A non-linear perturbation model for river flow forecasting is developed, based on consideration of catchment wetness using an antecedent precipitation index (API). Catchment seasonality, of the form accounted for in the linear perturbation model (the LPM), and non-linear behaviour both in the runoff generation mechanism and in the flow routing processes are represented by a constrained non-linear model, the NLPM-API. A total of ten catchments, across a range of climatic conditions and catchment area magnitudes, located in China and in other countries, were selected for testing daily rainfall-runoff forecasting with this model. It was found that the NLPM-API model was significantly more efficient than the original linear perturbation model (the LPM). However, restriction of explicit non-linearity to the runoff generation process, in the simpler LPM-API form of the model, did not produce a significantly lower value of the efficiency in flood forecasting, in terms of the model efficiency index R 2.

This paper first summarizes the characteristics and distribution of water resources in China and then addresses the three major types of water problems from both historical and geographical perspectives. Major water problems, i.e. floods, droughts and water shortages, and water pollution, have tremendous impacts on the economic development and social well being in China. Analyses of water problems in the context of natural causes and human influences lead to the discussion of the role of the hydrological sciences in sustainable management of water resources, with an example of the preliminary findings of a study of water resources renewability in the Yellow River basin. Finally, challenges and opportunities for hydrologists are highlighted to present a brief summary and prospect on the development of the hydrological sciences in China.

本文以湖北汉川洪西垸径流试验区为对象，探讨了水网地区水量转化的系统模拟问题。通过单元系统的水均衡分析，提出一种能反映平原湖区水文基本特征的水资源系统模型。它能够定量描述降水、灌溉水、流域产水量、人渗补给量、潜水蒸发量以及地下水动态变化；可进行日径流长序列操怍，由系统输入自动实现地表和地下水动态过程分割和水资源总量评价。该模型用洪西垸径流试验区实测资料做了验证与分析。

基于时间序列多重信息利用的扩维原理和灰色系统理论的关联分析思想，提出一种应用于水文中长期预报的方法。它的特点是直接从径流序列的扩维相型关联分析中，寻求径流情势变化规律。较适合于缺乏输入因子资料或选择影响因子有困难条件下的水文中长期预报。利用海河、黄河和长江流域若干水文站的实测资料序列对该方法傲了初步验证。