Snow Hydrology and Streamflow Response to Snowmelt: A Case Study on SWE Dataset Comparisons, Regional Water Balance, and Snowmelt-Induced Runoff within the Smith River Watershed, Montana

Seasonal snowpacks in snow-dominated watersheds across the western United States play a critical role in sustaining regional water resources by delaying runoff and regulating streamflow. This research examined snow hydrology in the Smith River Watershed, located in Montana, USA, over five water years (2017 to 2021) to evaluate snow water equivalent (SWE) values, assess the regional water balance, and quantify snowmelt contributions to runoff. SWE estimates from five open-source datasets (UA 4km, UA 800m, WUS-SR, SNODAS, and Noah-MP via WLDAS) and SnowModel were validated against observations from five Snow Telemetry (SNOTEL) stations using correlation (r), mean absolute error (MAE), and root mean square error (RMSE). Models assimilating SNOTEL data (SNODAS, UA 800m, and UA 4km) performed best. Comparisons of SWE accumulation and melt pattern across elevation zones revealed a general underestimation of SWE at high elevations, and watershed-scale comparisons revealed that WLDAS and UA 800m estimated earlier peak SWE timings than other products. Annual watershed-averaged water balance analyses were carried out using the Noah-MP (via WLDAS) land surface model (LSM) and hybrid observation-model-based approaches. While the hybrid approach depicted the most accurate variable values for the water balance, the land surface model-based approach was more suitable for the annual water balance analysis due to the lowest annual residual storage differences, and since the LSM simulates hydrologic processes to produce its variables. Lastly, snow-induced runoff was quantified by partitioning rain- and snow-generated surface and subsurface runoff using WLDAS outputs and mass balance approaches, yielding a value ~32% (85 mm) for the watershed—substantially lower than previous regional estimates (~65%) reported in the literature. The results of this study highlight the importance of improved snow and land surface modeling for accurately representing watershed hydrology and supporting water resource management in snow dominated regions of the western United States.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Geography

Grantor

Texas State University

Year dc:date.issued

2026

Author dc:creator

• Cooverji, Farhaan Paterusp

Advisor dc:contributor.advisor

• Li, Yanan

Committee members dc:contributor.committeemember

• Cho, Eunsang
• Julian, Jason

• snow hydrology
• runoff
• snow water equivalent (SWE)
• water balance
• land surface model

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10877/24785

OAI identifier oai:identifier

oai:digital.library.txst.edu:10877/24785