白海及其流域生态-社会经济系统建模

IF 0.7 Q4 OCEANOGRAPHY
V. Menshutkin, N. Filatov
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引用次数: 0

摘要

目的。这项工作旨在开发白海(Beloe more)及其流域(简称Belomor 'e)的生态-社会经济系统的认知模型。与以前开发的区域认知模型不同,该系统的新模型具有层次结构,包括由共同管理系统统一的五个子模型。该模型旨在获得在各种自然管理和气候变化情景下复杂系统中正在进行的转变的预测定性评估。该模式使确定不同的目标成为可能,而这些目标又使我们能够评估提高人口生活水平、环境的合理利用和保护以及白海地区社会领域发展的可能性。这些因素是实现本区域可持续发展的重要基础。研究结果可为构建管理决策支持系统所需的定量模型系统提供基础。方法与结果。白海的认知模型被认为是一种综合复杂生态-社会经济系统异构信息的工具。应用了连续逻辑或概率逻辑的概念建模和数学工具。与传统的认知模型不同,新的认知模型暗示了变量在100年内的时间变化。这使我们能够描述相互作用因子之间的关系,并描述它们相互适应的机制。模型中的时间步长预设为一年。白海地区认知模型的发展得到了以下信息的支持:地理信息系统、数据库、白海及其流域的综合电子和纸质地图集、海洋热流体动力学和生态系统的原始三维数学模型。研究了气候变化模式、水文条件和渔业(当地人口的基本职业-波莫尔人)。在此基础上,建立了区域经济状况评估模型和区域经济发展预测模型。结论。基于层次性原则,建立了白海地区生态社会经济系统的新认知模型。已开发的子模型涉及各个知识领域:经济学、人口学、海洋学、土壤和农业物理学。对模型单元进行了100年的动力学分析。此外,在准周期气候波动下,经济参数变化不显著,但对人口生活水平和白海生态系统的影响显著。气候变化对白海生态系统的影响主要表现在水温、浮游植物生物量和渔业的变化上,而底栖动物的变化则不明显。分析了白海地区人口外流与区域生产总值、生产设施可用性和水质的关系。不幸的是,该地区的水质有所提高,不是由于对水处理的投资,而是由于人口和生产萎缩导致的污染减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling the Ecological-Socio-Economic System of the White Sea and its Watershed
Purpose. The work is aimed at developing a cognitive model of the ecological-socio-economic system of the White Sea (Beloe more) and its watershed (called for short Belomor’e). Unlike the previously developed cognitive models for the region, the new model of the system has a hierarchical structure including five sub-models united by a common management system. The model is intended for obtaining prognostic qualitative assessments of the transformations ongoing in a complex system under various scenarios of nature management and climate change. The model makes it possible to determine different targets, which, in their turn, permit to assess the possibilities of improving the population living standards, the environment rational use and protection, and development of the White Sea region social sphere. These factors constitute an important foundation for achieving sustainable development of the region. The results can serve a basis for constructing a system of quantitative models required to develop the management decision support systems. Methods and Results. The cognitive model of the White Sea is considered to be a tool for synthesizing heterogeneous information about a complex ecological-socio-economic system. The conceptual modeling and the mathematical apparatus of continuous or probabilistic logic are applied. Unlike the traditional cognitive models, the new one implies the variables’ change in time over 100 years. This allows us to describe the relationship between the interaction agents, and to characterize the mechanisms of their mutual adaptation. The time step in the model is preset to be one year. Development of the cognitive models for the White Sea region was supported by the following information: geographic information systems, databases, integrated electronic and paper atlases of the White Sea and its watershed area, original 3D mathematical models of the sea thermohydrodynamics and ecosystem. The patterns of climate change, hydrological conditions and fishing (basic occupation of local population – the Pomors) were studied. At that, the models both for assessing the regional economy state and for forecasting its development are used. Conclusions. A new cognitive model of the White Sea region ecological-socio-economic system was created based on the hierarchical principle. The developed sub-models relate to various fields of knowledge: economy, demography, oceanography, soil and agrophysics. Dynamics of the model elements over 100 years was demonstrated. Besides, it was shown that with the quasi-cyclic climate fluctuations, the economic parameters change insignificantly, whereas they have a noticeable impact upon the population living standards and the White Sea ecosystem. The demonstrated features resulted from the climate change effects upon the White Sea ecosystem are manifested in the fluctuations of water temperature, phyto- and zooplankton biomass and fishing, but the changes in benthos are hardly noticeable. Dependence of the White Sea region population outflow upon the gross regional product size, availability of production facilities and water quality is shown. Water quality in the region increases, unfortunately, not due to the investments in water treatment, but because of the pollution decrease resulted from the population and production shrinkage.
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来源期刊
Physical Oceanography
Physical Oceanography OCEANOGRAPHY-
CiteScore
1.80
自引率
25.00%
发文量
8
审稿时长
24 weeks
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