The Agricultural Policy/Environmental eXtender (APEX) model has been widely used to assess changes in agrochemical loadings in response to conservation and management led by US Department of Agriculture (USDA). However, the existing APEX model is limited in quantification of wetland water quality functions. This study improved the current model capacity to represent wetland water quality functions by addition of a new biogeochemical module into the APEX model. The performance of an enhanced APEX model was tested against five observed outgoing water quality variables (e.g., sediment, organic N, NO₃, NH₄ and PO₄) from a wetland within the Eastern Shore of Maryland. Generalized Likelihood Uncertainty Estimation (GLUE) was implemented to assess model uncertainty. The enhanced APEX model demonstrated that it could effectively represent N and P cycling within the study wetland. Although improvement of model performance was limited, the additions of wetland biogeochemical routines to the APEX model improved our understanding of inner mass exchanges within N and P cycling for the study wetland. Overall, the updated APEX model can provide policymakers and managers with improved means for assessment of benefits delivered by wetland conservation.

High frequency in-situ measurements of nitrate can greatly reduce uncertainty in nitrate flux estimates. Water quality databases maintained by various federal and state agencies often consist of pollutant concentration data obtained from periodic grab samples collected from gauged reaches of a stream. Regression models, such as the LOAD ESTimator (LOADEST), are frequently used to model variations in concentrations associated with changes in water discharge to provide integrated solute flux measurements. However, uncertainty in the relationships between nutrient concentration and flow may lead to errors in the corresponding flux estimates. In this study, a high frequency, in-situ measurement of nitrate concentration was implemented to ascertain uncertainty in the concentration/discharge relationship caused by nitrate hysteresis. It was found that observed nitrate hysteresis, as influenced by complex storm/watershed interactions, was not readily predictable. Therefore, it can lead to substantial nitrate flux uncertainty, based on periodic grab sample monitoring approaches. Scientists and engineers should take advantage of the proposed findings in future studies to enhance the quality of the associated decision making processes.