涉及居民生活的多途径海水利用运营模式探讨

涉及居民生活的多途径海水利用是沿海地区海水直接利用的重要组成部分,为了合理规划水资源配置,要求科学客观地预测居民生活海水需水量。根据某沿海城市历年居民生活用水量的统计资料,运用一元线性回归模型、生长曲线模型和人均生活杂用水定额法对其居民生活海水需求量进行了预测,结果表明生长曲线预测模型较为符合实际。对涉及居民生活的多途径海水利用的水价进行了探讨,对海水供水水价的组成进行了分析,提出了推广居民区海水利用产业发展的建议。

Integrated assessment of sea water quality based on BP artificial neural network

In order to carry out an integrated assessment of sea water quality objectively, this paper based on the concept and principle of artificial neural network, generated appropriate training samples for BP artificial neural network model through the method of producing samples to the concentration of various pollution index of sea water quality from the viewpoint of threshold, established the BP artificial neural network model of sea water quality assessment using multi-layer neural network with error back-propagation algorithm. This model was used to assess water environment and obtain sea water quality categories of offshore area in Bohai Bay through calculating. The calculations shown that pollution index in river＇s wet season was higher than that in dry season from 2004 to 2007, and the pollution was particularly serious in 2005 and 2006, but a little better in 2007. The assessed results of cases shown that the model was reasonable in design and higher in generalization, meanwhile, it was common, objective and practical to sea water quality assessment.

Comprehensive Assessment of Seawater Quality Based on an Improved Attribute Recognition Model

The attribute recognition model (ARM) has been widely used to make comprehensive assessment in many engineering fields, such as environment, ecology, and economy. However, large numbers of experiments indicate that the value of weight vector has no relativity to its initial value but depends on the data of Quality Standard and actual samples. In the present study, the ARM is enhanced with the technique of data driving, which means some more groups of data from the Quality Standard are selected with the uniform random method to make the calculation of weight values more rational and more scientific. This improved attribute recognition model (IARM) is applied to a real case of assessment on seawater quality. The given example shows that the IARM has the merits of being simple in principle, easy to operate, and capable of producing objective results, and is therefore of use in evaluation problems in marine environment science.

Coastal Water Quality Assessment by Self-Organizing Map

A new approach to coastal water quality assessment was put forward through study on self-organizing map （ SOM ）. Firstly, the water quality data of Bohai Bay from 1999 to 2002 were prepared. Then, a set of software for coastal water quality assessment was developed based on the batch version algorithm of SOM and SOM toolbox in MATLAB environment. Furthermore. the training results of SOM could be analyzed with single water quality indexes, the value of N ： PC atomic ratio） and the eutrophication index E so that the data were clustered into five different pollution types using k-means clustering method. Finally, it was realized that the monitoring data serial trajectory could be tracked and the new data be classified and assessed automatically. Through application it is found that this study helps to analyze and assess the coastal water quality by several kinds of graphics, which offers an easy decision support for recognizing pollution status and taking corresponding measures.

Assessing seawater quality with a variable fuzzy recognition model

With the rapid development of the marine economy industry, human exploitation of marine resources is increasing, which is contributing to the growing trend of eutrophication and frequent occurrence of red tide. Accordingly, investigations of seawater quality have attracted a great deal of attention. This study was conducted to construct a seawater environmental quality assessment model based on the variable fuzzy recognition model. The uncertainty and ambiguity of the seawater quality assessment were then considered, combining the monitoring values of evaluation indicators with the standard values of seawater quality. Laizhou Bay was subsequently selected for a case study. In this study, the correct variable model for different parameters was obtained according to the linear and nonlinear features of evaluation objects. Application of the variable fuzzy recognition model for Laizhou Bay, water quality evaluation and comparison with performance obtained using other approaches revealed that the generated model is more reliable than traditional methods, can more reasonably determine the water quality of various samples, and is more suitable for evaluation of a multi-index, multi-level, nonlinear marine environment system; accordingly, the generated model will be an effective tool for seawater quality evaluation.

Water Shortage Risk Assessment in the Haihe River Basin, China

This paper studies water balance in the Haihe River Basin, China and assesses water shortage risk for the period 1994–2007. The authors identify that there is a water shortage problem in this area and propose that the non-intake water consumption （NIWC） is a very important water balance element. The NIWC in the Haihe River Basin flow is 5.91×109m3 in normal years. It was concluded from our evaluation that the water shortage risk during 1994–2007 was very high. Using international water risk assessment theory, multiyear risk indicators in Haihe River Basin can be calculated. Water risk rate, resiliency, stability, and vulnerability for the Haihe River Basin for the period 1994–2007 were 0.786, 0.000, 0.154 and 0.173 respectively. With the use of counter-force factors and adoption of different priorities to different water consumers, the water shortage risk can be decreased. The integrated water shortage risk indicators of the Haihe River Basin are 0.095–0.328. In this study, water availability from the South-North Water Diversion Project is also considered. By the year 2014, about 5×109m3 of water will be diverted from the Yangtse River, and the water shortage risk in the Haihe River Basin will drop from 0.229–0.297 to 0.152–0.234 under an inflow water frequency of 50%–75%. However, a risk of water shortage in this area will persist.