This report describes an enhanced version of the U.S. Geological Survey modular groundwater model, called MODFLOW-2000, for which the structure has been expanded to facilitate the solution of multiple related equations. The performance of the program has been tested in a variety of applications. Future applications, however, might reveal errors that were not detected in the test simulations. Users are requested to notify the U.

The methods and guidelines described in this report are designed to promote accuracy when simulating complex systems with mathematical models that need to be calibrated, and in which the calibration is accomplished using inverse modeling. This report focuses on the implementation of the described methods in the computer codes UCODE (Poeter and Hill, 1998) and MODFLOWP (Hill, 1992), which perform inverse modeling using nonlinear regression, but the methods have been implemented in other codes. The guidelines as presented depend on statistics described in this work, but other statistics could be used. Many aspects of the approach are applicable to any model calibration effort, even those conducted without inverse modeling. The methods and guidelines presented have been tested in a variety of groundwater modeling applications, many of which are cited in this report, and are described in the context of groundwater modeling concepts. They are, however, applicable to a much wider range of problems.

Abstract:Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and forecast the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, political, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and decision making; and providing a web-based platform for community interactions (e.g., continuous virtual workshops).

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