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CC BY-NC-ND V4.0, Open Access
Dissertation
RELIABLE SNOWPACK AND STREAMFLOW MODELING USING DATA-DRIVEN AND BIOPHYSICAL APPROACHES
Doctor of Philosophy (PhD), Washington State University
2025
Abstract
Seasonal snow is a critical component of the water and energy cycle in snow-dominated regions, supporting water supply, hydropower generation, agriculture, and ecosystems. Despite advances in land surface models, uncertainties in the representation of snow processes—particularly snow accumulation, melt dynamics, and precipitation phase partitioning—limit the reliability of model-based water resource forecasts. This dissertation addresses three key challenges in improving hydrologic modeling of snow-dominated basins: (1) identifying model parameters and processes most responsible for uncertainty in snow-related outputs, (2) improving precipitation phase partitioning, and (3) integrating snow metrics into model calibration. Application of a hybrid local-global sensitivity analysis on VIC-CropSyst model simulations for the Pacific Northwest USA revealed that a small subset of parameters exert disproportionate influence on snow metrics, with sensitivities varying by hydroclimatic setting. Building on these insights, an enhanced precipitation partitioning method incorporating surface relative humidity alongside surface air temperature reduced biases in snow and streamflow metrics in many, though not all, contexts. Finally, a blueprint framework for multi-objective calibration was detailed for further bias reduction by jointly optimizing snow and streamflow metrics, although computational and practical barriers to implementation need to be addressed. Together, these contributions provide both a foundation for targeted model improvements and a transferable approach for reducing hydrologic model biases in snow-dominated basins, with implications for water supply forecasting, hazard preparedness, and climate change adaptation.
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Details
- Title
- RELIABLE SNOWPACK AND STREAMFLOW MODELING USING DATA-DRIVEN AND BIOPHYSICAL APPROACHES
- Creators
- Bhupinderjeet Singh
- Contributors
- Kirti Rajagopalan (Advisor)Jennifer C. Adam (Committee Member)Joan Wu (Committee Member)Anantharaman Kalyanaraman (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Department of Biological Systems Engineering
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 155
- Identifiers
- 99901356973401842
- Language
- English
- Resource Type
- Dissertation