The Object Watershed Link Simulation (OWLS) Program is designed to physically and visually simulate the real time or short-term hydrological processes for small forested watersheds and to provide detailed information about watershed response to environmental changes.
Object Watershed Link Simulation (OWLS) is a physically based watershed model. In the OWLS model, a watershed is defined as a three-dimensional object with linkages between cells and their attributes (e.g., area, slope, soil type, etc.). A cell is defined as the linkages of edges and their attributes (e.g. length, slope, etc.) and an edge is defined as the linkage of nodes and their attributes (e.g., depth of soil, elevation). The watershed hydrologic components such as water depth, surface flow, etc., are features associated with the cells, edges and nodes of a watershed. Simulation of hydrologic processes across a watershed involves the calculation of flows and water balances for these cells, edges, and nodes and their linkages. Therefore, the OWLS model is a three-dimensional, object-linked, vector-based model.
OWLS includes four sub-models that focus on (1) Data Processing, (2) Geomorphology, (3) Hydrology and (4) Visualization. The Data Processing Model handles conversions of raw data from watershed surveys into OWLS format. It also handles missing data interpolation and extrapolation for air temperature, precipitation, and streamflow. The Geomorphologic Model handles the automatic watershed delineation for flowpaths, streams, and boundaries, as well as stream geometry and macropore geometry. The Hydrologic Model handles water balance, flow calculation and flow routing for the canopy, surface, subsurface and macropore system associated with each cell. The Visualization Model handles 3-D watershed projection, 2-D watershed projection, hydrograph presentation, and 3-D dynamic watershed animation for simulated flows and other hydrologic components of the Hydrologic Model.
The OWLS model was tested with data from the Bear Brook Watershed of Maine (BBWM). Results from parameter calibration and validation indicate that the model generally provided good estimation of streamflows for rain-based flood events and unstable estimations for rain-on-snow events or snowmelt-based events when air temperature was high.