Articles | Volume 10, issue 4
https://doi.org/10.5194/esurf-10-851-2022
© 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/esurf-10-851-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Aug 2022
Research article |
| 15 Aug 2022
| 15 Aug 2022
Comparison of rainfall generators with regionalisation for the estimation of rainfall erosivity at ungauged sites
Ross Pidoto
Institute of Hydrology and Water Resources Management, Leibniz University Hannover, Hanover, Germany
Nejc Bezak
University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia
Hannes Müller-Thomy
CORRESPONDING AUTHOR
Leichtweiß Institute for Hydraulic Engineering and Water Resources, Department of Hydrology, Water Management and Water Protection, Technische Universität Braunschweig, Brunswick, Germany
Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology, Vienna, Austria
previously published under the name Hannes Müller
Bora Shehu
Institute of Hydrology and Water Resources Management, Leibniz University Hannover, Hanover, Germany
Ana Claudia Callau-Beyer
Institute of Horticultural Production Systems, Leibniz University Hannover, Hanover, Germany
Katarina Zabret
University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia
Uwe Haberlandt
Institute of Hydrology and Water Resources Management, Leibniz University Hannover, Hanover, Germany
Related authors
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
Short summary
Short summary
Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-318, https://doi.org/10.5194/essd-2024-318, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The CAMELS-DE dataset features data from 1555 streamflow gauges across Germany, with records spanning from 1951 to 2020. This comprehensive dataset, which includes time series of up to 70 years (median 46 years), enables advanced research on water flow and environmental trends, and supports the development of hydrological models.
Golbarg Goshtasbpour and Uwe Haberlandt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-177, https://doi.org/10.5194/hess-2024-177, 2024
Preprint under review for HESS
Short summary
Short summary
We provide a method how to estimate extreme rainfall from radar observations. Extreme value statistic is applied for observed radar rainfall covering different areas from point size up to about 1000 km2. The rainfall extremes are supposed to be as higher as smaller the area is. This behaviour could not be confirmed by the radar observations. The reason is the limited single point sampling approach of the radar data. New multiple point sampling strategies are proposed to mitigate this problem.
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024, https://doi.org/10.5194/nhess-24-2025-2024, 2024
Short summary
Short summary
Future changes in sub-daily rainfall extreme values are essential in various hydrological fields, but climate scenarios typically offer only daily resolution. One solution is rainfall generation. With a temperature-dependent rainfall generator climate scenario data were disaggregated to 5 min rainfall time series for 45 locations across Germany. The analysis of the future 5 min rainfall time series showed an increase in the rainfall extremes values for rainfall durations of 5 min and 1 h.
Anne Bartens, Bora Shehu, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 28, 1687–1709, https://doi.org/10.5194/hess-28-1687-2024, https://doi.org/10.5194/hess-28-1687-2024, 2024
Short summary
Short summary
River flow data are often provided as mean daily flows (MDF), in which a lot of information is lost about the actual maximum flow or instantaneous peak flows (IPF) within a day. We investigate the error of using MDF instead of IPF and identify means to predict IPF when only MDF data are available. We find that the average ratio of daily flood peaks and volumes is a good predictor, which is easily and universally applicable and requires a minimum amount of data.
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
Short summary
Short summary
Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
Short summary
Short summary
Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
Short summary
Short summary
For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Bora Shehu and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 2075–2097, https://doi.org/10.5194/hess-27-2075-2023, https://doi.org/10.5194/hess-27-2075-2023, 2023
Short summary
Short summary
Design rainfall volumes at different duration and frequencies are necessary for the planning of water-related systems and facilities. As the procedure for deriving these values is subjected to different sources of uncertainty, here we explore different methods to estimate how precise these values are for different duration, locations and frequencies in Germany. Combining local and spatial simulations, we estimate tolerance ranges from approx. 10–60% for design rainfall volumes in Germany.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
Short summary
Short summary
Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Nejc Bezak, Pasquale Borrelli, and Panos Panagos
Hydrol. Earth Syst. Sci., 26, 1907–1924, https://doi.org/10.5194/hess-26-1907-2022, https://doi.org/10.5194/hess-26-1907-2022, 2022
Short summary
Short summary
Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of rainfall erosivity was constructed using data with a 30 min time interval. It was shown that the satellite-based precipitation products are an interesting option for estimating rainfall erosivity, especially in regions with limited ground data. However, ground-based high-frequency precipitation measurements are (still) essential for accurate estimates of rainfall erosivity.
