Drainage research

An example of a criterion factor is the depth of the water table: The underlying processes in the optimization (as in the insert of Figure 2) are manifold.

[5] In dealing with field data one must expect considerable random variation owing to the large number of natural processes involved and the large variability of plant and soil properties and hydrological conditions.

An example of a relation between crop yield and depth of water table subject to random natural variation is shown in the attached graph.

When analysing field data with random variation a proper application of statistical principles like in regression and frequency analysis is necessary.

Agro-hydro-salinity and leaching models like SaltMod[6] may be helpful to determine the drainage requirement.

Figure 1.
Figure 2.
Figure 3.
Crop yield (Y) and depth of water table (X in dm) [ 4 ]