Abstract: Scientific and accurate forecast of ecological environmental water consumption (EEWC) in the upper Yangtze River basin is of major prominence to the sustainable development of the basin and the formulation of eco-environmental protection policies. Firstly, a two parameter variable weight buffer operator is used to pre-processing the system shock behavior sequence. Then, an improved grey model IGM4(λ,γ,t^a) with four background values is established, introducing power exponential terms and linear correction terms to characterize data series with mixed linear and nonlinear relationships. The particle swarm optimization (PSO) algorithm is employed to find optimal parameters. Additionally, the model’s effectiveness is evaluated by comparing the fitting values of models with other grey models. The final results demonstrate that the IGM4( λ,γ,t^a) performs best with mean absolute percentage error only 0.0199%. Finally, model IGM4( λ,γ,t^a) is utilized to predict the EEWC in the upper Yangtze River basin from 2023 to 2028. The reasonableness of the predicted results is analyzed, and related policy measures are put forward. 

Key words: Grey predication model , Two-parameter variable weight buffer operator , New information priority principle , Background value , Ecological environmental water consumption(EEWC)