This study evaluates four project-selection strategies within the context of an irrigation-system upgrade conservation program. The strategies encompass a spectrum of cost-effectiveness, ranging from entirely non-quantitative approaches to Pareto-optimal methods. Program costs include expenditures for materials and labor associated with irrigation system upgrades, while program benefits are defined as reductions in edge-of-field phosphorus runoff. We investigate the sensitivity of program costs to uncertainty in landowner participation (recruitment percentage) and benefit valuations. We provide a comprehensive quantification of program costs capturing the effects of these uncertainties using a Monte Carlo sampling approach. Findings indicate that, under the most cost-effective strategy, program costs decline as participation increases. Furthermore, across all scenarios, the cost differential between less efficient strategies and the most cost-effective strategy widens with increasing participation rates. These results underscore the critical importance of employing cost-effective project-selection strategies, particularly under conditions of high participation. Additionally, we demonstrate probabilistic methods for integrating uncertainty in both recruitment percentage and project cost-effectiveness, and complement these with a non-probabilistic framework for assessing potential risks and windfalls. Collectively, these approaches advance understanding of the interactions among strategy choice, recruitment uncertainty, benefit valuation errors, and conservation program costs. Although the approach is demonstrated using an irrigation upgrade program, the underlying economic relationships among landowner participation, benefit valuation, and program cost are broadly applicable to other conservation contexts. • Greater landowner participation reduces prioritized conservation costs. • Cost is independent of landowner participation under net benefit constraints. • Under-valued benefits reduce costs but also increase risk of missing targets. • Probabilistic recruitment assumption errors propagate into cost estimates. • Non-probabilistic analysis informs risk/windfall potential.
Harp et al. (Fri,) studied this question.