现场研究的地点是由大卫德雷克管理的农场, 我们感谢他在这项长期研究中的合作。我们也感谢麦克墨菲多年来的实地工作, 在这个项目和罗宾 Montenieri 她的帮助与图形使用的本文。

1. 地面高程数据收集 <ol> <li> 站点的 gps 校准 <ol> <li> 在调查站点的安全位置定位或设置稳定的基准, 以用作 RTKGPS 数据收集的基站 gps. </li>
		<li> 使用基站位置的最佳坐标 ( 即 、WAAS 校正的 GPS 位置), 在本地基准设置 RTKGPS 数据收集的基站. </li>
		<li> 使用漫游 GPS, 在 RTKGPS (大约10公里半径) 和记录位置的无线电通信限制中至少访问三水平和垂直控制点基准. 
		注: 国家大地测量测量所描述的基准可以在线搜索 33 , 并在此处使用. </li>
		<li> 给定控制点的测量和发布坐标, 请使用 RTKGPS 字段软件执行站点校准 34 , 以解决用作基站的本地基准坐标。检查控制点的坐标残差 (水平和垂直) 是否在可容忍的范围内 (和 #177; 0.02 m 用于此校准). </li>
	</ol> </li> <li> gps 点数据收集 <ol> <li> 将基站 gps 设置在本地基准上, 并使用本地站点校准和现场软件, 将 RTKGPS 位置数据记录到 gps 数据收集器中, 在整个调查中大约有5米的水平间距地区.
		<ol> <li> 通过在车辆上的地面上测量的固定高度, 并通过该区域 ( 图 6 ) 驱动样, 来有效地收集数据. </li>
		</ol> </li> <li> 用于车辆方法, 定义横断面端点以创建平行样间隔5米。将横断面端点导入 GPS 数据采集器, 用于样驾驶时的导航。在驱动样大约5米的 -1 时, 每秒自动收集一次数据收集器的点, 以获取每 5 m 的点数据. </li>
		<li> 重复点数据收集在现场如上所述, 在以后的时间 (8 到9年后在本研究), 使土地表面高程变化可以分析; 原始 GPS 站点校准用于所有调查, 并且不重复. </li>
	</ol> </li> </ol> <img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/56064/56064fig6.jpg"/> 图6。RTKGPS 高程表面数据收集. RTKGPS 高程表面数据是收集的, 当驾驶一辆实用工具通过领域 (a) , 而 real-time GPS 更正由 on-site 基站 (b) 提供. 
 2. DEM 的创建和处理 <ol> <li> 在 gis 软件中创建民主党 <ol> <li> 导入位置数据, 并插入到一个5米的网格 dem 中. 利用 gis 软件 cross-validate 测点高程值, 并选择最小化这些交叉验证错误的插值方法. 
		注: 采用高斯 semivariogram 模型的普通克里格是本站高程数据的最佳插值方法。交叉验证还提供了测量方法 35 的高程精度度量. </li>
		<li> 对第二组位置数据重复2.1.1 以创建第二个 DEM. </li>
	</ol> </li> <li> 映射 dem 更改 <ol> <li> 使用 GIS 中的光栅计算器工具, 从原始 dem 中减去最近的 dem, 以创建 dem 更改的光栅图 ( 图 5 ), 其中的高程变化的负值代表侵蚀和正面价值代表证言. </li>
	</ol> </li> <li> 土地分类 <ol> <li> 使用 dem 处理软件从第一个网格 dem 计算地表地形地貌属性 (斜率、方面、贡献区)。
		<li> 根据每个 DEM 网格单元的斜率和贡献区域将土地区域划分为山顶、边坡或 toeslope. 
		注: 首脑会议由低斜坡和低贡献地区代表。边坡由高边坡和中间贡献区代表。Toeslopes 由低斜坡和高贡献地区代表。定义这些分类的斜率和贡献区域值将取决于该站点的陆地表面地形, 并在定性上选择, 以便为特定站点的每个分类区域提供所需的表示形式. </li>
		<li> 将边坡区域划分为两个主要方面, 即在该站点朝北和面向南. </li>
	</ol> </li> </ol> 3。土壤取样 <ol> <li> 示例规划 <ol> <li> 参考地图在地理信息系统中规划土壤样品的位置。选择多个位置以充分代表所有景观位置. </li>
		<li> 将采样位置坐标上载到 GPS 数据收集器, 以便可以在字段中找到示例站点. </li>
		<li> 在站点上使用以前的土壤知识来指导取样深度增量的决策, 以捕获中亚 3 可变性。预先标签密封塑料袋, 以表明样品的位置和深度增量. </li>
	</ol> </li> <li> 字段取样 <ol> <li> 驱动器带一辆装有液压土取心机和 RTKGPS 漫游天线的实用工具, 用于导航. </li>
		<li> 在本研究中使用土壤取心机和取样管 (5.1 厘米), 从每个取样位置提取土壤核心 ( 图 7 ). 
		注: 在该研究中, 在每个位置提取的核芯数, 以及土壤的核心深度和增量都不同。在 2001年, 一个核心到深度 90 cm 被采取了并且被划分成 30 cm 增量。在 2012年, 两个土壤核心被采取了 (在对应的2001样品的 1 m 之内) 到深度 30 cm 并且被划分成 15 cm 增量, 与二个核心被聚合为分析。建议使用2012方法. </li>
		<li> 在每个采样位置记录 RTKGPS 位置数据 (x、y、z). </li>
		<li> 将土壤芯切成所需的深度增量, 并将其转移到 pre-labelled 密封塑料袋中, 然后将其放入冷却器中, 以便输送回实验室. </li>
		<li> 在进行了显著的侵蚀和/或沉积后重复野外取样 (本研究中样本之间的11年) </li>
	</ol> </li> </ol> <img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/56064/56064fig7.jpg"/> 图7。土壤取样. 使用装有液压土取心机的 GPS 导向的实用工具 (a) 来导航土壤取样位置, 以便可以提取土壤核心, 并将其划分为所需的深度增量. 
<ol start="3"> <li> 位置数据处理 <ol> <li> 测量两个采样日期之间在每个土壤取样位置记录的海拔差异 (在本研究中取样的198地点为2001年和 2012). 
		注: 2001 的高程取自 2001 DEM, 因为在土壤取样时没有记录点高程。海拔和 #62 的积极变化; 0.05 m 被认为是 depositional 网站, 而海拔和 #60 的负面变化;-0.05 m 被认为是侵蚀的网站. </li>
		<li> 将每个采样位置划分为山顶、朝北的边坡、面向南的边坡或基于 DEM 处理的 toeslope (参见协议 2.3.2); 根据斜率和贡献区域标准定义的单个位置的分类可以是重新归类, 以匹配周围点的主导分类. </li>
		<li> 在 GIS 软件中使用空间连接工具将样本位置分配给用于分析的其他空间数据层 (管理条和土壤测绘单位). </li>
	</ol> </li> </ol> 4。土壤分析 <ol> <li> 土壤样品制备 <ol> <li> 60 和 #176 的田间干燥土壤样品; C 在实验室烤箱过夜。
		<li> 研磨干燥的土壤通过一个2毫米的筛子使用机动磨床或迫击炮和杵. </li>
	</ol> </li> <li> 修改的压力-Calcimeter 设备安装程序 <ol> <li> 通过将压力传感器 (0-105 人民军范围, 0.03-5 V DC 输出) 连接到电源来设置修改后的压力-Calcimeter 装置 ( 图 8 )与14口径电线和数字电压表有线在线监测输出的传感器。
		<ol> <li> 将 9.5 mm ID 油管连接到压力传感器的底座上, 并将油管连接到一个18口径的口锁皮下注射针头, 其中有一个粒子过滤器 (0.6 和 #181; m), 用于收集到达压力传感器的任何回流. </li>
		</ol> </li> <li> 使用血清瓶作为连接到压力传感器的反应容器 ( 图 9 ). #160; 测定血清瓶的大小, 用水润湿金属汤匙, 并加入约5毫升土壤, 你期望有高中亚 3 浓度. 和 #160; 吸管1毫升的 0.5 N H 2 所以 4 到这个土壤和观察泡. </li>
		<li> 如果泡高, 则假定大于15% 中亚 3 浓度, 并使用100毫升血清瓶作为反应容器, 否则使用20毫升血清瓶. </li>
	</ol> </li> </ol> <img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/56064/56064fig8.jpg"/> 图8。改进的压力 calcimeter 装置. 改进的压力 calcimeter 装置使用一个血清瓶作为反应容器和一个压力传感器连接到电压表输出信号 (从谢罗德 et al 。 30 . <img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/56064/56064fig9.jpg"/> 图9。改性压力 calcimeter 法的反应容器. 改进的压力 calcimeter 法的反应容器是含有2毫升酸性试剂和1克土壤样品的 0.5 dram 小瓶的血清瓶. 
<ol start="3"> <li> 碳酸盐测量 <ol> <li> 将准备好的土壤 (见协议 4.1) 的1克子放置在一个标记的反应容器中。对于含有大于50% 中亚 3 的土壤, 只使用0.5 克土壤. </li>
		<li> 吸管2毫升的酸性试剂 (6 N HCI 包含 3% FeCL 2 O 4 H 2 o) 变成一个0.5 克玻璃小瓶。将小瓶放入反应容器中, 使溶液的内容不会通过倾斜反应容器而溢出到侧面位置. </li>
		<li> 在保持含有土壤样品和酸性小瓶的反应容器倾斜时, 用灰色丁基橡胶塞子密封, 用铝密封圈卷曲. </li>
		<li> 摇动反应容器以旋转运动, 以确保土壤与酸的完全混合。将反应容器放在实验室的长凳上, 让反应至少进行2小时. </li>
		<li> 当等待反应容器完成时, 通过测量已知中亚的电压来确定标准曲线 3 浓度使用相同的反应容器设置为土壤样本 ( 图 10 ). 和 #160; 混合100%中亚 3 与玻璃珠或沙在一个重量百分比基础上创建已知的中亚 3 浓度. #160; 包含一个没有中亚 3 的空白示例。
		<li> 在土壤样品反应完成后, 用18口径皮下注射针头刺穿反应容器的橡胶隔膜, 并通过压力传感器记录电压输出. </li>
		<li> 解决中亚 3 给定的测量电压和从标准曲线 ( 图 10a ) 确定的公式的百分比. 
		注: CO 2 释放产生的压力的增加与土壤中中亚的 3 的浓度线性相关, 例如:% 中亚 3 = (回归系数 * 伏特的压力变化) + 拦截. </li>
	</ol> </li> </ol> <img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/56064/56064fig10.jpg"/> 图10。中亚 3 测量。(a) 中亚的标准曲线 3 是使用基于已知百分比的中亚 3 (b) 与粉末玻璃珠或沙子混合的压力传感器的电压读数创建的. 
 5. 统计分析 <ol> <li> 将两个相关变量定义为地面高程和土壤表层中亚 3 浓度从第一个到第二个采样日期 (2001 到2012在本研究中) 的变化。将独立或解释变量定义为管理 (奇数或偶数条)、单个条、西或东块、土壤制图单元、景观分类和侵蚀/沉积分类. </li>
	<li> 执行相关性分析和方差分析, 以统计地量化变量之间的关系。在任何优选的统计数据包中进行分析. </li>
</ol>

