Articles | Volume 15, issue 15
https://doi.org/10.5194/gmd-15-6085-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6085-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
03 Aug 2022
Model description paper |
| 03 Aug 2022
| 03 Aug 2022
Multi-dimensional hydrological–hydraulic model with variational data assimilation for river networks and floodplains
Léo Pujol
CORRESPONDING AUTHOR
Laboratoire des sciences de l'ingenieur, de l'informatique
et de l'imagerie (ICUBE), Fluid Mechanics Team, CNRS, Université de
Strasbourg, France
Pierre-André Garambois
INRAE (Irstea), Aix Marseille Université, RECOVER, Aix-en-Provence, France
Jérôme Monnier
Institut de Mathematiques de Toulouse (IMT), Toulouse, France
INSA Toulouse, Toulouse, France
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Maxime Jay-Allemand, Julie Demargne, Pierre-André Garambois, Pierre Javelle, Igor Gejadze, François Colleoni, Didier Organde, Patrick Arnaud, and Catherine Fouchier
Proc. IAHS, 385, 281–290, https://doi.org/10.5194/piahs-385-281-2024, https://doi.org/10.5194/piahs-385-281-2024, 2024
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This work targets the improvement of a hydrologic model used for flash flood warnings. A gridded model is used to spatially describe the hydrological processes. We develop a method to estimate the best model setup based on scarce river flow observations. It uses a complex algorithm combined with geographical descriptors to generate gridded parameters that better capture catchment characteristics. Results are promising, improving the discharge estimations where no observations are available.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
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Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Reyhaneh Hashemi, Pierre Brigode, Pierre-André Garambois, and Pierre Javelle
Hydrol. Earth Syst. Sci., 26, 5793–5816, https://doi.org/10.5194/hess-26-5793-2022, https://doi.org/10.5194/hess-26-5793-2022, 2022
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Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.
François Colleoni, Pierre-André Garambois, Pierre Javelle, Maxime Jay-Allemand, and Patrick Arnaud
EGUsphere, https://doi.org/10.5194/egusphere-2022-506, https://doi.org/10.5194/egusphere-2022-506, 2022
Preprint archived
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This contribution presents the first evaluation of Variational Data Assimilation successfully applied over a large sample to the spatially distributed calibration of a newly taylored grid-based parsimonious model structure and corresponding adjoint. High performances are obtained in spatio-temporal validation and at flood time scales, especially for mediterranenan and oceanic catchments. Regional sensitivity analysis revealed the importance of the non conservative and production components.
Abubakar Haruna, Pierre-Andre Garambois, Helene Roux, Pierre Javelle, and Maxime Jay-Allemand
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-414, https://doi.org/10.5194/hess-2021-414, 2021
Manuscript not accepted for further review
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We compared three hydrological models in a flash flood modelling framework. We first identified the sensitive parameters of each model, then compared their performances in terms of outlet discharge and soil moisture simulation. We found out that resulting from the differences in their complexities/process representation, performance depends on the aspect/measure used. The study then highlights and proposed some future investigations/modifications to improve the models.
Kevin Larnier and Jerome Monnier
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npg-2020-32, https://doi.org/10.5194/npg-2020-32, 2020
Revised manuscript not accepted
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A hybrid A.I. algorithm (data-driven and physically-informed) to estimate river discharges observed by the altimetry satellite SWOT (launch 2021).
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Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
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Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
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Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev., 17, 881–898, https://doi.org/10.5194/gmd-17-881-2024, https://doi.org/10.5194/gmd-17-881-2024, 2024
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Stefan Hergarten
Geosci. Model Dev., 17, 781–794, https://doi.org/10.5194/gmd-17-781-2024, https://doi.org/10.5194/gmd-17-781-2024, 2024
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Arjun Babu Nellikkattil, Danielle Lemmon, Travis Allen O'Brien, June-Yi Lee, and Jung-Eun Chu
Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, https://doi.org/10.5194/gmd-17-301-2024, 2024
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Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
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Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024, https://doi.org/10.5194/gmd-17-71-2024, 2024
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This contribution presents a new method to numerically explore the evolution of mountain ranges and surrounding areas. The method helps in monitoring with details on the timing and travel path of material eroded from the mountain ranges. It is particularly well suited to studies juxtaposing different domains – lakes or multiple rock types, for example – and enables the combination of different processes.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, https://doi.org/10.5194/gmd-16-7237-2023, 2023
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This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
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Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
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We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
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Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
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Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
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Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
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Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
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To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
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A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
Xiaqiong Zhou and Hann-Ming Henry Juang
Geosci. Model Dev., 16, 3263–3274, https://doi.org/10.5194/gmd-16-3263-2023, https://doi.org/10.5194/gmd-16-3263-2023, 2023
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The National Centers for Environmental Prediction Global Forecast System version 16 experienced model instability failures in real-time runs resolved by increasing the minimum thickness depth parameter. Further investigation revealed that the issue was caused by the advection of geopotential heights at the model's layer interfaces. By replacing high-order boundary conditions with zero-gradient boundary conditions for interface-wind reconstruction, the instability was effectively addressed.
