A Study on the Associative Regulation Mechanism Based on the Water Environmental Carrying Capacity and Its Impact Indicators in the Songhua River Basin in Harbin City, China

With intensifying watershed pollution pressures and growing ecological vulnerability, scientifically revealing and enhancing the water environmental carrying capacity is crucial for ensuring the long-term health of the basin and the sustainable socioeconomic development of the region. However, the dynamic regulatory mechanisms linking narrow-sense and broad-sense water environmental carrying capacity remain poorly understood, limiting the development of integrated management strategies. This study systematically investigated the changing trends of both the narrow-sense and broad-sense water environmental carrying capacity in the Harbin section of the Songhua River basin through model calculations, along with the regulatory mechanisms of its key influence indicators. The results of the study on the carrying capacity of the water environment in the narrow sense show that permanganate, total phosphorus, and ammonia nitrogen exhibited partial carrying capacity across water periods, while dissolved oxygen decreased during flat and dry periods, with only limited capacity remaining at the Ash River estuary and in the Hulan River. The biochemical oxygen demand in the Ash River was consistently overloaded, and total nitrogen showed insufficient capacity except during the abundant water period. Broad-sense analysis indicated that improving urbanization quality, water supply infrastructure, and drinking water safety could effectively reduce future overload risks, with projections suggesting a transition from critical to loadable levels by 2030, though latent threats persist. Correlation analysis between narrow- and broad-sense indicators informed targeted control strategies, including stricter regulation of nitrogen- and phosphorus-rich industrial discharges, restoration of aquatic vegetation, and periodic dredging of riverbed sediments. This work is the first to dynamically integrate pollutant and socio-economic indicators through a hybrid modelling framework, providing a scientific basis and actionable strategies for improving water quality and achieving sustainable management in the Songhua River Basin.