A Probabilistic Framework for Projections of Watershed Services in US Headwaters under Climate Change ScenariosEPA Grant Number: R834196
Title: A Probabilistic Framework for Projections of Watershed Services in US Headwaters under Climate Change Scenarios
Investigators: Wagener, Thorsten
Institution: Pennsylvania State University
EPA Project Officer: Hiscock, Michael
Project Period: August 1, 2009 through July 31, 2012 (Extended to July 31, 2013)
Project Amount: $239,782
RFA: Consequences of Global Change for Water Quality (2008) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Global Climate Change , Water and Watersheds , Ecosystems , Climate Change , Water
Watersheds collect, store and release incoming precipitation and thus provide important freshwater!related ecosystem services for aquatic ecosystems and for human uses. US headwaters are particularly important source regions and highly sensitive to climate change impacts. However, observational networks are strongly biased towards larger rivers, despite the increasingly recognized importance of headwaters in controlling ecological and water quality functions throughout river basins. Our hydrologic knowledge of and modeling capabilities in these headwaters are very low, which severely limits our ability to assess ecosystem services.
To provide probabilistic projections of indicators of watershed services for aquatic ecosystems and human uses in US headwaters under climate change scenarios through  Characterizing changes to (freshwater flow and temperature dependent) indicators of watershed services under climate change scenarios in a probabilistic framework,  Identifying main controls (and uncertainties) on these indicators,  Estimation of resulting changes to watershed!scale ecosystem services for selected headwater basins in different US regions.
A general Bayesian framework – combining mechanistic watershed models and global sensitivity analysis tools – builds on and extends tools and methods of previous NOAA/NWS and NSF grants: (1) Assimilate local and regional information on watershed physical characteristics and response behavior into an ensemble of mechanistic models in a Bayesian framework, (2) Dynamically downscale climate change scenarios for different US headwaters over different time scales as model forcing and develop probabilistic hydrologic response scenarios (incl. stream flow and temperature) for these watersheds, (3) Characterize changes to watershed!scale services for aquatic ecosystem by extracting probability distributions of significant indicators, and by understanding their controls through global sensitivity analysis. (4) Use the probabilistic indices predictions to project changes to headwater ecosystem services in different regions of the US to understand the sensitivity of key water quality and ecosystem management targets to climate change.
Successful execution of this project would significantly advance our ability to simulate the impact of climate change on US headwater ecosystem services, and therefore on the future of aquatic ecosystems and the sustainability of human water uses.