Description: This proposal is submitted under the Innovative Tools and Techniques Supporting the Practical Uses of Earth Science Observations topic. We seek to evaluate and demonstrate technical approaches for linking remote sensing rangeland products with a soil biogeochemical model to form a decision support system for improved rangeland management. The resulting decision support system will be unique and innovative by not only providing operational remote sensing observations of rangeland condition, but also web-based tools that utilize these observations to provide critical information on soil fertility/productivity, greenhouse gas emissions, and potential erosion and sedimentation. Our Rangeland Decision Support System will build off of existing RANGES and DNDC tools. Landsat and MODIS prototype processing algorithms for rangeland condition (height, forage production, fractional cover) have been developed under the previous RANGES project. Our decision support system will couple RANGES products with the DeNtrification-DeComposition (DNDC) model. DNDC is a unique, spatially explicit, soil biogeochemical model that simulates both aerobic and anaerobic soil conditions, estimates crop yields based on a detailed crop physiology-phenology model, and is designed for assessing the net impact of alternative management on long-term soil organic carbon (SOC) dynamics and emissions of N2O, NO, CH4, and NH3 for upland and wetland agricultural ecosystems.

Benefits: We anticipate our routine mapping and monitoring of rangeland products will be a very useful service to support USDA Risk Management Program needs for Risk Management Products for Pasture /Rangeland and forage systems as part of the USDA Federal Crop Insurance Corporation (FCIC). In addition, as the US EPA Total Maximum Daily Load criteria are set for rangeland watersheds, tools will be needed to map and monitor pollutant contributions across these watersheds. The RANGES products coupled with the information on C and N cycling and susceptibility to erosion and sedimentation will be extremely useful for the TMDL process.