<ol>
	<li>Freebairn, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Erosion+control+-+some+observations+on+the+role+of+soil+conservation+structures+and+conservation.">Erosion control - some observations on the role of soil conservation structures and conservation.</a> Nat. Res. Mgt. 7 (1), 8-13 (2004).</li><li>Garcia-Orenes, F., Roldan, A., Mataix-Solera, J., Cerda, A., Campoy, M., Arcenegui, V., Caravaca, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Soil+structural+stability+and+erosion+rates+influenced+by+agricultural+management+practices+in+a+semi-arid+Mediterranean+agro-ecosystem.">Soil structural stability and erosion rates influenced by agricultural management practices in a semi-arid Mediterranean agro-ecosystem.</a> Soil Use and Mgt. 28, 571-579 (2012).</li><li>Hass, H. J., Willis, W. O., Bond, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=General+relationships+and+conclusions.">General relationships and conclusions.</a> Summer Fallow in the Western United States. USDA-ARS Conserv. Res. Rpt. No. 17. , 149-160 (1974).</li><li>Montgomery, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Soil+erosion+and+agricultural+sustainability.">Soil erosion and agricultural sustainability.</a> Proc. of the Nat. Acad. of Sci. of the USA. 104 (33), 13268-13272 (2007).</li><li>Skidmore, E. L., Layton, J. B., Armbrust, D. V., Hooker, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Soil+physical+properties+as+influenced+by+cropping+and+residue+management.">Soil physical properties as influenced by cropping and residue management.</a> Soil Sci. Soc. of Am. J. 50 (2), 415-419 (1986).</li><li>Sherrod, L. A., Erskine, R. H., Green, T. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatial+patterns+and+cross-correlations+of+temporal+changes+in+soil+carbonates+and+surface+elevation+in+a+winter+wheat-fallow+cropping+system.">Spatial patterns and cross-correlations of temporal changes in soil carbonates and surface elevation in a winter wheat-fallow cropping system.</a> Soil Sci. Soc. of Am. J. 79 (2), 417-427 (2015).</li><li>Stroosnijder, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+erosion:+Is+it+possible?.">Measurement of erosion: Is it possible?.</a> Catena. 64 (2-3), 162-173 (2005).</li><li>D&#261;bek, P., &#379;muda, R., &#262;mielewski, B., Szczepa&#324;ski, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+water+erosion+processes+using+terrestrial+laser+scanning.">Analysis of water erosion processes using terrestrial laser scanning.</a> Acta Geodynam. Et Geomat. 11 (1), 45-52 (2014).</li><li>Day, S. S., Gran, K. B., Belmont, P., Wawrzyniec, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+bluff+erosion+part+1:+terrestrial+laser+scanning+methods+for+change+detection.">Measuring bluff erosion part 1: terrestrial laser scanning methods for change detection.</a> Earth Surf. Proc. and Landforms. 38 (10), 1055-1067 (2013).</li><li>Eltner, A., Baumgart, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accuracy+constraints+of+terrestrial+Lidar+data+for+soil+erosion+measurement:+Application+to+a+Mediterranean+field+plot.">Accuracy constraints of terrestrial Lidar data for soil erosion measurement: Application to a Mediterranean field plot.</a> Geomorph. 245, 243-254 (2015).</li><li>Letortu, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Retreat+rates,+modalities+and+agents+responsible+for+erosion+along+the+coastal+chalk+cliffs+of+Upper+Normandy:+The+contribution+of+terrestrial+laser+scanning.">Retreat rates, modalities and agents responsible for erosion along the coastal chalk cliffs of Upper Normandy: The contribution of terrestrial laser scanning.</a> Geomorph. 245, 3-14 (2015).</li><li>Longoni, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+Riverbank+Erosion+in+Mountain+Catchments+Using+Terrestrial+Laser+Scanning.">Monitoring Riverbank Erosion in Mountain Catchments Using Terrestrial Laser Scanning.</a> Rem. Sens. 8 (3), 241 (2016).</li><li>Meijer, A. D., Heitman, J. L., White, J. G., Austin, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+erosion+in+long-term+tillage+plots+using+ground-based+lidar.">Measuring erosion in long-term tillage plots using ground-based lidar.</a> Soil &amp; Till. Res. 126, 1-10 (2013).</li><li>Rengers, F. K., Tucker, G. E., Moody, J. A., Ebel, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Illuminating+wildfire+erosion+and+deposition+patterns+with+repeat+terrestrial+lidar.">Illuminating wildfire erosion and deposition patterns with repeat terrestrial lidar.</a> J. of Geophys. Res.-Earth Surf. 121 (3), 588-608 (2016).</li><li>Schubert, J. E., Gallien, T. W., Majd, M. S., Sanders, B. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Terrestrial+Laser+Scanning+of+Anthropogenic+Beach+Berm+Erosion+and+Overtopping.">Terrestrial Laser Scanning of Anthropogenic Beach Berm Erosion and Overtopping.</a> J. of Coast. Res. 31 (1), 47-60 (2015).</li><li>Stenberg, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+erosion+and+surface+roughness+in+peatland+forest+ditches+using+pin+meter+measurements+and+terrestrial+laser+scanning.">Evaluation of erosion and surface roughness in peatland forest ditches using pin meter measurements and terrestrial laser scanning.</a> Earth Surf. Proc. and Landforms. 41 (10), 1299-1311 (2016).</li><li>Croke, J., Todd, P., Thompson, C., Watson, F., Denham, R., Khanal, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+multi+temporal+LiDAR+to+assess+basin-scale+erosion+and+deposition+following+the+catastrophic+January+2011+Lockyer+flood,+SE+Queensland,+Australia.">The use of multi temporal LiDAR to assess basin-scale erosion and deposition following the catastrophic January 2011 Lockyer flood, SE Queensland, Australia.</a> Geomorph. 184, 111-126 (2013).