Abstract
Eco-hydrology regionalization plays an important role in releasing contradiction between water resources development and ecological environment protection. Based on the theory of self-organizing feature map (SOFM) artificial neural network, an eco-hydrology regionalization model is developed. In the model, several integrated indexes, which contain most original information, are extracted from a large number of eco-hydrology indexes using the principal component analysis (PCA). On this basis, the cluster genealogy chart is obtained by the hierarchical cluster analysis (HCA). Then the self-organizing feature map (SOFM) artificial neural network is constructed to regionalize rational eco-hydrology regionalization, based on the characteristics and cluster genealogy char. As an example, Quanzhou region is regionalized. The result indicates that there are 4 eco-hydrology zones and each of them has the distinct characteristics. For the different characteristics of each eco-hydrology zone, 4 policies about are eco-environmental protection and water resources development proposed, that are general, enhancive, strict and strictest measures to protect eco-environment and develop water resources.
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