| Groundwater contamination caused by agricultural fertilization is a widely recognized problem. In Hawaii, nitrogen fertilization from pineapple and sugarcane fields has posed a threat to several basal aquifers. The objective of this dissertation research is to develop a practical methodology for realistically estimating nitrate leaching from fertilized agricultural lands.; Numerous mechanisms have impact on the distribution and migration of nitrate in the soil. Nitrogen fertilizer undergoes many N transformations and interactions with the soil and the plant after applications. In this study, an analysis of soil samples was performed to understand the leaching process of nitrate in the root zone of three different cropped fields in Hawaii. A detailed discussion is given to address various factors which control the nitrate transport process. To judge the sampling plan in relation to spatial variation, the field measurements were evaluated statistically by an uncertainty index, which is represented as the density of samples required for the estimate of sample mean of the nitrate concentration to fall within a defined limit of accuracy.; In order to predict the effect of nitrogen fertilization on the groundwater contamination with very limited input data, a simple, analytical, lumped parameter model (LPM), was developed. The model can estimate the average nitrate leaching from the root zone in response to agricultural practices, N transformations and other related processes. The model was tested against the field data and two detailed numerical models, LEACHM-N and CERES-Maize. It provides an alternative way to assess nitrate leaching from the root zone with acceptable accuracy.; Owing to the complex nature of nitrogen behavior in the unsaturated zone, some degree of uncertainty is involved in the development of modeling approaches. In this study, five major sources of uncertainty were identified. These are: uncertainty due to spatial variation, uncertainty related to the accuracy of the input data, uncertainty due to simplifications in the development of the models, uncertainty due to modeling parameters, and uncertainty due to the complexity of the unsaturated zone in Hawaii. The impact of these uncertainties on simulation results is evaluated. |
