School of Environment, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing, 100875, China.
Sci Total Environ. 2012 Aug 15;432:412-21. doi: 10.1016/j.scitotenv.2012.06.017. Epub 2012 Jul 5.
To better understand the spatial dynamics of non-point source (NPS) phosphorus loading with soil property at watershed scale, integrated modeling and soil chemistry is crucial to ensure that the indicator is functioning properly and expressing the spatial interaction at two depths. Developments in distributed modeling have greatly enriched the availability of geospatial data analysis and assess the NPS pollution loading response to soil property over larger area. The 1.5 km-grid soil sampling at two depths was analyzed with eight parameters, which provided detailed spatial and vertical soil data under four main types of landuses. The impacts of landuse conversion and agricultural practice on soil property were firstly identified. Except for the slightly bigger total of potassium (TK) and cadmium (Cr), the other six parameters had larger content in 20-40 cm surface than the top 20 cm surface. The Soil and Water Assessment Tool was employed to simulate the loading of NPS phosphorus. Overlaying with the landuse distribution, it was found that the NPS phosphorus mainly comes from the subbasins dominated with upland and paddy rice. The linear correlations of eight soil parameters at two depths with NPS phosphorus loading in the subbasins of upland and paddy rice were compared, respectively. The correlations of available phosphorus (AP), total phosphorus (TP), total nitrogen (TN) and TK varied in two depths, and also can assess the loading. The soil with lower soil organic carbon (SOC) presented a significant higher risk for NPS phosphorus loading, especially in agricultural area. The Principal Component Analysis showed that the TP and zinc (Zn) in top soil and copper (Cu) and Cr in subsurface can work as indicators. The analysis suggested that the application of soil property indicators is useful for assessing NPS phosphorus loss, which is promising for water safety in agricultural area.
为了更好地理解流域尺度上非点源(NPS)磷负荷的空间动态与土壤特性之间的关系,综合模型和土壤化学至关重要,这可以确保指标正常运行并表达两个深度的空间相互作用。分布式建模的发展极大地丰富了地理空间数据分析的可用性,并评估了较大区域内 NPS 污染负荷对土壤特性的响应。对 20-40cm 表层和 0-20cm 表层的土壤进行了 1.5km 格网采样,并分析了 8 个参数,这为四种主要土地利用类型下的土壤提供了详细的空间和垂直数据。首先确定了土地利用转化和农业实践对土壤特性的影响。除了钾(TK)和镉(Cr)总量略大外,其他六个参数在 20-40cm 表层的含量均大于 0-20cm 表层。采用土壤和水评估工具(SWAT)模拟 NPS 磷的负荷。与土地利用分布叠加后发现,NPS 磷主要来自以旱地和水稻田为主的子流域。比较了旱地和水稻田子流域表层和亚表层土壤中 8 个参数与 NPS 磷负荷之间的线性相关性。有效磷(AP)、总磷(TP)、总氮(TN)和 TK 在两个深度上的相关性不同,也可以评估负荷。土壤有机碳(SOC)较低的地区,NPS 磷负荷的风险显著较高,特别是在农业区。主成分分析表明,表层的 TP 和锌(Zn)以及亚表层的铜(Cu)和 Cr 可以作为指标。分析表明,土壤特性指标的应用有助于评估 NPS 磷的流失,这对于农业区的水安全具有广阔的应用前景。