Ecological Archives A015-057-A1

S. V. Smith, R. O. Sleezer, W. H. Renwick, and R. W. Buddemeier. 2005. Fates of eroded soil organic carbon: Mississippi Basin case study. Ecological Applications 15:1929–1940.

Appendix A. Details of materials and methods.

General

Much of the geographic information systems (GIS) data processing for this study was done with Arc View 3.2 or 8.2 (Environmental Systems Research Institute, ESRI, http://www.esri.com/).

Mean annual temperature and precipitation data used in Text Table 1 were derived from PRISM (http://www.wcc.nrcs.usda.gov/climate/prism.html). Elevation data are from HYDRO1k (http://lpdaac.usgs.gov/gtopo30/hydro/). Background agricultural data discussed in the text were derived from Agricultural Census data found in the National Atlas of the United States (http://www.nationalatlas.gov/).

Because of ongoing U.S. Geological Survey (USGS) studies there (with particular relevance to this paper, particularly the Mississippi River Basin NASQAN Program, http://water.usgs.gov/nasqan/progdocs/factsheets/missfact/missfs.html), it is relatively straightforward to divide the regional system into five sub-systems approximately equal to USGS Water Resources Hydrological (HUC2) Units 05-06 (Ohio and Tennessee: OH), 07 (Upper MS: UMS), 10 (Missouri: MO), 11 (Arkansas and Red: AR), and 08 (lower MS: LMS) (Seaber et al. 1987; http://water.usgs.gov/GIS/huc.html).

River-borne fluxes

We used U.S. Geological Survey (USGS) data from the National Stream Quality Accounting Network (http://water.usgs.gov/nasqan/). River gaging stations (stream flow, dissolved and particulate OC) summarized in Table A1 of this appendix were used for the period between 1996 and 2002. We calculated flow-weighted concentrations and then fluxes for the selected stations. The gaging stations used to examine river fluxes (Text Figure 1b; Appendix Table A1) do not exactly coincide with the sub-system downstream boundaries, but rather were chosen to exemplify the bulk of the individual drainage basin. For example, the station chosen for UMS was at Grafton, IL, rather than one further downstream, at Thebes, IL. That latter station, while including more of the UMS, also includes outflow from the MO. In all cases we scaled the station results to the entire sub-system by multiplying the flux values by the ratio of total sub-system area to the area above the selected station.

Erosion

Smith et al. (2001) used various data sources to develop a budget of soil erosion, transportation, and deposition for the conterminous U.S. Erosion data are from the Natural Resources Conservation Service (NRCS). We have undertaken further analyses with the NRCS data reported there on estimated soil erosion for the years 1982, 1987, and 1992. In both our original paper and this one, we aggregated the data at the scale of the USGS 8-digit hydrologic mapping units (“HUC8”; Seaber et al., 1987; http://water.usgs.gov/GIS/huc.html).

Organic Carbon

We analyzed SOC using the STATSGO database created by the NRCS (http://www.ncgc.nrcs.usda.gov/products/datasets/statsgo/; U.S. Department of Agriculture, 1994). While higher resolution data are locally available (e.g., SSURGO; Soil Survey Geographic Database; http://www.ncgc.nrcs.usda.gov/products/datasets/ssurgo), these data are designed to be used at local, rather than regional, scales. For the initial analysis and presentation of the STATSGO data here, the data were retained in approximately 33,000 separate map unit identifications (MUID) across the MS Basin. Each STATSGO map unit can have as many as 21 component soils and each component soil can have as many as six layers. For each layer STATSGO contains two values for OM (OML and OMH, low and high concentrations of OM, respectively).

Each component soil is also assigned a percent value (comp percent) that indicates what portion of each map unit it represents. Since our analyses focuses on soil erosion we confined our GIS analysis to the surface soil horizon properties. The area-weighted average OM content was calculated for each map unit by first calculating the average OM content for each surface layer ([OML + OMH] /2), multiplying each resultant value by the appropriate comp percent for the map unit component that corresponds to that layer, and then summing the resultant values. Area-weighted average values for OM were then converted to OC by division by 1.724 (Soil Survey Division Staff, 1993). OCA is the average SOC percentage, so calculated.


Comparison of OC in Upland and Floodplain Soils

One of the goals of the GIS analysis of the STATSGO OM data was a comparison of organic C contents between upland and floodplain soils. The STATSGO database does not contain an attribute that easily differentiates between upland and floodplain soils. Toward this end, the frequency of inundation classes for each component soil in each map unit were ranked in the following manner: None – No reasonable possibility = 0, Rare – 1-5 times in 100 years = 1, Occasional – 5-50 times in 100 years = 2, Frequent ≥ 50 times in 100 years. Units classified as “Water” (lakes, rivers, etc.) were eliminated from the data.

