Coupling a process-driven model with geographic information system enables the spatial predication of cadmium in paddy soils

Policies on the management of paddy fields are usually made at a broad scale and from a long-term perspective, while predicting the spatial extent of cadmium (Cd) contamination in paddy soils remains challenging. In this study, we developed a process-driven spatial model to quantify the transport of Cd in paddy soils and validated it against observed data from a 10-year regional investigation in southern China. Using a geographic information system and Monte Carlo simulation, the model was then applied to evaluate the effectiveness of different remediation strategies for contaminated paddy fields at field-to-regional scales in a 100-year period. In the last decade, atmospheric emissions have accounted for 43.5 % of the total Cd input in local paddy soils. However, the local clean air act failed to mitigate Cd contamination in 99.8 % of study area over the period of 2020-2120 because straw return became the dominant contributor to Cd inputs. Improving aerosol emission reductions by 3 % per year, stopping straw return to soil, and cleaning irrigation channels would take approximately 30 years (2020-2050) to protect 95 % of local rice production from causing an excessive human Cd kidney burden, especially in the paddy fields located in mining-affected areas.