Agriculture under arid environment is always become a challenge due to water scarcity and salinity problems. With average rainfall of 100 mm, agriculture in Oman is limited due to the arid climate and limited arable lands. More than 50 percent of the arable lands are located in the 300 km northern coastal belt of Al-Batinah region. In addition, country is facing severe problem of sea water intrusion into the groundwater aquifers due to undisciplined excessive groundwater (GW) abstraction for irrigation. Although farmers are allowed to use ground water with a quota system developed by the Ministry of Agriculture, groundwater over pumping has caused seawater intrusion and salinity issues in most arable lands. The main objective of this research is to find alternative options for minimizing the groundwater irrigation by developing a Decision Support System (DSS). The DSS could be used to optimize the precision management of conjunctive use of treated wastewater (TW) for irrigation. Oman follows guidelines available for the use of treated wastewater with two classes A and B both with tertiary treatments as per international standards. Class-A can be recommended for vegetables consumed raw while Class-B for after cooking. Current TW production in Muscat governorate along is over100,000 m3/day and it is predicted to be four fold by 2025. Currently this volume is underutilized and some have to be dumped in sea.
The developed DSS comprised of subsystems for data management, a model management, knowledge management and the user interface for easy use and interpretation of results. The date management was done under Excel domain, and the model management was through macro programming, linear programming (LP) optimization models including transportation algorithms all in Excel domain. A user interface was optional through either with excel or using Visual Basic. The results were based on two extreme scenarios; zero TW dumped and zero GW used for irrigation. The DSS could predict water balance for number of crop rotations and based on adjustable cost variables, farmer profit margins could be created. Using LP optimization, crop selections and rotation could be done while transportation algorithm could organized and predict best locations and capacities for treatment plants and the wastewater collection and transportation to farming areas via treatment plants. This type of DSS would be useful as a water management optimization and planning tool for managers and planners.
