We propose to develop 1km x 1km and merged 1o x 1 o global biofuel productivity potential (BPP) datasets for current (Sorgham, Switchgrass, Miscanthus) and for special case next generation cellulosic distributions, simulate the net productivity of biofuel crops, and their nutrient and water requirements for several sub-domains. Results from this study will be used to quantify the impacts of a shift in land use from natural vegetation and food crop distributions to natural vegetation and food and energy crop distributions, and will serve as input biofuel productivity distributions for complementary climate, water, and economic impacts analyses.
Determination of optimal BPP growing areas hinges on the regional-to-local physical properties; photosynthetically active radiation (PAR), growing season diurnal temperature range (DTR), volumetric soil moisture content (SWC), and available nutrients (nitrogen, phosphorus, sulfur). Spatial mapping of BPPs will be based on the improved Moderate Resolution Imaging Spectroradiometer (MODIS) products that are available only through the Numerical Terradynamic Simulation Group in the Department of Ecosystem and Conservation Science at UM combined with geographic information on the physical constraints available from the UCB Geospatial Imaging and Informatics Facility and the Geography Department. We will generate a unique and new assimilated product with layered Geographic Information System (GIS) distributions characteristic of optimal growing areas, and we will mask out regions that are deemed poor growing areas, as determined by the above physical properties. This will be revisited in the third year with an economic analysis overlay indicating likely regions that are sustainable and unsustainable under shifts in land use from food crops to food and fuel crops.
The resulting BPP spatial distributions will be used as input to numerical biofuel crop productivity potential simulations under current and projected conditions, including new BPP types and distributions, and climate change scenarios. We will use a state-of-the-art biogeochemistry cycling model to simulate the range of biofuel distributions with IPCC AR4 climate scenario data as input forcing to determine the productivity, nutrient loading, and water requirements.
This project brings together top researchers from the Berkeley Water Center, Geography Department, Agricultural and Resource Economics Department, Environmental Science, Policy, and Management Department, the LBNL Climate Science Department, and a joint UCB and UMM team that will work together to develop new assimilated products. Teaming with the Numerical Terradynamic Group was deemed essential if we want to advance our understanding of biofuel production and its limits with new satellite-observed capabilities, an important research area that we will jointly grow into the Geography Department and the Geospatial Imaging and Informatics Facility.
Collaborators
on this project include Norm Miller, Dave Sunding, Steve Running.
