Location:2011 Annual Report
1a. Objectives (from AD-416)
1. Streamline the procedure and training scientists for developing, testing, and improving stand-alone OMS-compatible science process modules of different agricultural systems derived from existing models or knowledge base for the OMS library, and integrating models from them. 2. Streamline the procedure and help scientists for testing and improving the modules and models created from them for a variety of applications. 3. Enhance the GPFARM-range modules and model for use in simulating a variety of range management practices, effects of climate change on forage, and soil carbon storage. Add modules for parameter estimation and scaling and improve root growth and water and N uptake components.
1b. Approach (from AD-416)
Procedures for building and testing modules and models will be streamlined and progressively improved. This will require storing in OMS of test datasets for testing the modules and models against. Active assistance will be provided to ASRU and other ARS modelers for creating, testing and improving OMS modules for a variety of agricultural systems, as well as auxiliary components (e.g., land unit delineation, parameter estimation, scaling, sensitivity and uncertainty analyses) needed for important applications, integration of these components into a running model, and showing the plug and play capability. A friendly, step-by-step, users manual and a tutorial developed for this purpose will be further improved. They will also be trained on how to test the modules and models against some data. The existing modules for a range-livestock model will be expanded to include components for effects of climate change on forage growth and quality of different forage species, and for soil carbon in the root zone. Continuing modifications will be made in OMS in response to users’ requirements and suggestions. Functionalities in OMS will be gradually progressively updated to make it an ARS advanced framework for developing, maintaining, and delivering models/tools at different scales for resource analysis, conservation planning, optimizing agricultural cropping and management practices, and practice design, from basic science components in a library. The components are readily updated or replaced as new knowledge becomes available.
3. Progress Report
Rangelands cover approximately 50% of the terrestrial surface of the earth. Consequently, the soil C and N storage and turnover in rangeland systems are becoming increasingly important for sustainable grazing management and climate change. With an increased concern for climate change, there has been a great interest in evaluating and enhancing C sequestration in rangelands. However, the GPFARM-Range package did not include a C-N cycle module for range simulation. In the past year, we developed a C-N cycle module for the GPFARM-Range model and tested the module against field measured carbon and nitrogen data from 1993-2006 at the USDA-ARS High Plains Grasslands Research Station near Cheyenne, WY. The C-N cycle module is written in JAVA, based on the science of Nitrogen Leaching and Environmental Analysis Package (NLEAP). This C-N cycle module includes environmental factor calculations, decomposition of surface forage residue, degradation of dead roots, nutrient cycle in the soil layers, and nutrient uptake by forage. Coefficients for the equations describing mineralization, immobilization and nitrification were adopted from NLEAP. The C-N cycle module of the GPFARM-Range model was calibrated and validated using field measured soil organic carbon and total organic nitrogen data from USDA-ARS High Plains Grasslands Research Station near Cheyenne, Wyoming. MODEVAL, a widely accepted statistical approach to evaluate the performance of C-N cycle modules, was used in this study. The results showed that the C-N cycle module of the GPFARM-Range model simulated the soil organic carbon and total nitrogen in a reasonable manner, with no significant bias or error. Meanwhile, the predicted annual peak standing crop for the period 1993-2006 matched well with the observed values with an index of agreement greater than 0.85. The C-N cycle module of GPFARM-Range model has a potential to simulate the carbon sequestration under climate change scenarios. Cooperating with China Agricultural University, we used the GPFARM-Range model to simulate the growth of Siberian grass in Inner Mongolia under various irrigation treatments. The preliminary result indicated that the simulated above ground biomass was in good agreement with observed data. The model has also been set up to simulate plant growth, soil water, and soil nitrate for a cultivated mixed forage land in Iowa. Using measured forage growth data under elevated [CO2], we are testing the capability of the GPFARM-Range model in predicting the biomass accumulation under various [CO2] levels. Further work is needed to enhance the use of the C-N cycle module of GPFARM-Range: 1) to evaluate the performance of GPFARM-Range model in simulating forage growth, hydrology, and nutrient cycling using data outside the Great Plains; 2) to test the C-N cycle module with a longer term dataset with more frequent soil carbon and nitrogen measurements; 3) to predict the carbon sequestration under climate change with increased temperature and [CO2], higher variance in precipitation, and changing plant structure. ADODR monitoring is performed via phone/conference calls, e-mails, and personal meetings.