Watershed pollution control plans effect assessment: Countermeasure adjustment modeling and simulation

As the effect of watershed pollution control planning is hard to evaluated, this paper brought forward a kind of methodology to assess the countermeasures´ effects on the water body. A kind of Artificial Neural Net (ANN) work called Radial Basis Function (RBF) was used to simulate the uncover interrelationships among the measures and the water quality indicators. After building their internal net, some certain input parameters which represents the environmental protection investments or alike in the net, were adjusted mandatorily. The variations of the output water quality indicators showed the effect of these countermeasures. The simulation result showed that investment on environmental protection is a positive index for water quality improvement.