Name: measuring and mapping patterns of soil erosion and deposition related to soil carbonate concentrations under agricultural management
Uploaded: 2017-09-12T13:00:00
Description: 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

The field study site is on a farm managed by David Drake and we thank him for his cooperation during this long-term research. We also thank Mike Murphy for his many years of field work on this project and Robin Montenieri for her help with graphics used in this paper.

1. Land Surface Elevation Data Collection
<ol>
	<li>GPS calibration for site
	<ol>
		<li>Locate or set a stable benchmark in a secure location at the survey site for use as the base station GPS for RTKGPS data collection.</li>
		<li>Set up base station for RTKGPS data collection at this local benchmark using best approximation of coordinates for the base station location (i.e., WAAS-corrected GPS position).</li>
		<li>With the rover GPS, visit at least three horizontal and vertical control point benchmarks wit...

<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. 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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. 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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. 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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. 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Mapped changes in elevation (Figure 5) illustrate significant erosion and deposition on an agricultural field and spatial patterns indicative of multiple controlling factors over multiple scales. From field scale patterns associated with wind, down to fine scale dendritic patterns produced by water flow, processes relevant to this study are discernable. The level of elevation change detection provided by repeated RTKGPS ground surveys appears optimal. Finer detection levels, as provided by T...

Soil erosion threatens the sustainability of agricultural lands. Crop management, such as a conventionally-tilled winter wheat-fallow crop rotation, can accelerate erosion and deposition processes as bare soils during fallow periods are more susceptible to wind and water forces1,2,3,4,5 (Figure 1). While these processes might be evident, they can be difficult to quantify.
The purpose of this study is first to provide an efficient method for quantifying and describing spatial patterns of erosion and deposition at the field scale using global positioning system (GPS) technology and geographic information systems (GIS) mapping tools. A simple conceptual model relating these patterns to near-surface soil carbonates (CaCO3) is also presented and tested by prescribed field and laboratory methods. These relationships provide indirect measures of erosion and deposition, while validating the results of the GPS method. The present paper emphasizes the methods used in Sherrod et al. so that they can be repeated, in part or whole, for similar research in other locations6.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56064/56064fig1.jpg" /> 
Figure 1. Photos of (a) Erosion and (b) Deposition at the Study Site Following a Heavy Rainfall Event. A tractor tire track in the lower right corner of photo (b) indicates the depth of deposition at the wheat/fallow strip border.
Various direct methods for measuring soil erosion were reviewed by Stroosnijder7. Suggested methods vary with the measurement purpose and resources available, but a &#34;change in surface elevation&#34; method is recommended at the hillslope scale and provides the advantage of measuring both erosion and deposition. One way to apply this method is to install pins in the soil and monitor the change in height of the soil relative to the top of the pin7. With advances in land surveying technology, however, this labor-intensive approach can be replaced by other techniques, such as terrestrial laser scanning (TLS)8,9,10,11,12,13,14,15,16, airborne laser scanning (ALS)17,18,19,20,21, GPS6,22, advanced photogrammetry23,24, or combinations of these techniques25,26,27. While laser scanning, commonly referred to as LiDAR (Light Detection And Ranging), provides the most rapid acquisition of dense surface elevation data sets, corrections must be made to remove standing objects, such as vegetation. With millimeter-level vertical precision, TLS can detect the smallest elevation change, however Perroy et al. recommended ALS over TLS for gulley erosion estimates due to the larger scanning footprint and better instrument orientation (less topographic shadowing) for scanning into deeply incised gullies28. Real-time kinematic GPS (RTKGPS), providing centimeter-level precision without data post-processing, is used for this study. The spatial resolution and precision of RTKGPS-collected data are optimal for detecting the dominant erosional and depositional features in an agricultural field or other environments with substantial ground cover.
The pressure-calcimeter method for quantifying soil CaCO3 relies on the soil&#39;s reaction to acid in a closed system, resulting in the release of CO2. The increase in pressure within the reaction vessel at a constant temperature is linearly correlated to the amount of soil CaCO329. Modifications to the traditional pressure-calcimeter method, described by Sherrod et al., include changing the reaction vessel to serum bottles and using a pressure transducer wired to a digital voltmeter for the detection of pressure changes30. These modifications allow for lower detection limits and a higher capacity for daily soil sample runs. Gravimetric or simple titrimetric methods for soil CaCO3 measurement produced larger errors and detection limits than this modified pressure-calcimeter method30.
Conceptual Model
