Process based calibration of a continental-scale hydrological model using soil moisture and streamflow data

Study region: Nelson Churchill River Basin (NCRB), Canada, and USA. Study Focus: Soil temperature and moisture are essential variables that fluctuate based on soil depth, controlling several sub-surface hydrologic processes. The Hydrological Predictions for the Environment (HYPE) model’s soil profil...

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Bibliographic Details
Published in:Journal of Hydrology: Regional Studies
Main Authors: Ajay Ratna Bajracharya, Mohamed Ismaiel Ahmed, Tricia Stadnyk, Masoud Asadzadeh
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2023
Subjects:
Hydrological model
Nelson Churchill River Basin
Multi-objective optimization
Soil layer discretization
Permafrost
Climate change
Physical geography
GB3-5030
Geology
QE1-996.5
Canada
Churchill River
permafrost
Online Access:https://doi.org/10.1016/j.ejrh.2023.101391
https://doaj.org/article/e52b376005204b39afeda24f6a675e57
Description
Summary:Study region: Nelson Churchill River Basin (NCRB), Canada, and USA. Study Focus: Soil temperature and moisture are essential variables that fluctuate based on soil depth, controlling several sub-surface hydrologic processes. The Hydrological Predictions for the Environment (HYPE) model’s soil profile depth can vary up to four meters, discretized into three soil layers. Here, we further discretized the HYPE subsurface domain to accommodate up to seven soil layers to improve the representation of subsurface thermodynamics and water transfer more accurately. Soil moisture data from different locations across NCRB are collected from 2013 to 2017 for model calibration. We use multi-objective optimization (MOO) to account for streamflow and soil moisture variability and improve the model fidelity at a continental scale. New hydrological insights: Our study demonstrates that MOO significantly improves soil moisture simulation from the median Kling Gupta Efficiency (KGE) of 0.21–0.66 without deteriorating the streamflow performance. Streamflow and soil moisture simulation performance improvements are statistically insignificant between the original three-layer and seven-layer discretization of HYPE. However, the finer discretization model shows improved simulation in sub-surface components such as the evapotranspiration when verified against reanalysis products, indicating a 12 % underestimation of evapotranspiration from the three-layer HYPE model. The improvement of the discretized HYPE model and simulating the soil temperature at finer vertical resolution makes it a prospective model for permafrost identification and climate change analysis.

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