4.7 Analyze Data

In this Section the data that has been collected will be analyzed by several equations to get the uniformity percentages, precipitation rate, and other information for decision making. This information will then be included in the report of the audit test.

A. Calculating Precipitation Rate (Net Precipitation.)

The net precipitation is useful in finding the amount of water actually reaching the ground or, in this case, the catch container. Overhead sprinklers lose up to 20 percent of the water in the air or from foliage on hot, dry days. By making the calculation using data from the catch cans, the water lost to evaporation has been removed. The net precipitation is that amount of water that reaches the ground.

If the data has been collected in volume rather than in inches of depth, this equation makes the conversion to depth. The top opening area, CDA, of the catch can must be determined. For a square container it is the width times the length. For a round top container, the area of a circle must be calculated.

The procedure is simply to take the average of all volumes collected and divide by the area of the top of the catch can through which the water fell to get the average depth of water or the net precipitation. The run time, TR, of the test and a constant (3.66) are used to convert the results to rate, inches per hour.

First, sum the volumes of all catch cans and divide that by the number of cans to get the average which is called CVavg . Its units are milliliters (ml). Calculate the top opening area of the catch can, CDA, using the diameter, D, in inches. CDA equals the (Diameter of top / 2) squared times π (3.1416) to give square inches.

PRnet (in/hr) = [(3.66) CVavg ] / [TR (CDA)], where

PRnet = Precipitation Rate (in./hr)

CVavg = Average Catch Can Volume (ml), average of all can volumes

3.66 = conversion constant

TR = Testing Runtime (minutes)

CDA = Catch Can Throat Area (sq in.) = 3.14 (d x d)/4 where d is the diameter

across the throat, in inches.

The precipitation rate is a useful number to compare back to the initial information on the sprinkler system. With the evaporation that is occurring, is enough water reaching the crop?

 

B. Distribution Uniformity (D.U.) (%) The distribution uniformity is one way to measure system uniformity. It is calculated by dividing the lowest 25% of catchments by the average value of the total catchments. It is referred to as the Lower Quarter Distribution Uniformity.

DULQ = [Average volume (or depth) of lower quarter / Average Volume (or depth) of all] X 100]

One way to display the data is to make a list of all catch can volumes starting with the largest to the smallest. Select and mark the lowest quarter of the readings on the bottom of the list. If there were 24 catch cans, then the lowest 6 catch can volumes (24/4) become the lowest quarter.

Sum the values of all volumes collected and divide that total volume by the number of catch cans to get an average, CVavg. Sum together the 6 lowest quarter volumes and average them to get CVLQ. Divide the lowest quarter average, CVLQ by the total average, CVavg, and multiply by 100%. This gives the DULQ.

The greater the variation in catch can volumes collected, the lower the uniformity.

 

Use the data in Figure 4.3b (Section 4.3) to do this calculation. Figure 4.7a illustrates the data of Figure 4.3b in a hand written form as done in the field. The data is repeated on another sheet where the DU is calculated. Figure 4.7b illustrates the ranking of the 16 values, selection of the lowest quarter of values, the calculation of averages, and the calculation of the Distribution Uniformity, DU. In this case the depth of water was recorded instead of the volumes but these will work as well. The average of all 16 can depths is 0.31 inches. Since there are 16 catch cans, find the four lowest quarter values; these are 0.24, 0.25, 0.27 and 0.28 inches. The average of these four lowest depths is 0.26 inches. Therefore, from the equation, DULQ = 100% x (0.26 inches) / 0.31 inches = 83.9%. This is a good DULQ value, as shown below.

For high cash crops, especially shallow roots or nursery crops in containers, the uniformities should be high. DU values greater than 80% are good. For typical field crops, DU values should be greater than 70%. For deep rooted orchard and forage crops, uniformities may be fairly low if chemicals are not injected; DU values above 55% are okay.

Go back to the site map that shows the volume data and with a colored pencil, mark the location of the 4 lowest volumes. Examine the map to see if a reason appears for the location of the lowest volumes.

.

Figure 4.7a. Hand drawn map shows the test area at Charlie's Nursery with a brief description of the site. Data from the study is written on the map as an official record.

Figure 4.7b. Hand written data is shown for the test at Charlie’s Nursery. The DU is determined by ranking the data, totaling and averaging data, and doing the DU calculation on the paper.

 

C. Christiansen’s Uniformity Coefficient (UC).

Christiansen’s Uniformity Coefficient is another widely used method of calculating the water application uniformity from sprinkler irrigation systems. It looks at the average deviation from the average depth of water applied.

