scholarly journals River ice phenology and thickness from satellite altimetry: potential for ice bridge road operation and climate studies

2021 ◽  
Vol 15 (12) ◽  
pp. 5387-5407
Author(s):  
Elena Zakharova ◽  
Svetlana Agafonova ◽  
Claude Duguay ◽  
Natalia Frolova ◽  
Alexei Kouraev
Keyword(s):  
Satellite Monitoring ◽  
River Ice ◽  
Ice Thickness ◽  
Radar Altimetry ◽  
Empirical Relations ◽  
Developing Area ◽  
Opening And Closing ◽  
Altimetric Measurements ◽  
First Time ◽  
Ice Phenology

Abstract. River ice is a key component of the cryosphere. Satellite monitoring of river ice is a rapidly developing area of scientific enquiry, which has wide-ranging implications for climate, environmental and socioeconomic applications. Spaceborne radar altimetry is widely used for monitoring river water regimes; however, its potential for the observation of river ice processes and properties has not been demonstrated yet. Using Ku-band backscatter measurements from the Jason-2 and Jason-3 satellite missions (2008–2019), we demonstrate the potential of radar altimetry for the retrieval of river ice phenology dates and ice thickness for the first time. The altimetric measurements were determined to be sensitive enough to detect the first appearance of ice and the beginning of thermal breakup on the lower Ob River (Western Siberia). The uncertainties in the retrieval of ice event timing were within the 10 d repeat cycle of Jason-2 and Jason-3 in 88 %–90 % of the cases analysed. The uncertainties in the river ice thickness retrievals made via empirical relations between the satellite backscatter measurements and in situ observations, expressed as the root mean square error (RMSE), were of 0.07–0.18 m. A novel application of radar altimetry is the prediction of ice bridge road operations, which is demonstrated herein. We established that the dates of ferry closing and ice road opening and closing in the city of Salekhard can be predicted with an accuracy (expressed as RMSE) of 3–5 d.

scholarly journals River ice phenology and thickness from satellite altimetry. Potential for ice bridge road operation

2020 ◽  
Author(s):  
Elena Zakharova ◽  
Svetlana Agafonova ◽  
Claude Duguay ◽  
Natalia Frolova ◽  
Alexei Kouraev
Keyword(s):  
Satellite Altimetry ◽  
Satellite Monitoring ◽  
River Ice ◽  
Ice Thickness ◽  
Empirical Relations ◽  
Good Potential ◽  
Altimetric Measurements ◽  
Road Closure ◽  
Ice Phenology

Abstract. River ice is an important component of land cryosphere. Satellite monitoring of river ice is rapidly developing scientific area with an important outcome for many climate, environmental and socio-economic applications. Radar altimetry, now widely used for monitoring of river water regime, demonstrates a good potential for observation of river ice phenology and for an estimation of river ice thickness. Jason-2 and -3 Ku-band backscatter measurements are sensitive enough for detection of first appearance of the ice and of beginning of thermal ice degradation on the Lower Ob River (Western Siberia). Uncertainties of the altimetric ice events timing are less than 10 days for 88–90 % of cases. River ice thickness retrieved from altimetric measurements via empirical relations with in situ observations, has an accuracy (expressed as RMSE) varying from 0.07 to 0.18 m. We demonstrated that using satellite altimetry the dates of ice road opening at Salekhard city can be predicted quite accurately with 4 days delay. Uncertainties for the prediction of dates of the ice road closure are of 3 days with the delay varying from 4 days (for late melting start) to 22 days (for yearly melting start).

scholarly journals The role of snow and ice thickness on river ice process in Songhua River basin, Northeast China

2019 ◽  
Author(s):  
Qian Yang ◽  
Kaishan Song ◽  
Xiaohua Hao ◽  
Zhidan Wen ◽  
Yue Tan ◽  
...  
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Snow Depth ◽  
Northeast China ◽  
River Ice ◽  
Ice Thickness ◽  
Songhua River ◽  
Songhua River Basin ◽  
Ice Phenology

