. This provides a comparison with reference ET.

Latent Heat of Vaporization (λ)

The latent heat of vaporization is calculated from mean air temperature. This differs from ASCE-EWRI (2005) which advises to use a constant value of 2.45 MJ kg^-1 as it varies only slightly over the ranges of air temperature that occur in agricultural or hydrologic systems. The equation used is from XXX.

where:

λ = latent heat of vaporization [MJ kg^-1]

T_mean = mean daily air temperature [°C]

Penman

where:

ET_o = grass reference evapotranspiration [mm d^-1]

W = weighting factor (depends on temperature and altitude)

R_n = net radiation in equivalent evaporation [mm d^-1]

f(ur) = wind-related function

(e_a - e_d) = difference between saturation vapor pressure at mean air temperature and the mean actual vapor pressure of the air [hPa]

where:

f(ur) = wind-related function

ur₂ = daily wind run at 2-m height [km d^-1]

(Penman, 1948).

Kimberly Penman 1982

Hargreaves-Samani

(Hargreaves and Samani, 1985).

Priestley-Taylor

`(Priestley and Taylor, 1972) <https://doi.org/10.1175/1520-0493(1972)100//<0081:OTAOSH//>2.3.CO;2>`_ .

Blaney-Criddle

[THIS CURRENTLY ISN’T SUPPORTED]

(Blaney and Criddle, 1950).

CropETPrep

CropET

The CropET module of the ET Demands model is the FAO-56 dual crop coefficient model (Allen et al., 1998) .

ET_c = crop evapotranspiration

K_c = crop coefficient

K_cb = Basal crop coefficient

K_e = coefficient representing bare soil evaporation

ET_o = reference crop evapotranspiration from a grass reference surface

Aridity Rating

Allen and Brockway (1983) estimated consumptive irrigation requirements for crops in Idaho, and developed an aridity rating for each meteorological weather station used to adjust temperature data. The aridity rating ranges from 0 (fully irrigated) to 100 (arid) and reflects conditions affecting the aridity of the site. The aridity rating was based on station metadata information, questionnaires, and phone conversations, and includes conditions close to the station (within a 50m radius),the area around the station (within a 1600m radius in the upwind direction), and the region around the station (within a 48km radius in the upwind direction).

Allen and Brockway (1983) used empirical data from Allen and Brockway (1982) to develop monthly aridity effect values (A_e). These values were used as adjustment factors for the temperature data based on the aridity rating. Stations with an aridity rating of 100 applied the adjustment factor directly, while stations with aridity ratings less than 100, weighted the adjustment factor by the aridity rating.

The empirical temperature data and aridity effect values used are show in the table below. These data are the average monthly departure of air temperatures over arid areas from air temperatures over irrigated areas in southern Idaho during 1981, and the aridity effect.

Month	Tmax	Tmin	Tmean	Ae
April	2.7	2.4	2.5	1.0
May	1.3	0.6	0.9	1.5
June	2.4	1.8	2.1	2.0
July	4.8	2.9	3.8	3.5
August	5.2	4.3	4.7	4.5
September	3.3	2.7	3.0	3.0
October	0.3	1.6	0.9	0.0

HOW WAS THE ARIDITY EFFECT DETERMINED. ARE THESE DATA GENERAL ENOUGH TO USE AT OTHER LOCATIONS IF AN ARIDITY RATING IS DEVELOPED? IF NOT, CAN WE GENERALIZE THE APPROACH TO DEVELOPING AN ARIDITY RATING, AND ASSOCIATED ARIDITY EFFECT ADJUSTMENTS? ALSO, THE ‘CropET’ MODULE HAS A WAY OF PULLING IN ARIDITY EFFECT VALUES, HOWEVER, THE ‘RefET’ MODULE DOES NOT. THIS MEANS THAT WHILE TEMPERATURES USED IN THE CropET MODULE ARE ADJUSTED, TEMPERATURES USED TO CALCUATE REFERENCE ET ARE NOT. IF WE WANT TO CONTINUE TO SUPPORT THE ARIDITY RATING, THIS SHOULD BE ADDRESSED. WOULD ALSO REQUIRE PASSING THE MODEL THE ARIDITY EFFECT ADJUSTMENT FACTORS.

AreaET

PostProcessing

References

Allen, R. G., & Brockway, C. E. (1982). Weather and Consumptive Use in the Bear River Basin, Idaho During 1982.

Allen, R. G., & Brockway, C. E. (1983). Estimating Consumptive Irrigation Requirements for Crops in Idaho.

