Water managers are increasingly using environmental flows (e-flows) as a tool to improve ecological conditions downstream from impoundments. Recent studies have called for e-flow approaches that explicitly consider impacts on hydrogeomorphic processes when developing management alternatives. Process-based approaches are particularly relevant in river systems that have been highly modified and where water supplies are over allocated. One-dimensional (1D) and two-dimensional (2D) hydrodynamic models can be used to resolve hydrogeomorphic processes at different spatial and temporal scales to support the development, testing, and refinement of e-flow hypotheses. Thus, the objective of this paper is to demonstrate the use of hydrodynamic models as a tool for assisting stakeholders in targeting and assessing environmental flows within a decision-making framework. We present a case study of e-flows on the Rio Chama in northern New Mexico, USA, where 1D and 2D hydrodynamic modeling was used within a collaborative process to implement an e-flow experiment. A specific goal of the e-flow process was to improve spawning habitat for brown trout by flushing fine sediments from gravel features. The results revealed that the 2D hydrodynamic model provided much greater insight with respect to hydrodynamic and sediment transport processes, which led to a reduction in the recommended e-flow discharge. The results suggest that 2D hydrodynamic models can be useful tools for improving process understanding, developing e-flow recommendations, and supporting adaptive management even when limited or no data are available for model calibration and validation.

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Due to the complexity and heterogeneity inherent to the hydrologic cycle, the modeling of physical water processes has historically and inevitably been characterized by a broad spectrum of disciplines including data management, visualization, and statistical analyses. This is further complicated by the sub-disciplines within the water science community, where specific aspects of water processes are modeled independently with simplification and model boundary integration receiving little attention. This can hinder current and future research efforts to understand, explore, and advance water science. We developed the Virtual Watershed Platform to improve understanding of hydrologic processes and more generally streamline model-data integration and data integration with tools for data visualization, analysis, and management. Currently, four models have been developed as components and integrated into the overall platform, demonstrating data prepossessing (e.g., sub gridding), data interaction, model execution, and visualization capabilities. The developed data management technologies provide a suite of capabilities, enabling diverse computation capabilities, data storage capacity, connectivity, and accessibility. The developed Virtual Watershed Platform explored the use of virtual reality and 3D visualization for scientific experimentation and learning, provided web services for the transfer of data between models and centralized data storage, enabled the statistical distribution of hydrometeorological model input, and coupled models using multiple methods, both to each other and to a distributed data management and visualization system.

River Board) for their input. Many thanks are also due to Skip Vecchia (U.S. Geological Survey), who provided guidance on the statistical analysis completed in support of this project and the provision of background information resulting from his effort on previous projects.