Preprints
https://doi.org/10.5194/egusphere-2025-4447
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-4447
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
09 Oct 2025
| 09 Oct 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Accumulation-based Runoff and Pluvial Flood Estimation Tool
Abstract. Knowledge about spatially distributed inundation depth and overland flow quantities, as well as related flow velocities, is critical information for establishing a pluvial flood forecasting system and the related disaster management. This kind of information is often derived from computationally demanding simulations with 2-dimensional hydrodynamic models, limiting the number of scenarios for which information can be provided and challenging real-time forecasting. To address this gap, we developed the model AccRo (Accumulation-based Runoff and Flooding), which is a computationally efficient method to derive maximum inundation depth, maximum flow velocity and maximum specific discharge of a flood event at larger spatial scales, based on an improved flow accumulation method to better represent the spatial extent of inundated areas. To assess the quality of AccRo, we compare the results from the AccRo model with the results of two different state-of-the-art 2-dimensional hydrodynamic models for design cases as well as real-world pluvial flood examples. We find that AccRo is able to represent both, the analytical solution for the design cases and the simulations of the hydrodynamic models in the real-world example in high quality, well within the range of the two hydrodynamic models. In combination with the low computational requirements, we conclude that AccRo is a valuable tool for assessing pluvial flood hazards.
How to cite. Leistert, H., Hänsler, A., Schmit, M., Steinbrich, A., and Weiler, M.: Accumulation-based Runoff and Pluvial Flood Estimation Tool, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4447, 2025.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Status: open (until 04 Dec 2025)
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RC1: 'Comment on egusphere-2025-4447', Anonymous Referee #1, 27 Oct 2025
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In the manuscript titled "Accumulation-based Runoff and Pluvial Flood Estimation Tool”, the authors present a novel and improved raster-based model to represent key hydrodynamic variables such as maximum inundation depth, maximum flow velocity and maximum specific discharge. The model results are compared against those from two 2D models. The raster-based model achieves a level of accuracy comparable to both 2D models while significantly reducing computational cost. The topic is relevant and timely, and the manuscript is generally clear and well-structured. Overall, I consider this work an interesting and useful contribution to flood modeling and a potential tool for real-time forecasting. For these reasons, I recommend the manuscript for publication in GMD after minor revision.General comments:
- Lines 39-47: Several 2D models implemented on GPUs can achieve faster-than-real-time performance even for large computational domains, with efficiency sufficient for real-time forecasting. However, this performance strongly depends on the characteristics of the simulated case. The main limitation arises when large domains include localized features (e.g., gullies, small rills) that require fine spatial resolution, leading to small time steps and many operations. I suggest clarifying these situations in the manuscript, as the proposed raster-based model could represent a valuable alternative under such conditions.
- Lines 56-60: I suggest emphasizing the novelty of the work in this paragraph. Highlighting how this approach differs from existing methods would help readers better understand the main contribution of the study.
- Section “Introduction": I recommend adding a short paragraph at the end of the Introduction to briefly outline the structure of the manuscript, summarizing the content of each section.
- Figure 6: The figure illustrates the details of the test cases. However, I recommend including a more detailed representation of cases (a) and (b), indicating relevant dimensions such as length and width. This would improve the clarity of the test case setup and facilitate reproducibility.
- Table 2: The table presents results from both 2D models and the raster-based model. However, two of the three simulations using RIM2D are unstable, and the remaining simulation produces results that differ substantially from the others. It is unclear how the model can be unstable for an analytical case. The authors should consider either using alternative software, modifying the simulated case, or removing the RIM2D column entirely, as the results are not informative when the model is unstable, and in the stable configuration, one of the reference 2D models provides results significantly different from the other models.
- Section "Discussion": The authors compare model results using the Figures 7, 8, 9, 11, etc., but the analysis is entirely qualitative. I recommend including at least one quantitative performance metric (e.g., Mean Absolute Error (MAE) or Root-Mean-Square Error (RMSE)) to provide a clearer comparison between models. It is not necessary to compute these metrics for all variables, but, for example, MAE, Peak Percentage Difference, or Peak Time Difference could be reported for the discharges in Figure 11. These metrics would strengthen the discussion.
- Section "Discussion": I suggest adding a table summarizing the computational cost for each model and test case. This would make the discussion of computational efficiency clearer and more concise.
- The abstract states that “… AccRo is a valuable tool for assessing pluvial flood hazards.” but the conclusions note limitations regarding temporal development and assumptions of constant velocity. I suggest revising the last sentence of the abstract to better reflect these limitations.
Specific comments:- Lines 10-16: I recommend homogenizing verb tenses for consistency. For example, the authors alternate between “we developed…” and “we find…” within the same paragraph.
- Figure 1: The variable L is included but not defined. If it represents cell length, a uniform notation should be used, as the same variable is defined as l in the text.
- Equation 3: Values “0.02m” and “0.15m” should include a space between the number and the unit, and the unit should not be italicized, consistent with the formatting used elsewhere in the manuscript: “0.02 m” and “0.15 m”.
- Figure 3: Values for ∑s are included but units are not specified. The same applies to smax.
- Line 446: The authors state “… (also for other events and test cases not included in this study).” I recommend either including these additional results in an Appendix, together with the corresponding references (if any), or removing this sentence.
Technical corrections:- Line 7: Replace “with two-dimensional hydrodynamic models, …” with “with 2-dimensional hydrodynamic models, …”.
- Line 13: Replace “state-of-the-art two-dimensional” with “state-of-the-art 2-dimensional”.
- Line 47: Replace “Reinecke et al., 2024” with “Reinecke et al, 2024”.
- Line 164: Include a space between ∑s and “change”.
- Figure 8: Add a period at the end of the figure caption.
ReplyCitation: https://doi.org/10.5194/egusphere-2025-4447-RC1
Data sets
Primary data and analysis scripts Hannes Leistert et al. https://doi.org/10.5281/zenodo.17154005
Model code and software
AccRo Model Code Hannes Leistert https://doi.org/10.5281/zenodo.17153807
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Hannes Leistert
CORRESPONDING AUTHOR
Hydrology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
Andreas Hänsler
Hydrology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
Max Schmit
Hydrology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
Andreas Steinbrich
Hydrology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
Markus Weiler
Hydrology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
Short summary
The newly developed model AccRo (Accumulation-based Runoff and Pluvial Flood Estimation Tool) is a computationally efficient method to derive key parameters for estimating pluvial flood hazards. Here, we compare results of AccRo with the data of two hydrodynamic models for different cases. We find that AccRo is able to represent the simulations of the hydrodynamic models in high quality, but with much lower computational effort, making it a valuable tool for assessing pluvial flood hazards.
The newly developed model AccRo (Accumulation-based Runoff and Pluvial Flood Estimation Tool) is...