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dc.contributor.authorTian, Yunhong
dc.date.accessioned2021-10-14 14:50:39 (GMT)
dc.date.available2021-10-14 14:50:39 (GMT)
dc.date.issued2021-10-14
dc.date.submitted2021-09-24
dc.identifier.urihttp://hdl.handle.net/10012/17638
dc.description.abstractSoil erosion remains a primary challenge in the 21st century threatening fresh water and cropland that supports more than 95% of global food production. It is of significance to plan for and prevent soil erosion in its initial stages rather than labor intensive repairing later. The Middle Thames River watershed has suffered from severe erosion issues for more than ten years with 21% highly erodible lands throughout the basin, where extensive soil conservation measures are highly encouraged. A series of practical measures that landowners can apply to enhance soil health and water quality while preserving or increasing agricultural production are termed farmland Best Management Practices (BMPs). Among these measures, grassed waterways, as broad and shallow channels to move concentrated surface runoff, are considered as one of the most effective measures to prevent ephemeral soil erosion. Therefore, identifying the site-specific opportunities for grassed waterways implementation in the Middle Thames River watershed can support targeted soil conservation and the watershed planning. This study aims to identify the potential locations for grassed waterways implementation in the Middle Thames River Watershed using four different techniques with high-resolution data (Compound Topographic Index model, Stream Power Index threshold model, weighted linear overlay, fuzzy logic analysis). The Compound Topographic Index model and Stream Power Index threshold model have been developed to predict the existing and potential grassed waterways at the field level. Then the Compound Topographic Index and Stream Power Index threshold models, the multi-criteria decision analysis (MCDA) has been conducted to map the priority areas for grassed waterways implementation at the watershed scale. The output maps of the Compound Topographic Index model and Stream Power Index threshold model display the location and length of predicted grassed waterways in each field. To better visualize the results of the Compound Topographic Index model and Stream Power Index threshold model, the density distribution maps of predicted grassed waterways throughout the studied watershed have been created based on the outputs from Compound Topographic Index and Stream Power Index threshold model. The performance of the Compound Topographic Index and Stream Power Index threshold model have been assessed by visual evaluation, occurrence evaluation and length evaluation. After developing Compound Topographic Index and Stream Power Index threshold models, the multi-criteria decision analysis (MCDA) has been conducted to map the priority areas for grassed waterways implementation at the watershed scale. Twelve factors were selected as criteria of MCDA based on literature review, data availability and geographic knowledge. Two methods including weighted linear combination and fuzzy logic analysis were employed in MCDA, which produced two outputs maps of priority areas for grassed waterways implementation. The results of these two maps have been validated using existing grassed waterways. The results of the Compound Topographic Index model and Stream Power Index threshold model display the existing and predicted grassed waterways in each field. The Compound Topographic Index model with the threshold of 600 has identified 30 existing grassed waterways, while the Stream Power Index threshold model with the threshold of 0.01 standard deviation identified 23 grassed waterways. Several discontinuities exist in predicted grassed waterways along the trajectories of digitized grassed waterways. The lengths of predicted grassed waterways by Compound Topographic Index model have a much better agreement with observation than that of Stream Power Index threshold model. The density distribution map of Compound Topographic Index and Compound Topographic Index model presented high-density areas of predicted grassed waterways which are mainly situated in the northern and central part of the study area, especially the areas along the upstream of Middle Thames River and Nissouri creek. The low-density areas for grassed waterways implementation are mostly located in the southwestern part of the study area. The results of weighted linear combination and fuzzy logic analysis displayed the high-priority areas mainly located in the northwestern part of the watershed, especially along the upstream of Nissouri creek. It is found that these upstream areas have relatively steeper slope gradient than other areas in the studied watershed, with dominant soil type of sandy loam and silty loam. There are more areas belonging to the lowest priority zone and lower areas falling into the most priority level in the fuzzy logic analysis output map, compared with the map of weighted linear combination. The fuzzy logic analysis required less prior knowledge of the relationship among criteria, which provide more flexibility and convenience to decision makers. The validation of both weighted linear combination and fuzzy logic analysis output maps displays relatively good performance, based on the criteria that a greater percentage of grassed waterways implementation must occur in the higher priority zones (Kanungo et al., 2009).en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.relation.uriThe quaternary Ontario Watershed Boundary (OWB) data: https://geohub.lio.gov.on.ca/maps/mnrf::ontario-watershed-boundaries-owb/explore?location=26.287578%2C-61.877361%2C3.53en
dc.relation.urithe Agricultural Resource Inventory (ARI) 1983 dataset: https://geohub.lio.gov.on.ca/documents/a576ce21cd9247c58ef039ebe7f4ed15/abouten
dc.relation.urithe The Southwestern Ontario Orthophotography (SWOOP) 2015: https://geohub.lio.gov.on.ca/documents/62d2c0ed59954290b35900b9e1fd8d44/abouten
dc.relation.uriThe Ontario Digital Elevation Model (DEM) data : https://geohub.lio.gov.on.ca/maps/mnrf::ontario-digital-elevation-model-imagery-derived/exploreen
dc.relation.urithe Annual Crop Inventory 2019 data: https://open.canada.ca/data/en/dataset/d90a56e8-de27-4354-b8ee-33e08546b4fcen
dc.relation.uriThe Ontario Road Network (ORN) Segment : https://geohub.lio.gov.on.ca/datasets/923cb3294384488e8a4ffbeb3b8f6cb2/exploreen
dc.relation.urithe soil survey complex data: https://geohub.lio.gov.on.ca/datasets/923cb3294384488e8a4ffbeb3b8f6cb2/exploreen
dc.relation.urithe Annual Crop Inventory (ACI) 2019 data: https://open.canada.ca/data/en/dataset/ba2645d5-4458-414d-b196-6303ac06c1c9en
dc.subjectmulticriteria decision analysisen
dc.subjecttopographic index modelen
dc.subjectBest Management Practicesen
dc.subjectGrassed Waterwaysen
dc.subjectephemeral gully erosionen
dc.subjectThe Ontario Hydro Network (OHN) data: https://geohub.lio.gov.on.ca/datasets/22bab3c9f37a4dd0845eb89e7b247a9f/exploreen
dc.titleIdentifying Prioritized Areas for Grassed Waterways Implementationen
dc.typeMaster Thesisen
dc.pendingfalse
uws-etd.degree.departmentGeography and Environmental Managementen
uws-etd.degree.disciplineGeographyen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeMaster of Environmental Studiesen
uws-etd.embargo.terms0en
uws.contributor.advisorPeter, Deadman
uws.contributor.affiliation1Faculty of Environmenten
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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