Analysis of Spatio-Temporal Changes and Driving Factors of Wetland Ecosystem Health Based on the AHP-SOM-DPSR Model—A Case Study of Wetlands in the Qin-Mang River

Abstract

Wetland ecosystems are vital for ecological security. However, rapid industrialization and urbanization have led to regional degradation, particularly in areas like the Qin-mang River Basin, a pivotal site in China’s ecological security strategy. Urgent measures are required to safeguard the health of its wetland ecosystems. This study employs the hierarchical analysis method-neural network-driver-pressure-state-response (AHP-SOM-DPSR) model to evaluate the ecological health of wetland ecosystems in the Qin-mang River Basin over a thirty-year period, from 1992 to 2022. Initially, the Drive-Pressure-State-Response (DPSR) model establishes a comprehensive indicator system encompassing 19 indicators spanning driving forces, pressures, states, and responses. Subsequently, a hybrid approach combining Analytic Hierarchy Process (AHP) and Self-Organizing Map (SOM) determines indicator weights to evaluate spatiotemporal ecosystem changes over the past three decades. Additionally, spatial autocorrelation theory analyzes ecosystem health in the study area. Finally, Pearson correlation coefficient analysis examines the driving factors influencing ecosystem health and their impacts. Results indicate: (1) Ecosystem health has deteriorated gradually from 1992 to 2022, underscoring the imperative for enhanced wetland management in the Qin-mang River Basin. (2) High spatial autocorrelation areas, primarily in the central-southern and northern regions, highlight priority zones for wetland ecosystem management. (3) Urbanization levels, average temperature, and total population significantly impact wetland ecosystem health in the Qin-mang River Basin. These findings offer valuable scientific insights for guiding ecological management and conservation efforts in the region.