基于DPSIR-Tapio模型的水环境治理绩效及障碍评价——以环太湖城市群为例

Evaluation of water environment governance performance and its obstacles based on DPSIR-Tapio model:A case study of the Taihu Lake city cluster

中文关键词:  水环境治理绩效  DPSIR模型  Tapio脱钩模型  障碍因子  环太湖城市群

英文关键词:water environment governance performance  DPSIR model  Tapio decoupling model  obstacle factor  Taihu Lake city cluster

中文摘要:

      在城市化与工业化快速进程中，日益凸显的水环境问题成为制约社会经济可持续发展的关键。构建基于水环境治理绩效评价的科学治理策略来减轻水环境压力，已成为可持续发展的迫切需求。目前研究大多基于统计数据和时空分析法进行绩效评价，忽视了子系统间的动态互动和影响因素的探究。以环太湖城市群为研究区，基于驱动力-压力-状态-影响-响应(DPSIR)模型构建水环境治理绩效评价体系，采用逼近理想解排序法(TOPSIS)模型对水环境治理绩效进行时空演变分析，运用Tapio脱钩模型揭示子系统间的动态互动关系，借助障碍度模型识别水环境治理的关键影响因素。结果表明：(1)环太湖城市群水环境治理绩效整体呈现上升的趋势，各地级市水环境治理绩效排序为：苏州>常州>湖州>嘉兴>无锡。(2)环太湖城市群在P-D和P-R主要呈现出弱脱钩或强脱钩状态，而P-S&I表现出较大的不稳定性；各地级市脱钩水平排序为：嘉兴>湖州=无锡>常州>苏州市；水环境治理绩效与脱钩水平并非正相关。(3)影响水环境治理的主要因素为政府投资、城镇化水平、产业结构优化调整、专业技术人才的投入、污水处理能力和水资源生产能力。

英文摘要:

      In the rapid process of urbanisation and industrialisation, the increasingly prominent water environment problem has become a key constraint to sustainable socio-economic development. It has become an urgent need for sustainable development to construct a scientific management strategy based on performance evaluation of water environment management to reduce the pressure on the water environment. Most of the current studies are based on statistical data and spatio-temporal analysis for performance evaluation, neglecting the dynamic interaction between subsystems and the exploration of influencing factors. Taking the urban agglomeration around Taihu Lake as the study area, we constructed a water environment governance performance evaluation system based on the Driving Force-Pressure-State-Impact-Response (DPSIR) model, analyzed the temporal and spatial evolution of water environment governance performance using the Approximate Ideal Solution Sorting Method (TOPSIS) model, used the Tapio decoupling model to reveal the dynamic interactions among the subsystems, and identified key influencing factors of water environment governance with the aid of the obstacle degree model. The key influencing factors of water environment governance were identified with the help of the obstacle degree model. The results show that: (1) the overall water environment governance performance of the city cluster around Taihu Lake shows an upward trend, and the water environment governance performance of each prefecture-level city is ranked as follows: Suzhou > Changzhou > Huzhou > Jiaxing > Wuxi. (2) The city cluster around Taihu Lake mainly shows weak or strong decoupling in P-D and P-R, while P-S&I shows greater instability; the decoupling level of each prefectural city is ranked as: Jiaxing>Huzhou=Wuxi>Changzhou>Suzhou; the performance of water environment governance is not positively correlated with the decoupling level. (3) The main factors affecting water environment governance are government investment, urbanisation level, optimisation and adjustment of industrial structure, input of professional and technical talents, sewage treatment capacity and water production capacity.