Type of Document:
Thesis or Dissertation
Virginia Polytechnic Institute and State University
Date of Publication:
Place of Publication:
Abstract: An increase in population in rural agricultural communities and higher demand for food throughout Bolivia create the need for increased agricultural production. The objectives of this study was to assess the suitability of the GLEAMS model as a tool for evaluating fertilization and cropping system practices for potatoes in the Andes of central Bolivia, and make recommendations for the continued development of the model as an analysis tool to improve sustainable crop production. Model suitability was evaluated through assessment of model representation of observed potato farms and behavior of simulated soil nitrogen (N) and N transformation trends; validation with field data taken from six agricultural sites in central Bolivia for runoff volume, soil total Kjeldahl N concentration, crop production, and crop N uptake; and sensitivity analysis.
Validation of model output with observed values was completed both graphically and by determining the root mean square error standard deviation ratio (RSR) and the percent bias (PBIAS). RSR and PBIAS values for runoff volume were 4.0 and 65%, 4.5 and 4%, and 2.7 and 55% for three respective experimental plot repetitions using a calibrated SCS curve number of 90. The RSR and PBIAS, respectively, for soil total Kjeldahl N concentration were 3.0 and -2.2%. The RSR and PBIAS, respectively, for crop dry matter production were 7 and 21%. The RSR and PBIAS, respectively, for crop N uptake were 10 and 21%.
The mineralization processes in GLEAMS must be improved before model application to central Bolivia, where agricultural production is highly dependent on mineralization of organic N from soil and applied animal manure. Recommendations for model improvement and development include modification to the process that determines mineralization from the soil potentially mineralizable N pool; validation of the percolation volume and nitrate leaching losses; and improved model representation of banded manure application.