Physical Mechanism and Parameterization for Correcting Radar Wave Velocity in Yellow River Ice with Air Temperature and Ice Thickness

Abstract

Unfrozen free and non-free water between ice crystals in flat and hummock ice in the Yellow River exists as water films with varying contents based on ice temperature. These contents can affect the radar wave velocity of the ice despite its theoretical dependence on the crystal structure and ice body components. The unfrozen water content in ice depends on the ice temperature, which is controlled by the air temperature, solar radiation, and ice thickness. Winter air temperature and radar-detected ice thickness data observed at the Shisifenzi bend in the Yellow River from 2020 to 2021 were analyzed. The unfrozen water content in the ice was the primary factor influencing the accuracy of flat ice thickness detection. The heat flux at the ice–water interface in the Yellow River was determined. The evolution of ice thickness and temperature were simulated using a one-dimensional (1D) ice thermodynamic model forced by the local weather station data (i.e., air temperature, solar radiation, wind speed, and cloud cover). On this basis, the measured ice thickness data of 13 drill holes were combined to calculate 1,251 thermodynamically simulated ice thicknesses consistent with the ice thickness detection time of the radar; therefore, statistical relationships regarding the influence of air temperature and the combined action of air temperature and ice thickness on the radar wave velocity in granular and columnar ice during air temperature increases and decreases were determined. Finally, the statistical relationship between the combined influence of air temperature and ice thickness on radar wave velocity was selected as a parameterization scheme to dynamically correct the radar wave velocity of flat ice. To enhance the radar detection accuracy for flat ice thickness, the radar wave velocity of ice was parameterized as a function. Given the presence of unfrozen frazil ice and accumulated broken ice blocks in the Yellow River, radar is suggested to detect the thickness of different types of ice in future research.

A Survey Method for Drift Ice Characteristics of the Yellow River Based on Shore-Based Oblique Images

“…The ice monitoring device (Figure 1d) is located in the concave bank of Shisifenzi bend. Li et al [47] introduces this device in detail, which includes mainly a video camera and a ground generating radar (GPR). The video camera, with infrared function, faces the downstream of this bend and automatically takes a 30 s video every hour to record drift ice on the bend during the freezing period and thawing period.…”

Morphology Dynamics of Ice Cover in a River Bend Revealed by the UAV-GPR and Sentinel-2

“…The convex bank is a wasteland and has no protection. According to records of the video camera system [13,33] fixed at the bend, sporadic ice floes appeared on the concave bank at 00:00 on 20 November 2021, with an air temperature of −8 °C. Afterward, the ice floes increased gradually, and ice concentration increased accordingly.…”

“…Figure 2b shows that the UAV-GPR, named IGPR-30, is equipped with a DJI M600, an air-coupled GPR with a central frequency of 400 MHz, the Trimble Real-Time Kinetic Global Positioning System (RTK GPS), and a two-megapixel infrared camera. The GPR weighs approximately 3.5 kg and is designed to detect ice thickness of 6 m, with a According to records of the video camera system [13,33] fixed at the bend, sporadic ice floes appeared on the concave bank at 00:00 on 20 November 2021, with an air temperature of −8 • C. Afterward, the ice floes increased gradually, and ice concentration increased accordingly. At 7:00 on 18 December 2021, ice cover first formed at the narrow location of the bend, i.e., between sections CS3 and CS5 in Figure 2a.…”

“…Air bubbles, unfrozen water, and sediment are the main factors affecting the dielectric permittivity of the ice cover. The dielectric permittivity of air bubbles, pure ice, unfrozen water, and sediment are 1, 3.17, 81, and 5.5, respectively [13].…”

“…The average dielectric permittivity of each survey was 3.231, 3.249, and 3.317 on 5 January 2022, 16 February 2022, and 25 February 2022, respectively. Since there was sediment within the Yellow River ice, three average values were larger than the pure ice dielectric permittivity of 3.17 [13]. This paper calculated the valid ice thickness data using the average dielectric permittivity for the corresponding survey time.…”