When direct measures of erosion and deposition are not feasible, indirect indicators of these processes may be used. Sherrod et al. hypothesized that soil surface layer CaCO3 concentration in a semi-arid climate is inversely correlated with the change in ground surface elevation (positively correlated with erosion, negatively correlated with deposition)6. The hypothesis should apply broadly, but specific relationships will depend upon site conditions (soil, vegetation, management, and climate). Soils at the test site (Table 1) typically contain a distinct calcareous layer 15-20 cm below the soil surface. Conceptually, erosion will remove the surface layer of relatively low CaCO3 concentration leaving this calcareous layer of high CaCO3 closer to the soil surface. The low CaCO3 soil is then transported to the depositional areas, causing the calcareous layer to be buried deeper below the soil surface (Figure 2). Sampling these soils over time at appropriate depth intervals, either erosion or deposition (or neither) may be inferred by CaCO3 concentration, according to this model.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Soil Series</td>
			<td>Slope</td>
			<td>Taxonomic classification</td>
			<td>Depth</td>
			<td>pH</td>
			<td>EC</td>
			<td>Total N</td>
			<td>SOC</td>
			<td>CaCO3</td>
		</tr>
		<tr>
			<td></td>
			<td>%</td>
			<td></td>
			<td>cm</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>Colby loam</td>
			<td>5-9</td>
			<td>fine-silty, mixed, superactive, calcareous, mesic 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>Kim sandy loam</td>
			<td>2-5</td>
			<td>fine-loamy, mixed, active, calcareous, mesic 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>fine-loamy, mixed, active, calcareous, mesic 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 loam</td>
			<td>0-2</td>
			<td>coarse-silty, mixed, superactive, mesic 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>coarse-silty, mixed, superactive, mesic 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>
	</tbody>
</table>
Table 1. Soils at the Test Site. Soil mapping units and taxonomic classification, with average soil pH, electrical conductivity (EC), total N, soil organic C (SOC), and CaCO3 concentrations in the 0- to 15- and 15- to 30-cm depth increments for the Scott field in 2012 (from Sherrod et al.)6.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56064/56064fig2.jpg" /> 
Figure 2. Conceptual Soil Profiles. Conceptual soil profiles for (a) a static soil matrix with CaCO3 leached from the surface layer and precipitated in a deeper layer, (b) moderate erosion of the surface layer, and (c) moderate deposition of material above the previous surface layer. Depth intervals (left) are approximate based on site data (from Sherrod et al.)6. <a href="//cloudflare.jove.com/files/ftp_upload/56064/56064fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Site Description and History
The 109-ha Scott field is part of the Drake Farm in northeastern Colorado (40.61oN, 104.84oW, Figure 3) and was monitored from 2001 to 2012 for this study. Average annual precipitation and evapotranspiration were approximately 350 and 1200 mm, respectively, in this semi-arid climate, where convective rain of short duration and high intensity were common during the summer. Elevations range from 1559 to 1588 m in this undulating terrain with distinct landscape positions: summit, sideslope north-facing (side-NF), sideslope south-facing (side-SF), and toeslope (Figure 4b). Alternating strips (~120 m wide) were typically managed in this rainfed winter wheat-fallow rotation such that every other strip was fallow for about 14 months out of every 24-month rotation cycle. Shallow tillage (~7 cm), typically v-blade sweeps, occurred 4 to 6 times through the fallow period for weed control. Soils at the site were classified to have a soil-loss tolerance, or T value, of 11 Mg ha-1 year-1, where erosion rates below this T value are considered acceptable for continued agricultural production4.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56064/56064fig3.jpg" /> 
Figure 3. Site Location is Shown on a Topographic Relief Image (1011 to 4401 m) of the State of Colorado, USA. Mean elevation of the site is 1577 m.
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56064/56064fig4.jpg" /> 
Figure 4. Soils map and Land Surface Elevation of the Scott Field. (a) Soils map of the Scott Field showing point soil sample locations and the crop management strips. Soil unit abbreviations are: 1 = Wagonwheel loam 0-2% slope, 2 = Wagonwheel loam 2-5% slope, 3 = Colby loam 5 - 9% slope, 4 = Kim fine sandy loam 2 - 5% slope, 5 = Kim fine sandy loam 5-9% slope; and (b) land surface elevation of the field based on the 2001 5-m grid digital elevation model (DEM), with soil sample locations shown by land classification (from Sherrod et al.)6.
The first ground surface elevation survey was collected by RTKGPS in 2001 to produce a digital elevation model (DEM) for the site. In conjunction with McCutcheon et al., an intensive soil sample (Figure 4a) was also performed in 2001, from which surface soil CaCO3 were analyzed by a modified pressure-calcimeter method30,31. Visually evident erosion and deposition occurring over the subsequent decade due to wind, predominantly from the northwest, and rainfall-runoff events prompted a second RTKGPS elevation survey in 2009 (with a portion of the field completed in 2010). Comparison of the new DEM to the original 2001 DEM via a DEM of Difference map32 confirmed significant erosion and deposition, displaying patterns which suggested multiple controlling factors for these processes (Figure 5). Given the substantial surface soil redistribution at the site and the historical soil CaCO3 data, the 2001 soil sample was repeated in 2012 to test a conceptual model of hydropedological processes6, as described in the previous section.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56064/56064fig5.jpg" /> 
Figure 5. Map of Changes (2001-2009*) in Land Surface elevation (&#916;z) on a 5-m Grid within the Scott Field in Northeastern Colorado. Crop strip numbers are labeled over the alternating winter-wheat-fallow cropping system, and section A-A&#39; is shown (details given in Figure 11). *Strips 2, 4, 6, 8 surveyed in 2010 to complete the 2009 DEM (from Sherrod et al.)6. <a href="//cloudflare.jove.com/files/ftp_upload/56064/56064fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</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

