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 Hydrology and Remote Sensing Laboratory: Beltsville, MD
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ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Hydrology and Remote Sensing Laboratory Research





- Zhang, Xuesong
- Water Availability and Watershed Management (211)
- Sustainable Agricultural Systems Research (216)

Research Project: **Location:
                            Hydrology and Remote Sensing Laboratory** Project Number: 8042-13610-030-082-I
                        
                        Project Type: Interagency Reimbursable Agreement Start Date: Aug 9, 2023
                        
                        End Date: Aug 8, 2024 **Objective:**
                        
                        Chesapeake Bay Program identified climate/carbon sequestration as an important co-benefit of nutrient and sediment and pollutant best management practices (BMPs) (e.g., cover crops, no-till or conservation tillage) that should be quantified and considered in planning future ecosystem restoration. However, to date, there is a lack of carbon monitoring system in the Chesapeake Bay Watershed that provide decision makers information regarding the amount of carbon is removed and sequestered as a result of those agricultural conservation practices. The project aims to develop a Carbon Monitoring System for the Chesapeake Bay Watershed (CBW-CMS) to monitor the changes in major carbon budget components to support ecosystem restoration decision making. **Approach:**
                        
                        ARS will (1) develop cropland tillage and cover crop maps over the entire CBW by leveraging multi-source remote sensing data (e.g., Landsat, Sentinel-2, WorldView-3, and PACE) and in situ measurements; (2) integrate the newly developed tillage and cover crop maps and other ancillary data (e.g., Evapotranspiration from  ECOSTRESS, vegetation characteristics from GEDI, SIF from OCO-2 and -3) with the Soil and Water Assessment Tool - Carbon (SWAT-C) to assess impacts of historical agricultural conservation on carbon sources and sinks in both land and river networks, as well as the export to the Bay; (3) collaborate with CBP and CC to use the data and modeling results to evaluate carbon budgets impacts of planned agricultural conservation efforts, thereby supporting prioritizing critical projects that maximize both water quality and climate benefits.


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