Metamodels to Bridge the Gap Between Modeling and Decision Support

Insights from process-based models are a mainstay of many groundwater investigations; however, long runtimes often preclude their use in the decision-making process. Screening-level predictions are often needed in areas lacking time or funding for rigorous process-based modeling. The U.S. Geological Survey (USGS) Groundwater Resources and National Water Quality Assessment Programs are addressing these issues by evaluating the “metamodel” to bridge these gaps. A metamodel is a statistical model founded on a computationally expensive model. Although faster, the question remains: Can a statistical model provide similar insights to a numerical model with faster results

Prediction Uncertainty in Simulated Groundwater Quality Trends

Although about 2 billion people worldwide rely on groundwater for their drinking water, our knowledge of the subsurface is sparse and imperfect. One of the primary tools to investigate groundwater is the simulation model. Sophisticated models are used that depict detailed subsurface processes, but model uncertainty is often not understood. A better understanding of model uncertainty is needed to make rational management decisions about this important yet imprecisely understood resource. ^ This work is motivated by the need to understand basin-scale changes in groundwater quality in transient groundwater systems. Basic information needs, some of which are addressed here, must be understood better before proceeding to the broader question. This work is divided into three sections. The first section describes a new algorithm to estimate pumping-well recharge-area uncertainty and its use to assess atmospheric tracer data in reducing model uncertainty. The second section describes new methods for calculating solute breakthrough curves in pumping wells. Simulation modeling involves compromise between time and accuracy, and this section provides guidelines for choosing among several popular solution methods. It also provides new algorithms to improve particle-based transport simulation near a pumping well. The final section combines previous work and applies uncertainty in particle-based simulations of breakthrough curves at a pumping well in a synthetic groundwater flow system. Future work will apply these methods to real basin-scale problems. ^ Model uncertainty is estimated using calibration-constrained Monte Carlo simulation with Latin Hypercube Sampling. Parameter covariance estimated using modified Gauss-Newton nonlinear regression is used to generate Monte Carlo realizations that are conditioned on model performance. Parameter correlations are important in groundwater simulation models, and Latin Hypercube Sampling increases simulation efficiency and preserves correlation. Convolution-based particle tracking is used to calculate breakthrough curves at pumping wells. To overcome the discrete nature of particle simulations, truncated Gaussian Kernel Density estimation is used to construct response functions. Increased hydraulic gradients near the pumping well are calculated by embedding an analytical solution in a commonly used semi-analytic particle tracking algorithm. Particle tracking is shown to be efficient and accurate in estimating model parameters.

Simulation of ground-water flow and application to the design of a contaminant removal system, Loring Air Force Base, Maine /

Shipping list no: 97-0253-P.Includes bibliographical references (p. 15).Mode of access: Internet

Hydrogeology and simulation of ground-water flow in the alluvial aquifer at Louisville, Kentucky /

Includes bibliographical references (p. 40-41).Mode of access: Internet

Mining and social movements:struggles over livelihood and rural territorial development in the Andes

Note: this full-text download is the accepted and/or submitted version of this work. Social movements have been viewed as vehicles through which the concerns of poor and marginalized groups are given greater visibility within civil society, lauded for being the means to achieve local empowerment and citizen activism, and seen as essential in holding the state to account and constituting a grassroots mechanism for promoting democracy. However, within development studies little attention has been paid to understanding how social movements can affect trajectories of development and rural livelihood in given spaces, and how these effects are related to movements\u27 internal dynamics and their interaction with the broader environment within which they operate. This paper addresses this theme for the case of social movements protesting contemporary forms of mining investment in Latin America. On the basis of cases from Peru and Ecuador, the paper argues that the presence and nature of social movements has significant influences both on forms taken by extractive industries (in this case mining) and on the effects of this extraction on rural livelihoods. In this sense, one can usefully talk about rural development as being co-produced by movements, mining companies, and other actors, in particular the state. The terms of this co-production, however, vary greatly among different locations, reflecting the distinct geographies of social mobilization and of mineral investment, as well as the varying power relationships among the different actors involved. © 2008 Elsevier Ltd. All rights reserved