SUGGESTED MODEL TO ESTIMATE IRRIGATION WATER REQUIREMENT FOR SOME CROPS IN SANDY SOIL - WADI EL NATRUN - EGYPT

Abstract

An experiment was performed during two winter successive seasons of (2016/2017-2017/2018), at a private farm in Wadi El-Natrun area, El-Behera Governorate, Egypt, to study the effect of applied irrigation water (IR) methods: fuzzy Logic controller (FLC) and manual irrigation water addition (Manual) based on ETc100% at different humic acid rates “HA” (10, 15 and 20 kg ha-1) under surface and sub-surface drip irrigation systems on marketable yield, crop quality parameters, actual evapotranspiration (ETa), water use efficacy (WUE) and irrigation water use efficiency (IWUE) for sugar beet roots and spinach leaves crops under surface (SDI) and sub- surface drip (SSDI). The results showed that, the marketable yield and studied quality parameters of sugar beet roots and spinach leaves gave the highest values under FLC and SSDI treatment for both seasons. While, the seasonal ETa of sugar beet and spinach crops gave the lowest values: 436.24and 141.82 mm; 429.16 and 139.93 mm for both seasons respectively, under FLC and SSDI treatment. The results recorded that, the marketable yield and studied quality parameters of sugar beet and spinach crops gave the highest values under FLC, HA =20 kg ha-1 and SSDI treatment for both seasons. While, the IR and ETa of both crops gave the lowest values under FLC, HA =15 kg ha-1 and SSDI treatment. Finally, the WUE and IWUE of both crops gave thehighest values under FLC, HA =15 kg ha-1 and SSDI treatment. This study concluded that the cultivation of sugar beet and spinach crops under FLC, HA =15 kg ha-1 and SSDI treatment can possibly save of the applied irrigation water about 35 and 45% for the 1st season while, were 41 and 47% for the 2nd season respectively, moreover, increased marketable yield 35 and 45% for the 1st season while, were 41 and 47% for the 2nd season respectively, compared with that under the control treatment (Manual, HA =20 kg ha-1 and SDI treatment).