</li><li>Earlie, C., Masselink, G., Russell, P., Shail, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sensitivity+analysis+of+the+methodology+for+quantifying+cliff+erosion+using+airborne+LiDAR+-+examples+from+Cornwall,+UK.">Sensitivity analysis of the methodology for quantifying cliff erosion using airborne LiDAR - examples from Cornwall, UK.</a> J. of Coast. Res. Spec. Iss. 65, 470-475 (2013).</li><li>Kessler, A. C., Gupta, S. C., Dolliver, H. A. S., Thoma, D. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lidar+Quantification+of+Bank+Erosion+in+Blue+Earth+County,+Minnesota.">Lidar Quantification of Bank Erosion in Blue Earth County, Minnesota.</a> J. of Env. Quality. 41 (1), 197-207 (2012).</li><li>Pye, K., Blott, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessment+of+beach+and+dune+erosion+and+accretion+using+LiDAR:+Impact+of+the+stormy+2013-14+winter+and+longer+term+trends+on+the+Sefton+Coast,+UK.">Assessment of beach and dune erosion and accretion using LiDAR: Impact of the stormy 2013-14 winter and longer term trends on the Sefton Coast, UK.</a> Geomorph. 266, 146-167 (2016).</li><li>Thoma, D. P., Gupta, S. C., Bauer, M. E., Kirchoff, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Airborne+laser+scanning+for+riverbank+erosion+assessment.">Airborne laser scanning for riverbank erosion assessment.</a> Rem. Sens. of Env. 95 (4), 493-501 (2005).</li><li>Zhang, C. L., Yang, S., Pan, X. H., Zhang, J. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+farmland+soil+wind+erosion+using+RTK+GPS+measurements+and+the+Cs-137+technique:+A+case+study+in+Kangbao+County,+Hebei+province,+northern+China.">Estimation of farmland soil wind erosion using RTK GPS measurements and the Cs-137 technique: A case study in Kangbao County, Hebei province, northern China.</a> Soil &amp; Till. Res. 112 (2), 140-148 (2011).</li><li>Neugirg, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Erosion+processes+in+calanchi+in+the+Upper+Orcia+Valley,+Southern+Tuscany,+Italy+based+on+multitemporal+high-resolution+terrestrial+LiDAR+and+UAV+surveys.">Erosion processes in calanchi in the Upper Orcia Valley, Southern Tuscany, Italy based on multitemporal high-resolution terrestrial LiDAR and UAV surveys.</a> Geomorph. 269, 8-22 (2016).</li><li>Pineux, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Can+DEM+time+series+produced+by+UAV+be+used+to+quantify+diffuse+erosion+in+an+agricultural+watershed?.">Can DEM time series produced by UAV be used to quantify diffuse erosion in an agricultural watershed?.</a> Geomorph. 280, 122-136 (2017).</li><li>Bremer, M., Sass, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combining+airborne+and+terrestrial+laser+scanning+for+quantifying+erosion+and+deposition+by+a+debris+flow+event.">Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow event.</a> Geomorph. 138 (1), 49-60 (2012).</li><li>Day, S. S., Gran, K. B., Belmont, P., Wawrzyniec, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+bluff+erosion+part+2:+pairing+aerial+photographs+and+terrestrial+laser+scanning+to+create+a+watershed+scale+sediment+budget.">Measuring bluff erosion part 2: pairing aerial photographs and terrestrial laser scanning to create a watershed scale sediment budget.</a> Earth Surf. Proc. and Landforms. 38 (10), 1068-1082 (2013).</li><li>De Rose, R. C., Basher, L. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+river+bank+and+cliff+erosion+from+sequential+LIDAR+and+historical+aerial+photography.">Measurement of river bank and cliff erosion from sequential LIDAR and historical aerial photography.</a> Geomorph. 126 (1-2), 132-147 (2011).</li><li>Perroy, R. L., Bookhagen, B., Asner, G. P., Chadwick, O. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+gully+erosion+estimates+using+airborne+and+ground-based+LiDAR+on+Santa+Cruz+Island,+California.">Comparison of gully erosion estimates using airborne and ground-based LiDAR on Santa Cruz Island, California.</a> Geomorph. 118 (3-4), 288-300 (2010).</li><li>Loeppert, R. H., Suarez, D. L., Sparks, D. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Carbonate+and+Gypsum.">Carbonate and Gypsum.</a> Methods of Soil Analysis. Part 3. Chemical Methods. , 437-474 (1996).</li><li>Sherrod, L. A., Dunn, G., Peterson, G. A., Kilberg, R. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inorganic+carbon+analysis+by+modified+pressure-calcimeter+method.">Inorganic carbon analysis by modified pressure-calcimeter method.</a> Soil Sci. Soc. of Am. J. 66 (1), 299-305 (2002).</li><li>McCutcheon, M. C., Farahani, H. J., Stednick, J. D., Buchleiter, G. W., Green, T. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+soil+water+on+apparent+soil+electrical+conductivity+and+texture+relationships+in+a+dryland+field.">Effect of soil water on apparent soil electrical conductivity and texture relationships in a dryland field.</a> Biosyst. Eng. 94 (1), 19-32 (2006).</li><li>Wheaton, J. M., Brasington, J., Darby, S. E., Sear, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accounting+for+uncertainty+in+DEMs+from+repeat+topographic+surveys:+improved+sediment+budgets.">Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets.</a> Earth Surf. Proc. and Landforms. 35 (2), 136-156 (2010).</li><li>. Survey Marks and Datasheets Available from: <a target="_blank" href="https://www.ngs.noaa.gov/datasheets/">https://www.ngs.noaa.gov/datasheets/</a> (2017)</li><li>Trimble Inc. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Trimble Access Software – General Survey. Version 1.60. Revision A. , (2011).</li><li>Erskine, R. H., Green, T. R., Ramirez, J. A., MacDonald, L. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+elevation+accuracy+and+grid+cell+size:+effects+on+estimated+terrain+attributes.">Digital elevation accuracy and grid cell size: effects on estimated terrain attributes.</a> Soil Sci. Soc. of Am. J. 71, 1371-1380 (2007).</li></ol>

