Mountains to sea – fluvial transport of carbon and nutrients and effects on ecosystems and people Active
Stream transport (lateral transfer) of carbon remains a poorly understood flux within the global carbon budget. This research addresses the need to refine our knowledge of both provenance and transformations of Dissolved Organic Matter (DOM) as it moves from mountains to sea. Interpreting shifts in carbon quality with increasing stream order, and how these patterns change with variation in hydrologic and climatic drivers, are key to understanding how riverine DOM flux will respond to climate changes. Advances in sensor technologies and computational capacity have made DOM flux forecasting a reality and USGS carbon cycle researchers are well-positioned to contribute to this effort. As the carbon cycle is closely coupled to the nitrogen and phosphorus cycles, an excess of any of these nutrients is problematic. Too much DOM is a challenge in the potable water supply, and associated nutrients can cause harmful algal blooms in recreational waters. This project aims to better understand these carbon and nutrient fluxes across scales and develop predictive capability to provide warning to resource managers when adverse conditions are developing.
Statement of Problem:
DOM in lakes and streams has been rising for the past few decades, increasing its potential contribution to atmospheric CO2 as it mineralizes. Stream transport of DOM is problematic because (1) it has an understated role in the global carbon cycle; (2) it transports toxic metals; (3) too much humic DOM can form carcinogens during drinking water treatment; and (4) DOM interacts strongly with nitrogen and phosphorous to impact aquatic ecological functioning. We seek to uncover how changing land use and climate, including extreme floods and drought, affect quantity and quality of fluvial carbon, nitrogen, and phosphorous export to receiving water bodies.
Why this Research is Important:
Lateral (stream) transport of carbon is the “forgotten flux” in the global carbon budget. This research will improve estimates of historic and present-day carbon fluxes associated with water and sediment transport. By combining high-frequency, in-stream sensor measurements with advances in carbon quality determinations, we will better understand DOM provenance and fate while observing how landscape sources and in-stream processes combine to affect DOM flux. This improved quantitative understanding of processes controlling the biogeochemical cycling of carbon will help addresses a significant uncertainty in the global carbon budget. Furthermore, incorporating terrestrial carbon cycling in scenario-based predictive modeling of global change impacts will help to inform land management decisions.
Objective(s):
Specific objectives for this project include:
- Assess how carbon and nutrient export change with climate and land use and identify underlying processes driving export.
- Model shifts in hydrology and biogeochemical cycles for the range of anticipated future climate scenarios.
- Pilot the idea on integrating in-stream sensor data with GIS-derivable landscape metrics and point weather forecasts, toward the ultimate goal of real-time maps of CONUS carbon and nutrient export.
- Determine the conditions under which too much or the wrong type of DOM pose a risk to water supply.
- Determine how shifts in snowpack amount and snowmelt timing affect ground frost extent and the corresponding effect on carbon and nutrient export.
Methods:
Objective 1. Utilize an array of sensors to evaluate processes controlling DOM movement and transformations from zero order to 8th order streams. Start in the Connecticut River basin, then coordinate with USGS Water Resources Mission Area scientists to apply our method to the Delaware River basin. Cull out extreme events, either from prior to or occurring during the project timeframe, for focused analysis of nutrient export thresholds and tipping points.
Objective 2. Pending funding for a post-doc, apply the PnET-BGC, or a similar biogeochemical model, to predict future water, carbon, and nitrogen fluxes in response to a range of future climate scenarios.
Objective 3. In coordination with the USGS Water Prediction Work Program (2WP), build predictive DOM concentration models and test them in the National Water Model framework to assess the feasibility of adding a water quality forecasting component. Start in the Connecticut River basin and expand in scale.
Objective 4. Assess approaches to understand conditions that lead to episodes of high stream humic DOM flux, as assessed by UV254 absorbance, spectral slope, and fluorescence Excitation-Emission Matrices, as available, testing success by hindcasting on a subset of existing data.
Objective 5. Analyze the 59-year snow record and 35-year ground frost record at Sleepers River, VT, as well as snow and frost data from Hubbard Brook, NH and other current networks, to fill in spatial gaps with the National Weather Service modeled snow water equivalent output. We will pair long-term stream chemistry data with snowpack and ground frost data and apply empirical regression models to evaluate whether frozen winter ground stimulates organic carbon and nitrogen mobility in the following growing season.