Grant T. Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott D. King
Geosci. Model Dev., 16, 3221–3239, https://doi.org/10.5194/gmd-16-3221-2023, https://doi.org/10.5194/gmd-16-3221-2023, 2023
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Due to the increasing availability of high-performance computing over the past few decades, numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously known information to modern methodologies.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
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This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Matt J. Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2023-643, https://doi.org/10.5194/egusphere-2023-643, 2023
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In paleoclimate research, proxy system models or PSMs model chemical or biological systems which receive environmental inputs, and output e.g. geochemical signals. The environmental inputs are rarely noiseless, which causes problems when calibrating multi-input PSMs. Here a PSM is developed which includes generalized noise in both model inputs and outputs, and prior information. A quasi-Bayesian method enhances the stability of the solution of the Measurement Error Proxy System Model.
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
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We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
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Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
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In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
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This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
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This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, https://doi.org/10.5194/gmd-16-961-2023, 2023
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We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
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We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
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In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
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While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
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A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Cited articles
Allen, M., Antwi-Agyei, P., Aragon-Durand, F., Babiker, M., Bertoldi, P., Bind,
M., Brown, S., Buckeridge, M., Camilloni, I., Cartwright, A., Masson-Delmotte, V., Zhai, P., Pörtner, H.-O.,
Roberts, D., Skea, J., Shukla, P. R., Pirani, A., Moufouma-Okia, W.,
Péan, C., Pidcock, R., Connors, S., Matthews, J. B. R., Chen, Y., Zhou, X.,
Gomis, M. I., Lonnoy, E., Maycock, T., Tignor, M., and Waterterfield, T.
(Eds.):
Technical Summary: Global warming of 1.5 ∘C, An IPCC Special Report on the
impacts of global warming of 1.5 ∘C above pre-industrial levels and related
global greenhouse gas emission pathways, in the context of strengthening the
global response to the threat of climate change, sustainable development, and
efforts to eradicate poverty, http://pure.iiasa.ac.at/15716 (last access: 27 June 2022),
2019. a
Amara, M., Capatina-Papaghiuc, D., and Trujillo, D.: Hydrodynamical modelling
and multidimensional approximation of estuarian river flows, Comput. Vis. Sci., 6, 39–46,
https://doi.org/10.1007/s00791-003-0106-z, 2004. a
Asch, M., Bocquet, M., and Nodet, M.: Data assimilation: methods, algorithms,
and applications, Fundamentals of Algorithms, SIAM,
https://hal.inria.fr/hal-01402885 (last access: 27 June 2022), 2016. a
Audusse, E. and Bristeau, M.-O.: A well-balanced positivity preserving
“second-order” scheme for shallow water flows on unstructured meshes, J.