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes in elevation are related to changes in near-surface soil carbonate (CaCO3) profiles. The objective is to describe a simple conceptual model and detailed protocol for repeatable field and laboratory measurements of these quantities. Here, accurate elevation is measured using a ground-based differential global positioning system (GPS); other data acquisition methods could be applied to the same basic method. Soil samples are collected from prescribed depth intervals and analyzed in the lab using an efficient and precise modified pressure-calcimeter method for quantitative analysis of inorganic carbon concentration. Standard statistical methods are applied to point data, and representative results show significant correlations between changes in soil surface layer CaCO3 and changes in elevation consistent with the conceptual model; CaCO3 generally decreased in depositional areas and increased in erosional areas. Maps are derived from point measurements of elevation and soil CaCO3 to aid analyses. A map of erosional and depositional patterns at the study site, a rain-fed winter wheat field cropped in alternating wheat-fallow strips, shows the interacting effects of water and wind erosion affected by management and topography. Alternative sampling methods and depth intervals are discussed and recommended for future work relating soil erosion and deposition to soil CaCO3.

Mapping DEM differences from 2001 and 2009 reveals erosion (red) and deposition (green) over that 8-year period, with decimeter-level changes in elevation over most areas (Figure 5). At the field-scale, erosion is dominant in the west and southwest, while deposition is seen along a northwest to southeast diagonal band on the eastern side of the field. Alternating bands of erosion and deposition are seen at the management-scale, often with abrupt changes at th...

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

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes in elevation are related to changes in near-surface soil carbonates. Repeatable methods for field and laboratory measurements of these quantities and data analysis methods are described here.