Stream transport (lateral transfer) of carbon remains a poorly understood flux within the global carbon budget. This research addresses the need to refine our knowledge of both provenance and transformations of Dissolved Organic Matter (DOM) as it moves from mountains to sea. Interpreting shifts in carbon quality with increasing stream order, and how these patterns change with variation in hydrologic and climatic drivers, are key to understanding how riverine DOM flux will respond to climate changes. Advances in sensor technologies and computational capacity have made DOM flux forecasting a reality and USGS carbon cycle researchers are well-positioned to contribute to this effort. As the carbon cycle is closely coupled to the nitrogen and phosphorus cycles, an excess of any of these nutrients is problematic. Too much DOM is a challenge in the potable water supply, and associated nutrients can cause harmful algal blooms in recreational waters. This project aims to better understand these carbon and nutrient fluxes across scales and develop predictive capability to provide warning to resource managers when adverse conditions are developing.
Statement of Problem:
DOM in lakes and streams has been rising for the past few decades, increasing its potential contribution to atmospheric CO2 as it mineralizes. Stream transport of DOM is problematic because (1) it has an understated role in the global carbon cycle; (2) it transports toxic metals; (3) too much humic DOM can form carcinogens during drinking water treatment; and (4) DOM interacts strongly with nitrogen and phosphorous to impact aquatic ecological functioning. We seek to uncover how changing land use and climate, including extreme floods and drought, affect quantity and quality of fluvial carbon, nitrogen, and phosphorous export to receiving water bodies.
Why this Research is Important:
Lateral (stream) transport of carbon is the “forgotten flux” in the global carbon budget. This research will improve estimates of historic and present-day carbon fluxes associated with water and sediment transport. By combining high-frequency, in-stream sensor measurements with advances in carbon quality determinations, we will better understand DOM provenance and fate while observing how landscape sources and in-stream processes combine to affect DOM flux. This improved quantitative understanding of processes controlling the biogeochemical cycling of carbon will help addresses a significant uncertainty in the global carbon budget. Furthermore, incorporating terrestrial carbon cycling in scenario-based predictive modeling of global change impacts will help to inform land management decisions.
Objective(s):
Specific objectives for this project include:
- Assess how carbon and nutrient export change with climate and land use and identify underlying processes driving export.
- Model shifts in hydrology and biogeochemical cycles for the range of anticipated future climate scenarios.
- Pilot the idea on integrating in-stream sensor data with GIS-derivable landscape metrics and point weather forecasts, toward the ultimate goal of real-time maps of CONUS carbon and nutrient export.
- Determine the conditions under which too much or the wrong type of DOM pose a risk to water supply.
- Determine how shifts in snowpack amount and snowmelt timing affect ground frost extent and the corresponding effect on carbon and nutrient export.
Methods:
Objective 1. Utilize an array of sensors to evaluate processes controlling DOM movement and transformations from zero order to 8th order streams. Start in the Connecticut River basin, then coordinate with USGS Water Resources Mission Area scientists to apply our method to the Delaware River basin. Cull out extreme events, either from prior to or occurring during the project timeframe, for focused analysis of nutrient export thresholds and tipping points.
Objective 2. Pending funding for a post-doc, apply the PnET-BGC, or a similar biogeochemical model, to predict future water, carbon, and nitrogen fluxes in response to a range of future climate scenarios.
Objective 3. In coordination with the USGS Water Prediction Work Program (2WP), build predictive DOM concentration models and test them in the National Water Model framework to assess the feasibility of adding a water quality forecasting component. Start in the Connecticut River basin and expand in scale.
Objective 4. Assess approaches to understand conditions that lead to episodes of high stream humic DOM flux, as assessed by UV254 absorbance, spectral slope, and fluorescence Excitation-Emission Matrices, as available, testing success by hindcasting on a subset of existing data.
Objective 5. Analyze the 59-year snow record and 35-year ground frost record at Sleepers River, VT, as well as snow and frost data from Hubbard Brook, NH and other current networks, to fill in spatial gaps with the National Weather Service modeled snow water equivalent output. We will pair long-term stream chemistry data with snowpack and ground frost data and apply empirical regression models to evaluate whether frozen winter ground stimulates organic carbon and nitrogen mobility in the following growing season.