Evaluation of reclaimed coal-mined prime farmland based on soil characteristics in lieu of the current yield-based approach

Armstrong, Kevin

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https://hdl.handle.net/2142/44380 Copy

Description

Title

Evaluation of reclaimed coal-mined prime farmland based on soil characteristics in lieu of the current yield-based approach

Author(s)

Armstrong, Kevin

Issue Date

2013-05-24T22:09:43Z

Director of Research (if dissertation) or Advisor (if thesis)

Bollero, German A.

Doctoral Committee Chair(s)

Bollero, German A.

Committee Member(s)

• Bullock, Donald G.
• Ellsworth, Timothy R.
• Villamil, Maria B.
• Dunker, Robert E.

Department of Study

Crop Sciences

Discipline

Crop Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• crop
• yield
• coal mining
• Mining
• coal
• reclamation
• coal mine reclamation
• soil
• soil model
• crop yield
• statistics
• statistical model
• compaction
• soil strength
• penetrometer
• soil penetrometer
• electrical conductivity
• elevation
• corn
• soybean
• geostatistics
• variography
• variogram
• logistic regression
• logistic
• regression
• probability

Abstract

Since the passage of Public Law 95-87, the Surface Mining Control and Reclamation Act (SMCRA) in 1977, reclamation success of prime farmland after coal mining has been determined by long-term crop yield testing. States such as Illinois and Indiana require that reclamation success be based on crop production of mined-land. This process often can continue for many years, especially for lands failing to meet production standards in a specified period. Needs have been expressed by landowners, mine operators, and regulators for methods to expedite this process. A soil property-based model could relieve this burden and ensure the most efficient process for returning crop production fields to the landowner. The objective of my work was to develop a soil-based model to replace the current crop yield-based system and to evaluate reclaimed land for diagnostic purposes. Georeferenced corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum aestivum L.) yield, cone penetrometer test (CPT), VIS-NIR spectrophotometer, apparent electrical conductivity (ECa), elevation and terrain derivatives, fertility, and other site characteristic data were collected on fields at the Cannelburg, Cypress Creek and Lewis Mine sites in southwestern IN, the Cedar Creek Mine site in western IL, and the Wildcat Hills Mine site in southern IL. Soil-based productivity models were developed using regression and multivariate techniques to assign probabilities of meeting target yield standards at the partial-field level. My research indicates that soil strength and water availability primarily influence a field’s ability (bonding area) to meet target yield standards over time. Model validation between fields and among sites has been encouraging, thus I propose modeling soil variability as a diagnostic tool to identify problematic field areas and to complement crop yield-based requirements.

Graduation Semester

2013-05

Permalink

http://hdl.handle.net/2142/44380

Copyright and License Information

Copyright 2013 Kevin L. Armstrong

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