River hydraulic modelling with ICEsat-2 land and water surface elevation

Coppo Frias, Monica; Liu, Suxia; Mo, Xingguo; Nielsen, Karina; Randall, Heidi; Jiang, Liguang; Ma, Jun; Bauer-Gottwein, Peter

doi:https://doi.org/10.5194/egusphere-2022-377

Preprints

https://doi.org/10.5194/egusphere-2022-377

Preprints

14 Jun 2022

| 14 Jun 2022

River hydraulic modelling with ICEsat-2 land and water surface elevation

Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Randall, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein

Abstract. Advances in geodetic altimetry instruments are providing more accurate measurements, enabling satellite missions to hand over useful data in narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation measurements in remote areas where in-situ data is scarce, that can be combined with hydraulic/hydrodynamic models to simulate water surface elevation and estimate discharge. In this study, we combine ICESat-2 land and water surface elevation measurements with a low-parametrized hydraulic calibration to simulate water surface elevation and discharge without the need for a rainfall-runoff model. ICESat-2 provides an opportunity to map river cross-section geometry very accurately with an along-track resolution of 0.7 m using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters, such as river depth or roughness coefficient. The low-parametrized model together with the assumption of steady-state hydraulics enables the application of a global search algorithm for parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parametrized models, with a root mean square error of around 0.41 m. With the calibrated model, we can calculate water surface elevation time series at any chainage point at any time of an available satellite pass within the river reach, and estimate discharge from water surface elevation. The discharge estimates are validated with in-situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation resulting in a RMSE of 0.59 m for the entire observation period.

Received: 23 May 2022 – Discussion started: 14 Jun 2022

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Journal article(s) based on this preprint

06 Mar 2023

River hydraulic modeling with ICESat-2 land and water surface elevation

Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein

Hydrol. Earth Syst. Sci., 27, 1011–1032, https://doi.org/10.5194/hess-27-1011-2023,https://doi.org/10.5194/hess-27-1011-2023, 2023

Short summary

Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Randall, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-377', Anonymous Referee #1, 05 Aug 2022
The paper is a good example of how to use ICEsat-2 satellite altimetry data in a hydraulic model built without in situ topographic survey of cross-sections. I found the paper interesting and adapt to the HESS journal. I think it deserves to be published after minor changes.

- In the analysis I have only one main concern that relates to the structure of the model without considering large tributaries. My main concern is the fact that you consider the boundary condition as uniformly distributed, but in fact from Figure 4 it is quite evident that there are at least two significant inflows from the two left tributaries (it is not clear whether the right tributary comes upstream or downstream of Jimay station). How did you simulate these significant inflows?

- Perhaps the organization of the article can be revised to avoid repetition and short paragraphs. In particular, the description of the ICEsat-2 dataset and the study area follow the method, but they are actually mentioned again and again to explain the different steps. Therefore, I think the best solution is to describe the material first (satellite and in situ dataset, study area) and then the method so that the reader is able to understand why the two satellite products and the hydraulic model scheme are used.

SPECIFIC COMMENTS:

Introduction: references on hydraulic simulations should include at least one of the studies conducted by Domeneghetti et al. (2014, 2015, 2020); references on altimetry densification should include the publication of one of the authors Nielsen et al. (2022).

Lines 119-125: the numbers are rather arbitrary. Please, justify the reason for these thresholds in the main text (93% for the water occurrence; 15 m from the river center-line; 500 m distance between observations and less than 15 times…).

Lines 132-138: I'm not sure I understand these lines. What is meant by "the reference water surface elevation of the cross-section changes "? If it is a reference, it should be fixed. And what is meant by "the change in flow rate is added to the corresponding depth of the cross section"? How can a flow discharge be added to a depth? Please, rephrase the sentences so that they are clear.

Line 141: it is not clear why the two products ATL03 and ATL13 are shifted of 41 cm. Is this explained somewhere in the manuscript? If not, please can the authors add the reason of this bias?