作者没有什么可透露的。

高程中的映射变化 (图 5) 说明了农业领域的大量侵蚀和沉积, 以及在多个尺度上指示多个控制因素的空间模式。从与风相关的场尺度模式, 到由水流产生的细小的树突状模式, 与此研究相关的过程是可辨识的。重复 RTKGPS 地面测量提供的高程变化检测的水平似乎是最佳的。根据 TLS 提供的更精细的检测级别可能会通过引入 microtopographic 特征 (如裁剪脊和犁沟) 而使结果复杂化, 而...

水土流失威胁着农业土地的可持续性。作物管理, 如传统耕作的冬小麦休耕轮作, 可以加速侵蚀和沉积过程, 因为裸露的土壤在休耕期间更容易受到风力和水的影响1,2,3,4,5 (图 1)。虽然这些过程可能是显而易见的, 但它们可能难以量化。
本研究的目的首先是利用全球定位系统 (GPS) 技术和地理信息系统 (GIS) 制图工具, 提供一种有效的方法来量化和描述在野外尺度上侵蚀和沉积的空间模式。一个简单的概念模型, 有关这些模式的近表层土壤碳酸盐 (中亚3) 也提出和测试的规定领域和实验室方法。这些关系提供了间接的侵蚀和沉积的措施, 同时验证了 GPS 方法的结果。本文着重介绍了谢罗德et al中使用的方法。因此, 它们可以在部分或全部中重复, 用于其他位置的类似研究6。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56064/56064fig1.jpg"> 
图1。(a) 侵蚀的照片和 (b) 在暴雨事件发生后的研究地点的沉积.在照片右下角的拖拉机轮胎轨道 (b) 表明在小麦/休耕带边界的沉积深度。
Stroosnijder7对土壤侵蚀的各种直接测量方法进行了综述。建议的方法随测量目的和可用资源的不同而有所不同, 但建议在山坡上采用 "表面高程变化" 方法, 并提供测量侵蚀和沉积的优点。应用此方法的一种方法是在土壤中安装针脚, 并监视相对于 pin7顶部的土壤的高度变化。然而, 随着土地测量技术的进步, 这种 labor-intensive 方法可以被其他技术所取代, 如地面激光扫描 (TLS)8,9,10,11,12,13,14,15,16, 机载激光扫描 (ALS)17,18,192021, GPS6,22, 高级摄影测量23 、24或这些技术的组合252627。激光扫描, 通常被称为激光雷达 (光探测和测距), 提供了密集的表面高程数据集的最快速的承购, 必须改正去除站立的对象, 例如植被。使用毫米级垂直精度, TLS 可以检测最小的仰角变化, 但 Perroy et al。推荐的 ALS 超过 TLS 的沟侵蚀估计, 由于更大的扫描足迹和更好的仪器定位 (较少地形阴影) 扫描到深切割沟28。本研究采用实时运动 GPS (RTKGPS), 提供厘米级精度, 无需数据后处理。RTKGPS 采集数据的空间分辨率和精度是检测农田或其他具有大量地面覆盖环境的主要侵蚀和沉积特征的最佳方法。
用压力 calcimeter 法定量土壤中亚3依赖于封闭系统中的土壤对酸的反应, 导致 CO 2 的释放.在恒定温度下, 反应釜内压力的增加与土壤中亚329的数量呈线性相关。对传统的压力-calcimeter 方法的修改, 由谢罗德et al描述, 包括将反应容器更改为血清瓶, 并使用连接到数字电压表的压力传感器来检测压力变化30. 这些修改允许更低的检测限制和更高的容量为每日土壤样品奔跑。土壤中亚的重量或简单滴定法3测量产生的误差和检测限制比此修改的压力-calcimeter 方法30大。
概念模型
当直接措施的侵蚀和沉积是不可行的, 这些过程的间接指标可以使用。谢罗德et al。假设在半干旱气候下土壤表层中亚3浓度与地表高程的变化 (与侵蚀呈正相关, 与沉积负相关)6呈反比关系。这一假说应广泛适用, 但具体的关系将取决于场地条件 (土壤、植被、管理和气候)。土壤在测试站点 (表 1) 通常包含一个独特的钙质层15-20 厘米以下的土壤表面。从概念上讲, 侵蚀将去除相对较低的中亚3浓度的表层, 从而使高中亚3的钙质层离土壤表面更近。低中亚的3土壤然后被运到沉积区, 导致钙质层深埋在土壤表层之下 (图 2)。根据这个模型, 可以通过中亚3浓度来推断这些土壤在适当的深度间隔时间内的取样, 无论是侵蚀还是沉积 (或者两者都不)。
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>土壤系列</td>
			<td>边坡</td>
			<td>分类学分类</td>
			<td>深度</td>
			<td>ph</td>
			<td>欧共体</td>
			<td>总计 N</td>
			<td>soc</td>
			<td>中亚3</td></tr></tbody></table>
		
