Abstract
BackgroundAs the key factor of soil P leaching risk assessment, soil P leaching change point (CP) has been widely reported. However, there was no report have clearly described the calculation method of soil P leaching CP value and its automation calculation. Additionally, there was no effective risk grading method performed on the classification of soil P leaching evaluation.ResultsThis study has optimized the calculation process of soil P leaching CP value under two different models. Subsequently, based on the Python programming language, a computation tool named SPOLERC (Soil Phosphorus Leaching Risk Calculator) was developed for soil P leaching risk assessment. SPOLERC not only embedded the calculation process of soil P leaching CP value, but also introduced the single factor index (SFI) method to grade the soil P leaching risk level. Considering the relationships between soil Olsen-P and leachable P fitted by using SPOLERC in paddy land soils and arid agricultural land soils in the Lake Xingkai basin, results have shown that there is a good linear fitting relationship between soil Olsen-P and leachable P; and the CP values were 59.63 and 35.35 mg Olsen-P kg-1 in paddy land soils and arid agricultural land soils, respectively. Additionally, 32.7%, 21.8%, and 3.64% of arid agricultural soil samples are at low risk, medium risk, and high risk of P leaching, and 40.6% of paddy land soil samples are at low risk. ConclusionsThe SPOLERC can accurately fit the split-line model relationship between soil Olsen-P and leachable P, and greatly improve the calculating efficiency for soil P leaching CP value. Additionally, the obtained CP value can be used for soil P leaching risk assessment, which can provide support for the quantitative study of soil P leaching loss and the control technology of soil P leaching loss.
A Tool (SPOLERC) to Guide the Evaluation of Phosphorus Leaching for Agricultural Soil by Using Soil Phosphorus Leaching Change Point in the Lake Xingkai Basin, China
