Developing a Robust Strategy for Implementing a Water Resources Master Plan in Lima, Peru

Abstract:

Lima, the capital of Peru, faces significant water stress. It is the fifth largest metropolitan area in Latin America, and the second largest desert city in the world. The city has developed a Master Plan of major investment projects to improve water reliability until 2040. Yet key questions remain. Is the Master Plan sufficient for ensuring reliability in the face of deeply uncertain future climate change and demand? How do uncertain budget and project feasibility conditions shape Lima’s options? How should the investments in the plan be prioritized, and can some be delayed? Lima is not alone in facing these planning challenges. Governments invest billions of dollars annually in long-term projects. Yet deep uncertainties pose formidable challenges to making near-term decisions that make long-term sense.

The World Bank has spearheaded a community of practice on methods for Decision Making Under Deep Uncertainty (DMU). This pilot project in Peru is the first in-depth application of DMU techniques to water supply planning in a developing country. It builds on prior analysis done in New York, California, and for the Colorado River, yet shows how these methods can be applied in regions which do not have as advanced data or tools available. The project combines three methods in particular -- Robust Decision Making, Decision Scaling, and Adaptive Pathways -- to help Lima implement its Master Plan in a way that is robust, no-regret, and adaptive. It was done in close partnership with SEDAPAL, the water utility company in Lima, and in coordination with other national WRM and meteorological agencies.

This talk will:

• Present the planning challenges Lima and other cities face, including climate change
• Describe DMU methodologies and how they were applied in collaboration with SEDAPAL
• Summarize recommendations for achieving long-term water reliability in Lima
• Suggest how these methodologies can benefit other investment projects in developing countries.