水文地质参数识别问题是水文地质学上的一个难题。针对传统水文地质参数识别方法的局限性，提出了水文地质参数识别的径向基函数(RBF )神经网络方法，并通过算例验证了它的可行性与有效性，实现了水文地质参数的自动识别，提高了计算效率，比BP神经网络具有更好的参数识别效果。

The problem of hydrogeological parameter identification is actually a complex one. With the limit of identifying the parameter by traditional methods, the radial basis function neural networks (RBF) is applied into this area. Not only the parameter identification is automatically realized, but also th.e problem of local optimization is solved. The feasibility and effectiveness have been proved by the examples.