| | 1: | | Title: | | | | | Volume/Number: | 2005 | | | | Issuing Agency: | | | | | Description: | This study provides a scientific basis for developing a classification system in support of nutrient criteria development for streams and rivers based on their susceptibility to algal growth. Those streams having high algal biomass as a result of low nutrient concentration are considered susceptible to algal growth. Conversely, streams having low algal biomass and high nutrient concentration are considered less susceptible to algal growth. The process of setting nutrient criteria is complex due to various designated water uses that require different levels of water-quality protection. That complexity is compounded further by the diversity in habitat conditions. Scientists have found that a stream's response to nutrient enrichment depends on various habitat factors such as water velocity, canopy cover along the streambank, and stream width/depth. Habitat conditions may differ considerably from one reach to another and also from season to season. To account for this spatial and temporal variability, monthly aggregated reach-scale habitat conditions were used to develop the classification system. Algae are either the direct or indirect cause of most problems related to nutrient enrichment. In this study, statistical methods were applied to develop a relationship between algal biomass and nutrients (total nitrogen and total phosphorus). Residuals of the developed relationship were considered to be attributable to stream susceptibility to algal growth. Variability of the residuals (i.e., susceptibility values) then can be explained by habitat conditions. Two sets of monitoring data for Illinois streams and rivers were used to develop the statistical models. The susceptibility-habitat model uses habitat monitoring data to predict stream susceptibility, and classify these streams based on their susceptibility. Eventually, the classification system may be used to develop site-specific nutrient standards based on stream tolerance to nutrients. It also can be used to prioritize streams and rivers for the Total Maximum Daily Load (TMDL) and for watershed management purposes. This two-stage model approach was tested on two datasets for Illinois. The Fox River dataset included nine locations on the Fox River in Lake, McHenry, Kane, Kendall, and LaSalle Counties. The Illinois Environmental Protection Agency (IEPA) dataset included extensive habitat factors and nutrient data observed at 142 locations on rivers and streams throughout the state. Those data were used to estimate the nonlinear regression model (f1) for calculating susceptibility based on the habitat factors. Validation entailed comparing predicted susceptibility with 'observed' susceptibility calculated as a residual from the nutrients-algal biomass (chlorophyll a) nonlinear regression model (f2). Various combinations of linear or squared inputs were examined for both f1 and f2 models, and those models giving the best-fit statistics were identified. Results show how the proposed two-stage model could be implemented for watershed classification based on stream susceptibility. Longer, more complete datasets will be required in the future to further test the results and to finetune the models, however. | | | | Date Created: | 5 10 2005 | | | | Agency ID: | CR-2005-02 | | | | ISL ID: | 000000000876 Original UID: 999999994451 FIRST WORD: Development | |
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