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Title:Evaluation of reclaimed coal-mined prime farmland based on soil characteristics in lieu of the current yield-based approach
Author(s):Armstrong, Kevin
Director of Research:Bollero, German A.
Doctoral Committee Chair(s):Bollero, German A.
Doctoral Committee Member(s):Bullock, Donald G.; Ellsworth, Timothy R.; Villamil, Maria B.; Dunker, Robert E.
Department / Program:Crop Sciences
Discipline:Crop Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(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.
Issue Date:2013-05-24
URI:http://hdl.handle.net/2142/44380
Rights Information:Copyright 2013 Kevin L. Armstrong
Date Available in IDEALS:2013-05-24
Date Deposited:2013-05


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