Artificial neural networks approach to estimate wetting pattern under point source trickle irrigation [electronic resource].

Includes reference.

Trickle irrigation is based on the principle of low quantity of water application at frequently close intervals. Water is supplied to only those parts: of the soil where water uptake by the root system is the most efficient Water trickling from a point source enters the soil and moves downwards and sideways. This reduced evaporation and minimal weed growth which result in considerable savings in the amount of water applied to a given field. There has been much speculation on the shape of the wetted soil volume. Based on this, it is then possible to detennine the number of emitters required per plant in order to wet a prescribed portion of the plants root zone. This is quite important in design, operation and management of a tridde: inigatioo system. There arc many attempts to determine the wetting panem under trickle irrigation using sophisticated mathematical and numerical models.

Summary in Arabic

1