Allen, R. G., Pereira, L. S., Smith, M., Raes, D., & Wright, J. L. (2005). FAO-56 Dual Crop Coefficient Method for Estimating Evaporation from Soil and Application Extensions. Journal of Irrigation and Drainage Engineering, 131(1), 2–13. https://doi.org/10.1061/(ASCE)0733-9437(2005)131:1(2)

Allen, R. G., & Robison, C. W. (2007). Evapotranspiration and Consumptive Irrigation Water Requirements for Idaho.

ASCE-EWRI. (2005). The ASCE Standardized Reference Evapotranspiration Equation.

Blaney, H. F., & Criddle, W. D. (1950). Determining Water Requirements in Irrigated Areas from Climatological and Irrigation Data. SCS-TP-96. Washington D.C.

Hargreaves, G. H., & A. Samani, Z. (1985). Reference Crop Evapotranspiration from Temperature. Applied Engineering in Agriculture, 1(2), 96–99. https://doi.org/https://doi.org/10.13031/2013.26773

Penman, H. L. (1948). Natural Evaporation from Open Water, Bare Soil and Grass. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 193(1032), 120–145. https://doi.org/10.1098/rspa.1948.0037

Priestley, C. H. B., & Taylor, R. J. (1972). On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters. Monthly Weather Review, 100(2), 81–92. https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2

Thornton, P. E., & Running, S. W. (1999). An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agricultural and Forest Meteorology, 93, 211–228. https://doi.org/10.1016/S0168-1923(98)00126-9

Data Sources

RefET

Meteorological data can be obtained from numerous sources.

Agricultural Weather Networks

Network	Supporting Organization	Coverage
CoAgMet	Colorado State University	Colorado
AZMET	University of Arizona	Arizona
AgWeatherNet	Washington State University	Washington

AgWeatherNet | Washington State University | Washington |

AgriMet-GP	Bureau of Reclamation Great Plains Regional Office	Montana
AgriMet-PN	Bureau of Reclamation Pacific Northwest Regional Office	Washington, Oregon, California (northern), Nevada, Utah, Idaho, Montana
CIMIS	California Department of Water Resources	California
NICE Net	Desert Research Institute	Nevada
West Texas Mesonet	Texas Tech University	Texas (western)

Other Weather Networks

Network	Supporting Organization	Coverage
Montana Mesonet	University of Montana	Montana
TexMesonet	Texas Water Development Board	Texas
Lower Colorado River Authority Hydromet	Lower Colorado River Authority (TX)	Texas (Colorado River Basin)
Kansas Mesonet	Kansas State University	Kansas
Nebraska Mesonet	University of Nebraska, Lincoln	Nebraska
Mesonet	University of Oklahoma, Oklahoma State University	Oklahoma

Multi-Network Sources

Source	Supporting Organization	Coverage
MesoWest and SynopticLabs	University of Utah	United States
Integrated Surface Database	NOAA National Center for Environmental Information (NCEI)	Global

CropET

Study Area

HUC8 and HUC10 features can be extracted from the full - [USGS Watershed Boundary Dataset](http://nhd.usgs.gov/wbd.html) (WBD) geodatabase. A subset of the WBD HUC polygons can downloaded using the [USDA Geospatial Data Gateway](https://gdg.sc.egov.usda.gov/) or the full dataset can be downloaded using the [USGS FTP](ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/WBD/).

County features can be downloaded from the [USDA Geospatial Data Gateway](https://gdg.sc.egov.usda.gov/). For the zonal stats prep tool to work, the shapefile must have a field called “COUNTYNAME”. Other county features (such as the [US Census Cartographic Boundary Shapefiles](https://www.census.gov/geo/maps-data/data/tiger-cart-boundary.html) could eventually be supported (or the name field could be manually changed to COUNTYNAME).

The GRIDMET grid cells can be constructed how?

Crop Type Data

Cropland Data Layer (CDL)

The Cropland Data Layer (CDL) is a product of the USDA National Agricultural Statistics Service (NASS) with the mission “to provide timely, accurate and useful statistics in service to U.S. agriculture” (Boryan et al 2011). The CDL is a crop-specific land cover classification product of more than 100 crop categories grown in the United States developed using remote sensing. The CDL can be downloaded using NASS’s CropScape tool. Updates about and references for the CDL can be found at NASS. A version of the CDL has been released annually from 1994-Present.

## Soils Data

The average agricultural area available water capacity (AWC) and hydrologic soils group are needed for each ET cell/unit. The hydrologic soils group can be estimated based on the percent sand and clay for each ET cell/unit.

The AWC, percent clay, and percent sand data cannot (currently) be directly downloaded. The easiest way to obtain these soils data is to download the [STATSGO] (http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053629) database for the target state(s) using the [USDA Geospatial Data Gateway](https://gdg.sc.egov.usda.gov/). Shapefiles of the soil properties can be extracted using the [NRCS Soil Data Viewer](http://www.nrcs.usda.gov/wps/portal/nrcs/detailfull/soils/home/?cid=nrcs142p2_053620) The [SURGO](http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053627) databases can also be used, but these typically cover a smaller area and may have areas of missing data.

