1a. Objectives (from AD-416):
1) Improve current decision making capabilities by building robust data on current practices existing agricultural systems where biomass production could be incorporated (Temple, Parlier, Mandan, Riverside); 2) Create management plans to optimize yield and stability of feedstock production (Temple, Palier, Mandan; 3) Optimize biomass stability and yield while minimizing environmental impacts at greater than field scales (Temple, Parlier, Mandan); and 4) Improve water and air resource management and optimize biomass production for other production areas in the Hawaiian Islands, Pacific Basin, and western United States (Temple, Parlier, Mandan, Hilo).
1b. Approach (from AD-416):
Objective 1: Develop spatial and temporal data sets from historic data for baseline analyses. Objective 2: Simulate current management impacts on feedstock yields and resource inputs. Objective 3: Demonstrate applicability of simulation approaches with validated present practices and explore watershed scale impacts of changes. Objective 4: Improve decision support for assessment of resource conditions, and utilize parallel computing and deep hydrology water balance as needed.
3. Progress Report:
The Navy's dependence on oil (petroleum) strains operational planning. Its focus is on securing a sustainable fuel supply. ARS research and models will help determine how best to manage natural resources to allow Office of Naval Research (ONR) sustainability in fuel supply while also promoting ecological services and the local economy in Hawaii. Energy sorghum and energy cane germplasm were exchanged with Hawaiian Commercial & Sugar Company (HC&S), and ARS used preliminary growth data from HC&S to validate ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria). In cooperation with Texas AgriLife Research scientists, SWAT (Soil and Water Assessment Tool) input files for more than 700 integrated management units (sugarcane fields) were developed using spatial data for elevation, land use, soils, stream network, canal network, dams/reservoirs, precipitation, and temperature. Model output was validated against measured sugarcane yields at six locations, and evapotranspiration algorithms were refined and validated. Web-based software was developed to allow users to remotely run the model, update daily precipitation and irrigation, and automatically map irrigation scheduling requirements on the web. We are currently working on an automated integration with HC&S management databases with implementation on HC&S computers. In cooperation with scientists at Baylor University and Texas AgriLife Research, seepage under irrigation canals and water supply reservoirs has been identified as potential sources of water loss. A geophysical technique called resistivity was applied to six irrigation reservoirs at varying elevations and geology to determine areas of active seepage. Initial results show a perched water table approximately 3 feet to 20 feet from the surface. To quantify the rate of seepage, a seepage meter was designed, developed, and applied to the six reservoirs that were analyzed using resistivity. Contrary to current understanding, all reservoirs showed a net influx of water, shifting focus on management of the perched water table to minimize seepage losses. Also, state-of-the-art doppler flow meter technology is being tested on canals to determine seepage losses. The methodology is currently being developed and refined for conditions on the HC&S plantation. Work was initiated to parallelize the SWAT code to run large, spatially detailed basins efficiently on supercomputers at the Hawaii Supercomputer Center. Current SWAT code was delivered to scientists at the University of Hawaii, and coding techniques to execute multiple subareas on individual processors of a supercomputer are being developed.