Collaborative Research: Modeling DOC dynamics from landscapes to coasts: hydrological connectivity and estuary processes

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Intellectual Merit: The origin, function, and fate of dissolved organic carbon (DOC) in terrestrial ecosystems and its transport processes from landscapes to sea are only partially understood. In this proposed research, statistical and GIS-based transport models are used to study DOC dynamics in terrestrial ecosystems and rivers. The research objectives are three-fold: 1) To analyze the spatial variability of DOC contributions from land surfaces to streams at sub-basin scales. 2) To identify the transport and transformation mechanisms behind long (decades) and short (days to months) term DOC fluctuations due to natural and anthropogenic influences. 3) To predict DOC concentration from remote sensing reflectance, turbidity and chlorophyll in rivers. In the past several years, a large amount of field data, has been collected including 5-years of monthly DOC measurements in 30 sub-basins, high spatial and temporal resolution riverine observations, and remote sensing imagery. Equipped with these data, the team will rely mainly on an approach that integrates statistical modeling and GIS-based transport modeling. Specifically, they will 1) Use an adaptive varying coefficient mixture model to derive monthly DOC loads from uniform land use types. 2) Construct a GIS-based transport model for routing DOC mass in the drainage stream network. 3) Use a varying coefficient functional linear model and nonparametric functional model to predict DOC through remote sensing 4) Validate the above models with independent data sets from two specific river watersheds. The geosciences contribution from this project lies in the improved understanding of the DOC export processes influenced by interactions among human activities, natural events, watershed characteristics, and climate. The statistical contribution lies in the innovative estimation and inference procedures that are particularly adapted to this complex geoscience data. Broader impacts: This proposed research will improve the scientific understanding of carbon export processes from land to coastal waters. Funding of this project will potentially change the public?s perception of the influence of their actions in coastal communities. This research will result in a modeling technique that is suitable for studying interactions among watershed properties, human activities, natural events and climate change. The project provides learning opportunities for all participating students. The methods, models, and data from this research will be integrated into undergraduate and graduate teaching programs in a broad range of disciplines (statistics, biogeochemistry, remote sensing, hydrology, and modeling). The collaboration offers students access to cutting edge modeling techniques and environmental sciences through an equal partnership of two diverse research institutions. Especially, the two female PIs will be valuable assets in guiding female graduate students to become future fellow scientists (statisticians and geo-scientists) with their own experiences. Coastal carbon research-related instructional materials will be developed and disseminated through existing educational programs and The Bridge website. These outreach efforts will strongly benefit from early experience on the COSEE-New England and Watershed-Integrated Sciences Partnership (GK-12) programs.