Comput. Phys., 206, 311–333, https://doi.org/10.1016/j.jcp.2004.12.016, 2005. a
Audusse, E., Bouchut, F., Bristeau, M.-O., Klein, R., and Perthame, B.: A Fast
and Stable Well-Balanced Scheme with Hydrostatic Reconstruction for Shallow
Water Flows, SIAM J. Sci. Comput., 25, 2050–2065,
https://doi.org/10.1137/S1064827503431090, 2004. a
Barth, T.: Numerical Methods for conservative Laws on Structured and
Unstructured Meshes, Tech. rep., VKI Lecture Series, 2003. a
Barthélémy, S., Ricci, S., Morel, T., Goutal, N., Le Pape, E., and
Zaoui, F.: On operational flood forecasting system involving 1D
Bates, P., Trigg, M., Neal, J., and Dabrowa, A.: LISFLOOD-FP, User manual,
School of Geographical Sciences, University of Bristol, Bristol, UK, https://vdocument.in/lisflood-fp-user-manual-university-of-bristol (last access: 1 August 2022), 2013. a
Bates, P. D., Horritt, M. S., and Fewtrell, T. J.: A simple inertial
formulation of the shallow water equations for efficient two-dimensional
flood inundation modelling, J. Hydrol., 387, 33–45,
https://doi.org/10.1016/j.jhydrol.2010.03.027, 2010. a
Bertalanffy, L. v.: General Systems Theory, 1968. a
Beven, K.: Prophecy, reality and uncertainty in distributed hydrological
modelling, Adv. Water Resour., 16, 41–51, 1993. a
Beven, K. J.: Uniqueness of place and process representations in hydrological modelling, Hydrol. Earth Syst. Sci., 4, 203–213, https://doi.org/10.5194/hess-4-203-2000, 2000. a
Biancamaria, S., Lettenmaier, D., and Pavelsky, T.: The SWOT Mission and Its
Capabilities for Land Hydrology, Surv. Geophys., 37, 307–337,
https://doi.org/10.1007/s10712-015-9346-y, 2016. a
Biancamaria, S., Frappart, F., Leleu, A.-S., Marieu, V., Blumstein, D.,
Desjonquères, J.-D., Boy, F., Sottolichio, A., and Valle-Levinson, A.:
Satellite radar altimetry water elevations performance over a 200 m wide
river: Evaluation over the Garonne River, Adv. Space Res., 59,
128–146, https://doi.org/10.1016/j.asr.2016.10.008, 2017. a
Brêda, J., Paiva, R., Bravo, J., Passaia, O., and Moreira, D.: Assimilation
of satellite altimetry data for effective river bathymetry, Water Resour.
Res., 55, 7441–7463,
https://doi.org/10.1029/2018WR024010, 2019. a
Brunner, G. W.: HEC-RAS River Analysis System, Hydraulic Reference Manual,
Version 1.0., Tech. rep., Hydrologic Engineering Center Davis, CA, https://apps.dtic.mil/sti/pdfs/ADA311952.pdf (last access: 27 June 2022) 1995. a
Buffard, T. and Clain, S.: Monoslope and Multislope MUSCL Methods for
unstructured meshes, J. Comput. Phys., 229, 3745–3776,
https://doi.org/10.1016/j.jcp.2010.01.026, 2010. a
Chévrier, P. and Galley, H.: A Van Leer finite volume scheme for the Euler
equations on unstructured meshes, ESAIM-Math. Model. Num., 27, 183–201, 1993. a
Chow, V.: Open-channel Hydraulics, McGraw-Hill civil engineering series, McGraw-Hill, New-York, USA, ISBN 9780070859067, 1959. a
Collischonn, W., Allasia, D., Da Silva, B. C., and Tucci, C. E.: The MGB-IPH
model for large-scale rainfall-runoff modelling, Hydrolog. Sci.
J., 52, 878–895, https://doi.org/10.1623/hysj.52.5.878,
2007. a
Coron, L., Thirel, G., Delaigue, O., Perrin, C., and Andréassian, V.: The
suite of lumped GR hydrological models in an R package, Environ.
Modell. Softw., 94, 166–171,
https://doi.org/10.1016/j.envsoft.2017.05.002, 2017. a, b
Couderc, F., Madec, R., Monnier, J., and Vila, J.-P.: DassFow-Shallow,
Variational Data Assimilation for Shallow-Water Models: Numerical Schemes,
User and Developer Guides, University of Toulouse, CNRS,
IMT, INSA, ANR, Research report,
https://hal.archives-ouvertes.fr/hal-01120285 (last access: 27 June 2022), 2013. a, b, c, d, e
Cunge, J. A., Holly, F., M., and Verwey, A.: Practical Aspects of Computational
River Hydraulics, Pitam Publishing, ISBN 978-0273084426, 1980. a
Davy, P., Croissant, T., and Lague, D.: A precipiton method to calculate river
hydrodynamics, with applications to flood prediction, landscape evolution
models, and braiding instabilities, J. Geophys. Res.-Earth, 122, 1491–1512,
https://doi.org/10.1002/2016JF004156, 2017. a, b
Delestre, O., Darboux, F., James, F., Lucas, C., Laguerre, C., and Cordier, S.:
FullSWOF: Full Shallow-Water equations for Overland Flow, J. Open Source Softw., 2, 448, https://doi.org/10.21105/joss.00448, 2017. a
Finaud-Guyot, P., Garambois, P.-A., Chen, S., Dellinger, G., Ghenaim, A., and
Terfous, A.: 1D
Fleischmann, A. S., Paiva, R. C. D.,
Collischonn, W., Siqueira, V. A., Paris, A., Moreira, D.