		<tr>
			<td></td>
			<td>%</td>
			<td></td>
			<td>厘米</td>
			<td>1:2</td>
			<td>dS m-1</td>
			<td>g kg-1</td>
			<td>g kg-1</td>
			<td>g kg-1</td>
		</tr>
		<tr>
			<td>科尔比沃土</td>
			<td>5-9</td>
			<td>细粉, 混合, superactive, 钙质, 梅西奇 Aridic Ustorthent</td>
			<td>0-15</td>
			<td>8。2</td>
			<td>0.24</td>
			<td>0。7</td>
			<td>6。1</td>
			<td>69。8</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>15-30</td>
			<td>8。3</td>
			<td>0.24</td>
			<td>0。5</td>
			<td>4。0</td>
			<td>84。3</td>
		</tr>
		<tr>
			<td>金砂壤土</td>
			<td>2-5</td>
			<td>细-壤土, 混合, 活性, 钙质, 梅西奇 Ustic Torriorthent</td>
			<td>0-15</td>
			<td>7。8</td>
			<td>0.26</td>
			<td>0。8</td>
			<td>7。0</td>
			<td>29。8</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>15-30</td>
			<td>8。0</td>
			<td>0.27</td>
			<td>0。6</td>
			<td>5。0</td>
			<td>51。5</td>
		</tr>
		<tr>
			<td></td>
			<td>5-9</td>
			<td>细-壤土, 混合, 活性, 钙质, 梅西奇 Ustic Torriorthent</td>
			<td>0-15</td>
			<td>8。1</td>
			<td>0.22</td>
			<td>0。6</td>
			<td>5。4</td>
			<td>26。7</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>15-30</td>
			<td>8。1</td>
			<td>0.19</td>
			<td>0。5</td>
			<td>4。1</td>
			<td>25。8</td>
		</tr>
		<tr>
			<td>Wagonwheel 沃土</td>
			<td>0-2</td>
			<td>粗粉, 混合, superactive, 梅西奇 Aridic Calciustept</td>
			<td>0-15</td>
			<td>8。2</td>
			<td>0.23</td>
			<td>0。7</td>
			<td>5。9</td>
			<td>66。2</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>15-30</td>
			<td>8。2</td>
			<td>0.23</td>
			<td>0。6</td>
			<td>3。7</td>
			<td>98。1</td>
		</tr>
		<tr>
			<td></td>
			<td>2-5</td>
			<td>粗粉, 混合, superactive, 梅西奇 Aridic Calciustept</td>
			<td>0-15</td>
			<td>8。3</td>
			<td>0.23</td>
			<td>0。8</td>
			<td>6。6</td>
			<td>52。0</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>15-30</td>
			<td>8。4</td>
			<td>0.26</td>
			<td>0。7</td>
			<td>5。4</td>
			<td>118。3</td>
		</tr>
	

表1。试验场的土壤.土壤制图单位和分类学分类, 以平均土壤 pH 值, 电导率 (EC), 总 N, 土壤有机 C (SOC) 和中亚3集中在 0-到 15-和 15-到 30 cm 深度增量为斯科特领域在 2012年 (从谢罗德etal.)6。
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56064/56064fig2.jpg"> 
图2。概念土壤剖面.(a)的概念性土壤剖面图: 具有中亚3的静态土壤矩阵从表层浸出并沉淀在更深的层中, (b)表面层的适度侵蚀, 和(c)适度沉积材料上表面层的上方。深度间隔 (左) 是基于站点数据 (来自谢罗德et al) 的近似值。6.<a href="//ecsource.jove.com/files/ftp_upload/56064/56064fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
网站描述和历史记录
109公顷斯科特领域是德雷克农场的一部分在东北部科罗拉多 (40.61oN, 104.84oW,图 3) 和被监视从2001年到2012为这项研究。在这个半干旱的气候中, 年平均降水量和蒸散量分别是大约350和1200毫米, 在夏季, 短时间和高强度的对流雨是普遍的。海拔范围从1559年到 1588 m 在这起伏的地形与独特的风景位置: 山顶, 边坡北部面对 (边 NF), 边坡南面对 (边 SF) 和 toeslope (图 4b)。交替带 (〜120米宽) 通常管理在这个旱作冬小麦休耕轮作, 使每一个其他地带休耕约14月的每24月轮换周期。浅耕作 (约7厘米), 典型的 v 型叶片扫, 发生4至6次, 通过休耕期杂草控制。土壤在站点被分类了有土壤损失容忍或T价值, 11 毫克 ha-1年-1, 那里侵蚀率在这个T价值之下被认为可接受为连续的农业生产4.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56064/56064fig3.jpg"> 
图3。网站的位置显示在地形地貌图像 (1011 到4401米) 的科罗拉多州, 美国的状态.平均海拔的网站是 1577 m。
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56064/56064fig4.jpg"> 
图4。土壤地图和地面海拔斯科特领域.(a)斯科特领域的土壤地图显示点土壤样品地点和庄稼管理小条。土壤单位简称是: 1 = Wagonwheel 沃土0-2% 倾斜, 2 = Wagonwheel 沃土2-5% 倾斜, 3 = 科尔比沃土 5-9% 倾斜, 4 = 金细沙子沃土 2-5% 倾斜, 5 = 金细砂壤土5-9% 倾斜;和(b)基于 2001 5 m 网格数字高程模型 (DEM) 的地面海拔, 用土地分类显示的土壤样本位置 (从谢罗德et al)。6。
RTKGPS 在2001年收集了第一个地面高程测量数据, 为该场地制作了数字高程模型 (DEM)。与 McCutcheon et al一起, 在2001年也执行了一个密集型土壤样本 (图 4a), 其中地表土壤中亚3被修改过的压力-calcimeter 方法30,31.在随后的十年中, 由于风, 主要是从西北部, 和降雨径流事件发生的视觉上明显的侵蚀和沉积, 促使第二次 RTKGPS 海拔调查在 2009年 (部分的领域完成在 2010年)。新 dem 与原始 2001 dem 的差分图的对比研究32确认了显著的侵蚀和沉积, 显示了这些过程的多个控制因素的模式 (图 5)。考虑到土地的大量地表土壤再分配和历史土壤中亚3数据, 在2012年重复了2001土壤样本, 以测试 hydropedological 进程的概念模型6, 如上一节所述。
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56064/56064fig5.jpg"> 
图5。地图的变化 (2001-2009 *) 在陆地表面高程 (Δz) 的5米网格内的斯科特领域在科罗拉多州东北部。作物条数在交替的冬小麦休耕种植系统上标记,a 节 a-显示 (在图 11中给出的详细信息)。* 2、4、6、8条在2010年接受调查, 以完成 2009 DEM (来自谢罗德et al)。6.<a href="//ecsource.jove.com/files/ftp_upload/56064/56064fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

