Abstract In arable land management, different crop rotation patterns and sequences, such as changing agricultural land use to erosion prone crops, or crops providing less ground cover, can greatly influence soil loss rate through their impact on soil cover status (C factor value). The influence of crop rotation on C value and on erosion rate is often determined on an experimental plot scale, so the results are often erroneous when extrapolated to large heterogeneous landscapes, where they fail to capture the spatiotemporal variability beyond the experimental sites. In the present study we have endeavored to investigate the impact of various crop rotation patterns on C value and on subsequent soil erosion rate, at a landscape level, by combining 28 time-series satellite images (from 2013 to 2016) along with annually updated land-use data, via the integrated administration and control system (IACS), from the Uckermark district of north eastern Germany. In total, 21 different crop sequences were investigated. Winter wheat (WW), winter rape (WR), and maize (Mz) were found to be the predominant arable crops grown in the study area. The highest average annual C values were estimated from crop sequences involving Mz and sugar beet (SB), both as pre-crops and succeeding crops. The highest value of 0.39 was computed from SB/Mz rotation. On the other hand, crop rotation involving WR gave significantly lower annual C values in all the years considered, with the lowest average annual C value of 0.07 calculated on WR parcels preceded by winter cereals. It was also apparent that crop rotation patterns influenced C value in a temporally variable manner. Among the self-sequencing patterns, WR/WR reduced the C value significantly compared with Mz/Mz and to a lesser extent compared with WW/WW. Continuous cultivation of Mz increased the potential soil loss rate by as much as 72 % compared to WR/WR and by 51 % compared to WW/WW. It was also possible to determine the spatial distribution of the impact of crop rotation on soil erosion risk within the study area. The results obtained agreed with the results of other international and regional studies. Overall, the output from this research could contribute towards further efficient investigation of the impact of agronomic practices on the environment in a large agricultural landscape, without the need to set up multi-location experimental plots.

中文翻译：

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通过遥感和 GIS 方法确定各种轮作的农业景观尺度 C 因子和侵蚀预测

摘要 在耕地管理中，不同的作物轮作模式和序列，例如将农业土地用途改为易受侵蚀的作物，或地被植物较少的作物，可以通过影响土壤覆盖状态（C 因子值）极大地影响土壤流失率。轮作对 C 值和侵蚀率的影响通常是在实验地块尺度上确定的，因此当外推到大型异质景观时，结果往往是错误的，因为它们无法捕捉到实验地点以外的时空变异性。在本研究中，我们通过结合 28 幅时间序列卫星图像（2013 年至 2016 年）以及每年更新的土地，努力在景观水平上调查各种作物轮作模式对 C 值和随后的土壤侵蚀率的影响- 使用数据，通过集成管理和控制系统 (IACS)，来自德国东北部的 Uckermark 区。总共研究了 21 种不同的作物序列。发现冬小麦 (WW)、冬油菜 (WR) 和玉米 (Mz) 是研究区种植的主要农作物。最高年平均 C 值是从涉及 Mz 和甜菜 (SB) 的作物序列估计的，无论是作为前作物还是后作作物。最高值 0.39 是根据 SB/Mz 旋转计算得出的。另一方面，在所有考虑的年份中，涉及 WR 的作物轮作显着降低了年 C 值，在冬季谷物之前的 WR 地块上计算的年平均 C 值最低，为 0.07。很明显，作物轮作模式以时间可变的方式影响 C 值。在自测序模式中，WR/WR 与 Mz/Mz 相比显着降低了 C 值，与 WW/WW 相比降低了较小程度。与 WR/WR 相比，连续种植 Mz 使潜在土壤流失率增加了多达 72%，与 WW/WW 相比增加了 51%。还可以确定研究区域内作物轮作对土壤侵蚀风险影响的空间分布。获得的结果与其他国际和区域研究的结果一致。总体而言，这项研究的成果有助于进一步有效调查农艺实践对大型农业景观中环境的影响，而无需设置多地点试验田。与 WR/WR 相比，连续种植 Mz 使潜在土壤流失率增加了多达 72%，与 WW/WW 相比增加了 51%。还可以确定研究区域内作物轮作对土壤侵蚀风险影响的空间分布。获得的结果与其他国际和区域研究的结果一致。总体而言，这项研究的成果有助于进一步有效调查农艺实践对大型农业景观中环境的影响，而无需设置多地点试验田。与 WR/WR 相比，连续种植 Mz 使潜在土壤流失率增加了多达 72%，与 WW/WW 相比增加了 51%。还可以确定研究区域内作物轮作对土壤侵蚀风险影响的空间分布。获得的结果与其他国际和区域研究的结果一致。总体而言，这项研究的成果有助于进一步有效调查农艺实践对大型农业景观中环境的影响，而无需设置多地点试验田。获得的结果与其他国际和区域研究的结果一致。总体而言，这项研究的成果有助于进一步有效调查农艺实践对大型农业景观中环境的影响，而无需设置多地点试验田。获得的结果与其他国际和区域研究的结果一致。总体而言，这项研究的成果有助于进一步有效调查农艺实践对大型农业景观中环境的影响，而无需设置多地点试验田。