A modelling framework for nature-based solutions expansion planning considering the benefits to downstream urban water users. (June 2022) - Possantti, Iporã; Marques, Guilherme
Abstract: How and when to upscale and finance nature-based solutions in watersheds in order to improve downstream urban water security is a global concern. In this paper we address such challenge by providing a novel method for planning the expansion of a chosen set of nature-based solutions that couples optimization of sequential decision-making, hydrology modelling and hydroeconomics in a single modeling framework. The benefits were considered the avoided costs of water scarcity and water treatment perceived downstream. The optimal expansion schedule of decisions was then defined under the objective function of minimizing total cost. We demonstrated the framework by applying it to a set of benchmark alternative scenarios for the Sinos River watershed (Brazil). We found that the optimal schedule of nature-based solutions expansion is sensitive to the initial land use and future drivers. Treatment cost reduction was the greatest feature in some scenarios, confirming it as a strategy for addressing water quality issues of degraded watersheds. But the accounting of water scarcity cost introduced a tradeoff: expansion of nature-based solutions in well-preserved watersheds may not worth the investment. Future research may improve current limitations in scope and models without structural changes in the framework. Practical implications of this work arise from the funding of watershed payments for environmental services projects by institutions and governments, which demand evidence-based policies to support investment of public resources. Graphical abstract: Image 1 Highlights: A modelling framework for nature-based solutions expansion planning is provided considering benefits to downstream cities. The framework integrates hydrology modelling, sequential decision-making optimization and water resource economics. Given future projections, the tool help water managers understand how land use can be dynamically and optimally changed. The framework is both conceptually and procedurally flexible to allow continuous improvement from future research.