field-based input studies (e.g. Cohn et al., 1989). SPARROW model based loading estimates are 
available from USGS for the larger watersheds throughout the nation and we will test those 
estimates in our response models and against field measurements when possible. However, for 
smaller systems, SPARROW estimates may not be available and different watershed models or 
alternative methods may be required. Where possible, NHEERL will also seek loading data from 
NERL to test other loading models and loading-relationships for coastal water bodies; 
Table 3. Preliminary list of factors influencing response to excess nutrient inputs in coastal 
receiving waters. 
Biological Factors 
Physical Factors 
Chemical Factors 
SAV 
Food web efficiency 
Phytoplankton community 
Primary productivity base 
(e.g., phytoplankton base vs. 
sea grass based) 
Grazing type (e.g., benthic 
filter feeders, zooplankton) 
and grazing intensity 
Flushing 
Light/Suspended 
solids/Water color 
Stratification 
Depth 
Temperature 
Volume 
Area 
Tidal Height 
Geomorphology (e.g., 
drowned river valley) 
Physical energy (wind, etc.) 
Hypsography (area-depth 
relationship) 
N:P:Si:Fe Ratios 
Salinity 
Allochthonous C 
Denitrification potential 
Nutrient form 
(organic/inorganic) 
however, if this is not possible, we may need to estimate loading in smaller systems by direct 
measurement (flow versus concentration). 
In addition, since water quality management is frequently based on returning to some historical 
loading or reference condition, to be most useful to OW, the load-response relationships should 
be based on historical loading to the maximum extent possible. 
Response Models 
Nutrient loading-response models are the ultimate products of the new research initiative. They 
will be produced using two parallel, yet integrated, efforts. Numerical models will be used to 
provide refinement of empirically derived loading-response models and to aid in understanding 
mechanisms. If our classification schemes are appropriate, they will identify groups of receiving 
water that have significantly less variability in nutrient load-endpoint response relationships than 
is present among all receiving waters. Improvement in these relationships will provide the test 
for our classification schemes (Step 3) and will provide the scientific basis for grouping receiving 
waters to simplify the nutriait criteria/TMDL process. 
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