Document Details

Document Type : Thesis 
Document Title :
Building Simulation Models to Achieve Optimal Economic Efficiency of the Use of Groundwater- A Case Study on the Agricultural Sector in Saudi Arabia
بناء نماذج محاكاة لتحقيق الكفاءة الاقتصادية المثلى من استخدام المياه الجوفية - دراسة تطبيقية على القطاع الزراعي بالمملكة العربية السعودية
 
Subject : Faculty of Meteorology, Environment and Arid Land Agriculture 
Document Language : Arabic 
Abstract : Although the Kingdom of Saudi Arabia is an energy resources rich country, it is considered as poor in regard of water resources, whereas the Kingdom is located in an arid region with an average annual rainfall of less than 100 mm. Over the past four decades, Saudi Arabia has witnessed a comprehensive development in all sectors. This has created an unprecedented increase of water consumption, both in the agricultural and urban sectors causing a challenge represented in the scarcity of fresh water in the Kingdom. The total water consumption in Saudi Arabia is estimated at 24 billion cubic meters per year. Urban consumption (municipal and industrial) sector accounts for 17% of total demand while the agricultural sector accounts for 83% of the total water demand in Saudi Arabia. The water consumption of the agricultural sector depends on renewable and non-renewable groundwater without restrictions governing efficient use of water. An agricultural hydro-economic System Dynamics model is built to study optimal solutions for economic efficiency of groundwater use and to achieve water and food sustainability in Wadi Al Dawasir using Stella software. Stella is a platform that enable user to create simulation model by relating the input data through the software tools. Seven scenarios are proposed for the period (2017-2030). These scenarios are designed to study the anticipated effects of the government’s decision to stop growing fodder crops by 2019. A field survey is conducted covering 39 farms in Wadi al-Dawasir area, including Alfalfa farms, other fodders farms, dates farms, vegetables and wheat farms. A random stratified sampling method is used to collect the data. As well, data were collected from the Ministry of environment, water and agriculture publications, the annual statistical book and other official publications. The results showed that the implementation of the government’s decision to stop growing fodder crops would reduce the cumulative depletion of water by 21 billion m3 for the period (2017-2030). In addition, the transfer from fodder to vegetable farming is the least water consuming and offers higher value agricultural products than other scenarios. The results showed that farmer pays for groundwater between 0.13 to 0.41 SR/M3. This cost is very low and is negligible if we compare it to alternative opportunity cost of water desalination by the National Water Company for the residential sector, which is up to 6 SR/ M3 (for the upper range of tariff of water bills). The study concluded that lifting the governmental subsidies on diesel will stop the cultivation of wheat and Rhodes and will affect the cultivation of Alfalfa. However, vegetable and date crops will be less affected due to their high profit. The study recommends that the competent authorities of water management through the establishment of farmers’ cooperative association to coordinate between the farmers and the authorities responsible for import and export in order to achieve balance of supply and demand to prevent the water wasting resulting from the cultivation of crops that exceed the need of the markets. Keywords: System dynamic, water demand, agriculture sector, simulation, Wadi Al Dawasir, irrigation water, groundwater, water resource management, water value, Saudi Arabia. 
Supervisor : Prof. Ahmad Sami 
Thesis Type : Doctorate Thesis 
Publishing Year : 1440 AH
2019 AD
 
Co-Supervisor : Prof. Jalal BaSahi 
Added Date : Tuesday, January 15, 2019 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
عبدالعزيز محمد القرعاويAlqarawy, Abdulaziz MohammedResearcherDoctorate 

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