An area-weighted average inundation frequency for each map unit was then calculated by multiplying each component soil’s inundation frequency rank by its component percents and then summing the resultant values for each map unit. Map units with area-weighted average inundation frequencies < 1 are interpreted as being dominantly upland soils. Values ≥ 1 are interpreted as soils in modern floodplains and low terraces that are inundated at least once each 100 years. The assumption is that upland soils are the sources of eroded soil carbon and the floodplain and low terrace soils are depositional areas for that eroded carbon.

For many subsequent comparisons, the soil data were aggregated back to HUC8’s or sub-system values. We were interested in the relationship between the OCA of upland soils and their nearby floodplain soils. The various local and regional case studies cited in the text demonstrate that most anthropogenically generated erosion products are still relatively near the sites where these sediments were generated. This is also true with respect to naturally generated erosion products produced and material deposited over longer time periods. We therefore compiled a scatter diagram of average OCA by HUC8 (Fig. 1).

Of the 833 HUC8’s included in our coverage of the MS Basin, 637 (76%) include both upland and floodplain soils. Our general hypothesis was that floodplain soils should have OCA similar to nearby upland soils from which they were derived if erosion is a conservative process with respect to SOC.

There is a clear ~1:1 trend in the overall values, but a few HUC8’s with either upland or floodplain soil OCA above 4% fall well to either side of this trend (Appendix Fig. A1a). The Pearson’s correlation coefficient (R) between upland and floodplain OCA is only  0.36 at the HUC8 scale if high-C soils are included. Querying the STATSGO database demonstrates that most of the high-OCA soils in the UMS sub-system are organic-rich Histosols, characteristic of cool climates and poor drainage. Similarly, high-OCA values in the LMS are poorly drained swamp and wetland areas.

We therefore restricted our further analyses to HUC8’s with average OCA below 4% for both upland and floodplain soils. This eliminated only 19 of the 637 (3%) HUC8’s having both upland and floodplain soils. A model II regression between the remaining upland and floodplain OCA values aggregated by HUC8 is OCAflood = -0.20 + 1.20 x OCAup (R = 0.70; R2 = 0.49) (Appendix Fig A1b ). Further, the averages ± standard errors for floodplain and upland OCA at the HUC8 aggregation are 1.52 ± 0.06 and 1.53 ± 0.04, respectively. These percentages do not differ statistically from one another (p > 0.05). We conclude that, for most regions in the MS Basin, upland and their associated floodplain soils are very similar to one another in OCA, both at the scale of the HUC8’s and as an average across the Basin.


LITERATURE CITED

Seaber, P. R., F. P. Kapinos, and G. L. Knapp. 1987. Hydrologic Unit Maps. Water Supply Paper 2294, U.S. Geological Survey, 63 pp.

Smith, S.V., W. H. Renwick, R.W. Buddemeier, and C. J. Crossland. 2001. Budgets of soil erosion and deposition for sediments and sedimentary organic carbon across the conterminous United States. Global Biogeochemical Cycles 15:697–707.

Soil Survey Division Staff. 1993. Soil Survey Manual.  U.S. Department of Agriculture Handbook 18.  U.S. Government Printing Office, Washington, D.C., USA.

Soil Survey Division Staff. 1999. Soil Taxonomy. Second Edition.  USDA-NRCS Agricultural Handbook 436. U.S. Government Printing Office, Washington, D.C., USA.

U.S. Department of Agriculture. 1994. State Soil Geographic (STATSGO) Data Base. Miscellaneous Publication 1492, 35 pp.


TABLE A1. Locations of river flow monitoring for the MS Basin, as employed here. Derived from USGS web sites reported in the text and at http://water.usgs.gov/nasqan/.

Station Name

Station Number

Sub-System

Arkansas R., David Terry Dam, AR

07263620

AR

Missouri R., Herman, MO

06934500

MO

Mississippi R., Grafton IL

05587455

UMS

Ohio River, near Grand Chain, IL

03612500

OH

Lower Atchafalaya R., near Melville, LA

07381495

LMS

Mississippi R., near St. Francisville, LA

07373420

LMS

 

 
FIG. A1 . Comparison of % OCA between upland and floodplain soils, averaged for HUC8’s across the Mississippi Basin. (a) Entire data set. (b) Model II regression analyses for those HUC8’s for which OCA in both upland and floodplain soils is less than or equal to 4%..



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