Lines 142-148: Please, explain the concept better. It is not clear why you are removing the red dots in Figure 3a that correspond to the zero change in discharge, or the dot at 400. In fact, I do not understand the logic of these analyses. Perhaps, they deserve more detail in the text.

Line 212: remove “the”

Looking at Figure 5 the shape of some cross-sections looks rather unrealistic (c,d,e,f). The river bottom looks high (shallow) and this could affect all the analysis. Do you have information on the topographic survey of some cross sections that could help to understand how much error is in the bottom estimate?

Please, define all acronyms: e.g. RHS, UPA, Obj

It is not clear why the paragraph 2.4.2 is described here and what is the role after. Try to explain why you are using the MIKE Hydro model.

Line 290-294: For a reader who is not thoroughly familiar with the satellite product, this sentence is difficult to understand. Please try to explain what is the difference between weak and strong beam data. Also, since this is a product feature, I think it can be moved to a methods section.

Line 296-297: please, add the references for these distances (e.g. cross-section chainage and longitudinal distance.

Line 320-321 the sentence is not clear. Please, reformulate it.

Line 333: the biggest errors are in the downstream sections because I think the estimated bottom of the river is too high. Can I see some cross-sections in the stretch from 65000 to 68000?

Figure 13 a: please specify the Depth coming from Mike 11 and Depth coming from ATL13 in the x-axis and y-axis. Are you able to explain the differences between the simulated and satellite observed WSE in the July-August 2020?

Lines 384-385: do these studies refer to the same study areas? Please, specify.

Line 439: please clarify this sentence because the paper does not show any comparison with other satellite missions to be stated that it “performs better than previous altimetry missions”
Citation: https://doi.org/10.5194/egusphere-2022-377-RC1
- AC1: 'Reply on RC1', Monica Coppo Frias, 29 Sep 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-377/egusphere-2022-377-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-377-AC1
RC2:
'Comment on egusphere-2022-377', Anonymous Referee #2, 09 Sep 2022

This work presents the calibration of a 1D hydraulic model on ICEsat-2 altimetric data, for a river portion with unknown bathymetry-friction and given discharge upstream and downstream, which is an interesting topic. The calibrated parameters lead to fair performances in terms of fit to observed water surface elevations (WSE). The parameter space representation and sensitivity analysis are pertinent.

However the scientific novelty of the study and scientific positioning is not sufficiently clear, the authors omit lots of recent works about inverse hydraulic-hydrological modeling with current altimetric and water extent data, and forthcoming SWOT data.

I recommend the authors thoroughly rework the manuscript, rewrite the introduction and sharpen the analysis of results, reoganize some parts to ease the reading. I provide some elements below.

This work relies on :

- ICEsat-2 data, preprocessed using water masks and an effective parameterization (from Dingman) for unobserved low flow cross section bathymetry. (which has been used with altimetry and hydraulic modeling in Bjerklie et al. 2018).

- a 1D steady state Saint-Venant shallow water model with 3 spatially uniform parameters (Manning friction, low flow depth, power shape) used in the calibration process. Rerun with calibrated parameters and unsteady solver in the MIKE platform. (Other 1D hydraulic models are used with altimetric data and effective bathymetry parameterization in references provided bellow).

- a global calibration algorithm and a global sensitivity analysis algorithm, both from literature are used.

I require clarifications and improvements on these points :

- No real analysis about the hydraulic inverse problem from satellite data, and of the scientfic difficulties related to it as the "bathymetry-fricion" equifinality (Garambois and Monnier 2015), existing elaborate algorithms including variational data assimilation used for high dimensional calibrations and adapted to satellite hydraulics (cf. Larnier et al. 2020, Garambois et al. 2020 and references therein).

- Model derived rating curves (and even stage fall discharge relationships, with WS slope...) have already been presented and thoroughly analyzed in Malou et al. with a hydraulic model calibrated on altimetry and water extents.