M., Papa, F., Bitar, A. A., Parrens, M., Aires, F., and
Garambois, P. A.: Trade-offs between
1-D and 2-D regional river hydrodynamic models, Water Resour. Res., 56,
e2019WR026812, https://doi.org/10.1029/2019WR026812, 2020. a, b, c
Galland, J.-C., Goutal, N., and Hervouet, J.-M.: TELEMAC: A new numerical model
for solving shallow water equations, Adv. Water Resour., 14,
138–148, 1991. a
Garambois, P., Calmant, S., Roux, H., Paris, A., Monnier, J., Finaud-Guyot, P.,
Montazem, A., and da Silva, J.: Hydraulic visibility: Using satellite
altimetry to parameterize a hydraulic model of an ungauged reach of a braided
river, Hydrol. Process., 31, 756–767,
https://doi.org/10.1002/hyp.11033, 2017. a, b
Garambois, P.-A. and Monnier, J.: Inference of effective river properties from
remotely sensed observations of water surface, Adv. Water Resour.,
79, 103–120,
https://doi.org/10.1016/j.advwatres.2015.02.007, 2015. a, b
Garambois, P.-A., Larnier, K., Monnier, J., Finaud-Guyot, P., Verley, J.,
Montazem, A., and Calmant, S.: Variational estimation of effective channel
and ungauged anabranching river discharge from multi-satellite water heights
of different spatial sparsity, J. Hydrol., 581, 124409,
https://doi.org/10.1016/j.jhydrol.2019.124409, 2020. a, b, c, d
Garandeau, L., Belleudy, A., Javelle, P., Organde, D., Janet, B., Demargne, J.,
De Saint-Aubin, C., and Fouchier, C.: Vigicrues Flash, un service
automatique d'avertissement pour les crues rapides, De la prévision
des crues à la gestion de crise, Société Hydrotechnique
de France, Avignon, France, 11,
https://hal.inrae.fr/hal-02608801 (last access: 27 June 2022), 2018. a
Gejadze, I. Y. and Monnier, J.: On a 2D zoom for the 1D shallow water
model: Coupling and data assimilation, Comput. Method. Appl. M., 196, 4628–4643,
https://doi.org/10.1016/j.cma.2007.05.026, 2007. a
Gervasio, P., Lions, J.-L., and Quarteroni, A.: Heterogeneous coupling by
virtual control methods, Numer. Math., 90, 241–264,
https://doi.org/10.1007/s002110100303, 2001. a
Goutal, N. and Maurel, F.: A finite volume solver for 1D shallow-water
equations applied to an actual river, Int. J. Numer. Meth. Fl., 38, 1–19,
https://doi.org/10.1002/fld.201, 2002. a
Grimaldi, S., Li, Y., Walker, J., and Pauwels, V.: Effective representation of
river geometry in hydraulic flood forecast models, Water Resour. Res.,
54, 1031–1057, https://doi.org/10.1002/2017WR021765, 2018. a, b
Gudmundsson, G. H.: Transmission of basal variability to a glacier surface,
J. Geophys. Res.-Sol. Ea., 108, B5,
https://doi.org/10.1029/2002JB002107, 2003. a
Guinot, V.: Wave propagation in fluids: models and numerical techniques, 2nd edn., vol. 49, edited by: ISTE Ltd., ISBN 978-9812707789, 2010. a
Guinot, V., Delenne, C., Rousseau, A., and Boutron, O.: Flux closures and
source term models for shallow water models with depth-dependent integral
porosity, Adv. Water Resour., 122, 1–26,
https://doi.org/10.1016/j.advwatres.2018.09.014, 2018. a, b, c
Hascoet, L. and Pascual, V.: The Tapenade automatic differentiation tool:
principles, model, and specification, ACM T. Math.
