| dc.description.abstract | To feed the growing global population, agriculture production must be intensified using existing land and resources. Sustainable agriculture intensification is particularly important in the Middle East and North Africa (MENA), the most water-stressed region in the world. Solar-powered drip irrigation (SPDI) has the potential to increase water use efficiency and reduce fossil fuel use for irrigation. Despite these benefits, SPDI adoption is limited by its high investment cost and the misalignment between farmers' risk tolerance and broader sustainability goals. Past work has explored three areas of SPDI innovation: low-pressure drip emitters, system cost optimization, and precision irrigation control. This thesis integrates previous innovations in an end-to-end design process to generate SPDI architectures that are accessible to resource-constrained farmers.
A market study was conducted to understand farmers' priorities and constraints and articulate SPDI value propositions for the target users. Stakeholder surveys were conducted in Jordan and Morocco for farms ranging from 1–130 hectares. Three market segments were identified, grouping farmers who face similar economic and knowledge barriers. While farmers generally prioritized irrigation reliability and low system costs, the observed variety in farm size, production volume, and technical expertise suggested that SPDI architectures must be tailored to each market segment.
This thesis proposes an energetic framework that captures system parametric relationships to identify feasible SPDI design trade-offs. The optimized solar power systems were 14%–80% less expensive than conventionally-sized designs. Despite significant changes to the hydraulic operating parameters, the proposed SPDI architectures were as reliable as existing systems. For farms with long irrigation times, it was optimal to pair low-pressure drip emitters with an irrigation schedule that tracks the daily solar profile, termed “solar profile matching” (SPM), to maximize direct solar power use. The SPM schedule reduced system cost by minimizing the battery capacity. An economic analysis demonstrated that the optimal SPDI designs could be made cost-competitive with grid power through SPDI retrofit subsidies, which some local governments already support. Researchers and industry professionals could use the energetic framework and techno-economic analysis presented in this thesis to inform system design and policy decisions and promote SPDI adoption.
Finally, this work created guidelines for designing a precision irrigation controller in resource-constrained markets. A controller was conceptualized to implement the SPDI-SPM architecture. The controller functional requirements and design specifications were iteratively defined with stakeholders, and a prototype was tested on two farms in the MENA region. The controller reduced water and energy use by up to 44% and 43%, respectively, while maintaining crop yield. However, the controller relied on battery power to execute the irrigation schedule. A yield loss sensitivity analysis found that using 72%–79% of the available solar energy on average, an increase of about 40% from the experiment SPM schedules, would have been sufficient to reliably irrigate with solar alone. The results suggest that, with software modifications, the proposed controller could eliminate the need for a battery and enable low-cost SPDI systems. If adopted, the proposed controller could make sustainable irrigation practices more accessible to farmers. | |
