Use of remote sensing for irrigation scheduling in arid lands of Saudi Arabia

Abstract

Irrigation water requirement of major crops (alfalfa, potato, tomato and wheat) grown in Wadi Sirhan, northwestern Saudi Arabia have been estimated in the present study from agro-climatic data. These data are integrated with the remotely sensed data and the irrigation scheduling efficiencies have been computed using guidelines of Food Agriculture Organisation (FAO) (Doorenbos and Pruitt, 1977, Doorenbos and Kassarn, 1979, Nimah et al., 1986, Menenti et aL, 1994, FAO, 1998, Raut et al., 1998, Bastiaanssen, 1999, Anon, 2001, Rumikhani and Saif ud din, 2003). Comparison between the actual irrigation application and the crop water requirement has been made for different crops. As per crop water requirement of major crops in the area irrigation can be reduced considerably without affecting the crop yield. The over irrigation percentage in the region varies from 35 % to 64% for different crops in the season (Table 2). The strategic requirement of food sufficiency and food security has given impetus to agriculture development in Kingdom of Saudi Arabia. The ground water is a major source of irrigation. The ground water from deeper aquifers which are exploited for irrigation is non-renewable fossil water of 10000 to 28000 Years Before Present (Edgell, 1997). The irrigation utilizes 80 to 88% of the total water consumption in the Kingdom (Sadik and Barghouti, 1994) The pattern of ground water exploitation, if not managed will generate environmental degradation of the fragile arid ecosystem. The present trend of irrigation is expected of 25% depletion of the ground water reserves by the year 2010 (Alawi and Abdulrazzak, 1994). The fossil ground water reserves may not last for more than 50 years with increasing demand for irrigation. This has prompted scientists to use remote sensing technology for the management of regional irrigation water requirements in the Kingdom of Saudi Arabia. The present study demonstrates the use of remote sensing in crop water requirement estimation to regulate irrigation application rate in the arid ecosystem. The present results show that the remote sensing technique is time and cost effective for crop identification, growth stage evaluation and crop area estimation, together with agro-meteorological data to evolve efficient irrigation management practices for sustainable agriculture in arid ecosystem.