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Example
Spacing of sprinklers: 12 x 18 m (216 m)
Average application rate: 8.0 mm/h
When the DU = 75%, then 25% of the area (with random distribution) received an average minimal value of only 6 mm/h.
Analysis of the implications of distribution uniformity.
It has been said that a person can drown in a lake that is only an average of one meter deep. A mere statistical analysis does not always show the “dips”. The plant whose growing area falls into the “dip” will receive less water and fertilizer, unless it receives extra irrigation.
In the computer era, examination, analysis and evaluation of the statistical analysis can be conducted and accurate decisions can be made.
The points that we wish to examine and define are:
- What are the gaps between minimum, maximum and average?
- Are there focused areas with water surplus or shortage?
- What is the economic significance in each situation?
The data of CU distribution uniformity alone cannot provide us with a full answer. For this reason, we must conduct an additional data analysis using DU and/or Scheduling Coefficients, which relate to gaps between minimum and average and to their position in the field.
In the end, the picture will be completed by physical observation of the water distribution grid provided by the software, in values of mm/h.
Example:
Data: Sprinkler field with square positioning of 12 x 16 m
Working pressure: 3.5 – 4.0 bar
Average sprinkler rate: 8.5 mm/h
Distribution uniformity according to CU: 85%
Distribution uniformity according to DU: 79%
Implications
According to the DU definition, the ratio of the lowest 25% of the readings and the average precipitation rate is 0.79. This means that if the average is 8.5 mm/h, we will receive readings of 6.7 mm/h in 25% of the field.
3. A third method: Sc (Scheduling Coefficient)
This method enables specific observation of the water distribution map and location of the field that receives the minimal water portion. We can define the size of the required area as a percentage of the spacing area.
The Sc measurement enables planning of the irrigation portion and the required extra irrigation, based on the field that receives the minimal portion.
The Sc coefficient can help us to select a better solution than the CU values for different sprinklers or spacing.
Example
Scheduling Coefficient 1.3 means that the minimal area receives 30% less than the average.
The computer software shows us the ratio between the average of this defined unit and the general average.
1 = Sc: No deviation, the entire field is uniform
1-1.5 = Sc: Scope of results is reasonable
Sc > 2.0: Bad results, not recommended
For sensitive crops, we can define an area of 5 to 10%. For less sensitive crops, we can define a larger area – 15 to 25%. The larger the definition of the area size, the lower the Sc value.
Table: Example of calculation of the water portion required for completion for Sc values and different field percentages.
Sprinkler positioning: 12 x 18 m (216 sq. m)
Irrigation rate: 8.5 mm/h
|
Calculated
field
% |
Defined
unit size
Sq.m/h |
Calculated
Sc |
Water volume
relative to
average
application rate
% |
Water volume
required to
complement
mm/ha/h |
|
5 |
10.8 |
1.43 |
70 |
25.5 |
|
10 |
21.6 |
1.40 |
71 |
25 |
|
15 |
32.4 |
1.34 |
75 |
21 |
|
20 |
43.2 |
1.30 |
77 |
19 |
|
25 |
54.0 |
1.21 |
83 |
14.4 |
Conclusions:
In compiling such a table, we can analyze the implications of the required extra water, compared with the percentage of the area that we wish to define. With high economic sensitivity to the crop, we can focus the decision on a basis of 5 to 10% of the area. In less sensitive situations, the field can be defined as 15 to 25%.
General view
We currently hold more precise tools for efficient irrigation analysis. Based on water and energy prices (irrigation/pumping duration) on the one hand, and income forecast from yields on the other, we will consider the feasibility of improving distribution uniformity.
Sometimes a small change in the sprinkler positioning and/or spacing will contribute to significant change in the distribution uniformity and the scheduling coefficient.
Example
Situation A: A sprinkler system with distribution uniformity of CU = 86%
Sc = 1.6, 9 x 10 m spacing in a rectangular positioning
Situation B: (Improved) Changing the positioning to triangular, with 9 x 10 m spacing
CU = 89%
Sc = 1.3
Result
Possible average savings in water for the growing season
Water portion in Situation A (6,000 cu.m/ha)
Water portion in Situation B (4,870 cu.m/ha) |
