Evaluation effect of watershed ecological compensation based on improved SobolSSA-ANP in the Taihu basin
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Abstract:
To improve the watershed ecological environment, and to realize the sustainable development of water resources, government and scholars have taken a series of investigations. Combined with the flexibility of payment for watershed ecosystem services and the efficient management of government, China proposed watershed ecological compensation and has piloted numerous ecological compensation programs in Xin'an Jiang, Taihu, and other watersheds. The implementation of ecological compensation has played an important role in the improvement of watershed ecology, and it has also impacted the economy, society, and other aspects of watersheds. Therefore, it is crucial to assess the impacts of ecological compensation on the ecology, economy, and society to further promote the implementation and improvement of ecological compensation policy.The evaluation index system, which includes the ecology, economy, social equity, and government investment is established by taking Taihu basin as a case study area. The ecology subsystem includes the per capita water resource, eutrophication index, and cyanobacteria density. The economy subsystem includes the total water supply, per capita disposable income, pollutant emission per unit gross domestic product, and the proportion of tertiary industry. The social equity subsystem includes the disposable income ratio between urban and rural, the health security number of beds per 10 thousand people. The government investment includes the investment in ecological protection. Based on the Dithering Sobol Sequence improved Sparrow Search Algorithm (SobolSSA) and Analytic Network Process (ANP), the evaluation model SobolSSA-ANP is constructed. In the proposed model, the ANP is adopted to analyze the influence relationship among indexes and to determine the evaluation matrix. The SobolSSA model is adopted to optimize the coefficients in the matrix dynamically. Subsequently, the optimized coefficients are input into the AHP model to reconstruct the evaluation matrix and to assess the eco-compensation effect.The results show that: (1) The SobolSSA-ANP improves the consistency and stability of the AHP model, and the evaluation results are more accurate. The CR values decrease by 1~10 orders of magnitude in the multiple ranges given by the experts, and the convergence results are more stable than the AHP model. (2) The implementation of Eco-compensation in the Taihu basin was effective and has improved the ecological environment. Especially, the effect from 2017 is significantly better than that before 2012. (3) The eco-compensation fund is the most important factor that influences the eco-compensation effect. The weight of the eco-compensation fund is 0.191 421, which is higher than the other indexes. Thus, it is necessary to explore market-based and multi-agent eco-compensation mechanisms to broaden the source of eco-compensation funds. (4) The eutrophication index and cyanobacteria density are the second and third important factors, respectively. That is consistent with the actual problems in the Taihu basin. The improvement of the above two factors will improve the ecological environment in the Taihu basin greatly.The implementation of eco-compensation in the Taihu basin has promoted the improvement of ecology, economy, and social equity. However, the eco-compensation funds, the design, and implementation of the eco-compensation mechanism required to be enhanced. It is suggested to promote innovation of eco-compensation mechanisms, explore the multi-agent and market-based eco-compensation, and establish a dynamic evaluation mechanism for the watershed. Meanwhile, establishing the ecological information-sharing mechanism, and transferring the ecological resource to ecological capital promotes the sustainable development of the watershed. The proposed model and results can provide a reference for the evaluation of the watershed eco-compensation effect, and are effective in improving the modernization of the governance capacity. In future research, the blockchain and marker-based eco-compensation mechanism can be coupled together to improve the trading mechanism of ecosystem services.
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