Use the data in Figure 4.3b (Section 4.3) to do this calculation. To calculate, one first determines the average water depth applied. Then, one at a time, subtract the average depth from each catch can depth. Some will be negative and some will be positive numbers. Disregard the plus or negative sign; make them absolute values with no sign. Total these deviation values and average them.

UC = 100% [1 – (Average Deviation from the Average Depth of Application / Overall Average Depth of Application)]

Using the data from Figure 4.3b, The overall average depth is 0.31 inches and the average deviation is 0.46 / 16 = 0.029 inches. Therefore,

UC = {1.0 – (0.029 / 0.31)] = 1.0 – 0.094 = 90.6%

Figure 4.7c. illustrates these calculations done by hand in the field. The calculations are not difficult to do. The raw volume data is listed in the first column on the left. After the average total depth (AVdepth) in the catch cans is determined to be 0.31, that values is subtracted from each value. Since the absolute value is required, no positive or negative sign is given to the answer of each subtraction. These values are the deviations from the average total depth. Sum the total value of the deviations and divide by 16 (catch cans) to get the average deviation (AVdeviation). Put these values into the equation for calculating UC to obtain 90.6%.

 

Figure 4.7c. Hand written data is shown for Charlie ’s Nursery. The UC is calculated by finding the overall average depth of water, calculating the deviation of each test value from the overall average depth (absolute value), and then using the equation for Christiansen’s Uniformity Coefficient.

Uniformity coefficients should be high for high value crops, especially shallow rooted and container crops, with UC greater than 87%. For typical field crops the UC should be greater than 81%. For deep rooted orchard and forage crops, if chemicals are not injected, CU should be above 72%.

The UC in this case is good, being above 87%.

D. Scheduling Coefficient (SC). Scheduling Coefficient is a measure of uniformity in an area that compares the lowest precipitation rate (volume) for a defined contiguous area to the average precipitation rate (volume) over the entire test area.

Scheduling Coefficient (SC) = Average Catch (volume) overall / Average Catch in Critical Dry Area.

The SC becomes a multiplier that tells how many times longer the watering must be done in order to water the dry area as much as the average area was getting at the time of the test.

Irrigation efficiency takes a back seat when there is an area that does not receive enough water. A grower must water to meet the requirements of the driest area. Thus, in Figure 3.4b of Section 4.3, the low quarter of volumes were 0.24, 0.25, 0.27 and 0.28 inches while the average depth collected was 0.31 inches. Using this scheduling coefficient calculation we can expect the grower to apply water to satisfy the dry area that is receiving 0.24 inches. With this in mind,

SC = 0.31 in. / 0.24 in. = 1.29 or about 1.3 times the amount of water needed on the average in order to satisfy the driest area which is 1/16 (6.25%) of the area. Of course, the 0.25 in. value is not much better, compared to the average.

This calculation points out the need to achieve high water application uniformity in order to conserve both water and energy.

E. Flow Rate from a Nozzle. This equation is not required for the evaluation of uniformity but may be used to estimate the flow discharge of a nozzle if it is not known. It requires a good measurement of the nozzle size if the size is not given on the nozzle. Also, the water pressure at the nozzle must be measured.

Q = 28.62 (d x d) (square root of p)

Where: Q = flow rate of nozzle {gpm}

d = nozzle diameter {in.}

p = pressure at nozzle {psi}

28.62 = constant to convert units

F. Precipitation Rate (gross). This is the gross amount coming out of the nozzle and does not account for losses to evaporation in the air before reaching the ground. Use this equation when the nozzle flow rate and the sprinkler spacing are known.

PR = (96.3 Q) / Area = (96.3 Q) / (S1 x S2)

PR = average precipitation rate in area {in./hr}

Q = flow rate into the area {gpm}

S1 = sprinkler spacing in one direction {ft}

S2 = sprinkler spacing in other direction {ft}

Area = area associated with the precipitation {sq ft}

96.3 = constant to convert units

 

References:

Rochester, E.W. August 2005. Irrigation System Performance Audit. Irrigation Association Education Foundation, 6540 Arlington Boulevard, Falls Church, VA 22042-6638. www.iaef.org. Notebook of instructor manual, powerpoint CD, worksheets, student manual.

Smajstrla, A.G., B.J. Boman, G.A. Clark, D.Z. Haman, D.J. Pitts and F.S. Zazueta. May 1997, reviewed 2005 by Haman. Bulletin 266. Agricultural and Biological Engineering Department, Florida Cooperative Extension, Institute of Food and Agricultural Sciences, University of Florida. 9 pp. http://edis.ifas.ufl.edu/pdffiles/AE/AE38400.pdf