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

The overall goals of this study are first to provide an efficient method for quantifying and describing spatial patterns of soil erosion and deposition at field scales and second, to test a conceptual model relating these patterns to near surface soil carbonates. These methods give us a better understanding of the inter relationships between surface soil carbonates and the land surface processes of erosion and deposition. The main advantages of these techniques are the accurate detection of changes in soil surface elevation over time and the rapid analysis of soil carbonates over many soil samples.We first had the idea for this research after updating the digital elevation maps. A map of the elevation differences showed clear patterns of erosion and deposition and we wanted to look at how that related to carbonate concentrations. For this protocol, use field software to record the RTK GPS position data at every five minutes throughout the survey area.Begin by performing a site calibration to local benchmarks to ensure the highest level of accuracy. A local site calibration for the area to be surveyed, provides necessary horizontal and vertical control for the GPS method. This ensures a centimeter level accuracy needed to detect small elevation changes.For efficient data collection, mount a rover GPS antenna at a fixed height above the ground on a vehicle. Then import the transect in points into the GPS data collector, and navigate between them while driving and collecting data at a constant speed to map five meter intervals. Additionally, have a vehicle mounted hydraulic soil coring machine and use a sampling tube of desired soil core diameter.To extract cores at locations identified with RTK GPS position data. Soil sampling is performed by pulling a soil core with the soil coring machine. Push the soil core out of the sampling tube and cut into desired depth increments.Transfer the soil samples into pre-labeled sealable plastic bags. Then store the samples in coolers to transport them to the laboratory. When repeating these analysis after significant soil erosion and deposition events have occurred, return to the same sample locations using the GPS and collect new soil cores.In the lab, prepare the soil samples for analysis. To begin, dry them in a 60 degree celsius oven overnight. The next day, grind the dry soil samples through a two millimeter sieve, using either a motorized grinder or grind manually with a mortar and pestle.The next step, requires setting up a modified pressure calcimeter apparatus. First, connect a pressure transducer to a power supply with 14 gauge wire. Include an attached digital volt meter to monitor output from the transducer.Include a 0.6 micron particle filter to collect an even flux and thus, protect the pressure transducer. Next, attach tubing to the base of the particle filter and connect the tubing to an 18 gauge luer lock hypodermic needle. Next, determine if the reaction vessels should be at 20 or 100 milliliter serum bottle.Wet a metal tablespoon with water and scoop up about a teaspoon of soil that may have a high carbonate concentration. Pipette one milliliter of 0.5 anhydrous sulfuric acid onto the soil and observe effervescence. If effervescence is high, then assume calcium carbonate is greater than 15%and use a 100 milliliter vessel.Otherwise, use a 20 milliliters serum bottle. To determine the carbonate concentration, weigh one gram of prepared soil sample into a labeled reaction vessel. Next, pipette two milliliters of acid reagent into a vial.Gently place the vial into the reaction vessel, so it doesn't spill, then carefully seal the vessel using a gray butyl rubber stopper and clip it with an aluminum sealing ring. Now shake the vessel to spill the acid onto the soil sample and let the reaction proceed for at least two hours. While waiting, make a standard gar using standards in a parallel setup with the same parameters.Make standards by mixing 100%calcium carbonate with glass beads or sand based on weight, not volume. When determining a standard gar, it's important to accurately know the voltage of the zero calcium carbonate since this defines the detection limit of the method. I typically measure the blank three times along with a known standard concentrations to derive a gar.After the soil sample reaction is complete, pierce the rubber septum of the reaction vessel and record voltage output by the pressure transducer. Later, solve for the calcium carbonate percentage in the sample using the standard curve. Mapping DEM differences from 2001 and 2009, revealed erosion and deposition over that eight year period.With decimeter level changes in elevation over most areas. Find scale erosional and depositional patterns that resemble water flow paths occurred in areas of topographic convergence. Calcium carbonate samples were taken in 2001 and 2012, to compare with the erosion and deposition that occurred in the study area and to test the conceptual model.When comparing soil samples of the east and west block of management strips, an inverse relationship was found between the change in surface soil calcium carbonate and the change in land surface elevation. An analysis of variants show that change in elevation is significantly affected by all side variables. Whereas, changes in calcium carbonate were most significantly affected by erosional class or EDU or mapped soil unit.Five soil units were determined previously by a soil survey of the site. Interpolations of the point sample results show that the relatively small concentrated areas of high and low calcium carbonate in 2001 were not evident in 2012. The spatial pattern had become less complex.The sensitivity of elevation change detection provided by repeated RTK GPS ground surveys appears optimal in quantifying and describing the erosion and deposition processes of the field scale. The modified pressure proximity method is a great technique for measuring carbonates and we can process many samples in a short amount of time. Soil surface elevation were more readily detected than changes in soil carbonates, probably due to the core's increment of sampling which was 30 centimeters in 2001.Future sampling increments of 15 centimeters should improve our detection of soil carbonates. The conceptual model and methods described here can be applied to other sides where calcareous layers are present near the soil surface.

