Ecosystem health risk assessment of lakes in the Inner Mongolian Plateau based on the coupled AHP-SOM-CGT model

The ecosystem health risk assessment of lake basins can provide a crucial foundation and support for the sustainable development of ecosystems in the arid regions of northern China. This study adopts the Driver-Pressure-State-Impact-Response (DPSIR) framework to select evaluation indicators, and utilizes a coupled model of the Analytic Hierarchy Process (AHP)-Self-Organizing Mapping Neural Network Algorithm (SOM)-Combinatorial Game Theory Algorithm (CGT) to determine the weight values of each indicator, and ultimately calculate the Ecosystem Health Index (EHI) of a typical lake basin from 1990 to 2020. AHP and SOM are employed to determine the subjective and objective weights of the evaluation indicators, respectively. While, the CGT is used to establish a balance between these two weights. This ensures that the final weight values embody both the subjective preferences of the decision-makers and the objective characteristics inherent in the data. The calculations show that the EHI of the basin fluctuated from a healthy state (69.8) in 1990 to a sub-healthy state (47.0) in 2020, although the dominant factors influencing EHI varied across different stages, the decline in the Driver and Impact health indices emerged as the primary reason for the decrease in EHI. Before 2009, driven by socio-economic development, the area of irrigated land and water withdrawals in the basin increased significantly, which led to an increase in ecosystem pressures, resulting in a rapid decrease in EHI. After 2009, the increase in per capita water resources and water-saving irrigation facilities reduced the pressure on the ecological system. the increased ecological water use and afforestation area improved the ecosystem’s status, leading to an increase in the vegetation cover within the basin and a gradual upward trend in EHI.