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A RETROSPECTIVE ANALYSIS OF MODEL UNCERTAINTY FOR FORECASTING HYDROLOGIC CHANGE
Citation:
SEMMENS, D. J., M. HERNANDEZ, D. C. GOODRICH, AND W. G. KEPNER. A RETROSPECTIVE ANALYSIS OF MODEL UNCERTAINTY FOR FORECASTING HYDROLOGIC CHANGE. In Proceedings, 2006 International Environmental Modeling and Software Society, Burlington, VT, July 09 - 12, 2006. International Society for Ecological Modeling, Severna Park, MD, 1-6, (2006).
Impact/Purpose:
The primary objectives of this research are to:
Develop methodologies so that landscape indicator values generated from different sensors on different dates (but in the same areas) are comparable; differences in metric values result from landscape changes and not differences in the sensors;
Quantify relationships between landscape metrics generated from wall-to-wall spatial data and (1) specific parameters related to water resource conditions in different environmental settings across the US, including but not limited to nutrients, sediment, and benthic communities, and (2) multi-species habitat suitability;
Develop and validate multivariate models based on quantification studies;
Develop GIS/model assessment protocols and tools to characterize risk of nutrient and sediment TMDL exceedence;
Complete an initial draft (potentially web based) of a national landscape condition assessment.
This research directly supports long-term goals established in ORDs multiyear plans related to GPRA Goal 2 (Water) and GPRA Goal 4 (Healthy Communities and Ecosystems), although funding for this task comes from Goal 4. Relative to the GRPA Goal 2 multiyear plan, this research is intended to "provide tools to assess and diagnose impairment in aquatic systems and the sources of associated stressors." Relative to the Goal 4 Multiyear Plan this research is intended to (1) provide states and tribes with an ability to assess the condition of waterbodies in a scientifically defensible and representative way, while allowing for aggregation and assessment of trends at multiple scales, (2) assist Federal, State and Local managers in diagnosing the probable cause and forecasting future conditions in a scientifically defensible manner to protect and restore ecosystems, and (3) provide Federal, State and Local managers with a scientifically defensible way to assess current and future ecological conditions, and probable causes of impairments, and a way to evaluate alternative future management scenarios.
Description:
GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate potential environmental impacts as part of this process. Model error, however, can be significant and potentially compounded when projecting future land-cover/use change and management conditions. To address this problem we have utilized repeat observations of land cover/use as a proxy for projected future conditions. A systematic analysis of model efficiency during simulations based on observed land-cover/use change is used to quantify error associated with simulations for a series of known "future" landscape conditions over a 24-year period. Calibrated and uncalibrated assessments of relative change over different lengths of time are also presented to determine the types of information that can reliably be used in planning efforts for which calibration is not possible.