Abstract

Non-point source (NPS) pollution caused by unsustainable cultivated land use is becoming more severe. It is therefore critical to understand the complex relationships between cultivated land use forms and NPS pollutant loads from the perspective of integrated cultivated land use. This study used the cultivated land use pattern to integration represent the various forms of cultivated land use, and constructed a model to estimate NPS pollutant outputs at an administrative-region scale. This model was used to quantitatively simulate the NPS total phosphorus (TP) loads of townships with different cultivated land-use patterns in Chaohu Lake Basin, China, since 2000. The relationships between the TP loads and the different cultivated land use patterns were then assessed to clarify the corresponding function mechanisms and provide scientific support for effective NPS pollution controls. The cultivated land-use patterns of the townships in Chaohu Lake Basin were classified as suburban compound operations (SC); grain and economical crop scale operations (GES); grain and economical crop extensive operations (GEE); and grain, oil, and cotton scale operations (GOCS). The TP loads of townships with various cultivated land-use patterns were significantly different. The average TP load of GEE pattern townships was the highest (5.39 kg ha−1a−1), which was 1.85 times the lowest value of the SC pattern townships. The TP loads of GES and GOCS pattern were similar (3.52 kg ha−1a−1 and 3.19 kg ha−1a−1, respectively). The heterogeneous NPS TP loads are due to the face that cultivated land-use forms exhibit different marginal inhibition/promotion effects on NPS pollutant outputs with different patterns. Different correlations and significances were observed between various cultivated land-use form factors and NPS TP loads with different patterns. Therefore, accurate classifications and recognition of cultivated land-use patterns can be utilized to clarify the function mechanism between cultivated land use and NPS pollutant loads.

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