Abstract. Songhua River basin is a sensitive area to global warming in Northeast China that could be indicated by changes in lake and river ice development. The regional role and trends of ice characteristics of this area have been scarcely investigated, which are critical for aquatic ecosystem, climate variability, and human activities. Based on the ice record of hydrological stations, we examined the spatial variations of the ice phenology and ice thickness in Songhua River basin in Northeast China from 2010 to 2015 and explored the role of ice thickness, snow during ice-on and ice-off process. All five river ice phenology including freeze-up start, freeze-up end, break-up start, break-up end and complete frozen duration showed latitudinal distribution and a changing direction from southeast to northwest, and five typically geographic zones were identified based on rotated empirical orthogonal function. Maximum ice thickness had a higher correlation with five parameters than that of average snow depth and air temperature on bank. A linear regression function was established between ice thickness and snow depth on ice and indicated ice thickness was closely associated with snow depth on ice. The air temperature had higher correlation with ice phenology and influenced the lake ice phenology significantly, and snow cover did not show significant correlation with the ice phenology. However, snow cover correlated with ice thickness significantly and positively during the periods when the freshwater is completely frozen.

scholarly journals Investigation of spatial and temporal variability of river ice phenology and thickness across Songhua River Basin, northeast China

2020 ◽  
Vol 14 (11) ◽  
pp. 3581-3593
Author(s):  
Qian Yang ◽  
Kaishan Song ◽  
Xiaohua Hao ◽  
Zhidan Wen ◽  
Yue Tan ◽  
...  
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Regression Models ◽  
River Ice ◽  
Changbai Mountains ◽  
Ice Thickness ◽  
Songhua River ◽  
Songhua River Basin ◽  
The Songhua River Basin ◽  
Ice Phenology

Abstract. The regional role and trends of freshwater ice are critical factors for aquatic ecosystems, climate variability, and human activities. The ice regime has been scarcely investigated in the Songhua River Basin of northeast China. Using daily ice records of 156 hydrological stations across the region, we examined the spatial variability in the river ice phenology and river ice thickness from 2010 to 2015 and explored the role of snow depth and air temperature on the ice thickness. The river ice phenology showed a latitudinal distribution and a changing direction from southeast to northwest. We identified two spatial clusters based on Moran's I spatial autocorrelation, and results showed that the completely frozen duration with high values clustered in the Xiao Hinggan Range and that with low values clustered in the Changbai Mountains at the 95 % confidence level. The maximum ice thickness over 125 cm was distributed along the ridge of the Da Hinggan Range and Changbai Mountains, and the maximum ice thickness occurred most often in February and March. In three subbasins of the Songhua River Basin, we developed six Bayesian regression models to predict ice thickness from air temperature and snow depth. The goodness of the fit (R2) for these regression models ranged from 0.80 to 0.95, and the root mean square errors ranged from 0.08 to 0.18 m. Results showed significant and positive correlations between snow cover and ice thickness when freshwater was completely frozen. Ice thickness was influenced by the cumulative air temperature of freezing through the heat loss of ice formation and decay instead of just air temperature.

scholarly journals Brief Communication: Mapping river ice using drones and structure from motion

2018 ◽  
Vol 12 (2) ◽  
pp. 627-633 ◽  
Author(s):  
Knut Alfredsen ◽  
Christian Haas ◽  
Jeffrey A. Tuhtan ◽  
Peggy Zinke
Keyword(s):  
Structure From Motion ◽  
Low Cost ◽  
Cold Climate ◽  
River Ice ◽  
River Morphology ◽  
Ice Thickness ◽  
Surface Model ◽  
Engineering Data ◽  
Site Access ◽  
Remote Sensing Methods

Abstract. In cold climate regions, the formation and break-up of river ice is important for river morphology, winter water supply, and riparian and instream ecology as well as for hydraulic engineering. Data on river ice is therefore significant, both to understand river ice processes directly and to assess ice effects on other systems. Ice measurement is complicated due to difficult site access, the inherent complexity of ice formations, and the potential danger involved in carrying out on-ice measurements. Remote sensing methods are therefore highly useful, and data from satellite-based sensors and, increasingly, aerial and terrestrial imagery are currently applied. Access to low cost drone systems with quality cameras and structure from motion software opens up a new possibility for mapping complex ice formations. Through this method, a georeferenced surface model can be built and data on ice thickness, spatial distribution, and volume can be extracted without accessing the ice, and with considerably fewer measurement efforts compared to traditional surveying methods. A methodology applied to ice mapping is outlined here, and examples are shown of how to successfully derive quantitative data on ice processes.

scholarly journals Annual variation characteristics of Eurasian hydrologic elements and their linkage with climate and environment changes during 1951–2015

