Targeting severe saline‐sodic soils in western Songnen Plain of China: A new perspective on critical flocculation concentration for clay dispersion

The critical flocculation concentration (CFC) of clay dispersion in saline‐sodic soils is pivotal for restoring aggregate stability, alleviating salinity/sodicity, and sustaining agroecosystem productivity. To delineate the CFC governing clay dispersion in severe saline‐sodic soils, this study investigated clay flocculation‐dispersion dynamics in Songnen Plain soils under systematic CaCl 2 leaching, providing mechanistic insights and quantitative benchmarks for targeted mitigation. A soil column leaching experiment was conducted with CaCl 2 solutions across an 11‐point gradient (0–100 mmol L − 1 , 10 mmol L − 1 increments). Post‐leaching, key physicochemical properties (pH, EC, Na + , HCO 3 − , CO 3 2 − , sodium adsorption ratio [SAR], and exchangeable sodium percentage [ESP]) and clay dispersion indices (turbidity, zeta potential, water‐dispersible clay [WDC], total clay, clay dispersion rate [CDR], and clay flocculation index [CFI]) were quantified. Nonlinear regression (Sigmoid model) was used to determine the CFC and establish predictive relationships between CaCl 2 concentration, soil properties, and dispersion behavior. Results showed 30–40 mmol L − 1 CaCl 2 effectively inhibited clay dispersion. This dosage improved soil properties: pH, SAR, cations ratio of soil structural stability, and ESP decreased to 8.01, 2.32 (mmol c L − 1 ) 1/2 , 2.97 (mmol c L − 1 ) 1/2 , and 4.98, respectively. Clay dispersion indices also improved: WDC, mechanical dispersion turbidity, spontaneous dispersion turbidity, mechanical dispersion zeta potential, and CDR declined to 2.93%, 59.93 Nephelometric Turbidity Units (NTU), 1.96 NTU, −22.09 mV, and 0.15, while CFI increased to 0.85. The Sigmoid model well described nonlinear relationships, identifying the CFC as 30–40 mmol c L − 1 Ca 2 + . Univariate regression models were developed to optimize Ca 2 + amendment dosages and quantitatively forecast post‐treatment clay dispersion behavior.