- It is not clear to me how much snapshots of WS are used, what about temporal variability ? Is there any nadir altimetric time series available on this study zone? The only validation regarding temporal variability is thus at gauging stations used as boundary conditions for the hydraulic models?

- Hydraulic analysis are not deep enough, regarding forward-inverse hypothesis and resulting misfit wrt observations and river morphological features, regarding also "WS interpolation at any river point" as mentioned in the flowchart of Fig 1. Detailed discussions about hydraulic extrapolation in altimetry context can be found in Pujol et al. 2020, Malou et al. 2021.

- An algorithm enabling Bayesian uncertainty analysis is used "To study the uncertainty of the model", the uncertainty is provided on infered parameters but not on other estimates in the rest of the paper ; analysis are not deep. What is the sensitivity of the parameter inference to first guess, to pdf choices and other calibration algorithm parameters?

- Is "80-180 meter in low flow season" corresponding to a narrow river ? This corresponds to rivers visible with current nadir altimeters and by the future swot mission, which should be properly discussed with a litterature review.

- Clarify UPA_{x} in Eq. 7.

****

Bjerklie, D. M., Birkett, C. M., Rover, J. A., Jones, J. W., Fulton, J. W., Garambois, P.-A.. (2018). « Satellite Remote Sensing Determination of River Discharge: Application to the Yukon River Alaska ». Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2018.04.005

Garambois, P. -A, Monnier, J. (2015). « Inference of effective river properties from remotly sensed observations of water surface ». Advances in Water Ressources. (79) 103-120. doi:10.1016/j.advwatres.2015.02.007

Garambois, P.-A., Larnier, K., Monnier, J., Finaud-Guyot, P., Verley, J., Montazem, A. S., Calmant, S. (2020). « Variational estimation of effective channel and ungauged anabranching river discharge from multi-satellite water heights of different spatial sparsity ». Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2019.124409

Larnier, K., Monnier, J., Garambois, P.-A., Verley, J. (2020) « River discharge and bathymetry estimation from SWOT altimetry measurements ». Inverse Problems in Science and Engineering (IPSE). https://doi.org/10.1080/17415977.2020.1803858

Malou T., P.-A. Garambois, A. Paris, J. Monnier, K. Larnier. (2021) Generation and analysis of stage-fall-discharge laws from coupled hydrological-hydraulic river network model integrating sparse multi-satellite data. Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2021.126993

Pujol, L, Garambois, P.-A., Finaud-Guyot, P., Monnier, J., Larnier, K., Mosé, R., Biancamaria, S., Yésou, H., Moreira, D., Paris, A., Calmant, S. (2020). « Estimation of Multiple Inflows and Effective Channel by Assimilation of Multi-satellite Hydraulic Signatures: Case of the Ungauged Anabranching Negro River ». Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2020.125331

Citation: https://doi.org/10.5194/egusphere-2022-377-RC2
- AC2: 'Reply on RC2', Monica Coppo Frias, 29 Sep 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-377/egusphere-2022-377-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-377-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-377', Anonymous Referee #1, 05 Aug 2022
The paper is a good example of how to use ICEsat-2 satellite altimetry data in a hydraulic model built without in situ topographic survey of cross-sections. I found the paper interesting and adapt to the HESS journal. I think it deserves to be published after minor changes.

- In the analysis I have only one main concern that relates to the structure of the model without considering large tributaries. My main concern is the fact that you consider the boundary condition as uniformly distributed, but in fact from Figure 4 it is quite evident that there are at least two significant inflows from the two left tributaries (it is not clear whether the right tributary comes upstream or downstream of Jimay station). How did you simulate these significant inflows?

- Perhaps the organization of the article can be revised to avoid repetition and short paragraphs. In particular, the description of the ICEsat-2 dataset and the study area follow the method, but they are actually mentioned again and again to explain the different steps. Therefore, I think the best solution is to describe the material first (satellite and in situ dataset, study area) and then the method so that the reader is able to understand why the two satellite products and the hydraulic model scheme are used.