2019 ◽  
Author(s):  
Jia Qin ◽  
Yongjian Ding ◽  
Tianding Han ◽  
Junhao Li ◽  
Shaoping Wang ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Discharge Pattern ◽  
River Ice ◽  
Ice Thickness ◽  
High Latitudes ◽  
Middle Latitudes ◽  
Variation Characteristics ◽  
Snow Water ◽  
The 1950S ◽  
Monthly Discharge

Abstract. In this paper, the variations of the lowest monthly discharge (LD), mean monthly discharge (MD), and highest monthly discharge value (HD) during 1951–2015, as well as spring snowmelt water and winter river ice change, in eleven major rivers, distributed respectively in the high-latitudes (55° N–70° N), middle latitudes (40° N–55° N), and lower latitudes (30° N–40° N) of Eurasia, were analysed. Energy and water budgets in different watersheds were compared to detect the reasons for Eurasian hydrological changes. We found that the annual LD in most Eurasian rivers was increasing since the 1950s, with rates of (5 %–8 %) per decade. But the increase rate slowed down after the late 1990s in the middle latitudes of Eurasia. Both the MD and HD in the lower latitudes of Eurasia had increasing trends during 1951–2015, while they had little changes in the high and middle latitudes. The river ice thickness and volume have been continuously reducing since the 1950s, as well as the maximum snow water equivalent. And ice period of the Eurasian rivers has shortened about 24 days. The LD trend is mostly dominated by temperature via impacting river ice thickness and extent, while the HD is mostly impacted by snowmelt water and rainfall respectively in different latitudes. Annual MD trend is controlled by evapotranspiration, especially after the late 1990s. After the late 1990s, a warm Arctic-large discharge pattern existed in the lower and high latitudes of Eurasia, but a warm Arctic- few discharge pattern in the middle latitudes (except the winter).

The impact of snow products on detecting trends in sea ice thickness during the CryoSat-2 era

2020 ◽  
Author(s):  
Heidi Sallila ◽  
Samantha Buzzard ◽  
Eero Rinne ◽  
Michel Tsamados
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Ice Age ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Seasonal Snow ◽  
Uncertainty Estimates ◽  
The One ◽  
The Impact ◽  
First Time

<p>Retrieval of sea ice depth from satellite altimetry relies on knowledge of snow depth in the conversion of freeboard measurements to sea ice thickness. This remains the largest source of uncertainty in calculating sea ice thickness. In order to go beyond the use of a seasonal snow climatology, namely the one by Warren created from measurements collected during the drifting stations in 1937 and 1954–1991, we have developed as part of an ESA Arctic+ project several novel snow on sea ice pan-Arctic products, with the ultimate goal to resolve for the first time inter-annual and seasonal snow variability.</p><p><span>Our products are inter-compared and calibrated with each other to guarantee multi-decadal continuity, and also compared with other recently developed snow on sea ice modelling </span><span>and satellite based </span><span>products. Quality assessment and uncertainty estimates are provided at a gridded level and as a function of sea ice cover characteristics such as sea ice age, and sea ice type.</span></p><p>We investigate the impact of the spatially and temporally varying snow products on current satellite estimates of sea ice thickness and provide an update on the sea ice thickness uncertainties. We pay particular attention to potential biases of the seasonal ice growth and inter-annual trends.</p>

scholarly journals The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

2015 ◽  
Vol 9 (1) ◽  
pp. 37-52 ◽  
Author(s):  
S. Kern ◽  
K. Khvorostovsky ◽  
H. Skourup ◽  
E. Rinne ◽  
Z. S. Parsakhoo ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Ice Thickness ◽  
Data Sets ◽  
Snow Density ◽  
Radar Altimetry ◽  
Sea Ice Thickness ◽  
The Mean ◽  
Satellite Radar ◽  
Satellite Radar Altimetry

Abstract. We assess different methods and input parameters, namely snow depth, snow density and ice density, used in freeboard-to-thickness conversion of Arctic sea ice. This conversion is an important part of sea ice thickness retrieval from spaceborne altimetry. A data base is created comprising sea ice freeboard derived from satellite radar altimetry between 1993 and 2012 and co-locate observations of total (sea ice + snow) and sea ice freeboard from the Operation Ice Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) airborne campaigns, of sea ice draft from moored and submarine upward looking sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer (AMSR-E) and the Warren climatology (Warren et al., 1999). We compare the different data sets in spatiotemporal scales where satellite radar altimetry yields meaningful results. An inter-comparison of the snow depth data sets emphasizes the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. We test different freeboard-to-thickness and freeboard-to-draft conversion approaches. The mean observed ULS sea ice draft agrees with the mean sea ice draft derived from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the approaches are able to reproduce the seasonal cycle in sea ice draft observed by moored ULS. A sensitivity analysis of the freeboard-to-thickness conversion suggests that sea ice density is as important as snow depth.

