1a. Objectives (from AD-416):
1) Improve current decision making capabilities on Hawaii Commercial and Sugarcane (HC&S) land by building robust data on current practices; 2) Create management plans to maximize yield and stability of feedstock production; 3) Maximize bioenergy biomass stability and yield while minimizing environmental impacts at watershed scale; and 4) Improve water resource management and optimize biomass production for other production areas in the Hawaiian Islands and Pacific Basin.
1b. Approach (from AD-416):
Collect and synthesize available topography, soils, climate and historical management data. Improve ALMANAC Soil Carbon modeling abilities with historical and contemporary. Initial ALMANAC runs with historical data (plant growth parameters, soils, precipitation, etc.) on three individual fields under current management. ALMANAC runs with current sugarcane as compared to other potential biomass crops on 3 individual fields. ALMANAC simulation changing agronomic management to achieve maximum yields on 3 individual fields. Install or identify fields/plots of sugarcane and other biofuel crops in Hawaii. Measure plant physiological and soil parameters over time, under changing climatic conditions. With improved model, simulate alternative agronomic management of additional fields, including changing feedstocks, and nutrient and water management. Conduct a biomass production assessment for potential agricultural production areas of the islands using ALMANAC. Develop and analyze Island-wide scenarios, as defined by local stakeholders, related to the impact of bioenergy feedstock development on annual production risk, water resources, potential carbon sequestration, and displacement of other agricultural and natural systems. Explore applicability of the models on other islands and countries in the Pacific Basin.
3. Progress Report:
Progress has been made to gather key ALMANAC model parameterization data for the evaluation of candidate high biomass energy crops: sugarcane, energy cane, energy sorghum, and banagrass. (1) Crop parameters - the basic plant growth processes that need to be parameterized to simulate bioenergy crop growth and yields. Model simulations of growth processes, such as leaf area index (LAI) over time, and dry matter accumulation, are currently being conducted to fine-tune the parameters and test the accuracy of model simulated vs. measured data. (2) Crop management - this includes information on land preparation, fertilizer application, planting, irrigation and harvesting. For sugarcane, historical crop management data for 8 fields during a 13-year period (1999-2012) will be used to further validate model performance. (3) Soils data – Currently, the ALMANAC model uses the USDA-NRCS Soil Survey Geographic (SSURGO) database for soil parameter inputs. Soil parameter data gathered by project co-operating partners (University of Hawaii at Manoa, and USDA-ARS Parlier, CA) has proved invaluable in correcting soil parameter errors in some specific test field sites. (4) Weather data - For more accurate model testing, field-specific weather data (18 stations) was obtained from Hawaiian Commercial and Sugar Company and processed into ALMANAC compatible input formats. Given the competition for the water resources in Hawaii, sustainable production of bioenergy feedstocks will be driven by management strategies that optimize water use efficiency, enhance feedstock yields, while minimizing environmental impacts. By working closely with project cooperators, we were able to obtain crucial model parameterization data for evaluating water use efficiency and potential bioenergy cropping systems' impacts on ecosystems services; soil organic carbon by depth, greenhouse gas fluxes (CO2, N2O, and CH4, and related soil moisture and temperature), pH, soil nutrient content, etc. Simulations to compare the productivity and global warming potentials of sugarcane (a crop with a high water-demand) and banagrass (a relatively drought-tolerant bioenergy crop) at three irrigation levels (full irrigation-100%, 75%, and 50%) are being conducted. Set to begin in 2014, we will adapt and apply the generated technologies to the southern USA, a region that has the perfect agroclimate for optimizing bioenergy feedstock production.
Meki, M.N., Snider, J.L., Kiniry, J.R., Raper, R.L., Rocateli, A.C. 2013. Energy sorghum biomass harvest thresholds and tillage effects on soil organic carbon and bulk density. Industrial Crops and Products. 43:172-182.