Mapping Stormwater Retention in the Cities: A Flexible Model for Data-Scarce Environments

Abstract:

There is a growing demand for understanding and mapping urban hydrological ecosystem services, including stormwater retention for flood mitigation and water quality improvement. Progress in integrated urban water management and low impact development in Western countries increased our understanding of how grey and green infrastructure interact to enhance these services. However, valuation methods that account for a diverse group of beneficiaries are typically not made explicit in urban water management models. In addition, the lack of spatial data on the stormwater network in developing countries makes it challenging to apply state-of-the-art models needed to understand both the magnitude and spatial distribution of the stormwater retention service. To fill this gap, we designed the Urban InVEST stormwater retention model, a tool that complements the suite of InVEST software models to quantify and map ecosystem services. We present the model structure emphasizing the data requirements from a user’s perspective and the representation of services and beneficiaries. We illustrate the model application with two case studies in a data-rich (New York City) and data-scarce environment. We discuss the difference in the level of information obtained when less resources (data, time, or expertise) are available, and how this affects multiple ecosystem service assessments that the tool is ultimately designed for.