<table width="1330">
	<tbody>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Real-time kinematic GPS system</td>
			<td style="width:200px;">Trimble</td>
			<td style="width:119px;">Model 5800</td>
			<td style="width:759px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">GPS field data collector</td>
			<td style="width:200px;">Trimble</td>
			<td style="width:119px;">Model TSC2</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">GPS field software</td>
			<td style="width:200px;">Trimble</td>
			<td style="width:119px;"></td>
			<td>Trimble Access (Trimble Survey Controller used in 2001 for site calibration but this software is no longer supported)</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Hydraulic soil coring machine</td>
			<td style="width:200px;">Giddings Machine Company</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Utility vehicle</td>
			<td style="width:200px;">John Deere</td>
			<td style="width:119px;">Gator 6x4</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">GIS software</td>
			<td style="width:200px;">ESRI</td>
			<td style="width:119px;"></td>
			<td>ArcGIS for Desktop with Spatial Analyst and Geostatistical Analyst Extensions</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Statistical software</td>
			<td style="width:200px;">SAS</td>
			<td style="width:119px;"></td>
			<td>SAS Institute Inc.</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Pressure transducer 0-105 kPa</td>
			<td style="width:200px;">Serta</td>
			<td style="width:119px;">Model 280E</td>
			<td>Setra Systems, In., Boxborough, MA</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Volt meter</td>
			<td style="width:200px;">WaveTek</td>
			<td style="width:119px;">5XL</td>
			<td>Digital meter set to read volts</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Serum Bottles</td>
			<td style="width:200px;">Wheaton</td>
			<td align="right" style="width:119px;">223747</td>
			<td>100 ml</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Serum Bottles</td>
			<td style="width:200px;">Wheaton</td>
			<td align="right" style="width:119px;">223762</td>
			<td>20 ml</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Sealing Cap 20 mm Aluminum</td>
			<td style="width:200px;">Wheaton</td>
			<td style="width:119px;">224183-01</td>
			<td>Case of 1000</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">20 mm gray butyl stopper (2-prong)</td>
			<td style="width:200px;">Wheaton</td>
			<td style="width:119px;">224100-192</td>
			<td>Septum; Case of 1000</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Hand crimper</td>
			<td style="width:200px;">Wheaton</td>
			<td style="width:119px;">W225303</td>
			<td>20 mm size</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Hand Decapper</td>
			<td style="width:200px;">Wheaton</td>
			<td style="width:119px;">W225353</td>
			<td>20 mm size</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Acid vials</td>
			<td style="width:200px;">Wheaton</td>
			<td align="right" style="width:119px;">224881</td>
			<td>0.50 dram size (2-ml)</td>
		</tr>
		<tr height="23">
			<td height="23" style="width:252px;height:23px;">Power supply</td>
			<td style="width:200px;">SR Components</td>
			<td style="width:119px;">DDU240060</td>
			<td>Class 2 Transformer AC adaptor; Input 120VAC , Output 24VDC</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:252px;height:21px;">Calcium carbonate</td>
			<td style="width:200px;">Fisher</td>
			<td style="width:119px;">471-34-1</td>
			<td>500 g of 100% w/w CaCO3</td>
		</tr>
	</tbody>
</table>

measuring and mapping patterns of soil erosion and deposition related to soil carbonate concentrations under agricultural management

土壤侵蚀和沉积的空间模式可以从在适当时间增量映射的地面高程的差异中推断出来。这种海拔变化与近地表土壤碳酸盐 (中亚3) 剖面的变化有关。目的是描述一个简单的概念模型和详细的协议, 可重复的领域和实验室测量这些数量。这里, 用地面差分全球定位系统 (GPS) 测量精确高程;其他的数据采集方法也可以应用于相同的基本方法。土壤样品是从规定的深度间隔收集和分析在实验室中使用的有效和精确的修改压力 calcimeter 方法定量分析无机碳浓度。将标准统计方法应用到点数据中, 具有代表性的结果表明, 土壤表层中亚的变化与概念模型的变化有显著的相关性 (3 );中亚3在沉积区普遍减少, 在侵蚀地区增加。地图是从海拔和土壤的点测量中亚3获得的, 以帮助分析。一张侵蚀和沉积模式的地图在研究地点, 一个降雨哺养的冬天麦田在交替的麦子休闲的小条被裁剪, 显示水和风蚀的相互作用影响受管理和地形。本文讨论了替代取样方法和深度间隔, 并建议今后有关土壤侵蚀和沉积的工作中亚3。

映射 DEM 的差异, 从2001年和2009揭示了侵蚀 (红色) 和沉积 (绿色) 在这8年期间, 与分米波级的变化海拔超过大多数地区 (图 5)。在场尺度上, 侵蚀在西部和西南地区占主导地位, 而沉积则沿西北向东南对角带, 在该场的东侧出现。侵蚀和沉积交替带在管理范围被看见, 经常以突然的变动在管理条边界。与土壤类型相关的模式 (图 4a) 较...