Software, 39, 1–43, https://doi.org/10.1145/2450153.2450158, 2013. a, b, c, d
Hocini, N., Payrastre, O., Bourgin, F., Gaume, E., Davy, P., Lague, D., Poinsignon, L., and Pons, F.: Performance of automated methods for flash flood inundation mapping: a comparison of a digital terrain model (DTM) filling and two hydrodynamic methods, Hydrol. Earth Syst. Sci., 25, 2979–2995, https://doi.org/10.5194/hess-25-2979-2021, 2021. a, b, c
Hostache, R., Lai, X., Monnier, J., and Puech, C.: Assimilation of
spatially distributed water levels into a shallow-water flood model. Part
II: Use of a remote sensing image of Mosel River, J. Hydrol., 390, 257–268,
https://doi.org/10.1016/j.jhydrol.2010.07.003, 2010. a
Hunter, N. M., Bates, P. D., Neelz, S.,
Pender, G., Villanueva, I., Wright, N. G., Liang, D.,
Falconer, R. A., Lin, B., Waller, S., Crossley, A. J., and
Mason, D. C.: Benchmarking 2D
hydraulic models for urban flooding, in: Proceedings of the Institution of
Civil Engineers-Water Management, Thomas Telford Ltd, 161, 13–30,
https://doi.org/10.1680/wama.2008.161.1.13, 2008. a
Iturbide, M., Gutiérrez, J. M., Alves, L. M., Bedia, J., Cerezo-Mota, R., Cimadevilla, E., Cofiño, A. S., Di Luca, A., Faria, S. H., Gorodetskaya, I. V., Hauser, M., Herrera, S., Hennessy, K., Hewitt, H. T., Jones, R. G., Krakovska, S., Manzanas, R., Martínez-Castro, D., Narisma, G. T., Nurhati, I. S., Pinto, I., Seneviratne, S. I., van den Hurk, B., and Vera, C. S.: An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets, Earth Syst. Sci. Data, 12, 2959–2970, https://doi.org/10.5194/essd-12-2959-2020, 2020. a
Jay-Allemand, M., Javelle, P., Gejadze, I., Arnaud, P., Malaterre, P.-O., Fine, J.-A., and Organde, D.: On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment, Hydrol. Earth Syst. Sci., 24, 5519–5538, https://doi.org/10.5194/hess-24-5519-2020, 2020. a, b
Kirstetter, G., Delestre, O., Lagrée, P.-Y., Popinet, S., and Josserand, C.: B-flood 1.0: an open-source Saint-Venant model for flash-flood simulation using adaptive refinement, Geosci. Model Dev., 14, 7117–7132, https://doi.org/10.5194/gmd-14-7117-2021, 2021. a
Lai, X. and Monnier, J.: Assimilation of spatially distributed water levels
into a shallow-water flood model. Part I: Mathematical method and test case,
J. Hydrol., 377, 1–11,
https://doi.org/10.1016/j.jhydrol.2009.07.058, 2009. a
Le Lay, M.: Modélisation hydrologique dans un contexte de variabilité
hydro-climatique. Une approche comparative pour l'étude du cycle
hydrologique à méso-échelle au Bénin, PhD thesis, Institut
National Polytechnique de Grenoble (INPG),
https://tel.archives-ouvertes.fr/tel-00116912 (last access: 27 June 2022), 2006. a
Leopold, L. B. and Maddock, T.: The hydraulic geometry of stream channels and
some physiographic implications, US Government Printing Office, 252, https://doi.org/10.3133/pp252,
1953. a
Lorenc, A. C., Ballard, S. P., Bell, R. S., Ingleby,
N. B., Andrews, P. L. F., Barker, D. M., Bray, J. R., Clayton, A. M.,
Dalby, T., Li, D., Payne, T. J., and Saunders, F. W.: The Met. Office global
three-dimensional variational data assimilation scheme, Q. J. Roy. Meteor. Soc., 126, 2991–3012, 2000. a
Malou, T. and Monnier, J.: Double-scale diffusive wave model dedicated to spatial river observation and associated covariance kernel for variational data assimilation , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10355, https://doi.org/10.5194/egusphere-egu21-10355, 2021. a
Malou, T. and Monnier, J.: Covariance kernels investigation from diffusive wave
