Developing an Automated Uncertainty Quantification Tool to Improve Watershed-Scale Predictions of Water and Nutrient Cycling; Topic/Subtopic: 1c

Managing the flow of water, nutrients, and contaminants in watersheds is vital to addressing pressing issues related to water scarcity, access to clean drinking water, energy production, resilience to natural and anthropogenic perturbations, and ecological restoration- Decisions about the management of watersheds critically depend on the accuracy with which the flow of water and chemicals through the watershed can be predicted by computer models- Prediction uncertainty can be reduced by matching the model to data, which are collected in the field at great expense- The contribution of watershed characterization data to reducing uncertainty of relevant model predictions can be evaluated in a so-called data-worth analysis- The purpose of the proposed data-worth analysis (and the associated computer programs) is to help decision-makers allocate resources for watershed characterization such that the uncertainty in model predictions can be significantly reduced, which leads to better, more effective management decisions- At the same time, watershed characterization costs can be reduced- This goal is achieved by calculating how much each data point collected in the field can reduce the uncertainty in target predictions requested by the decision-makers- An uncertainty analysis determines whether the prediction uncertainties are sufficiently low, i-e-, acceptable for the decision-maker- If so, the data-worth analysis indicates which existing data could be removed to arrive at a cheaper monitoring design without substantially increasing prediction uncertainty- If uncertainties are unacceptably high, the data-worth analysis suggests which additional data should be collected to effectively reduce the prediction uncertainty- A few iterations of this process—conducted prior to actual data collection—is likely to yield a testing or monitoring design that is robust and effective in reaching the calibration and modeling goals in support of clearly defined watershed management objectives-