Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta
Abstract
:1. Introduction
2. Study Site and Methods
2.1. Study Site
2.2. Methods
2.2.1. RIVICE Model
2.2.2. Remote Sensing Dataset
2.2.3. Ice Volume Calculation by Using MODIS
2.2.4. Data Preparation for Model
3. Results
3.1. Ice Volume
3.2. Model Calibration
3.3. Ice Jam Flooding
3.4. Local Sensitivity Analysis
4. Discussion
Author Contributions
Conflicts of Interest
References
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Parameters | Description | Units |
---|---|---|
Hydraulic roughness | ||
River bed roughness | s/m1/3 | |
Ice roughness | s/m1/3 | |
Boundary conditions | ||
Q | Upstream discharge | m3/s |
W | Downstream water level | m a.s.l. 1 |
Ice cover characteristics | ||
Ice deposit velocity | m/s | |
Ice erosion velocity | m/s | |
Inflowing ice volume | m3 | |
FT | Thickness of ice cover front | m |
PC | Porosity of ice cover | — |
X | Ice bridge location (from XS1 in Figure 1) | m |
Strength properties | ||
K1TAN | Lateral: longitudinal stresses | — |
K2 | Longitudinal: vertical stresses | — |
Slush ice characteristics | ||
PS | Porosity of slush | — |
ST | Thickness of slush pans | m |
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Zhang, F.; Mosaffa, M.; Chu, T.; Lindenschmidt, K.-E. Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta. Water 2017, 9, 306. https://doi.org/10.3390/w9050306
Zhang F, Mosaffa M, Chu T, Lindenschmidt K-E. Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta. Water. 2017; 9(5):306. https://doi.org/10.3390/w9050306
Chicago/Turabian StyleZhang, Fan, Mahtab Mosaffa, Thuan Chu, and Karl-Erich Lindenschmidt. 2017. "Using Remote Sensing Data to Parameterize Ice Jam Modeling for a Northern Inland Delta" Water 9, no. 5: 306. https://doi.org/10.3390/w9050306