Bora Shehu and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 26, 1631–1658, https://doi.org/10.5194/hess-26-1631-2022, https://doi.org/10.5194/hess-26-1631-2022, 2022
Short summary
Short summary
In this paper we investigate whether similar storms behave similarly and whether the information obtained from past similar storms can improve storm nowcast based on radar data. Here a nearest-neighbour approach is employed to first identify similar storms and later to issue either a single or an ensemble nowcast based on k most similar past storms. The results indicate that the information obtained from similar storms can reduce the errors considerably, especially for convective storm nowcast.
Anne Bartens and Uwe Haberlandt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-466, https://doi.org/10.5194/hess-2021-466, 2021
Preprint withdrawn
Short summary
Short summary
River flow data is often provided as mean daily flow (MDF), in which a lot of information is lost about the actual maximum flow or instantaneous peak flow (IPF) within a day. We investigate the error of using MDFs instead of IPFs and identify means to predict IPFs when only MDF data is available. We find that the average ratio of daily flood peaks and volumes is a good predictor, which is easily and universally applicable and requires a minimum amount of data.
Hannes Müller-Thomy
Hydrol. Earth Syst. Sci., 24, 169–188, https://doi.org/10.5194/hess-24-169-2020, https://doi.org/10.5194/hess-24-169-2020, 2020
Short summary
Short summary
Simulation of highly dynamic floods requires high-resolution rainfall time series. Observed time series of that kind are often too short; rainfall generation is the only solution. The applied rainfall generator tends to underestimate the process memory of the rainfall. By modifications of the rainfall generator and a subsequent optimisation method the process memory is improved significantly. Flood simulations are expected to be more trustable using the rainfall time series generated like this.
Anne Fangmann and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 23, 447–463, https://doi.org/10.5194/hess-23-447-2019, https://doi.org/10.5194/hess-23-447-2019, 2019
Short summary
Short summary
Low-flow events are little dynamic in space and time. Thus, it is hypothesized that models can be found, based on simple statistical relationships between low-flow metrics and meteorological states, that can help identify potential low-flow drivers. In this study we assess whether such relationships exist and whether they can be applied to predict future low flow within regional climate change impact assessment in the northwestern part of Germany.
Theano Iliopoulou, Cristina Aguilar, Berit Arheimer, María Bermúdez, Nejc Bezak, Andrea Ficchì, Demetris Koutsoyiannis, Juraj Parajka, María José Polo, Guillaume Thirel, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 73–91, https://doi.org/10.5194/hess-23-73-2019, https://doi.org/10.5194/hess-23-73-2019, 2019
Short summary
Short summary
We investigate the seasonal memory properties of a large sample of European rivers in terms of high and low flows. We compute seasonal correlations between peak and low flows and average flows in the previous seasons and explore the links with various physiographic and hydro-climatic catchment descriptors. Our findings suggest that there is a traceable physical basis for river memory which in turn can be employed to reduce uncertainty and improve probabilistic predictions of floods and droughts.
Hannes Müller-Thomy, Markus Wallner, and Kristian Förster
Hydrol. Earth Syst. Sci., 22, 5259–5280, https://doi.org/10.5194/hess-22-5259-2018, https://doi.org/10.5194/hess-22-5259-2018, 2018
Short summary
Short summary
Rainfall time series are disaggregated from daily to hourly values to be used for rainfall–runoff modeling of mesoscale catchments. Spatial rainfall consistency is implemented afterwards using simulated annealing. With the calibration process applied, observed runoff statistics (e.g., summer and winter peak flows) are represented well. However, rainfall datasets with under- or over-estimation of spatial consistency lead to similar results, so the need for a good representation can be questioned.
Ehsan Rabiei, Uwe Haberlandt, Monika Sester, Daniel Fitzner, and Markus Wallner
Hydrol. Earth Syst. Sci., 20, 3907–3922, https://doi.org/10.5194/hess-20-3907-2016, https://doi.org/10.5194/hess-20-3907-2016, 2016
Short summary
Short summary
The value of using moving cars for rainfall measurement purposes (RCs) was investigated with laboratory experiments by Rabiei et al. (2013). They analyzed the Hydreon and Xanonex optical sensors against different rainfall intensities. A continuous investigation of using RCs with the derived uncertainties from laboratory experiments for areal rainfall estimation as well as implementing the data in a hydrological model are addressed in this study.
