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Built infrastructure for water and energy supply, transportation, and other such services underpins human well-being and socioeconomic development. A fundamental understanding of how infrastructure design and user strategies interact can guide important design decisions as well as policy formulation for ensuring long-term infrastructure viability in conjunction with improved individual user benefits. In this work, an agent based model (ABM) is developed to study this issue for the specific case of irrigation canals. Cooperatively maintained irrigation canals serve essential roles in sustaining agriculture-based economies in many regions. Canal system design can strongly affect benefits derived by distributed users, regional agricultural output, and the long-term viability of the shared infrastructure itself. Here, an ABM is used to investigate how an option to use an independent water source interacts with canal design to affect canal maintenance cooperation and farmer income. The independent water source is stylized as a well that provides access to groundwater and represents a strategically robust design option; a design option that reduces the implementer's utility vulnerability to unfavorable actions by other actors. Research in other systems has demonstrated that strategically robust designs can improve both implementer utility and the probability of collaboration. The results of this research, in contrast, demonstrate that the option of individual resource access, the strategically robust design option, as represented by a well, reduces cooperative maintenance in most cases. However, wells also improve farmer income, especially for downstream farmers that are most affected by water theft.


© 2023 The Authors. Systems Engineering published by Wiley Periodicals LLC.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. (CC BY-NC)

Funding note: National Science Foundation. Grant Number: 1943433

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Systems Engineering