Advancing hydrological modeling through multivariate calibration of multi-layer soil moisture dynamics
(2025) In Journal of Hydrology: Regional Studies 57.- Abstract
Study region: The Meichuan Basin, China Study focus: Soil water processes are critical in hydrological modeling, yet most studies focus on surface moisture due to data limitations, which hampers accurate simulations of root zone soil moisture dynamics. To address this gap, we developed three calibration schemes: M1 and M2, two benchmarks that rely solely on traditional streamflow data and incorporate both streamflow data and top-layer soil moisture data, respectively. In contrast, M3 integrates both streamflow data and multi-layer soil moisture information from SMCI 1.0. These schemes aim to assess the added value of integrating multi-layer soil moisture data to enhance hydrological modeling performance. New hydrological insights for... (More)
Study region: The Meichuan Basin, China Study focus: Soil water processes are critical in hydrological modeling, yet most studies focus on surface moisture due to data limitations, which hampers accurate simulations of root zone soil moisture dynamics. To address this gap, we developed three calibration schemes: M1 and M2, two benchmarks that rely solely on traditional streamflow data and incorporate both streamflow data and top-layer soil moisture data, respectively. In contrast, M3 integrates both streamflow data and multi-layer soil moisture information from SMCI 1.0. These schemes aim to assess the added value of integrating multi-layer soil moisture data to enhance hydrological modeling performance. New hydrological insights for the region: The M3 scheme yielded the most accurate simulation of the spatial and temporal distribution of multi-layer soil moisture compared to M1 and M2 benchmarks. In this subtropical humid basin, the M3 model effectively captured the pronounced fluctuations in soil moisture driven by frequent and intense precipitation events, as well as the seasonal variability between wet and dry periods. M3 also improved the accuracy of evapotranspiration simulations across all subbasins, while maintaining acceptable streamflow simulations at gauge stations. These findings underscore the importance of using advanced multi-layer soil moisture data in models to regulate hydrological processes and control water distribution within the hydrological cycle.
(Less)
- author
- He, Yan ; Mao, Huihui ; Wang, Chen ; Hu, Jinghao ; Ninsawat, Sarawut ; Song, Xianfeng ; Jing, Guifei ; Li, Runkui ; Wang, Mingyu and Duan, Zheng LU
- organization
- publishing date
- 2025-02
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Hydrological modeling, Multivariate calibration, Spatio-temporal multi-layer soil moisture data SMCI, Streamflow, evapotranspiration, Water balance
- in
- Journal of Hydrology: Regional Studies
- volume
- 57
- article number
- 102125
- publisher
- Elsevier
- external identifiers
-
- scopus:85213843344
- ISSN
- 2214-5818
- DOI
- 10.1016/j.ejrh.2024.102125
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025
- id
- 0774731b-f734-4d92-9d3d-9ceacaa65e11
- date added to LUP
- 2025-03-14 10:41:05
- date last changed
- 2025-04-04 14:58:26
@article{0774731b-f734-4d92-9d3d-9ceacaa65e11,
abstract = {{<p>Study region: The Meichuan Basin, China Study focus: Soil water processes are critical in hydrological modeling, yet most studies focus on surface moisture due to data limitations, which hampers accurate simulations of root zone soil moisture dynamics. To address this gap, we developed three calibration schemes: M1 and M2, two benchmarks that rely solely on traditional streamflow data and incorporate both streamflow data and top-layer soil moisture data, respectively. In contrast, M3 integrates both streamflow data and multi-layer soil moisture information from SMCI 1.0. These schemes aim to assess the added value of integrating multi-layer soil moisture data to enhance hydrological modeling performance. New hydrological insights for the region: The M3 scheme yielded the most accurate simulation of the spatial and temporal distribution of multi-layer soil moisture compared to M1 and M2 benchmarks. In this subtropical humid basin, the M3 model effectively captured the pronounced fluctuations in soil moisture driven by frequent and intense precipitation events, as well as the seasonal variability between wet and dry periods. M3 also improved the accuracy of evapotranspiration simulations across all subbasins, while maintaining acceptable streamflow simulations at gauge stations. These findings underscore the importance of using advanced multi-layer soil moisture data in models to regulate hydrological processes and control water distribution within the hydrological cycle.</p>}},
author = {{He, Yan and Mao, Huihui and Wang, Chen and Hu, Jinghao and Ninsawat, Sarawut and Song, Xianfeng and Jing, Guifei and Li, Runkui and Wang, Mingyu and Duan, Zheng}},
issn = {{2214-5818}},
keywords = {{Hydrological modeling; Multivariate calibration; Spatio-temporal multi-layer soil moisture data SMCI; Streamflow, evapotranspiration; Water balance}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Journal of Hydrology: Regional Studies}},
title = {{Advancing hydrological modeling through multivariate calibration of multi-layer soil moisture dynamics}},
url = {{http://dx.doi.org/10.1016/j.ejrh.2024.102125}},
doi = {{10.1016/j.ejrh.2024.102125}},
volume = {{57}},
year = {{2025}},
}