Dynamic Water Environmental Capacity Accounting and Total Load Allocation in Tidal River Networks Based on the WASP Model

Abstract

The accurate quantification of water environmental capacity in tidal river networks remains a persistent challenge in water quality management, largely due to the intricate interplay between tidal oscillations and riverine flows that generates pronounced spatiotemporal heterogeneity. This study develops a dynamic water environmental capacity accounting framework coupled with a total pollutant load allocation methodology for a representative tidal river network in southern China, employing the Water Quality Analysis Simulation Program as the core modeling engine. A hydrodynamic-water quality model was constructed and calibrated using field measurements spanning both wet and dry seasons, with particular attention given to the treatment of tidal boundary conditions—a process that required iterative refinement given the sensitivity of model stability to upstream boundary specifications. The dynamic water environmental capacity was subsequently computed through an inverse modeling approach, yielding monthly and reach-specific allowable loads that deviate considerably from conventional steady-state estimates, with tidal forcing alone contributing to approximately 25-40% of seasonal variability. Building upon these results, a two-tier allocation scheme was formulated: a Gini coefficient-based equitable distribution plan considering regional socioeconomic disparities, and a cooperative game-theoretic optimization that minimizes overall abatement costs. The comparative analysis reveals that efficiency-oriented allocation can reduce system-wide costs by 12-18% relative to purely equitable schemes, though this efficiency gain entails trade-offs with distributional equity that require further negotiation. Uncertainty analysis suggests that model parameter sensitivity may introduce non-negligible biases, indicating that adaptive management frameworks should complement model-based recommendations.