SPECIFIC COMMENTS:

Introduction: references on hydraulic simulations should include at least one of the studies conducted by Domeneghetti et al. (2014, 2015, 2020); references on altimetry densification should include the publication of one of the authors Nielsen et al. (2022).

Lines 119-125: the numbers are rather arbitrary. Please, justify the reason for these thresholds in the main text (93% for the water occurrence; 15 m from the river center-line; 500 m distance between observations and less than 15 times…).

Lines 132-138: I'm not sure I understand these lines. What is meant by "the reference water surface elevation of the cross-section changes "? If it is a reference, it should be fixed. And what is meant by "the change in flow rate is added to the corresponding depth of the cross section"? How can a flow discharge be added to a depth? Please, rephrase the sentences so that they are clear.

Line 141: it is not clear why the two products ATL03 and ATL13 are shifted of 41 cm. Is this explained somewhere in the manuscript? If not, please can the authors add the reason of this bias?

Lines 142-148: Please, explain the concept better. It is not clear why you are removing the red dots in Figure 3a that correspond to the zero change in discharge, or the dot at 400. In fact, I do not understand the logic of these analyses. Perhaps, they deserve more detail in the text.

Line 212: remove “the”

Looking at Figure 5 the shape of some cross-sections looks rather unrealistic (c,d,e,f). The river bottom looks high (shallow) and this could affect all the analysis. Do you have information on the topographic survey of some cross sections that could help to understand how much error is in the bottom estimate?

Please, define all acronyms: e.g. RHS, UPA, Obj

It is not clear why the paragraph 2.4.2 is described here and what is the role after. Try to explain why you are using the MIKE Hydro model.

Line 290-294: For a reader who is not thoroughly familiar with the satellite product, this sentence is difficult to understand. Please try to explain what is the difference between weak and strong beam data. Also, since this is a product feature, I think it can be moved to a methods section.

Line 296-297: please, add the references for these distances (e.g. cross-section chainage and longitudinal distance.

Line 320-321 the sentence is not clear. Please, reformulate it.

Line 333: the biggest errors are in the downstream sections because I think the estimated bottom of the river is too high. Can I see some cross-sections in the stretch from 65000 to 68000?

Figure 13 a: please specify the Depth coming from Mike 11 and Depth coming from ATL13 in the x-axis and y-axis. Are you able to explain the differences between the simulated and satellite observed WSE in the July-August 2020?

Lines 384-385: do these studies refer to the same study areas? Please, specify.

Line 439: please clarify this sentence because the paper does not show any comparison with other satellite missions to be stated that it “performs better than previous altimetry missions”
Citation: https://doi.org/10.5194/egusphere-2022-377-RC1
- AC1: 'Reply on RC1', Monica Coppo Frias, 29 Sep 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-377/egusphere-2022-377-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-377-AC1
RC2:
'Comment on egusphere-2022-377', Anonymous Referee #2, 09 Sep 2022

This work presents the calibration of a 1D hydraulic model on ICEsat-2 altimetric data, for a river portion with unknown bathymetry-friction and given discharge upstream and downstream, which is an interesting topic. The calibrated parameters lead to fair performances in terms of fit to observed water surface elevations (WSE). The parameter space representation and sensitivity analysis are pertinent.

However the scientific novelty of the study and scientific positioning is not sufficiently clear, the authors omit lots of recent works about inverse hydraulic-hydrological modeling with current altimetric and water extent data, and forthcoming SWOT data.

I recommend the authors thoroughly rework the manuscript, rewrite the introduction and sharpen the analysis of results, reoganize some parts to ease the reading. I provide some elements below.

This work relies on :

- ICEsat-2 data, preprocessed using water masks and an effective parameterization (from Dingman) for unobserved low flow cross section bathymetry. (which has been used with altimetry and hydraulic modeling in Bjerklie et al. 2018).

- a 1D steady state Saint-Venant shallow water model with 3 spatially uniform parameters (Manning friction, low flow depth, power shape) used in the calibration process. Rerun with calibrated parameters and unsteady solver in the MIKE platform. (Other 1D hydraulic models are used with altimetric data and effective bathymetry parameterization in references provided bellow).

