ATLSS LANDSCAPE AND HIGH RESOLUTION HYDROLOGY OVERVIEW Scott M. Duke-Sylvester and Louis J. Gross The Institute for Environmental Modeling Departments of Ecology and Evolutionary Biology and Mathematics University of Tennessee, Knoxville 37996-1610 Two primary components of the ATLSS project have been development of methodologies for linking dynamic ecological models to spatially- explicit information which can itself be dynamic, and development of a high resolution hydrology. The first of these, called the ATLSS Landscape Structure Model, provides the primary interface between all ATLSS component models and landscape data, as well as providing a framework for communication of spatially explicit information between ATLSS components. The High Resolution Hydrology model translates coarse resolution hydrologic information to a finer resolution appropriate for the biotic components in ATLSS. ATLSS LANDSCAPE STRUCTURE ATLSS models and the data are tied together by the Landscape classes, a collection of C++ classes each designed to handle a different facet of spatial data. Objects derived from some of these classes manage the data while the models are running, objects from other classes provide an interface to several input and output devices, others provide GIS type functions which can by applied to the spatial data, and others manage metadata. There are three related tasks fundamental to the integration needed for ATLSS that are handled by the Landscape Structure Model. These are: (1) providing spatial data and GIS functionality to ATLSS component models; (2) providing a structure for the spatially-explicit components internal to the various ATLSS component models; and (3) providing a mechanism for communicating spatial data between ATLSS component models. Similarities between these elements have been utilized to simplify many aspects of the models and the model design process. The simplifications stem from using functionally identical programming elements throughout the models and model development and using these elements for a variety of related tasks. The solutions we have developed are applicable to other modeling systems where agent-based modeling incorporates spatially-explicit data. Therefore, we expect the basic ATLSS formulation to be useful for a variety of ecosystem modeling projects that are unrelated to the current South Florida effort. ATLSS HIGH RESOLUTION HYDROLOGY MODEL A key component of the ATLSS project is the use of a high resolution hydrology model based on vegetation maps to convert the low resolution hydrologic output of the South Florida Water Management Model (1 water value per 2 x 2 mile cell) to the higher resolution needed to model ecological processes and the distribution of wildlife species. The ATLSS High Resolution Hydrology Model post-processes the output of the South Florida Water Management Model (WMM) using an algorithm based on conservation of water volume, and redistributes the water volume over a surface of high resolution topography (ATLSS "pseudotopography") to produce a high resolution map of water depth. This process is repeated on daily timesteps (corresponding to the daily output of the WMM) to create a map of water depth across the wetlands of South Florida with over 3000 separate values within each 2 x 2 mile cell (using topography based on the 28.5 meter resolution of a Landsat image). The two main steps involved in calculating the high resolution hydrology are: (1) processing the output of the Water Management Model to obtain above and below ground water volumes for each 2 x 2 mile cell; and (2) redistributing the water volume for each 2 x 2 mile cell over the irregular topographic surface of the ATLSS pseudotopography. Pseudotopography is used to replace the completely flat surface of the WMM 2 x 2 mile cell with an undulating surface that corresponds to the topography underlying the vegetation, with these elevations calculated based upon estimates of appropriate length hydroperiods for each vegetation type in the Landsat image. The high resolution hydrology thus generated estimates water depths for each 28.5 x 28.5 meter area within the region covered by the WMM, rather than a single water depth for each 2 x 2 mile area. Thus, the ATLSS High Resolution Hydrology Model converts a low resolution map of 1700 surface water elevation values into a high resolution map with as many as 5.5 million surface water elevation values within the same total area. The ATLSS High Resolution Hydrology Model provides water depth estimates at resolutions that are relevant to the vegetation and wildlife species of the Everglades and Big Cypress. Nonetheless, this level of resolution (28.5 m) is not fine enough to detect certain biologically important features, such as alligator holes. For other purposes, such a high resolution is not necessary. Consequently, some of the ATLSS animal models use water data that has been aggregated to 100m or 500m cells, which are based on averages of the 28.5 meter data. FUTURE PLANS The current pseudotopography was developed using the Florida GAP analysis map, and we expect there to be an ongoing effort, as revisions of this map are developed, to revise the pseudotopography. Additionally, alternative methods to calculate the pseudotopography that utilize an optimization approach are expected to be developed, as more data on fine-resolution topography are obtained from various field efforts. Continuing comparisons between the high resolution hydrology model and historical water depths are needed, particularly as better characterization of topography are obtained and as the WMM is modified. Finally, the ongoing effort to optimize the Landscape Structure Model will be continued, as well as the efforts to develop appropriate documentation (in addition to that currently on the ATLSS Home page at http://atlss.org/). REFERENCES Duke-Sylvester, S. M. and L. J. Gross. 1999. Integrating spatial data into an agent-based modeling system: Ideas and lessons from the development of the ATLSS (Across Trophic Level System Simulation). To appear in: Integrating GIS and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes, R. Gimblett (ed.). Univ. of Arizona Press.