Mapping soil trafficability by way of temporal hydrology modeling and spatial wet-areas-mapping
| dc.contributor.advisor | Arp, Paul | |
| dc.contributor.author | Jones, Marie-France | |
| dc.date.accessioned | 2023-03-01T16:18:11Z | |
| dc.date.available | 2023-03-01T16:18:11Z | |
| dc.date.issued | 2019 | |
| dc.date.updated | 2020-11-24T00:00:00Z | |
| dc.description.abstract | Heavy forest operations can lead to extensive soil disturbances in the form of soil compaction and displacement resulting in deep rut formations, and increased erosion. To mitigate these effects through forecasting, this Thesis reports on a Soil Trafficability Model (STRAM) to estimate daily soil moisture, penetrability and potential machine-specific soil rut depths, using the Forest Hydrology Model ForHyM in conjunction with digital high-resolution wet-area and soil property maps. Model development was guided using in-field data for model validation. The data so acquired refer to (i) biweekly year-round observations of soil moisture and penetrability conditions at select sites in Fredericton, (ii) reporting on GPS-tracked wood-forwarding machine clearances in select harvest blocks across northwestern New Brunswick, and (iii) analyzing soil moisture, soil penetrability and rut depths inside and outside some of the wood-forwarding tracks, by harvest block conditions. It was found that, through multivariate regression analysis (MR), 40 to 60 % of the field-determined soil penetrability variations by way of the cone penetrability index (CI) could be related to combined variations in pore space, coarse fragment content and weather-affected variations in soil moisture. The variations in wood-forwarding machine clearances and rut depths followed a similar pattern, but the number of passes over the same track needed to be taken into account as well. Block-specific variations in elevation, forest cover type and time of operation and machine specific variations in foot-print pressure also contributed to the rut depth variations. Using Random Forest (RF) techniques considerably improved the fitting of the field-determined variations in soil moisture, cone index and wood-forwarding rut depth to greater than 80 %. From MR to RF, the uncertainty range narrowed for best-fitted pore-filled soil moisture content from ±15 to ±4.5 %, for best-fitted soil cone penetrability from ±0.7 to ±0.4 MPa, and for best-fitted rut depth from ±13 to ±5cm. | |
| dc.description.copyright | ©Marie-France Jones, 2019 | |
| dc.description.note | Electronic Only. | |
| dc.format | text/xml | |
| dc.format.extent | xxii, 199 pages | |
| dc.format.medium | electronic | |
| dc.identifier.other | Thesis 10458 | |
| dc.identifier.uri | https://unbscholar.lib.unb.ca/handle/1882/13405 | |
| dc.language.iso | en_CA | |
| dc.publisher | University of New Brunswick | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.subject.discipline | Forestry and Environmental Management | |
| dc.title | Mapping soil trafficability by way of temporal hydrology modeling and spatial wet-areas-mapping | |
| dc.type | master thesis | |
| dc.type | doctoral thesis | |
| thesis.degree.discipline | Forestry and Environmental Management | |
| thesis.degree.fullname | Doctor of Philosophy in Forestry and Environmental Management | |
| thesis.degree.grantor | University of New Brunswick | |
| thesis.degree.level | masters | |
| thesis.degree.level | doctoral | |
| thesis.degree.name | Ph.D. |
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