Climate-Smart Watershed Investments in the Montane Tropics of South America
Compensating upstream residents to manage their land in beneficial ways is one way to improve downstream water resources. Projects like this, referred to as Investments in Watershed Services (IWS), are spreading rapidly in montane regions of South America. But the hydrology of changing landscapes in tropical mountains is understudied, as are the impacts of climate change.
ClimateWIse, a new three-year project involving scientists from the University of Minnesota, the University of North Texas, the University of São Paulo, the University of Kassel, Germany, and the Natural Capital Project with support from the Belmont Forum through national funding agencies, is evaluating whether IWS projects increase water quality and availability. To do so, the project is using information and data from the Latin American Water Funds Partnership and the Brazilian Water Producer Program to measure and model impacts of land use and climate change on high-elevation páramo grasslands and Andean and Atlantic forests of South America.
In montane tropical South America, hydrologic impacts of changing land use and changing climate are poorly characterized, yet have tremendous impact on water security for both urban and rural communities. Millions of people depend on water from páramo grasslands and Andean and Atlantic forests, so it is critical to ensure clean, secure water through climate-resilient source water protection. ClimateWIse’s goals are to enhance sustainable water management by improving understanding of the hydrologic impacts of land use and climate change, increase the scientific foundation for ecosystem services–based management and enhance outcomes for water users throughout the region.
An existing network of IWS projects provides an unparalleled opportunity to assess and model current and future water resources in the region. ClimateWIse is helping answer critical questions about the hydrologic impacts of changing land use and changing climate by addressing two persistent questions about IWS projects: 1) Are IWS projects successfully delivering water services now? 2) How can the IWS approach be resilient to climate change?
To quantify the impact of land use change on water resources and thereby assess current IWS performance, the project is structured into six interconnected parts, three assessing the current situation and three investigating IWS climate resilience:
- evaluating the outcomes expected by IWS stakeholders
- compiling and analyzing IWS monitoring data
- improving modeled predictions of land use change impacts on water
- evaluating how IWS projects incorporate climate in their planning
- producing regional downscaled climate data and improving robustness and uncertainty assessment of climate-change impact predictions
- integrating findings to inform IWS planning.
ClimateWIse aims to improve water resource management by:
- quantifying hydrologic fluxes in tropical montane South America
- evaluating the impact of land-use change on water resources
- identifying critical conditions for IWS to successfully enhance water resources
- developing guidance to improve IWS design
- communicating findings specifically for IWS.
ClimateWIse aims to increase IWS resilience by:
- improving climate forecasts and predictions of watershed response for this region
- conceiving climate-smart IWS
- helping mainstream these adaptations into IWS planning
- working with stakeholders to communicate uncertainty.
Ultimately, the project aims to improve IWS design while providing crucial basic science about the impacts of land use and climate change on water resources in this sensitive region.
Meet the ClimateWIse Team
Humberto Rocha, at the Universidade de São Paulo, is leading field data collection and SWAT modeling in watersheds of the Atlantic Forest as well as developing downscaled climate data for use in evaluating IWS performance under climate change. This builds on his ongoing work in this region.
Martina Flörke, at the Center for Environmental Systems Research at the University of Kassel, is leading application of the WaterGAP3 model. Integrating a large-scale model into the analysis is crucial because there are many places for which there exists little or no data so modeled baselines are necessary.