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

Research

JoVE Journal

Environment

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.

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

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.

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.

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.

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

A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a series of incubators. A temperature gradient is passively established across the surface of the table between the heated and cooled ends and is lost quickly at distances above the surface. Since temperature is only controlled on the table surface, experiments are restricted to shallow containers, such as Petri dishes, placed on the table. Welding continuous aluminum vertical strips or gussets perpendicular to the surface of a table enables temperature control in depth via convective heat flow. Soil in the channels between gussets was maintained across a gradient of temperatures allowing a greater diversity of experimentation. The gusseted design was evaluated by germinating oat, lettuce, tomato, and melon seeds. Soil temperatures were monitored using individual, battery-powered dataloggers positioned across the table. LED lights installed in the lids or along the sides of the gradient table create a controlled temperature chamber where seedlings can be grown over a range of temperatures. The gusseted design enabled accurate determination of optimum temperatures for fastest germination rate and the highest percentage germination for each species. Germination information from gradient table experiments can help predict seed germination and seedling growth under the adverse soil conditions often encountered during field crop production. Temperature effects on seed germination, seedling growth, and soil ecology can be tested under controlled conditions in a laboratory using a gusseted thermogradient table.

Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a ...

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.

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.

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

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions

Soil organic matter (SOM) underlies numerous soil processes and functions. Fourier transform infrared (FTIR) spectroscopy detects infrared-active organic bonds that constitute the organic component of soils. However, the relatively low organic matter content of soils (commonly &#60; 5% by mass) and absorbance overlap of mineral and organic functional groups in the mid-infrared (MIR) region (4,000-400 cm-1) engenders substantial interference by dominant mineral absorbances, challenging or even preventing interpretation of spectra for SOM characterization. Spectral subtractions, a post-hoc mathematical treatment of spectra, can reduce mineral interference and enhance resolution of spectral regions corresponding to organic functional groups by mathematically removing mineral absorbances. This requires a mineral-enriched reference spectrum, which can be empirically obtained for a given soil sample by removing SOM. The mineral-enriched reference spectrum is subtracted from the original (untreated) spectrum of the soil sample to produce a spectrum representing SOM absorbances. Common SOM removal methods include high-temperature combustion (&#39;ashing&#39;) and chemical oxidation. Selection of the SOM removal method carries two considerations: (1) the amount of SOM removed, and (2) absorbance artifacts in the mineral reference spectrum and thus the resulting subtraction spectrum. These potential issues can, and should, be identified and quantified in order to avoid fallacious or biased interpretations of spectra for organic functional group composition of SOM. Following SOM removal, the resulting mineral-enriched sample is used to collect a mineral reference spectrum. Several strategies exist to perform subtractions depending on the experimental goals and sample characteristics, most notably the determination of the subtraction factor. The resulting subtraction spectrum requires careful interpretation based on the aforementioned methodology. For many soil and other environmental samples containing substantial mineral components, subtractions have strong potential to improve FTIR spectroscopic characterization of organic matter composition.

SOM underlies many soil functions and processes, but its characterization by FTIR spectroscopy is often challenged by mineral interferences. The described method can increase the utility of SOM analysis by FTIR spectroscopy by subtracting mineral interferences in soil spectra using empirically obtained mineral reference spectra.

Soil organic matter (SOM) underlies numerous soil processes and functions. Fourier transform infrared (FTIR) spectroscopy detects infrared-active organic ...

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.

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.

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