skip to main content

Title: Erosion mechanisms of claypan soils in southeastern Kansas
Claypan soils cover approximately 40,469 km2 in the United States and are characterized by a highly impermeable layer within 0.5 m from the ground surface. This impermeable layer acts as a barrier for infiltrating water, which may increase erosion rates and sediment transport. Two of the main problems associated with these processes are abutment scour and reservoir sedimentation. This study focuses on the undermining of surficial soils due to an impermeable claypan layer in Southeastern Kansas. The potential areas of critical soil loss and hydrologic flow patterns were determined using LiDAR-derived digital elevation maps across two 0.45 km2 sites. These sites were located in areas of both high and low elevation. Electrical resistivity tomography (ERT) was used in areas identified with LiDAR to measure the depth to claypan, which was originally believed to be uniform across the region. The results indicated that the claypan layer was located from 0.5 to 0.75 m and dissipated moving across the site from an area of high elevation to an area of low elevation. Undisturbed soil samples were collected based on the ERT analysis, in areas with and without the claypan. An erosion function apparatus (EFA) was used to directly measure erosion due to more » sheet flow and to identify the controlling mechanism causing surficial soil loss. The knowledge gained on claypan erosion mechanisms will improve the prediction of near surface soil erodibility to support aging infrastructure. « less
Authors:
Award ID(s):
1705823
Publication Date:
NSF-PAR ID:
10126912
Journal Name:
Eighth International Conference on Case Histories in Geotechnical Engineering
Volume:
2019
Sponsoring Org:
National Science Foundation
More Like this
  1. The objective of this research is to determine the fundamental mechanisms that cause loss of topsoil. Claypan soils cover approximately 10 million acres in the United States and are characterized by a highly impermeable layer below the topsoil. This impermeable layer acts as a barrier for infiltrating water which may be increasing the erosion rate and sediment transport of upper soil layers. This increasing topsoil depletion ultimately limits the productive capacity of agronomic fields. This study focuses on the undermining of the topsoil due to the impermeable claypan layer in Southeastern Kansas where the topsoil depth is limited and, in places, the claypan layer is exposed at the surface. Using LiDAR-derived digital elevation maps, the potential areas of critical soil loss and hydrologic flow patterns is determined. Surface soil apparent electrical conductivity (EC) measurements highlight the soil variability throughout the field. Electrical Resistivity Tomography (ERT) surveys is also performed to determine the depth to the claypan layer in low and high crop yield areas. The results indicate that the areas of high EC correlated with high clay content and low crop yield, while areas of low EC correlated with high crop yield. The results also indicate that the claypan layermore »in the low crop yield area is 1.0 m thick and significantly thins once reaching the high crop yield area. The next phase of this ongoing research is to measure the soil properties between the low and high crop yield areas, measure the movement of water at the claypan interface, and measure sediment transport at the claypan interface.« less
  2. Claypan soils cover approximately 10 million acres across several states in the central United States. The soils are characterized by a highly impermeable clay layer within the profile that impedes water flow and root growth. While some claypan soils can be productive, they must be carefully managed to avoid reductions to crop productivity due to root restrictions, water, and nutrient limitations. Clay soils are usually resistant to erosion but may exacerbate erosion of the silt-loam topsoil. Soil production potential is the capacity of soil to produce at a given level (yield per acre). The productive capacity is tied to soil characteristics, which can be highly variable within a field. In this project, we have used imagery analysis to study the aerial images and terrain of fields during different productive times of the year to identify where soil samples should be collected for more discrete analysis. Soil samples provide valuable information; however, the amount of data obtained from a relatively small area within a field does not provide sufficient information to delineate the subsurface characteristics. To address the limitations of sampling, we have also employed the use of yield maps collected from commercial yield monitors on production-scale combines and surface