M. Tähtikarhu, T. Räsänen, J. Oksanen, J. Uusi-Kämppä
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引用次数: 1
摘要
农业景观中侵蚀区分布和泥沙运移路径的空间信息是有限的。因此,我们通过使用数字高程模型(2 × 2 m2)和基于rusle的侵蚀估计来计算连通性指数(IC)和沉积物输送估计,通过地表径流评估结构沉积物连通性。分析了两个地形差异较大的子集水区内部和之间的变量。我们发现,同一子集水区内IC的空间变异性大于子集水区之间的空间变异性。大部分地块(65%-97%)在结构上与相邻的明沟和溪流相连。在像元(Pearson r = 0.58-0.63)和地块尺度(r = 0.49-0.67)上,高侵蚀估算值的地区在结构上也往往连接良好。IC模型对参数变化的敏感性不高。相比之下,输沙量估算值对参数变化高度敏感。然而,基于计算出的输沙量估计值之间的高度相关性(Spearman r = 0.95),该工具提供了潜在的高输沙量区域的一致信息。可以采用更多的经验数据和动态模型来提高估计的准确性。该方法为生成有关连通性的开放数据提供了一种可行的工具。
Exploring structural sediment connectivity via surface runoff in agricultural lands of Finland
ABSTRACT Spatial information on the distribution of erosion areas and sediment transport pathways within agricultural landscapes is limited. Thus, we assess structural sediment connectivity via surface runoff by using a digital elevation model (2 × 2 m2) and RUSLE-based erosion estimates to compute index of connectivity (IC) and sediment delivery estimates. The variables were analyzed within and between two topographically contrasting subcatchments. We found greater spatial variability of IC within a subcatchment than between the subcatchments. The majority of field parcel areas (65%–97%) were structurally connected to adjacent open ditches and streams. Areas with high erosion estimates also tended to be structurally well-connected, both at the pixel (Pearson r = 0.58–0.63) and parcel scale (r = 0.49–0.67). The IC model was not highly sensitive to parameter variations. In contrast, the magnitude of sediment delivery estimates was highly sensitive to parameter variations. However, based on the high rank correlation (Spearman r s > 0.95) between computed sediment delivery estimates, the tool provided consistent information on potentially high sediment delivery areas. More empirical data and dynamic model applications could be applied to improve the accuracy of the estimates. The method provides a feasible tool to generate open data on connectivity.