Sprinkler Irrigation - Can its efficiency be improved?

Kobi Shilo, Chief Agronomist, NaanDanJain

This article presents further options for more efficient irrigation. Use of a computer and software to analyze the water distribution allows anyone to examine and analyze the sprinkler data in an optimum manner. Analysis of different indices presented by the CU, DU and Scheduling Coefficient, and flexible execution of changes in sprinkler positioning, spacing and location will reveal to us the full picture of the optimal water distribution.

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High uniformity with Maestro mounted on Amirit System Corriander irrigation with 5022
High uniformity with Maestro
mounted on Amirit System
Corriander irrigation with 5022


Up to now, when planning and applying the sprinkler system, numerous compromises are made in: convenience of operation, spacing position, pipe diameter, working pressure and more.

Opening a window
Water is nature’s treasure and it must be protected. A magnifying glass must be used when applying the sprinkler system. The message of more intelligent and cautious use of water is accepted in certain regions and it must also be penetrated into and accepted by regions that are blessed with an abundance of water.
This article will open a small window onto understanding water distribution. It will examine where the designer and user can make decisions that will contribute to irrigation efficiency.

Conventional basic assumptions
The basic assumptions for efficient application is presented in brief, and they will not be discussed here.

Methods for evaluating water distribution
The conventional method for examining the sprinkler’s water distribution is based on Christiansen’s distribution coefficient. This is a statistical formula that examines the deviations from the average over the entire field and provides an evaluation in percentage.

Conventional values:

2. A second method, which is called DU,
examines the ratio between the average of 25% of the low readings and the general average of all readings.

Conventional values:

This method enables location of dry area problems and planning of an irrigation water portion that will be taken into account in the required application.

Leaching of salts


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:

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.



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.


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.

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.


Calculated field % Defined unit size
Calculated Sc Water volume
relative to
average appli-
cation rate %
Water volume
required to
5 10.8
70 25.5
10 21.6 1.40 71
1.34 75 21
20 43.2 1.30 77
25 54.0
1.21 83 14.4




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.


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


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)


Article tags: field crops, irrigation software, efficient irrigation