equations for data assimilation in hydrology, Inverse Probl.,
https://doi.org/10.1088/1361-6420/ac509d, accepted, 2022. a
Malou, T., Garambois, P.-A., Paris, A., Monnier, J., and Larnier, K.:
Generation and analysis of stage-fall-discharge laws from coupled
hydrological-hydraulic river network model integrating sparse multi-satellite
data, J. Hydrol., 603, 126993,
https://doi.org/10.1016/j.jhydrol.2021.126993, 2021. a, b, c
Marin, J. and Monnier, J.: Superposition of local zoom models and simultaneous
calibration for 1D–2D shallow water flows, Math. Comput. Simulat., 80, 547–560,
https://doi.org/10.1016/j.matcom.2009.09.001, 2009. a
Martin, N. and Monnier, J.: Inverse rheometry and basal properties inference
for pseudoplastic geophysical flows, Eur. J. Mech. B-Fluid.,
50, 110–126,
https://doi.org/10.1016/j.euromechflu.2014.11.011, 2015. a
Miglio, E., Perotto, S., and Saleri, F.: Model coupling techniques for
free-surface flow problems: Part I, Nonlinear Anal.-Theor., 63, e1885–e1896,
https://doi.org/10.1016/j.na.2005.03.083, 2005a. a
Miglio, E., Perotto, S., and Saleri, F.: Model coupling techniques for
free-surface flow problems: Part II, Nonlinear Anal.-Theor., 63, e1897–e1908,
https://doi.org/10.1016/j.na.2005.03.085, 2005b. a
Milly, P.: Climate, soil water storage, and the average annual water balance,
Water Resour. Res., 30, 2143–2156,
https://doi.org/10.1029/94WR00586, 1994. a
Monnier, J.: Variational data assimilation: from optimal control to large scale
data assimilation, Open Online Course, INSA Toulouse,
https://www.math.univ-toulouse.fr/~jmonnie/Enseignement/CourseVDA.pdf (last access: 27 June 2022),
2014. a
Monnier, J.: Variational Data Assimilation and Model Learning, https://hal.archives-ouvertes.fr/hal-03040047 (last access: 1 August 2022), 2021. a
Monnier, J., Couderc, F., Dartus, D., Larnier, K., Madec, R., and Vila, J.-P.:
Inverse algorithms for 2D shallow water equations in presence of wet dry
fronts: Application to flood plain dynamics, Adv. Water Resour., 97,
11–24, https://doi.org/10.1016/j.advwatres.2016.07.005,
2016. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q
Montazem, A., Garambois, P.-A., Calmant, S., Finaud-Guyot, P., Monnier, J.,
Moreira, D., Minear, J., and Biancamaria, S.: Wavelet-Based River
Segmentation Using Hydraulic Control-Preserving Water Surface Elevation
Profile Properties, Geophys. Res. Lett., 46, 6534–6543,
https://doi.org/10.1029/2019GL082986, 2019. a, b, c
Nguyen, P., Thorstensen, A., Sorooshian, S., Hsu, K., AghaKouchak, A., Sanders,
B., Koren, V., Cui, Z., and Smith, M.: A high resolution coupled
hydrologic-hydraulic model (HiResFlood-UCI) for flash flood modeling,
J. Hydrol., 541, 401–420,
https://doi.org/10.1016/j.jhydrol.2015.10.047, 2016. a, b, c
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil,
F., and Loumagne, C.: Which potential evapotranspiration input for a lumped
rainfall-runoff model?: Part 2 Towards a simple and efficient potential
evapotranspiration model for rainfall-runoff modelling, J. Hydrol.,
303, 290–306, https://doi.org/10.1016/j.jhydrol.2004.08.026,
2005. a
Özgen, I., Zhao, J.-h., Liang, D.-f., and Hinkelmann, R.: Wave propagation
speeds and source term influences in single and integral porosity shallow
water equations, Water Sci. Eng., 10, 275–286,
https://doi.org/10.1016/j.wse.2017.12.003, 2017. a
Pontes, P., Fan, F., Fleischmann, A., Paiva, R., Buarque, D., Siqueira, V.,
Jardim, P., Sorribas, M., and Collischonn, W.: MGB-IPH model for
