水库鱼产力评价标准与模式的研究

本文在总结国内外已有成果的基础上,运用专家系统和灰色统计方法,初步建立了一套水库鱼产力评价的指标体系、指标权重体系和指标标准体系,首次给出了比较系统和具有普适意义的评价方案;并运用模糊数学方法建立了综合定量评价模式,从而在很大程度上解决了以往评价中由于多指标重迭、交错造成的难判、误判问题,为水库渔业资源的合理开发利用提供了比较科学的依据。

A STUDY ON STANDARDS AND MODELS OF RESERVOIR FISH PRODUCTIVITY ASSESSMENT

In order to assess fish productivity of reservoirs on a local scale, a system of indices, a system of index criteria, and a system of index weight were proposed, on these bases, an overall assessment method was established.By arranging the assessment indices into hree independent levels, i.e., the level of basic factors, including the characteristics of the drainage area, the reservoir morphology and the hydrological features, the level of hydrochemical factors, and the level of biological factors, and determining the effective indices in each level through a Delphi investigation, the system of indices, complete and simple, was established.Reservoirs were classified into five ranks according to their fish productivity (from high level to low level). On the basis of the results of the Delphi invetigation, the criterion of every index corresponding to each rank was determined. Thereby, the system of index criterion was worked out.The importance of different indices in indicating fish productivity is quite different, so, a different weight should be given to each of them. The index weight system was .established by Delphi investigation and Grey Statistical Method.In view of the fuzziness of the distinction between high and low fish productivity, Fuzzy Method was used to establish a comprehensive assessment model. First, Fuzzy Membership Function of each index to fish productivity was determined according to the index criterion system, which was comparable to each other on a same scale and can be used as a specific fish productivity index (FPIi). Then all the FPIi in the same level was added up according to the index weight system, thus a comprehensive fish productivity index (FPIc) for each level was obtained. Finally, an overall conclusion of reservoir fish productivity was drawn by means of averaging FPIc of all three levels, o by refined classification.