It may also be possible to used the gridded SSRUGO data, but this has not been tested.

Add additional details about which options were used in the Soil Data Viewer

To use the soil prep tools, the soils data must be provided as separate shapefiles for each product. The names of the soil shapefiles are hard coded in the rasterize_soil_polygons.py script as “{}_WTA_0to152cm_statsgo.shp”, where {} can be “AWC”, “Clay”, or “Sand” (see [Model Structure](structure.md)). For each shapefile, the value field name is hardcoded as the upper case of the property (i.e. “AWC”, “CLAY”, or “SAND”).

Appendix

Cropland Data Layer (CDL) Crop Codes

Crops [1-20]

Categorization Code	Land Cover
1	Corn
2	Cotton
3	Rice
4	Sorghum
5	Soybeans
6	Sunflower
10	Peanuts
11	Tobacco
12	Sweet Corn
13	Pop or Orn Corn
14	Mint

Grains, Hay, Seeds [21-40]

Categorization Code	Land Cover
21	Barley
22	Durum Wheat
23	Spring Wheat
24	Winter Wheat
25	Other Small Grains
26	Dbl Crop WinWht/Soybeans
27	Rye
28	Oats
29	Millet
30	Speltz
31	Canola
32	Flaxseed
33	Safflower
34	Rape Seed
35	Mustard
36	Alfalfa
37	Other Hay/Non Alfalfa
38	Camelina
39	Buckwheat

Crops [41-60]

Categorization Code	Land Cover
41	Sugarbeets
42	Dry Beans
43	Potatoes
44	Other Crops
45	Sugarcane
46	Sweet Potatoes
47	Misc Vegs; Fruits
48	Watermelons
49	Onions
50	Cucumbers
51	Chick Peas
52	Lentils
53	Peas
54	Tomatoes
55	Caneberries
56	Hops
57	Herbs
58	Clover/Wildflowers
59	Sod/Grass Seed
60	Switchgrass

Non-Crops [61-65]

Categorization Code	Land Cover
61	Fallow/Idle Cropland
63	Forest
64	Shrubland
65	Barren

Crops [66-80]

Categorization Code	Land Cover
66	Cherries
67	Peaches
68	Apples
69	Grapes
70	Christmas Trees
71	Other Tree Crops
72	Citrus
74	Pecans
75	Almonds
76	Walnuts
77	Pears

Other [81-109]

Categorization Code	Land Cover
81	Clouds/No Data
82	Developed
83	Water
87	Wetlands
88	Nonag/Undefined
92	Aquaculture

NLCD-Derived Classes [110-195]

Categorization Code	Land Cover
111	Open Water
112	Perennial Ice/Snow
121	Developed/Open Space
122	Developed/Low Intensity
123	Developed/Med Intensity
124	Developed/High Intensity
131	Barren
141	Deciduous Forest
142	Evergreen Forest
143	Mixed Forest
152	Shrubland
176	Grass/Pasture
190	Woody Wetlands
195	Herbaceous Wetlands

Crops [195-255]

Categorization Code	Land Cover
204	Pistachios
205	Triticale
206	Carrots
207	Asparagus
208	Garlic
209	Cantaloupes
210	Prunes
211	Olives
212	Oranges
213	Honeydew Melons
214	Broccoli
216	Peppers
217	Pomegranates
218	Nectarines
219	Greens
220	Plums
221	Strawberries
222	Squash
223	Apricots
224	Vetch
225	Dbl Crop WinWht/Corn
226	Dbl Crop Oats/Corn
227	Lettuce
229	Pumpkins
230	Dbl Crop Lettuce/Durum Wht
231	Dbl Crop Lettuce/Cantaloupe
232	Dbl Crop Lettuce/Cotton
233	Dbl Crop Lettuce/Barley
234	Dbl Crop Durum Wht/Sorghum
235	Dbl Crop Barley/Sorghum
236	Dbl Crop WinWht/Sorghum
237	Dbl Crop Barley/Corn
238	Dbl Crop WinWht/Cotton
239	Dbl Crop Soybeans/Cotton
240	Dbl Crop Soybeans/Oats
241	Dbl Crop Corn/Soybeans
242	Blueberries
243	Cabbage
244	Cauliflower
245	Celery
246	Radishes
247	Turnips
248	Eggplants
249	Gourds
250	Cranberries
254	Dbl Crop Barley/Soybeans

Indices and tables

• Index
• Module Index
• Search Page