- a global calibration algorithm and a global sensitivity analysis algorithm, both from literature are used.

I require clarifications and improvements on these points :

- No real analysis about the hydraulic inverse problem from satellite data, and of the scientfic difficulties related to it as the "bathymetry-fricion" equifinality (Garambois and Monnier 2015), existing elaborate algorithms including variational data assimilation used for high dimensional calibrations and adapted to satellite hydraulics (cf. Larnier et al. 2020, Garambois et al. 2020 and references therein).

- Model derived rating curves (and even stage fall discharge relationships, with WS slope...) have already been presented and thoroughly analyzed in Malou et al. with a hydraulic model calibrated on altimetry and water extents.

- It is not clear to me how much snapshots of WS are used, what about temporal variability ? Is there any nadir altimetric time series available on this study zone? The only validation regarding temporal variability is thus at gauging stations used as boundary conditions for the hydraulic models?

- Hydraulic analysis are not deep enough, regarding forward-inverse hypothesis and resulting misfit wrt observations and river morphological features, regarding also "WS interpolation at any river point" as mentioned in the flowchart of Fig 1. Detailed discussions about hydraulic extrapolation in altimetry context can be found in Pujol et al. 2020, Malou et al. 2021.

- An algorithm enabling Bayesian uncertainty analysis is used "To study the uncertainty of the model", the uncertainty is provided on infered parameters but not on other estimates in the rest of the paper ; analysis are not deep. What is the sensitivity of the parameter inference to first guess, to pdf choices and other calibration algorithm parameters?

- Is "80-180 meter in low flow season" corresponding to a narrow river ? This corresponds to rivers visible with current nadir altimeters and by the future swot mission, which should be properly discussed with a litterature review.

- Clarify UPA_{x} in Eq. 7.

****

Bjerklie, D. M., Birkett, C. M., Rover, J. A., Jones, J. W., Fulton, J. W., Garambois, P.-A.. (2018). « Satellite Remote Sensing Determination of River Discharge: Application to the Yukon River Alaska ». Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2018.04.005

Garambois, P. -A, Monnier, J. (2015). « Inference of effective river properties from remotly sensed observations of water surface ». Advances in Water Ressources. (79) 103-120. doi:10.1016/j.advwatres.2015.02.007

Garambois, P.-A., Larnier, K., Monnier, J., Finaud-Guyot, P., Verley, J., Montazem, A. S., Calmant, S. (2020). « Variational estimation of effective channel and ungauged anabranching river discharge from multi-satellite water heights of different spatial sparsity ». Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2019.124409

Larnier, K., Monnier, J., Garambois, P.-A., Verley, J. (2020) « River discharge and bathymetry estimation from SWOT altimetry measurements ». Inverse Problems in Science and Engineering (IPSE). https://doi.org/10.1080/17415977.2020.1803858

Malou T., P.-A. Garambois, A. Paris, J. Monnier, K. Larnier. (2021) Generation and analysis of stage-fall-discharge laws from coupled hydrological-hydraulic river network model integrating sparse multi-satellite data. Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2021.126993

Pujol, L, Garambois, P.-A., Finaud-Guyot, P., Monnier, J., Larnier, K., Mosé, R., Biancamaria, S., Yésou, H., Moreira, D., Paris, A., Calmant, S. (2020). « Estimation of Multiple Inflows and Effective Channel by Assimilation of Multi-satellite Hydraulic Signatures: Case of the Ungauged Anabranching Negro River ». Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2020.125331

Citation: https://doi.org/10.5194/egusphere-2022-377-RC2
- AC2: 'Reply on RC2', Monica Coppo Frias, 29 Sep 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-377/egusphere-2022-377-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-377-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Publish subject to revisions (further review by editor and referees) (22 Oct 2022) by Elena Toth

AR by Monica Coppo Frias on behalf of the Authors (29 Nov 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (07 Dec 2022) by Elena Toth

RR by Anonymous Referee #1 (03 Jan 2023)

RR by Anonymous Referee #2 (11 Jan 2023)

Suggestions for revision or reasons for rejection

Dear authors,

Thank you for this revised version of your article. I appreciate the revision work that has been done seriously, with addition of graphes, analysis and rewriting. I provide some specific comments below for minor revisions.

