Process-based calibration of HYPE model for climate change impact assessment of Nelson Churchill River Basin

dc.contributor.authorBajracharya, Ajay
dc.contributor.examiningcommitteeClark, Shawn (Civil Engineering)en_US
dc.contributor.examiningcommitteeAli, Genevieve (Civil Engineering)en_US
dc.contributor.examiningcommitteeHayley, Jocelyn (University of Calgary)en_US
dc.contributor.supervisorStadnyk, Tricia
dc.contributor.supervisorAsadzadeh, Masoud
dc.date.accessioned2023-03-31T14:37:37Z
dc.date.available2023-03-31T14:37:37Z
dc.date.copyright2023-03-27
dc.date.issued2023-03-27
dc.date.submitted2023-03-27T16:14:57Zen_US
dc.degree.disciplineCivil Engineeringen_US
dc.degree.levelDoctor of Philosophy (Ph.D.)en_US
dc.description.abstractProcess-based calibration of a hydrological model is an important step to ensuring model fidelity, or how ‘faithfully’ the model reproduces reality, which is even more meaningful for the catchments in northern latitudes subjected to the complexity of cold regions processes. The effectiveness of process-based calibration is examined using the Hydrological Predictions of the Environment (HYPE) model implemented for the Nelson Churchill River Basin (NCRB) using multi-objective optimization to both streamflow and soil moisture observations. The calibration process is guided by time-variant sensitivity analysis using flow signatures, which was influential in detecting highly seasonal parameters that previously went undetected by conventional methods. The model calibration is further improved by vertical discretization of the default three soil layers in HYPE to seven soil layers, which improved soil thermodynamic processes and, ultimately the simulation of soil moisture and evapotranspiration over longer-term periods. Spatial evaluation of soil moisture suggested the seven-layer discretization better represents surface soil moisture storage, which is essential for long-term water balance, agricultural water management, and climate change studies. Finally, given the importance of model fidelity for long-term simulation, climate change impact assessment on permafrost degradation was examined using the discretized HYPE model. Results showed a reduction in permafrost coverage up to 82% by the end of the mid-future period under the RCP 8.5 scenario within the NCRB. The novelty of this work includes utilizing multi-objective optimization to improve process representation of soil moisture and evaporation across a large domain hydrologic model. This study also underscores the importance of long-term water balance projection at the continental scale, which is valuable for large-scale planning and implementation of sustainable development principles and guidelines for decision-making.en_US
dc.description.noteMay 2023en_US
dc.identifier.urihttp://hdl.handle.net/1993/37233
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectHydrological modelen_US
dc.subjectModel fidelityen_US
dc.subjectClimate changeen_US
dc.subjectOptimizationen_US
dc.subjectDiscretizationen_US
dc.titleProcess-based calibration of HYPE model for climate change impact assessment of Nelson Churchill River Basinen_US
dc.typedoctoral thesisen_US
local.subject.manitobanoen_US
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Bajracharya_Ajay.pdf
Size:
9.79 MB
Format:
Adobe Portable Document Format
Description:
Thesis
License bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.2 KB
Format:
Item-specific license agreed to upon submission
Description: