DWR_2807910

• Title: STATE AND DIVISION ENGINEER'S FORUM ENGINEERING ASSUMPTIONS - ATTACHMENT: CROP COEFFICIENT MEMO
• Author/Source: DEAN SANTISTEVAN, P.E.
• Author/Source: DIVISION OF WATER RESOURCES
• Keywords: CROP COEFFICIENT, CROP GROWTH
• Document Type - Reference Library: Presentations
• Document Date: 4/15/2014
• Year: 2014
• Team/Office: Division 1 Office

MEMORANDUM
December 13, 2013
Issues with Selecting an Appropriate Crop Growth Stage Coefficient for the SCS Mod. Blaney
Page 18 of 34

For orchards without cover, it appears that the SCS relied upon the average of the “deciduous orchard”
and walnut data. The data from ARS 1275 showed a strong correlation (R
curve as shown in Chart 15. The data suggests an average ele

Figure 18 - kc vs. month for

Implications and Further Research:
The level of probability, or the confidence level, can be best represented by the R
regression analysis. When it was shown that there was a strong correlation, i
presented in ARS 1275 were used in the development of the SCS TR
the data, which result in a lower correlation coefficient, could be du
temperature data used in this study, or in the interpretation of
the SCS TR-21 data, or from other data
plotted points” indicating that they were not mathematically interpolated.
were made in the smooth curves so that for a number of locations the sum of the computed monthly
values…would approximate the…values developed from the original
explain some variability. Furthermore, Woodward indicates that the values were adjusted so that the sum
of monthly values would equal the previously calculated seasonal amounts developed for the original
Blaney-Criddle equation. This may explain why some crop curves like sorghum, wheat, and small grains
(Barley) track below the ARS 1275 data set.
to the ARS 1275 data, and may have been adjusted upward to fit
true for sugar beets and corn as there is no other clear explanation.

The SCS TR-21 curve for pasture grasses appears to better describe lawn grass at or near sea level.
Alfalfa and orchard without cover appear to re
appears to represent the high-end of the data set during peak use and at or near the average of the data
set during the winter months. Dry beans were the only crop where a rational explanation coul
provided.

Based upon the work performed in this study,
considered when performing calculations of consumptive use with the SCS m
equation. Further research and analysis should be performed to validate the appropriateness of specific
crop growth stage coefficients when quantifying the historical consumptive use in a change of use
analysis. For example, is it appropriate to use the SCS TR
when they are based upon data for “deciduous fruit,” citrus, and walnuts in California and Arizona? The
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 2
Issues with Selecting an Appropriate Crop Growth Stage Coefficient for the SCS Mod. Blaney-Criddle Eqn.
orchards without cover, it appears that the SCS relied upon the average of the “deciduous orchard”
and walnut data. The data from ARS 1275 showed a strong correlation (R2=0.991) to the SCS TR
The data suggests an average elevation of 441 feet above sea level.
vs. month for Orchards without cover
Implications and Further Research:
The level of probability, or the confidence level, can be best represented by the R2 term in the linear
When it was shown that there was a strong correlation, it is probable that the data
used in the development of the SCS TR-21 coefficient curves
the data, which result in a lower correlation coefficient, could be due to assumptions in the mean monthly
, or in the interpretation of monthly crop growth stage coefficient
, or from other data. Woodward indicated that “smoothed curves were drawn thru
” indicating that they were not mathematically interpolated. In addition, “minor adjustments
o that for a number of locations the sum of the computed monthly
values developed from the original Blaney-Criddle equation
Furthermore, Woodward indicates that the values were adjusted so that the sum
of monthly values would equal the previously calculated seasonal amounts developed for the original
equation. This may explain why some crop curves like sorghum, wheat, and small grains
track below the ARS 1275 data set. The crop curve for small vegetables had a strong correlation
to the ARS 1275 data, and may have been adjusted upward to fit a seasonal amount. The same may be
true for sugar beets and corn as there is no other clear explanation.
21 curve for pasture grasses appears to better describe lawn grass at or near sea level.
Alfalfa and orchard without cover appear to represent the average of ARS 1275 data. Orchard with cover
end of the data set during peak use and at or near the average of the data
set during the winter months. Dry beans were the only crop where a rational explanation coul
work performed in this study, it is recommended that the information
considered when performing calculations of consumptive use with the SCS modified Blaney
Further research and analysis should be performed to validate the appropriateness of specific
crop growth stage coefficients when quantifying the historical consumptive use in a change of use
analysis. For example, is it appropriate to use the SCS TR-21 crop coefficients for orchards in Colorado
when they are based upon data for “deciduous fruit,” citrus, and walnuts in California and Arizona? The
4 6 8 10
Deciduous Fruit
Walnuts, Davis
Walnuts, Southern Area
SCS TR-21 Orchard, no cover
AVG -No Cover
Criddle Eqn.
orchards without cover, it appears that the SCS relied upon the average of the “deciduous orchard”
=0.991) to the SCS TR-21
vation of 441 feet above sea level.

term in the linear
t is probable that the data
curves. Disparity in
the mean monthly
monthly crop growth stage coefficients from
smoothed curves were drawn thru
minor adjustments
o that for a number of locations the sum of the computed monthly
Criddle equation,” which may
Furthermore, Woodward indicates that the values were adjusted so that the sum
of monthly values would equal the previously calculated seasonal amounts developed for the original
equation. This may explain why some crop curves like sorghum, wheat, and small grains
The crop curve for small vegetables had a strong correlation
a seasonal amount. The same may be
21 curve for pasture grasses appears to better describe lawn grass at or near sea level.
present the average of ARS 1275 data. Orchard with cover
end of the data set during peak use and at or near the average of the data
set during the winter months. Dry beans were the only crop where a rational explanation couldn’t be
information in Table 15 be
odified Blaney-Criddle
Further research and analysis should be performed to validate the appropriateness of specific
crop growth stage coefficients when quantifying the historical consumptive use in a change of use
rop coefficients for orchards in Colorado
when they are based upon data for “deciduous fruit,” citrus, and walnuts in California and Arizona? The
12