WEB-BASED IRRIGATION SCHEDULING - Management, Performance, and Applications of Micro Irrigation Systems - page 150

T = 17.817 × (D × A)/(Q × eff) (3)

where: T is time in hours, D is depth of irrigation water in mm, A is effective field area
in acres, Q is flow rate in gallons per minute and eff is irrigation system efficiency.
Using D = 13.7 mm, A = 10 acres, Q = 300 gallons per minute and eff = 0.85, yields:

T = 17.817 × (13.7 × 10)/(300 × 0.85) = 9.6 h

11.4 IRRIGATION MANAGEMENT
To evaluate the irrigation management with the approach described in this chapter,
construction of a graph similar to the one shown in Fig. 5 is recommended. The graph
shows the cumulative depth of irrigation and ET c plotted with time. The goal of ir-
rigation scheduling is to try to match the applied irrigation with the ETc. By the end
of the season, the cumulative irrigation (plus rainfall) should more or less equal the
cumulative ETc. If these two curves stay close together, this is an indication that good
irrigation management is being achieved. Note that the graph shown in Fig. 5 is not
related to the example problem given above.

11.5 SUMMARY
Irrigation scheduling is critically important to avoid the loss of water, fuel and chemi-
cals by over application of water, or a reduction in crop yield if too little water is
applied. In this chapter a web-based irrigation scheduling approach is described. The
approach is based on applying irrigation water at the rate of the estimated potential
evapotranspiration, which is equivalent to the crop water requirement. Reference
evapotranspiration is obtained from an operational water and energy balance algo-
rithm (GOES-PREWEB), which produces a suite of hydro-climate variables on a daily
basis for Puerto Rico. The algorithm produces daily estimates of the Penman-Mon-
teith, Priestly Taylor and Hargreaves-Samani reference evapotranspiration. The crop
coefficient curve is constructed per the methodology recommended by the United Na-
tions Food and Agriculture Organization (FAO). Daily rainfall can be obtained from
radar (NEXRAD) if rain gauge data is not available for the farm. A detailed example
is provided for a farm growing tomato in Juana Diaz, PR, USA. The approach is rela-
tively simple and the near-real time data is available to any farmer in Puerto Rico with
internet access. Using the procedures described in this chapter, the approach could be
developed at any location throughout the world.

KEYWORDS

• Crop coefficient

• Crop water use

• Evapotranspiration

• FAO

• GOES-PRWEB

• Hargreaves-Samani