Uwe Haberlandt and Christian Berndt
Proc. IAHS, 373, 81–85, https://doi.org/10.5194/piahs-373-81-2016, https://doi.org/10.5194/piahs-373-81-2016, 2016
U. Haberlandt and I. Radtke
Hydrol. Earth Syst. Sci., 18, 353–365, https://doi.org/10.5194/hess-18-353-2014, https://doi.org/10.5194/hess-18-353-2014, 2014
E. Rabiei, U. Haberlandt, M. Sester, and D. Fitzner
Hydrol. Earth Syst. Sci., 17, 4701–4712, https://doi.org/10.5194/hess-17-4701-2013, https://doi.org/10.5194/hess-17-4701-2013, 2013
Related subject area
Cross-cutting themes: Quantitative and statistical methods in Earth surface dynamics
Introducing standardized field methods for fracture-focused surface process research
Full four-dimensional change analysis of topographic point cloud time series using Kalman filtering
Inverse modeling of turbidity currents using an artificial neural network approach: verification for field application
Automated quantification of floating wood pieces in rivers from video monitoring: a new software tool and validation
Particle size dynamics in abrading pebble populations
Computing water flow through complex landscapes – Part 3: Fill–Spill–Merge: flow routing in depression hierarchies
A photogrammetry-based approach for soil bulk density measurements with an emphasis on applications to cosmogenic nuclide analysis
Dominant process zones in a mixed fluvial–tidal delta are morphologically distinct
Identifying sediment transport mechanisms from grain size–shape distributions, applied to aeolian sediments
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
Systematic identification of external influences in multi-year microseismic recordings using convolutional neural networks
Earth's surface mass transport derived from GRACE, evaluated by GPS, ICESat, hydrological modeling and altimetry satellite orbits
The R package “eseis” – a software toolbox for environmental seismology
Bayesian inversion of a CRN depth profile to infer Quaternary erosion of the northwestern Campine Plateau (NE Belgium)
A new CT scan methodology to characterize a small aggregation gravel clast contained in a soft sediment matrix
Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics
An introduction to learning algorithms and potential applications in geomorphometry and Earth surface dynamics
Sensitivity analysis and implications for surface processes from a hydrological modelling approach in the Gunt catchment, high Pamir Mountains
Constraining the stream power law: a novel approach combining a landscape evolution model and an inversion method
Martha Cary Eppes, Alex Rinehart, Jennifer Aldred, Samantha Berberich, Maxwell P. Dahlquist, Sarah G. Evans, Russell Keanini, Stephen E. Laubach, Faye Moser, Mehdi Morovati, Steven Porson, Monica Rasmussen, and Uri Shaanan
Earth Surf. Dynam., 12, 35–66, https://doi.org/10.5194/esurf-12-35-2024, https://doi.org/10.5194/esurf-12-35-2024, 2024
Short summary
Short summary
All rocks have fractures (cracks) that can influence virtually every process acting on Earth's surface where humans live. Yet, scientists have not standardized their methods for collecting fracture data. Here we draw on past work across geo-disciplines and propose a list of baseline data for fracture-focused surface process research. We detail the rationale and methods for collecting them. We hope their wide adoption will improve future methods and knowledge of rock fracture overall.
Lukas Winiwarter, Katharina Anders, Daniel Czerwonka-Schröder, and Bernhard Höfle
Earth Surf. Dynam., 11, 593–613, https://doi.org/10.5194/esurf-11-593-2023, https://doi.org/10.5194/esurf-11-593-2023, 2023
Short summary
Short summary
We present a method to extract surface change information from 4D time series of topographic point clouds recorded with a terrestrial laser scanner. The method uses sensor information to spatially and temporally smooth the data, reducing uncertainties. The Kalman filter used for the temporal smoothing also allows us to interpolate over data gaps or extrapolate into the future. Clustering areas where change histories are similar allows us to identify processes that may have the same causes.
Hajime Naruse and Kento Nakao
Earth Surf. Dynam., 9, 1091–1109, https://doi.org/10.5194/esurf-9-1091-2021, https://doi.org/10.5194/esurf-9-1091-2021, 2021
Short summary
Short summary
This paper proposes a method to reconstruct the hydraulic conditions of turbidity currents from turbidites. We investigated the validity and problems of this method in application to actual field datasets using artificial data. Once this method is established, it is expected that the method will elucidate the generation process of turbidity currents and will help to predict the geometry of resultant turbidites in deep-sea environments.
Hossein Ghaffarian, Pierre Lemaire, Zhang Zhi, Laure Tougne, Bruce MacVicar, and Hervé Piégay
Earth Surf. Dynam., 9, 519–537, https://doi.org/10.5194/esurf-9-519-2021, https://doi.org/10.5194/esurf-9-519-2021, 2021
Short summary
Short summary
Quantifying wood fluxes in rivers would improve our understanding of the key processes in river ecology and morphology. In this work, we introduce new software for the automatic detection of wood pieces in rivers. The results show 93.5 % and 86.5 % accuracy for piece number and volume, respectively.
