Madicke Seck
Madicke Seck
Postdoctoral
NOAA
NOAA/National Oceanic and Atmospheric Administration
1401 Constitution Avenue NW, Room 5128
Washington, DC 20230
WY
20230
Email
Phone
Website
Fields of interest
Inland Waters, Carbon Biogeochemistry, Remote Sensing and GIS, Land-Water linkages
Description of scientific projects
This methodology outlines the systematic approach to studying inland waters, carbon biogeochemistry, remote sensing and GIS applications, and the critical linkages between terrestrial and aquatic systems.
1. Inland Waters
The focus is on understanding the dynamics of inland water systems, including lakes, rivers, and wetlands.
• Hydrological Monitoring:
o Install and maintain field-based sensors for real-time measurement of water flow, temperature, and turbidity.
o Utilize stream gauges and automated water level loggers to collect hydrological data over time.
• Water Quality Assessment:
o Conduct sampling for parameters such as dissolved oxygen, nutrients (nitrogen and phosphorus), and contaminants.
o Use portable spectrophotometers and laboratory analysis for chemical and biological testing.
• Modeling and Analysis:
o Apply hydrodynamic models (e.g., SWAT or HEC-RAS) to simulate water flow and pollutant transport.
o Perform statistical analyses to identify trends and assess the impact of climate and anthropogenic changes.Carbon Biogeochemistry
The aim is to explore carbon cycling within aquatic and terrestrial ecosystems and its contribution to global carbon fluxes.
• Carbon Flux Measurements:
o Deploy eddy covariance towers to measure carbon dioxide (CO₂) and methane (CH₄) fluxes in wetland and inland water systems.
o Use floating chambers and dissolved gas analysis for precise quantification of carbon emissions.
• Soil and Sediment Sampling:
o Collect sediment cores to analyze organic carbon content and historical deposition trends.
o Perform isotopic analysis (δ¹³C and δ¹⁵N) to trace carbon sources and processes.
• Biogeochemical Modeling:
o Employ ecosystem models like CENTURY or PnET-CN to simulate carbon storage, decomposition, and exchange dynamics.
o Integrate climate data to project future carbon cycle feedbacks.
o Remote Sensing and GIS Applications
2. Remote sensing and GIS are essential for spatial analysis and monitoring of land and water systems.
• Satellite Data Acquisition:
o Utilize datasets from satellites like Landsat, MODIS, Sentinel-2, and ICESat-2 for high-resolution imagery and environmental monitoring.
o Integrate LiDAR data to analyze topography and vegetation structure.
• Image Processing:
o Use software such as ENVI, ArcGIS Pro, or Google Earth Engine to process remote sensing data for classification and change detection.
o Develop indices (e.g., NDVI, NDWI) to assess vegetation health and water surface dynamics.
• Geospatial Analysis:
o Apply GIS to map land-use changes, watershed boundaries, and areas of potential erosion or pollution.
o Use spatial statistics and machine learning models for predictive mapping and scenario analysis.
Land-Water Linkages
Investigating the interactions between terrestrial ecosystems and aquatic systems is critical for understanding nutrient flows and ecosystem health.
• Nutrient Flux Monitoring:
o Install automated samplers at river mouths and watershed outlets to measure nutrient transport during various flow regimes.
o Analyze soil erosion and runoff patterns using tracer techniques and sediment fingerprinting.
• Biodiversity Surveys:
o Conduct field assessments of aquatic and riparian species to understand the impact of land-use changes on biodiversity.
o Use eDNA (environmental DNA) techniques for non-invasive monitoring of aquatic species.
• Integrated Modeling:
o Use coupled land-water models such as HydroTrend or SPARROW to simulate nutrient and sediment fluxes across landscapes.
o Incorporate climate and land-use scenarios to predict future impacts on water quality and ecosystem services.
Cross-Cutting Strategies
• Data Integration:
o Combine field measurements, remote sensing, and model outputs to create a comprehensive understanding of inland waters and their linkages with terrestrial systems.
