Collaborative models and uncertain water quality in payments for watershed services: China’s Jiuzhou River eco-compensation

• The relationship between PWS and water quality uncertainty is examined. • A stochastic differential game model of PWS is builded to examine this relationship. • Collaborative eco-compensation model in the PWS can achieve social optimality. • The collaborative eco-compensation is riskier than the horizontal eco-compensation. • Designing incentive-compatible PWS schemes remains challenging. As Payments for Watershed Services (PWS) schemes are widely implemented around the world, determining downstream payment rates based on expected water quality is critical to designing efficient PWS schemes. Combined with a case study of the Jiuzhou River Horizontal Eco-compensation (JRBHE) in China, this study builds a stochastic differential game model of PWS considering water quality uncertainty. Using this model, this study explores how water quality uncertainty affects the decision-making of watershed protection behaviors of various stakeholders in PWS. In comparing changes in stakeholder watershed protection behaviors in multiple JRBHE scenarios, this study argues that the collaborative eco-compensation model in the PWS can achieve social optimality as it can coordinate multi-stakeholder goals regarding watershed services and water quality. In addition, this study also emphasizes that the collaborative eco-compensation model is riskier than the existing horizontal eco-compensation model due to water quality uncertainty, and penalties aimed at reducing risk are often necessary for the collaborative eco-compensation model. Finally, this study highlights that designing incentive-compatible PWS schemes remains challenging because both water quality uncertainty and stakeholders’ risk preferences influence their ultimate watershed protection behavior.