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Abstract Increasing wildfire activity can impact the global carbon cycle, aquatic ecosystem health, and drinking water treatment through alterations in aquatic dissolved organic matter (DOM) composition. However, uncertainty remains about the spatial and temporal variability in wildfire effects on DOM composition. We sought to improve understanding of how burn severity affects stream DOM and how weather, hydrology, and landscape factors contribute to variability in post‐fire DOM responses across space and time. Following a large 2020 wildfire in Oregon, USA, we collected water samples to quantify dissolved organic carbon and DOM optical properties at 129 stream sites across the fire‐affected stream network. Sampling was repeated across seasonal hydrologic conditions to capture variation in hydrologic pathways and organic matter sources. We developed a PARAFAC model using excitation‐emission matrices (EEMs) and used spatial stream network (SSN) models to determine how DOM composition changed across the stream network with burn severity. The greatest shifts in DOM composition were observed during the dry and wetting seasons, with an increase in aromatic DOM at higher burn severities. In contrast, an increase in protein‐like DOM was observed during the wet season at higher burn severities. Drainage area, 31‐day and 1‐day antecedent precipitation, and baseflow index impacted the relationship between DOM composition and burn severity, which could partially explain the variability in post‐fire DOM responses. Our study contributes a mechanistic understanding of how wildfire impacts DOM sources and composition, which is critical to predicting wildfire effects on aquatic biogeochemical cycling and preserving ecosystem health and source water quality.
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Characterizing hydrologic networks: Developing a tool to enable research of macroscale aquatic networks
Addressing continental scale challenges affecting inland aquatic systems requires data at comparable scales. Critically, local in-situ observations for both lotic and lentic ecosystems are frequently fragmented across federal, state and local agencies, and nonprofit or academic organizations and must be linked to other geospatial data to be useful. To advance macro-scale aquatic ecosystem science, better tools are needed to facilitate dataset integration. Key to integration of aquatic data is the linking of spatial data to the hydrologic network. This integration step is challenging as hydrologic network data are large and cumbersome to manage. Here we develop a new R package, hydrolinks, to ease linking aquatic data to the hydrologic network. We use hydrolinks to evaluate the spatial data quality for all lake and stream sites available through the U.S. Water Quality Portal. We find that 76.5% of lake sites and 13.9% of stream sites do not correspond with mapped waterbodies.
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- Award ID(s):
- 1638704
- PAR ID:
- 10092237
- Date Published:
- Journal Name:
- Environmental modelling & software
- Volume:
- 104
- ISSN:
- 1364-8152
- Page Range / eLocation ID:
- 94-101
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5281/zenodo.1169399