Watch this Scientific Journal Video about Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management at JoVE.com

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

农业经营条件下土壤侵蚀和沉积与土壤碳酸盐浓度关系的测量与制图

土壤侵蚀和沉积的空间模式可以从在适当时间增量映射的地面高程的差异中推断出来。这种海拔变化与近地表土壤碳酸盐的变化有关。本文描述了这些数量和数据分析方法的现场和实验室测量的可重复方法。

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes ...

measuring-mapping-patterns-soil-erosion-deposition-related-to-soil

Universidad de Cartagena UDEC

Research

Education

JoVE Core

JoVE Journal

Civil Engineering

Environment

Unit 1

Geographic Information Systems (GIS)

SCIENTISTS IN ACTION

11.7K 次观看.  USDA Agricultural Research Service (ARS). 土壤侵蚀和沉积的空间模式可以从在适当时间增量映射的地面高程的差异中推断出来。这种海拔变化与近地表土壤碳酸盐的变化有关。本文描述了这些数量和数据分析方法的现场和实验室测量的可重复方法。

视频: Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes and soil organic matter formation to small-scale stable-isotope biomarker probing. Coupling multiple stable isotopes such as 13C with 15N, 18O or&#160;2H has the potential to reveal even more information about complex stoichiometric relationships during biogeochemical transformations. Isotope labeled plant material has been used in various studies of litter decomposition and soil organic matter formation1-4. From these and other studies, however, it has become apparent that structural components of plant material behave differently than metabolic components (i.e. leachable low molecular weight compounds) in terms of microbial utilization and long-term carbon storage5-7. The ability to study structural and metabolic components separately provides a powerful new tool for advancing the forefront of ecosystem biogeochemical studies. Here we describe a method for producing 13C and 15N labeled plant material that is either uniformly labeled throughout the plant or differentially labeled in structural and metabolic plant components.
Here, we present the construction and operation of a continuous 13C and 15N labeling chamber that can be modified to meet various research needs. Uniformly labeled plant material is produced by continuous labeling from seedling to harvest, while differential labeling is achieved by removing the growing plants from the chamber weeks prior to harvest. Representative results from growing Andropogon gerardii Kaw demonstrate the system&#39;s ability to efficiently label plant material at the targeted levels. Through this method we have produced plant material with a 4.4 atom%13C and 6.7 atom%15N uniform plant label, or material that is differentially labeled by up to 1.29 atom%13C and 0.56 atom%15N in its metabolic and structural components (hot water extractable and hot water residual components, respectively). Challenges lie in maintaining proper temperature, humidity, CO2 concentration,&#160;and light levels in an airtight 13C-CO2 atmosphere for successful plant production. This chamber description represents a useful research tool to effectively produce uniformly or differentially multi-isotope labeled plant material for use in experiments on ecosystem biogeochemical cycling.

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

This method explains how to build and operate a continuous 13C and 15N isotope labeling chamber for uniform or differential plant tissue labeling. Representative results from metabolic and structural labeling of Andropogon gerardii are discussed.

设计一个连续和操作<sup&gt; 13</sup&gt; C和<sup&gt; 15</sup&gt;Ñ贴标商会统一或差分，代谢和结构，植物同位素标记

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes ...

科研

环境科学

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24&#160;hr&#160;after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff.

A rainfall simulator was used to apply a consistent rate of uniform rainfall to packed soil boxes in a study of the fate and transport of urea, a nonpoint source environmental contaminant. Under uniform soil and rainfall conditions, antecedent soil moisture content exerted strong control over urea loss in surface runoff.

一个协议，用于开展降雨模拟研究土壤径流

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The ...

Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.

This article showcases the static chamber-based method for measurement of greenhouse gas flux from soil systems. With relatively modest infrastructure investments, measurements may be obtained from multiple treatments/locations and over timeframes ranging from hours to years.

从农业土壤使用静态钱伯斯温室气体流量测量

Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the ...

A Protocol for Collecting and Constructing Soil Core Lysimeters

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the landscape has complex and varied soil morphology, an accompanying disparity in flow paths for leachate through the soil macropore and matrix structure is present. The rate of flow through these paths is further affected by antecedent soil moisture. Lysimeters are used to quantify flow rate, volume of water and concentration of nutrients leaching downward through soils. While many lysimeter designs exist, accurately determining the volume of water and mass balance of nutrients is best accomplished with bounded lysimeters that leave the natural soil structure intact. 
Here we present a detailed method for the extraction and construction of soil core lysimeters equipped with soil moisture sensors at 5 cm and 25 cm depths. Lysimeters from four different Coastal Plain soils (Bojac, Evesboro, Quindocqua and Sassafras) were collected on the Delmarva Peninsula and moved to an indoor climate controlled facility. Soils were irrigated once weekly with the equivalent of 2 cm of rainfall to draw down soil nitrate-N concentrations. At the end of the draw down period, poultry litter was applied (162 kg TN ha-1) and leaching was resumed for an additional five weeks. Total recovery of applied irrigation water varied from 71% to 85%. Nitrate-N concentration varied over the course of the study from an average of 27.1 mg L-1 before litter application to 40.3 mg L-1 following litter application. While greatest flux of nutrients was measured in soils dominated by coarse sand (Sassafras) the greatest immediate flux occurred from the finest textured soil with pronounced macropore development (Quindocqua).

A detailed method for extraction and assembly of intact soil core lysimeters and their use for study of leachate and associated loss of nutrients from surface applied poultry litter is demonstrated.

一种用于收集和构建土芯协议测渗计

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the ...

Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils

Recent soils research has shown that important chemical soil characteristics can change in less than a decade, often the result of broad environmental changes. Repeated sampling to monitor these changes in forest soils is a relatively new practice that is not well documented in the literature and has only recently been broadly embraced by the scientific community. The objective of this protocol is therefore to synthesize the latest information on methods of soil resampling in a format that can be used to design and implement a soil monitoring program. Successful monitoring of forest soils requires that a study unit be defined within an area of forested land that can be characterized with replicate sampling locations. A resampling interval of 5 years is recommended, but if monitoring is done to evaluate a specific environmental driver, the rate of change expected in that driver should be taken into consideration. Here, we show that the sampling of the profile can be done by horizon where boundaries can be clearly identified and horizons are sufficiently thick to remove soil without contamination from horizons above or below. Otherwise, sampling can be done by depth interval. Archiving of sample for future reanalysis is a key step in avoiding analytical bias and providing the opportunity for additional analyses as new questions arise.

Repeated soil sampling has recently been shown to be an effective way to monitor forest soil change over years and decades. To support its use, a protocol is presented that synthesizes the latest information on soil resampling methods to aid in the design and implementation of successful soil monitoring programs.

土壤重采样的方法监控森林土壤的化学浓度的变化

Recent soils research has shown that important chemical soil characteristics can change in less than a decade, often the result of broad environmental ...

Capturing Flow-weighted Water and Suspended Particulates from Agricultural Canals During Drainage Events

The purpose of this study is to describe the methods used to capture flow-weighted water and suspended particulates from farm canals during drainage discharge events. Farm canals can be enriched by nutrients such as phosphorus (P) that are susceptible to transport. Phosphorus in the form of suspended particulates can significantly contribute to the overall P loads in drainage water. A settling tank experiment was conducted to capture suspended particulates during discrete drainage events. Farm canal discharge water was collected in a series of two 200 L settling tanks over the entire duration of the drainage event, so as to represent a composite subsample of the water being discharged. Imhoff settling cones are ultimately used to settle out the suspended particulates. This is achieved by siphoning water from the settling tanks via the cones. The particulates are then collected for physico-chemical analyses.