hydrological and hydraulic simulation of large floodplain river systems
coupled with open source GIS, Environ. Modell. Softw., 94,
1–20, https://doi.org/10.1016/j.envsoft.2017.03.029, 2017. a
Pujol, L., Garambois, P.-A., Finaud-Guyot, P., Monnier, J., Larnier, K.,
Mosé, R., Biancamaria, S., Yesou, H., Moreira, D., Paris, A., and
Calmant, S.: Estimation of multiple inflows and effective channel by
assimilation of multi-satellite hydraulic signatures: The ungauged
anabranching Negro river, J. Hydrol., 591, 125331,
https://doi.org/10.1016/j.jhydrol.2020.125331, 2020. a, b, c, d, e, f, g, h, i
Pujol, L., Garambois, P.-A., and Monnier, J.: DassFlow2D-V3 code and cases, Zenodo [code], https://doi.org/10.5281/zenodo.6342723, 2022. a, b
Rodríguez, E., Durand, M., and Frasson, R. P. d. M.: Observing rivers with
varying spatial scales, Water Resour. Res., 56, 9,
https://doi.org/10.1029/2019WR026476, 2020. a
Sanders, B. F., Schubert, J. E., and Detwiler, R. L.: ParBreZo: A parallel,
unstructured grid, Godunov-type, shallow-water code for high-resolution flood
inundation modeling at the regional scale, Adv. Water Resour., 33,
1456–1467, https://doi.org/10.1016/j.advwatres.2010.07.007,
2010.
a, b
Schuite, J., Flipo, N., Massei, N., Rivière, A., and Baratelli, F.:
Improving the Spectral Analysis of Hydrological Signals to Efficiently
Constrain Watershed Properties, Water Resour. Res., 55, 4043–4065,
https://doi.org/10.1029/2018WR024579, 2019. a
Schumann, G. J.-P. and Domeneghetti, A.: Exploiting the proliferation of
current and future satellite observations of rivers, Hydrol. Process.,
30, 2891–2896, https://doi.org/10.1002/hyp.10825, 2016. a
Steinstraesser, J. G. C., Delenne, C., Finaud-Guyot, P., Guinot, V., Casapia,
J. K., and Rousseau, A.: SW2D-LEMON: a new software for upscaled shallow
water modeling, in: Simhydro 2021 – 6th International Conference Models for
complex and global water issues-Practices and expectations, Sophia Antipolis, 16–18 June 2021,
https://hal.inria.fr/hal-03224050/ (last access: 27 June 2022), 2021. a
Uhe, P., Mitchell, D., Bates, P. D., Addor, N., Neal, J., and Beck, H. E.: Model cascade from meteorological drivers to river flood hazard: flood-cascade v1.0, Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, 2021. a, b
Vila, J.-P.: Simplified Godunov schemes for 2×2 systems of conservation laws,
SIAM J. Numer. Anal., 23, 1173–1192, https://doi.org/10.1137/0723079, 1986. a
Vila, J.-P. and Villedieu, P.: Convergence of an explicit finite volume scheme
for first order symmetric systems, Numer. Math., 94, 573–602,
https://doi.org/10.1007/s00211-002-0396-y,
2003. a
Zhu, C., Byrd, R. H., Lu, P., and Nocedal, J.: Algorithm 778: L-BFGS-B:
Fortran subroutines for large-scale bound-constrained optimization, ACM
T. Math. Software, 23, 550–560,
https://doi.org/10.1145/279232.279236, 1997. a, b, c
Short summary
This contribution presents a new numerical model for representing hydraulic–hydrological quantities at the basin scale. It allows modeling large areas at a low computational cost, with fine zooms where needed. It allows the integration of local and satellite measurements, via data assimilation methods, to improve the model's match to observations. Using this capability, good matches to in situ observations are obtained on a model of the complex Adour river network with fine zooms on floodplains.
This contribution presents a new numerical model for representing hydraulic–hydrological...
