That GIS-based hydrological response units (HRUs) incorporated watershed variables and their potential spatial correlation into ANN modeling was clarified in the paper. The process and final results of neural network modeling were both assessed by the deterministic or statistical methods, spatial regression kriging (RK). The relation of prediction errors and HRUs area scale can provide useful information to optimize the design of stream monitoring network. It is indicated that potential advantage of ANN for watershed and the assessment of estuarine river impacts can be done by precise spatial prediction and sensitive factors analysis.
