基于灰色扩维识别的农业面源污染驱动因素分析—以江苏省为例

Driving Factor Analysis of Agricultural Non-point Source Pollution Based on Grey Extended Dimension Identification Method—A Case Study of Jiangsu Province

摘要:

针对农业面源污染的驱动因素分析中存在“少数据”和双向作用机制的问题,采用灰色扩维识别模型构建农业面源污染驱动因素识别方法。首先,阐述了经济发展对农业面源污染的影响方式；然后,确定面源污染的主要测量指标—总氮排放量(TN),以及影响因素测量指标,建立了基于灰色扩维识别的灰色关联度模型。通过分析各影响因素子序列与系统行为序列的灰色关联度,识别农业面源污染的驱动因素,为深入分析、有效治理和评价面源污染提供思路。

Abstract:

In order to settle the problems of "little data" and two-way mechanism existing in driving factors analysis in agricultural non-point source pollution, grey extended dimension identification model is applied to construct driving factors’ identifying method. Firstly, the ways that economic development can translate to agricultural non-point source pollution are stated. After that, this paper selects the main measurement indexes of agricultural non-point source pollution, total nitrogen emissions (TN), and measurement indexes of influencing factors to construct grey incidence degree model based on grey extended dimension identification model. By analyzing the grey incidence degree between each sub-sequence and system behavioral sequence, the driving factors are identified which offers new thoughts for deeply comprehending, effectively administrating and evaluating agricultural non-point source pollution.