Midwinter breakup and jamming on the upper Saint John River: a case study

2003 ◽  
Vol 30 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Spyros Beltaos ◽  
Sayed Ismail ◽  
Brian C Burrell
Keyword(s):  
Climate Change ◽  
Environmental Changes ◽  
Flood Damage ◽  
River Ice ◽  
Ice Thickness ◽  
Ice Jams ◽  
Damage Reduction ◽  
Saint John

Changing climates will likely result in more frequent midwinter ice jams along many Canadian rivers, thereby increasing the likelihood of flood damage and environmental changes. Therefore, the possibility of more frequent ice jams has to be considered during the planning of flood damage reduction measures, the design of waterway structures, and the enactment of measures to protect the environment. As a case study of midwinter jamming, four winter breakup and jamming events that occurred along an upper stretch of the Saint John River during the 1990s are described and the implications of similar midwinter jamming are discussed.Key words: breakup, river ice, climate change, ice jamming, ice thickness, winter, winter thaw.

scholarly journals A Study on the Measurement of River Ice Thickness by Using X-band Scatterometer

2012 ◽  
Vol 15 (1) ◽  
pp. 16-22
Author(s):  
Hyang-Sun Han ◽  
Bum-Jun Kim ◽  
Hoon-Yol Lee
Keyword(s):  
River Ice ◽  
Ice Thickness ◽  
X Band

scholarly journals Drone Surveying of Volumetric Ice Growth in a Steep River

2021 ◽  
Vol 2 ◽  
Author(s):  
Einar Rødtang ◽  
Knut Alfredsen ◽  
Ana Juárez
Keyword(s):  
Structure From Motion ◽  
Complex Geometry ◽  
Low Cost ◽  
Single Point ◽  
Ice Cover ◽  
River Ice ◽  
Ice Thickness ◽  
Surface Geometry ◽  
Ice Volume ◽  
Anchor Ice

Representative ice thickness data is essential for accurate hydraulic modelling, assessing the potential for ice induced floods, understanding environmental conditions during winter and estimation of ice-run forces. Steep rivers exhibit complex freeze-up behaviour combining formation of columnar ice with successions of anchor ice dams to build a complete ice cover, resulting in an ice cover with complex geometry. For such ice covers traditional single point measurements are unrepresentative. Gathering sufficiently distributed measurements for representativeness is labour intensive and at times impossible with hard to access ice. Structure from Motion (SfM) software and low-cost drones have enabled river ice mapping without the need to directly access the ice, thereby reducing both the workload and the potential danger in accessing the ice. In this paper we show how drone-based photography can be used to efficiently survey river ice and how these photographic surveys can be processed into digital elevation models (DEMs) using Structure from Motion. We also show how DEMs of the riverbed, riverbanks and ice conditions can be used to deduce ice volume and ice thickness distributions. A QGIS plugin has been implemented to automate these tasks. These techniques are demonstrated with a survey of a stretch of the river Sokna in Trøndelag, Norway. The survey was carried out during the winter 2020–2021 at various stages of freeze-up using a simple quadcopter with camera. The 500 m stretch of river studied was estimated to have an ice volume of up to 8.6 × 103 m3 (This corresponds to an average ice thickness of ∼67 cm) during the full ice cover condition of which up to 7.2 × 103 m3 (This corresponds to an average ice thickness of ∼57 cm) could be anchor ice. Ground Control Points were measured with an RTK-GPS and used to determine that the accuracy of these ice surface geometry measurements lie between 0.03 and 0.09 m. The ice thicknesses estimated through the SfM methods are on average 18 cm thicker than the manual measurements. Primarily due to the SfM methods inability to detect suspended ice covers. This paper highlights the need to develop better ways of estimating the volume of air beneath suspended ice covers.

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