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Declining water quality has exacerbated water scarcity worldwide, and effective water quality management requires a solid understanding of the factors of water quality. The response of water quality to landscape composition and configuration has been extensively studied, but landscape intensity has been disregarded. Therefore, constructing a comprehensive impact factor indicator and determining the pivotal factors are essential. This study focused on the response relationship of landscape composition, configuration, and intensity metrics to water quality. Water quality index included total nitrogen (TN) and total phosphorus (TP) from 43 monthly sites in the main rivers of the Taihu Lake Basin (TLB) in 2017. The TN:TP index was calculated. We used the partial least squares regression (PLS) method to explore the response strength between each index at different temporal and spatial scales, and the coefficient of determination (R2) calculated based on PLS was 0.4677 to 0.9039, in which the simulation effect was acceptable. In terms of pivotal influenced factors, industrial and domestic effluents for TN and TP showed a major effect in crop (CDR) and forest dominated region (FDR). For the TN:TP index, the pivotal influencing factors was merely industrial waste water discharge. In the fitting based on the pivotal factors of polynomial regression (PR), the landscape threshold of industrial and domestic effluents intensities to TN in CDR were higher than FDR, and landscape threshold substantially exceeded the water quality standard lines in CDR. This research can provide a reference for water quality precision management, distribution of pollutant emissions, and regional sustainable planning from the perspective of landscape regulation in TLB.