Kind regards,

****
Comments :

Could you add some more clarifications in introduction regarding the problem of bathymetry-friction estimation in hydraulic models, from water surface observations especially in altimetry context. After line 80 and before your paragraph line80-90 on inverse problem, please clarify what is a calibrated hydraulic model - classically bathymetry is assumed to be known and friction is calibrated, spatially uniform in most cases, spatially distributed in case enough WS data available (and forward/inverse algorithm enables it...); next briefly explain the issue related to estimating uncertain/unknown bathymetry-friction (cf. for example Pujol et al.) ; equifinality issue... You should mention in this context the use of a bathymetry shape parameterization as you use, that is a parameter space reduction compared to estimating a "full" bathymetry.

l330. you should clarify that the steady state hypothesis is reasonable given altimetric snapshots.

Is eq. 4. definite for multi-regimes flows, i.e. fluvial, critical and torrential flows. You can say that one can assume fluvial flows, i.e. Froude<1, in an altimetry context (cf. Garambois and Monnier).

The river stretch is roughly west-east and crossed "orthogonally" by satellite tracks, what about briefly discussing the transposability of the method to other rivers, especially for north-south reaches?

In abstract/intro/methodology please clarify that your calibration parameters are spatially uniform (in 5.2 : "uniform low-flow depth, and Manning’s roughness, correction factor α, and cross-section form exponent r ").

l95 ; modulate please ; swot will be more than a low resolution mission.

I suggest you use the word "friction" instead of roughness in your work ; it is the parameter of an empirical friction law in the hydraulic model of interest.

§ 4.1.4, \Delta Q computed with simulated discharge ?

l369 and elsewhere use the word compute instead of calculate for numerical computations.

l406, "comes from the lateral inflow, " for which measurements are not available

l634, "400", typo?

l710. "Previous studies on hydraulic calibration used hydraulic signatures from satellite remote sensing measurements, but they did not include cross-section geometry (Bjerklie, et al. 2018, Pujol, et al. 2020)". You may clarify they also used simplified geometries (rectangular in Pujol, which is the simplest power law parameterizaiton, rectangular+trapezoidal cross section geometry is used in Garambois et al. 2020 on a braided river). You can say that they used simple cross section parameterizations, with rectangular low-flow channel while you use a non trivial power law parameterization.

Hide

ED: Publish subject to minor revisions (review by editor) (29 Jan 2023) by Elena Toth

AR by Monica Coppo Frias on behalf of the Authors (10 Feb 2023) Author's response Author's tracked changes Manuscript

ED: Publish as is (14 Feb 2023) by Elena Toth

AR by Monica Coppo Frias on behalf of the Authors (15 Feb 2023) Manuscript

Journal article(s) based on this preprint

06 Mar 2023

River hydraulic modeling with ICESat-2 land and water surface elevation

Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein

Hydrol. Earth Syst. Sci., 27, 1011–1032, https://doi.org/10.5194/hess-27-1011-2023,https://doi.org/10.5194/hess-27-1011-2023, 2023

Short summary

Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Randall, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein

Supplement

https://doi.org/10.5194/egusphere-2022-377-supplement

Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Randall, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein

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This paper uses remote sensing data from ICESat-2 to calibrate a 1D hydraulic model. With the model, we can make estimations of discharge and water surface elevation, which are important indicators in flooding risk assessment. ICESat-2 data gives an added value thanks to its 0.7 meters resolution, which allows for measuring narrow river streams. In addition, ICESat-2 provides measurements on the river dry portion geometry that can be included in the model.


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