Nutrients present in particulate form can contribute significantly to the overall loads in agricultural drainage waters. This study describes a novel method to capture flow-weighted water and suspended particulates from farm canal drainage over the entire duration of the drainage event.

在排水过程中捕获农用运河中的流动加权水和悬浮颗粒

The purpose of this study is to describe the methods used to capture flow-weighted water and suspended particulates from farm canals during drainage ...

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it regulates the gravity-driven soil movement induced by runoff and tillage activities. The recent application of Light Detection and Ranging (LiDAR) data holds promise for generating high spatial resolution topographic metrics that can be used to investigate soil property variability. In this study, fifteen topographic metrics derived from LiDAR data were used to investigate topographic impacts on redistribution of soil and spatial distribution of soil organic carbon (SOC). Specifically, we explored the use of topographic principal components (TPCs) for characterizing topography metrics and stepwise principal component regression (SPCR) to develop topography-based soil erosion and SOC models at site and watershed scales. Performance of SPCR models was evaluated against stepwise ordinary least square regression (SOLSR) models. Results showed that SPCR models outperformed SOLSR models in predicting soil redistribution rates and SOC density at different spatial scales. Use of TPCs removes potential collinearity between individual input variables, and dimensionality reduction by principal component analysis (PCA) diminishes the risk of overfitting the prediction models. This study proposes a new approach for modeling soil redistribution across various spatial scales. For one application, access to private lands is often limited, and the need to extrapolate findings from representative study sites to larger settings that include private lands can be important.

Landscape processes are critical components of soil formation and play important roles in determining soil properties and spatial structure in landscapes. We propose a new approach using stepwise principal component regression to predict soil redistribution and soil organic carbon across various spatial scales.

利用主成分扩展地形模型绘制土壤再分配和土壤有机碳

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it ...

Measuring Phosphorus Release in Laboratory Microcosms for Water Quality Assessment

Phosphorus (P) is a critical limiting nutrient in agroecosystems requiring careful management to reduce transport risk to aquatic environments. Routine laboratory measures of P bioavailability are based on chemical extractions performed on dried samples under oxidizing conditions. While useful, these tests are limited with respect to characterizing P release under prolonged water saturation. Labile orthophosphate bound to oxidized iron and other metals can rapidly desorb to solution in reducing environments, increasing P mobilization risk to surface runoff and groundwater. To better quantify P desorption potential and mobility during extended saturation, a laboratory microcosm method was developed based on repeated sampling of porewater and overlying floodwater over time. The method is useful for quantifying P release potential from soils and sediments varying in physicochemical properties and can improve site-specific P mitigation efforts by better characterizing P release risk in hydrologically active areas. Advantages of the method include its ability to simulate in situ dynamics, simplicity, low cost, and flexibility.

Accurate quantification of phosphorus (P) desorption potential in saturated soils and sediments is important for P modeling and transport mitigation efforts. To better account for in situ soil-water redox dynamics and P mobilization under prolonged saturation, a simple approach was developed based on repeated sampling of laboratory microcosms.

测量实验室微量微生物中的磷释放,用于水质评估

Phosphorus (P) is a critical limiting nutrient in agroecosystems requiring careful management to reduce transport risk to aquatic environments. Routine ...

Electrostatic Method to Remove Particulate Organic Matter from Soil

Estimations of soil organic carbon are dependent on soil processing methods including removal of undecomposed plant material. Inadequate separation of roots and plant material from soil can result in highly variable carbon measurements. Methods to remove the plant material are often limited to the largest, most visible plant materials. In this manuscript we describe how electrostatic attraction can be used to remove plant material from a soil sample. An electrostatically charged surface passed close to dry soil naturally attracts both undecomposed and partially decomposed plant particles, along with a small quantity of mineral and aggregated soil. The soil sample is spread in a thin layer on a flat surface or a soil sieve. A plastic or glass Petri dish is electrostatically charged by rubbing with polystyrene foam or nylon or cotton cloth. The charged dish is passed repeatedly over the soil. The dish is then brushed clean and recharged. Re-spreading the soil and repeating the procedure eventually results in a diminishing yield of particulates. The process removes about 1 to 5% of the soil sample, and about 2 to 3 times that proportion in organic carbon. Like other particulate removal methods, the endpoint is arbitrary and not all free particulates are removed. The process takes approximately 5 min and does not require a chemical process as do density flotation methods. Electrostatic attraction consistently removes material with higher than average C concentration and C:N ratio, and much of the material can be visually identified as plant or faunal material under a microscope.

Removing recently deposited and incompletely decomposed plant material from soil samples reduces the influence of temporary seasonal inputs on soil organic carbon measurements. Attraction to an electrostatically charged surface can be used to quickly remove a substantial amount of particulate organic matter.

从土壤中去除颗粒有机物的静电方法

Estimations of soil organic carbon are dependent on soil processing methods including removal of undecomposed plant material. Inadequate separation of ...

Estimation of Crystalline Cellulose Content of Plant Biomass using the Updegraff Method

Cellulose is the most abundant polymer on Earth generated by photosynthesis and the main load-bearing component of cell walls. The cell wall plays a significant role in plant growth and development by providing strength, rigidity, rate and direction of cell growth, cell shape maintenance, and protection from biotic and abiotic stressors. The cell wall is primarily composed of cellulose, lignin, hemicellulose and pectin. Recently plant cell walls have been targeted for the second-generation biofuel and bioenergy production. Specifically, the cellulose component of the plant cell wall is used for the production of cellulosic ethanol. Estimation of cellulose content of biomass is critical for fundamental and applied cell wall research. The Updegraff method is simple, robust, and the most widely used method for the estimation of crystalline cellulose content of plant biomass. The alcohol insoluble crude cell wall fraction upon treatment with Updegraff reagent eliminates the hemicellulose and lignin fractions. Later, the Updegraff reagent resistant cellulose fraction is subjected to sulfuric acid treatment to hydrolyze the cellulose homopolymer into monomeric glucose units. A regression line is developed using various concentrations of glucose and used to estimate the amount of the glucose released upon cellulose hydrolysis in the experimental samples. Finally, the cellulose content is estimated based on the amount of glucose monomers by colorimetric anthrone assay.

The Updegraff method is the most widely used method for the cellulose estimation. The main purpose of this demonstration is to provide a detailed Updegraff protocol for estimation of cellulose content in plant biomass samples.

使用上格拉夫方法估计植物生物质的晶体纤维素含量

Cellulose is the most abundant polymer on Earth generated by photosynthesis and the main load-bearing component of cell walls. The cell wall plays a ...