Stochastic dynamic optimization approach for revegetation of reclaimed mine soils under uncertain weather regime

Simple item page
dc.contributor.authorMustafa, Golamen
dc.contributor.committeechairDillaha, Theo A. IIIen
dc.contributor.committeememberDaniels, W. Leeen
dc.contributor.committeememberSarin, Subhash C.en
dc.contributor.committeememberMostaghimi, Saieden
dc.contributor.committeememberParker, John C.en
dc.contributor.departmentAgricultural Engineeringen
dc.date.accessioned2015-07-10T19:59:58Zen
dc.date.available2015-07-10T19:59:58Zen
dc.date.issued1989en
dc.description.abstractThis study presents a comprehensive physically based stochastic dynamic optimization model to assist planners in making decisions concerning mine soil depths and soil mixture ratios required to achieve successful revegetation of mined lands at different probability levels of success, subject to an uncertain weather regime. A perennial grass growth model was modified and validated for predicting vegetation growth in reclaimed mine soils. The plant growth model is based on continuous relationships between plant growth, air temperature, day length, leaf area, photoperiod and plant-soil-moisture stresses. A plant available soil moisture model was adopted to estimate daily soil moisture for mine soils. A general probability model was developed to estimate the probability of successful revegetation in a 5-year bond release period. The probability model considers five possible bond release criteria ir1 mine soil reclamation planning. A stochastic dynamic optimization model (SDOM) was developed to find the optimum combination of soil depth and soil mixture ratios that met the successful vegetation standard under non-irrigated conditions with weather as the only random element of the system. The SDOM was applied for Wise County, Virginia, and the model found that 2:1 sandstone/siltstone soil mixture required the minimum soil depth to achieve successful revegetation. These results were also supported by field data. The developed model allows the planners to better manage lands drastically disturbed by surface mining.en
dc.description.degreePh. D.en
dc.format.extentviii, 169 leavesen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/10919/54394en
dc.language.isoen_USen
dc.publisherVirginia Polytechnic Institute and State Universityen
dc.relation.isformatofOCLC# 19841242en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V856 1989.M877en
dc.subject.lcshReclamation of landen
dc.subject.lcshRevegetationen
dc.subject.lcshMine soilsen
dc.subject.lcshStochastic processesen
dc.titleStochastic dynamic optimization approach for revegetation of reclaimed mine soils under uncertain weather regimeen
dc.typeDissertationen
dc.type.dcmitypeTexten
thesis.degree.disciplineAgricultural Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
LD5655.V856_1989.M877.pdf
Size:
5.29 MB
Format:
Adobe Portable Document Format
Download

Collections

Doctoral Dissertations