Claire R Tiedeman (Former Employee)

In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (hereafter also referred to as "the Center"). The Center has been the flagship research center for the USGS in the western United States for more than 50 years...

An advantage of using optimization for model development and calibration is that optimization provides methods for evaluating and quantifying prediction uncertainty. Both deterministic and statistical methods can be used. Guideline 13 discusses using regression and post-audits, which we classify as deterministic methods. Guideline 14 discusses inferential statistics and Monte Carlo...

No abstract available.

No abstract available.

The methods presented in Chapters 3 to 8 are applicable to models of any system. However, there are special considerations when applying the methods to certain types of models. This chapter discusses three types of models that are of special interest to many scientific and engineering fields: transient models, transport models, and existing models that are to be recalibrated.

We develop a new observation‐prediction (OPR) statistic for evaluating the importance of system state observations to model predictions. The OPR statistic measures the change in prediction uncertainty produced when an observation is added to or removed from an existing monitoring network, and it can be used to guide refinement and enhancement of the network. Prediction uncertainty is...

We simulate three types of forced‐gradient tracer tests (converging radial flow, unequal strength two well, and equal strength two well) and natural‐gradient tracer tests in multiple realizations of heterogeneous two‐dimensional aquifers with a hydraulic conductivity distribution characterized by a spherical variogram. We determine longitudinal dispersivities (αL) by analysis of forced...

In models of natural and engineered systems, sensitivity analysis can be used to assess relations among system state observations, model parameters, and model predictions. The model itself links these three entities, and model sensitivities can be used to quantify the links. Sensitivities are defined as the derivatives of simulated quantities (such as simulated equivalents of...

Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about...

This paper investigates four issues related to weighting observations in the context of groundwater models calibrated with nonlinear regression: (a) terminology, (b) determining values for the weighting, (c) measurement and model errors, and (4) the effect weighting can have on the accuracy of calibrated models and measures of uncertainty. It is shown that the confusing aspects of...

Use of open wells to conduct aquifer tests in fractured crystalline rock aquifers is potentially problematic, because open wells can hydraulically connect highly permeable fracture zones at different depths within the rock. Because of this effect, it is questionable whether estimates of the hydraulic properties of the rock obtained from analysis of an open-well aquifer test in fractured...

When a model is calibrated by nonlinear regression, calculated diagnostic statistics and measures of uncertainty provide a wealth of information about many aspects of the system. This report presents a method of ranking the likely importance of existing observation locations using measures of prediction uncertainty. It is suggested that continued monitoring is warranted at more important...