Asset Details
Do you wish to reserve the book?
Characterization of Preferential Flow Occurrence During Freeze‐Thaw Cycles
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Characterization of Preferential Flow Occurrence During Freeze‐Thaw Cycles
Do you wish to request the book?
Characterization of Preferential Flow Occurrence During Freeze‐Thaw Cycles
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Characterization of Preferential Flow Occurrence During Freeze‐Thaw Cycles
2026
Overview
Preferential flow (PF) critically influences water and energy dynamics in frozen soils, yet its quantification and mechanisms remain poorly understood due to observational challenges. This study proposes a novel method to identify PF by analyzing soil temperature response times across depths. The method detects thermal anomalies—such as earlier or synchronized temperature peaks across depths—indicate rapid, advective heat transfer driven by PF and phase‐change latent heat. We conducted our investigation in the Qilian Mountain areas using a network of soil temperature stations. Our findings reveal that PF significantly enhances magnitude and speed of energy transfer to deeper soil. Furthermore, the frequency of PF varies significantly across the partially frozen, frozen and partially thawing phases, as well as across different sites and depths, driven by shifts soil properties and meteorological forcing. Using random forest analysis, we identified key spatial drivers related to soil pore structure: soil organic carbon (partially frozen phase), residual soil moisture (frozen phase), and wilting point (partially thawed phase). Furthermore, classification and regression tree analysis revealed that the snowmelt rates and maximum near‐surface (5 cm) soil temperatures are the primary temporal drivers of PF. Our study demonstrates that PF can be effectively identified by analyzing soil temperatures at various depths. By utilizing temperature‐based detection during the frozen phase and moisture monitoring in the unfrozen phase, we can better correlate PF with soil hydrothermal conditions, ultimately elucidating the complex mechanisms governing water and energy dynamics during the freeze‐thaw cycle.
