Mapping agricultural water productivity for center pivot irrigation systems based on satellite data [electronic resource].

Includes bibliographic reference.

Developing and launching many remote sensing satellites with varying spatial-temporal accuracy, have provided various types
of data at spatial, spectral, radiometric, and temporal scales, therefore, mapping agricultural ecosystems' physical
and ecological characteristics with high accuracy became available by integrating remote sensing models with meteorological data.
The primary goal of this research is to determine the agricultural water productivity under center pivot irrigation systems based
on satellite data analysis. Landsat 8 images, agrometeorological stations, and the use of the light Use Efficiency model of Monteith
(LUE) and SSEB (Simplified Surface Energy Balance) models were used to calculate the amount of crop production biomass (BIO)
and The amount of water consumed, represented by the actual evapotranspiration (ET), respectively, and then, based on ET,
the water productivity was determined. (WP = BIO/ET). The average ET, BIO, and WP values in 2021 summer season crops,
ranged from 3.01± 1.73 to 4.1 ± 2.35 mm day-1; 96.4 ± 55.4 to 191.6 ± 110.2 kg ha-1 day-1; and 1.64 ± 0.94 to 2.43 ± 1.4 kg m-3,
respectively. The average water productivity values for the crops cultivated in the research region ranged from 1.1 to 1.4 Kg m?3
for watermelon, 1.1 to 1.6 Kg m?3 for peanut, 3 to 3.3 Kg m?3 for Alfalfa, and 1.3 to 2.1 Kg m?3 for maize. These findings demonstrate
that water productivity estimates derived from remote sensing data may be utilized as an indication for increasing water rationalization
via improved land and water management methods.

Summary in Arabic.