electricalmore »conductivity measurements (Sassenrath and Kulesza, 2017). Soil conductivity is a measurement of how well a representative volume of soil conducts electricity. Soil conductivity is a function of the soil clay content, moisture content, and other measurable soil properties (Kitchen et al., 2003); as such, it has become a valuable tool for mapping in-field variability. The main advantage of a soil conductivity measurement is that the entire surface of a field can be imaged. The disadvantage of a soil conductivity measurement is that data are only collected near the surface (10 – 30 inches) and the measurements are relative measurements. This means that the conductivity mappers can identify changes in soil properties, but they cannot directly tell researchers what caused these changes. Electrical resistivity tomography (ERT) is a popular near-surface geophysical measurement for geophysical and engineering applications. The term “near-surface” generally means down to around 30 feet in the subsurface. Electrical resistivity is the reciprocal measurement of electrical conductivity; therefore, both systems measure differences in the same soil properties. ERT measurements are different than surface electrical conductivity measurements because ERT collects a “slice” of data into the subsurface, as opposed to only changes at the surface area. Relative measurements, similar to those collected in an electrical conductivity survey, are collected; however, in ERT studies the data are mathematically inverted to yield the true electrical resistivity of the soil with depth. This allows an interpretation of the changing soil properties with depth to reduce the required amount of sampling. A disadvantage of an ERT survey is that the data acquisition is stationary so mapping an entire field is not feasible. We have used a coupled process of imagery and terrain analysis, yield maps, and electrical conductivity measurements to guide the locations of ERT surveys in this project (Tucker-Kulesza et al. 2017).« less
  3. Abstract
    Site description. This data package consists of data obtained from sampling surface soil (the 0-7.6 cm depth profile) in black mangrove (Avicennia germinans) dominated forest and black needlerush (Juncus roemerianus) saltmarsh along the Gulf of Mexico coastline in peninsular west-central Florida, USA. This location has a subtropical climate with mean daily temperatures ranging from 15.4 °C in January to 27.8 °C in August, and annual precipitation of 1336 mm. Precipitation falls as rain primarily between June and September. Tides are semi-diurnal, with 0.57 m median amplitudes during the year preceding sampling (U.S. NOAA National Ocean Service, Clearwater Beach, Florida, station 8726724). Sea-level rise is 4.0 ± 0.6 mm per year (1973-2020 trend, mean ± 95 % confidence interval, NOAA NOS Clearwater Beach station). The A. germinans mangrove zone is either adjacent to water or fringed on the seaward side by a narrow band of red mangrove (Rhizophora mangle). A near-monoculture of J. roemerianus is often adjacent to and immediately landward of the A. germinans zone. The transition from the mangrove to the J. roemerianus zone is variable in our study area. An abrupt edge between closed-canopy mangrove and J. roemerianus monoculture may extend for up to several hundred metersMore>>
  4. Abstract
    Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems mayMore>>
  5. Abstract
    Assessment of lakes for their future potential to drain relied on the 2002/03 airborne Interferometric Synthetic Aperture Radar (IFSAR) Digital Surface Model (DSM) data for the western Arctic Coastal Plain in northern Alaska. Lakes were extracted from the IfSAR DSM using a slope derivative and manual correction (Jones et al., 2017). The vertical uncertainty for correctly detecting lake-based drainage gradients with the IfSAR DSM was defined by comparing surface elevation differences of several overlapping DSM tile edges. This comparison showed standard deviations of elevation between overlapping IfSAR tiles ranging from 0.0 to 0.6 meters (m). Thus, we chose a minimum height difference of 0.6 m to represent a detectable elevation gradient adjacent to a lake as being most likely to contribute to a rapid drainage event. This value is also in agreement with field verified estimates of the relative vertical accuracy (~0.5 m) of the DSM dataset around Utqiaġvik (formerly Barrow) (Manley et al., 2005) and the stated vertical RMSE (~1.0 m) of the DSM data (Intermap, 2010). Development of the potential lake drainage dataset involved several processing steps. First, lakes were classified as potential future drainage candidates if the difference between the elevation of the lake surface andMore>>