H12E-01:
Towards Fully Integrated Natural and Virtual Hydrologic Laboratories

Monday, 15 December 2014: 10:20 AM
Enrique R Vivoni, Arizona State University, Tempe, AZ, United States
Abstract:
A key challenge facing hydrologic research and education is the integrated use of natural and virtual laboratories to advance theory and process understanding, develop and test new modeling approaches and provide compelling materials for educational and outreach activities. Too often, the experimental and modeling activities in the hydrologic community are carried out in isolation of each other. This talk will describe our long-term efforts in building two natural watershed laboratories in the Sonoran and Chihuahuan Deserts for the purpose of studying the hydrologic effects of woody plant encroachment. Through the common use of environmental sensor networks, unmanned areal vehicles and spatial sampling methods, the two small watersheds provide unprecedented detail on the hydrologic responses to the bimodal precipitation regime in the southwestern United States in the presence of varying woody plant cover. By designing each natural laboratory using hydrologic modeling criteria, sensor and remote sensing data products and their analyses have been immediately useful for testing and developing meaningful applications of a distributed hydrologic model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). After building confidence in the model applications, the virtual laboratories at each site are used to test hypotheses on the spatial controls on hydrologic patterns and to infer underlying hydrologic mechanisms. Furthermore, the model-data comparisons allow for detailed investigation of the model improvements that are required related processes, parameters or forcings. Examples are provided to illustrate the information content of the natural and virtual laboratories, the identification of model deficiencies and their resolution, and the process understanding gained from combining the distributed observations and modeling approaches.