Integration of space-borne and air-borne data in monitoring river ice processes in the Slave River, Canada

Chu, Thuan

doi:10.1016/j.rse.2016.03.041

Cited by 39 publications

(40 citation statements)

References 31 publications

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“…The RADARSAT-2 image acquired on 30 April was compared with MODIS data for the same day ( Figure 9). The noticeable difference between images from these two satellites is partly due to the different acquisition times, other reasons can be found in [12].…”

Section: Ice Volumementioning

confidence: 99%

“…On cloudy days, backscatter values are difficult or even impossible to attain. Hence ice volumes for those days have to be interpolated between clear-day images [12]. The algorithm Harmonic Analysis of Time Series (HANTS) was used to replace cloud-contaminated pixels with MOD09GQ band2 (wavelength: 841-876 nm, resolution: 250 m) datasets were used to establish time series to estimate the ice cover situation of the Slave River [31].…”

Section: Ice Volume Calculation By Using Modismentioning

confidence: 99%

“…On cloudy days, backscatter values are difficult or even impossible to attain. Hence ice volumes for those days have to be interpolated between clear-day images [12]. The algorithm Harmonic Analysis of Time Series (HANTS) was used to replace cloud-contaminated pixels with Fourier series values from MODIS images [33].…”

Section: Ice Volume Calculation By Using Modismentioning

confidence: 99%

“…Due to the high penetration and resolution of RADARSAT-2 signals, it is possible to analyze ice types based on RADARSAT-2 backscatter. Chu and Lindenschmidt classified river ice types using RADARSAT-2 imagery [12]. In another study of the Slave River, different breakup patterns were tracked along the river, using RADARSAT-2 satellite imagery [13].…”

Section: Introductionmentioning

confidence: 99%

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Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta

Zhang

Mosaffa

Chu

et al. 2017

Water

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Abstract:The Slave River is a northern river in Canada, with ice being an important component of its flow regime for at least half of the year. During the spring breakup period, ice jams and ice-jam flooding can occur in the Slave River Delta, which is of benefit for the replenishment of moisture and sediment required to maintain the ecological integrity of the delta. To better understand the ice jam processes that lead to flooding, as well as the replenishment of the delta, the one-dimensional hydraulic river ice model RIVICE was implemented to simulate and explore ice jam formation in the Slave River Delta. Incoming ice volume, a crucial input parameter for RIVICE, was determined by the novel approach of using MODIS space-born remote sensing imagery. Space-borne and air-borne remote sensing data were used to parameterize the upstream ice volume available for ice jamming. Gauged data was used to complement modeling calibration and validation. HEC-RAS, another one-dimensional hydrodynamic model, was used to determine ice volumes required for equilibrium jams and the upper limit of ice volume that a jam can sustain, as well as being used as a threshold for the volumes estimated by the dynamic ice jam simulations using RIVICE. Parameter sensitivity analysis shows that morphological and hydraulic properties have great impacts on the ice jam length and water depth in the Slave River Delta.

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Section: Ice Volumementioning

confidence: 99%

Section: Ice Volume Calculation By Using Modismentioning

confidence: 99%

“…On cloudy days, backscatter values are difficult or even impossible to attain. Hence ice volumes for those days have to be interpolated between clear-day images [12]. The algorithm Harmonic Analysis of Time Series (HANTS) was used to replace cloud-contaminated pixels with Fourier series values from MODIS images [33].…”

Section: Ice Volume Calculation By Using Modismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta

Zhang

Mosaffa

Chu

et al. 2017

Water

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“…Rubble or slush ice also has the potential to jam and dam up a river section, causing even more backwater staging and river banks and levees to overflow and flood the surrounding floodplain. From an ecological perspective, many floodplain and wetland ecosystems require such periodic flooding for their replenishment of moisture, sediment and nutrients, especially in perched ponds and lakes of inland deltas such as, for example in Canada, the Peace-Athabasca Delta in Alberta [1], the Slave River Delta in the Northwest Territories [2,3] and the Saskatchewan River Delta along the Saskatchewan/Manitoba boundary [4,5]. However, ice jams and the flooding they induce can pose threats to, and wreak damage on, many communities located along these rivers.…”

Section: Introductionmentioning

confidence: 99%

RIVICE—A Non-Proprietary, Open-Source, One-Dimensional River-Ice Model

Lindenschmidt

2017

Water

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Currently, no river ice models are available that are free and open source software (FOSS), which can be a hindrance to advancement in the field of modelling river ice processes. This paper introduces a non-proprietary (conditional), open-source option to the scientific and engineering community, the River Ice Model (RIVICE). RIVICE is a one-dimensional, fully-dynamic wave model that mimics key river ice processes such as ice generation, ice transport, ice cover progression (shoving, submergence and juxtapositioning) and ice jam formation, details of which are highlighted in the text. Three ice jam events at Fort McMurray, Alberta, along the Athabasca River, are used as case studies to illustrate the steps of model setup, model calibration and results interpretation. A local sensitivity analysis reveals the varying effects of parameter and boundary conditions on backwater flood levels as a function of the location of ice jam lodgment along the river reach and the location along the ice jam cover. Some limitations of the model and suggestions for future research and model development conclude the paper.

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Estimating glacier mass balance in High Mountain Asia based on Moderate Resolution Imaging Spectroradiometer retrieved surface albedo from 2000 to 2020

Xiao

Fan

et al. 2022

Intl Journal of Climatology

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Glacier surface albedo is a key parameter of the glacier mass and energy balance process. Many scholars have used the albedo method to study mass balance for an individual glacier, but less attention has been given to largearea glaciers. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved glacier surface albedo and in situ mass balance, the correlations between albedo and mass balance are reported. The minimum/mean method (the whole glacier albedo is calculated by averaging the minimum/ mean albedo of each grid cell), the MODIS snow albedo products (MxD10A1) and the MCD43A3 shortwave albedo were tested during the melt season (June-August) for four glaciers in the High Mountain Asia (HMA). Results reveal that albedo is well correlated with mass balance, the correlation (r) ranging from 0.41 to 0.90. Overall, the minimum method is better than the mean method, and MxD10A1 is better than MCD43A3. The albedo changes were calculated based on the MxD10A1 and the mean method, and a linear relationship is established between albedo changes and digital elevation models (DEMs) calculated mass balance from 2000 to 2016. A strong linear correlation (r = .9) is found between albedo changes and mass balance while excluding some areas that have insignificant seasonal variation in albedo, and the reconstructed albedo-mass balance relationship can be used to retrieve mass balance in large-scale glaciers. Furthermore, the average loss of mass from 2000 to 2020 is calculated as −0.225 ± 0.040 m w.e.a −1 . The greatest glacier mass loss is concentrated in the southeastern part of HMA, the mass loss in the north and west is less than that in the southeast, and the glacier mass is in a state of aggravated loss in recent years. Our study also offers a new method for estimating the large-scale glacier mass balance.

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Integration of space-borne and air-borne data in monitoring river ice processes in the Slave River, Canada

Cited by 39 publications

References 31 publications

Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta

Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta

RIVICE—A Non-Proprietary, Open-Source, One-Dimensional River-Ice Model

Estimating glacier mass balance in High Mountain Asia based on Moderate Resolution Imaging Spectroradiometer retrieved surface albedo from 2000 to 2020

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