INFLUENCING FACTORS AND SYSTEM DYNAMIC MODELING OF WATER AND ENERGY CONSERVING IRRIGATION TECHNOLOGIES: A CASE STUDY OF PUNJAB, PAKISTAN
Journal: International Journal of Management (IJM) (Vol.12, No. 4)Publication Date: 2021-04-30
Authors : Muhammad Sajid Sufian Ahmad Salman Altaf Mubashra Nayyer Asima Ali;
Page : 909-930
Keywords : Agricultural water management; Technology Diffusion; water and energy conservation; water scarcity; Sustainability;
Abstract
Pakistan is an agricultural country and irrigation plays an important role in better agriculture practices, about 90% of total agriculture is dependent on irrigation. Advanced irrigation technologies are a way to use limited water more efficiently. The main purpose of this research is to investigate the influencing factors and development of system dynamics model for the diffusion of water and energy conserving irrigation technologies, leads to sustainable agriculture in Pakistan. Punjab province of Pakistan has been selected for the case study. To achieve study objectives, quantitative data have been collected through a structured questionnaire. Quantitative data has been collected from 325 farmers of Punjab Pakistan. For the system dynamic model Vensim software has used and to explore influencing factors for the adoption of high-efficiency irrigation system exploratory research, Reliability, correlation, and multiple regression analysis has been conducted by employing SPSS. Study findings revealed that adoption of water and energy conserving irrigation technologies is highly affected by Demographic factors, electricity availability, Technical assistance, Farmer' ability to pay, water availability, lack of awareness, after-sales, and service, and social networking factors. Study results will be very useful for the water management-planning unit of Pakistan and many other countries of the world working on high-efficiency irrigation systems. This saved water will help Pakistan improve agricultural land and production and be very imperative for drinking and power generation
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