• Stakeholder Collaboration:
o Engage local communities, policymakers, and scientists in co-designing research goals and applications.
• Monitoring and Evaluation:
o Establish long-term observation sites and protocols for data quality assurance and trend analysis.
1. Inland Waters
The focus is on understanding the dynamics of inland water systems, including lakes, rivers, and wetlands.
• Hydrological Monitoring:
o Install and maintain field-based sensors for real-time measurement of water flow, temperature, and turbidity.
o Utilize stream gauges and automated water level loggers to collect hydrological data over time.
• Water Quality Assessment:
o Conduct sampling for parameters such as dissolved oxygen, nutrients (nitrogen and phosphorus), and contaminants.
o Use portable spectrophotometers and laboratory analysis for chemical and biological testing.
• Modeling and Analysis:
o Apply hydrodynamic models (e.g., SWAT or HEC-RAS) to simulate water flow and pollutant transport.
o Perform statistical analyses to identify trends and assess the impact of climate and anthropogenic changes.Carbon Biogeochemistry
The aim is to explore carbon cycling within aquatic and terrestrial ecosystems and its contribution to global carbon fluxes.
• Carbon Flux Measurements:
o Deploy eddy covariance towers to measure carbon dioxide (CO₂) and methane (CH₄) fluxes in wetland and inland water systems.
o Use floating chambers and dissolved gas analysis for precise quantification of carbon emissions.
• Soil and Sediment Sampling:
o Collect sediment cores to analyze organic carbon content and historical deposition trends.
o Perform isotopic analysis (δ¹³C and δ¹⁵N) to trace carbon sources and processes.
• Biogeochemical Modeling:
o Employ ecosystem models like CENTURY or PnET-CN to simulate carbon storage, decomposition, and exchange dynamics.
o Integrate climate data to project future carbon cycle feedbacks.
o Remote Sensing and GIS Applications
2. Remote sensing and GIS are essential for spatial analysis and monitoring of land and water systems.
• Satellite Data Acquisition:
o Utilize datasets from satellites like Landsat, MODIS, Sentinel-2, and ICESat-2 for high-resolution imagery and environmental monitoring.
o Integrate LiDAR data to analyze topography and vegetation structure.
• Image Processing:
o Use software such as ENVI, ArcGIS Pro, or Google Earth Engine to process remote sensing data for classification and change detection.
o Develop indices (e.g., NDVI, NDWI) to assess vegetation health and water surface dynamics.
• Geospatial Analysis:
o Apply GIS to map land-use changes, watershed boundaries, and areas of potential erosion or pollution.
o Use spatial statistics and machine learning models for predictive mapping and scenario analysis.
Land-Water Linkages
Investigating the interactions between terrestrial ecosystems and aquatic systems is critical for understanding nutrient flows and ecosystem health.
• Nutrient Flux Monitoring:
o Install automated samplers at river mouths and watershed outlets to measure nutrient transport during various flow regimes.
o Analyze soil erosion and runoff patterns using tracer techniques and sediment fingerprinting.
• Biodiversity Surveys:
o Conduct field assessments of aquatic and riparian species to understand the impact of land-use changes on biodiversity.
o Use eDNA (environmental DNA) techniques for non-invasive monitoring of aquatic species.
• Integrated Modeling:
o Use coupled land-water models such as HydroTrend or SPARROW to simulate nutrient and sediment fluxes across landscapes.
o Incorporate climate and land-use scenarios to predict future impacts on water quality and ecosystem services.
Cross-Cutting Strategies
• Data Integration:
o Combine field measurements, remote sensing, and model outputs to create a comprehensive understanding of inland waters and their linkages with terrestrial systems.
• Stakeholder Collaboration:
o Engage local communities, policymakers, and scientists in co-designing research goals and applications.
• Monitoring and Evaluation:
o Establish long-term observation sites and protocols for data quality assurance and trend analysis.