Abstract
Abstract
Background
The soil P leaching change point (CP) has been widely used to evaluate soil P leaching risk. However, an automation calculation method for soil P leaching CP value, and an effective risk grading method performed for classifying soil P leaching risk evaluation have not been developed.
Results
This study optimized the calculation process for soil P leaching CP value with two different fitting models. Subsequently, based on the Python programming language, a computation tool named Soil Phosphorus Leaching Risk Calculator (SPOLERC) was developed for soil P leaching risk assessment. SPOLERC not only embedded the calculation process of the soil P leaching CP value, but also introduced the single factor index (SFI) method to grade the soil P leaching risk level. The relationships between the soil Olsen-P and leachable P were fitted by using SPOLERC in paddy soils and arid agricultural soils in the Xingkai Lake Basin, and the results showed that there was a good linear fitting relationship between the soil Olsen-P and leachable P; and the CP values were 59.63 and 35.35 mg Olsen-P kg−1 for paddy soils and arid agricultural soils, respectively. Additionally, 32.7, 21.8, and 3.64% of arid agricultural soil samples were at low risk, medium risk, and high risk of P leaching, and 40.6% of paddy soil samples were at low risk.
Conclusions
SPOLERC can accurately fit the split-line model relationship between the soil Olsen-P and leachable P, and greatly improved the calculation efficiency for the soil P leaching CP value. Additionally, the obtained CP value can be used for soil P leaching risk assessment, which could help recognize key area of soil P leaching.
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
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