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The water evaluation model and its application in China

机译：水质评价模型及其在中国的应用

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The fresh water in China occupies 6%of that of the whole world, while the population occupies 21.29% of that of the whole world. The shortage of the freshwater is a key factor limiting the development of China.According to the distribution of the water resources in the mainland China, with the aim of protecting the water resources, we give the priority to the earth surface water resource and regard it as the total amount of water resource to do the analysis and movement of the water. Firstly, by consulting the data and combining the Chinese national conditions, we reckon the provinces with water shortage. Using the combinationmodel of greymodel andBP neural network, thewater shortage inYear 2025 of the provinces with water deficiency can be predicted. The prediction relative error of themodel is 0.31%. The prediction precision is high. The water resource strategy set according to the prediction value can satisfy the needs of the water resources in Year 2025. Secondly, according to the different location of the provinces, the provinces with water shortage can be divided into inland areas and coastal areas. So we can get the best way of obtaining the water resources is to allocate. In the coastal areas, besides the movement of the water, we should consider the impacts of desalination to the economy, physics and the environment.
机译：中国的淡水占全世界的6％，而人口占全世界的21.29％。淡水短缺是制约中国发展的关键因素。根据中国大陆水资源的分布，为保护水资源，我们优先考虑地表水资源作为水资源总量来进行水的分析和移动。首先，通过查阅数据并结合中国国情，我们认为各省缺水。利用灰色模型和BP神经网络的组合模型，可以预测2025年缺水省的缺水情况。该模型的预测相对误差为0.31％。预测精度高。根据预测值制定的水资源战略可以满足2025年的水资源需求。其次，根据各省的不同位置，将缺水的省分为内陆地区和沿海地区。因此，我们获得水资源的最佳途径就是分配水资源。在沿海地区，除了水的流动外，我们还应考虑淡化对经济，物理和环境的影响。

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