USING REMOTE SENSING DATA FOR WATER CYCLE AND CARBON FLUX MODELING: MODEL SPIN-UP FOR THE AIRMOSS CAMPAIGN Xuan Yu 1, Christopher Duffy 1, Gopal Bhatt 1, Wade Crow 2, Hui Peng 3,4, Lorne Leonard 1, Yuning Shi 5, Sushil Milak 2 1. Civil & Environmental Engineering, Pennsylvania State University, 2. U.S. Dept. of Agric., Remote Sensing Lab., 3. Bren School of Environmental Science & Management, University of California at Santa Barbara, 4. Department of Water Resources Research, China Institute of Water Resources & Hydropower Research (IWHR), 5. Meteorology, Pennsylvania State University Works Cited K. E Mitchell et al., “The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system,” Journal of Geophysical Research 109, no. 7 (2004): D07S90. J. W. N. Smith et al., “Groundwater–surface water interactions, nutrient fluxes and ecological response in river corridors: Translating science into effective environmental management,” Hydrological Processes 22, no. 1 (2008): F. Stuart et al., Principles of terrestrial ecosystem ecology (Springer London, Limited, 2011). B. D Allen et al., “Proposed investigations from NASA’s Earth Venture-1 (EV-1) airborne science selections,” in Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International (IEEE, 2010), M. A White et al., “Parameterization and sensitivity analysis of the BIOME-BGC terrestrial ecosystem model: net primary production controls,” Earth interactions 4, no. 3 (2000): C. Zweck et al., “COSMOS: COsmic-ray Soil Moisture Observing System planned for the United States,” in AGU Fall Meeting Abstracts, vol. 1, 2008, F. Maselli et al., “Validating an integrated strategy to model net land carbon exchange against aircraft flux measurements,” Remote Sensing of Environment 114, no. 5 (2010): Cross Validation Penn State Integrated Hydrologic Model (PIHM) PIHM represents a strategy for the formulation and solution of fully-coupled process equations at the watershed and river basin scales, and includes a tightly coupled GIS tool for data handling, domain decomposition, optimal unstructured grid generation, and model parameterization. PIHM has been applied at different scales of watersheds across the world. AGU Chapman Hydro-Ecological Coupling of PIHM and Biome-BGC Vegetation Unsaturated Zone Saturated Zone Surface River Zone Saturated Zone Interception Snow Melt Overland Flow Unsaturated Zone Saturated Zone Channel Sub-Channel Aquifer H 2 O Cycle Litter Coarse Woody Debris Soil C and N Cycle Maintenance Respiration Photosynthesis Decomposition Allocation Growth Respiration Mortality Meteorological data, Vegetation parameters, Land cover, DEM, Soil, and Geology Hydrograph, ET, LAI, NEE, NPP, Biomass, fPAR, Soil Moisture, and Groundwater Table Level COSMOS AirMOSS Water Use Efficiency NPP/ET 0.92 g C/kg H 2 O Trends in Hydrologic Balance and Carbon Sink Carbon and Water Budget