András A. Sipos, Gábor Domokos, and János Török
Earth Surf. Dynam., 9, 235–251, https://doi.org/10.5194/esurf-9-235-2021, https://doi.org/10.5194/esurf-9-235-2021, 2021
Short summary
Short summary
Abrasion of sedimentary particles is widely associated with mutual collisions. Utilizing results of individual, geometric abrasion theory and techniques adopted in statistical physics, a new model for predicting the collective mass evolution of large numbers of particles is introduced. Our model uncovers a startling fundamental feature of collective particle dynamics: collisional abrasion may either focus size distributions or it may act in the opposite direction by dispersing the distribution.
Richard Barnes, Kerry L. Callaghan, and Andrew D. Wickert
Earth Surf. Dynam., 9, 105–121, https://doi.org/10.5194/esurf-9-105-2021, https://doi.org/10.5194/esurf-9-105-2021, 2021
Short summary
Short summary
Existing ways of modeling the flow of water amongst landscape depressions such as swamps and lakes take a long time to run. However, as our previous work explains, depressions can be quickly organized into a data structure – the depression hierarchy. This paper explains how the depression hierarchy can be used to quickly simulate the realistic filling of depressions including how they spill over into each other and, if they become full enough, how they merge into one another.
Joel Mohren, Steven A. Binnie, Gregor M. Rink, Katharina Knödgen, Carlos Miranda, Nora Tilly, and Tibor J. Dunai
Earth Surf. Dynam., 8, 995–1020, https://doi.org/10.5194/esurf-8-995-2020, https://doi.org/10.5194/esurf-8-995-2020, 2020
Short summary
Short summary
In this study, we comprehensively test a method to derive soil densities under fieldwork conditions. The method is mainly based on images taken from consumer-grade cameras. The obtained soil/sediment densities reflect
truevalues by generally > 95 %, even if a smartphone is used for imaging. All computing steps can be conducted using freeware programs. Soil density is an important variable in the analysis of terrestrial cosmogenic nuclides, for example to infer long-term soil production rates.
Mariela Perignon, Jordan Adams, Irina Overeem, and Paola Passalacqua
Earth Surf. Dynam., 8, 809–824, https://doi.org/10.5194/esurf-8-809-2020, https://doi.org/10.5194/esurf-8-809-2020, 2020
Short summary
Short summary
We propose a machine learning approach for the classification and analysis of large delta systems. The approach uses remotely sensed data, channel network extraction, and the analysis of 10 metrics to identify clusters of islands with similar characteristics. The 12 clusters are grouped in six main classes related to morphological processes acting on the system. The approach allows us to identify spatial patterns in large river deltas to inform modeling and the collection of field observations.
Johannes Albert van Hateren, Unze van Buuren, Sebastiaan Martinus Arens, Ronald Theodorus van Balen, and Maarten Arnoud Prins
Earth Surf. Dynam., 8, 527–553, https://doi.org/10.5194/esurf-8-527-2020, https://doi.org/10.5194/esurf-8-527-2020, 2020
Short summary
Short summary
In this paper, we introduce a new technique that can be used to identify how sediments were transported to their place of deposition (transport mode). The traditional method is based on the size of sediment grains, ours on the size and the shape. A test of the method on windblown sediments indicates that it can be used to identify the transport mode with less ambiguity, and therefore it improves our ability to extract information, such as climate from the past, from sediment deposits.
Taylor Smith, Aljoscha Rheinwalt, and Bodo Bookhagen
Earth Surf. Dynam., 7, 475–489, https://doi.org/10.5194/esurf-7-475-2019, https://doi.org/10.5194/esurf-7-475-2019, 2019
Short summary
Short summary
Representing the surface of the Earth on an equally spaced grid leads to errors and uncertainties in derived slope and aspect. Using synthetic data, we develop a quality metric that can be used to compare the uncertainties in different datasets. We then apply this method to a real-world lidar dataset, and find that 1 m data have larger error bounds than lower-resolution data. The highest data resolution is not always the best choice – it is important to consider the quality of the data.
Matthias Meyer, Samuel Weber, Jan Beutel, and Lothar Thiele
Earth Surf. Dynam., 7, 171–190, https://doi.org/10.5194/esurf-7-171-2019, https://doi.org/10.5194/esurf-7-171-2019, 2019
Short summary
Short summary
Monitoring rock slopes for a long time helps to understand the impact of climate change on the alpine environment. Measurements of seismic signals are often affected by external influences, e.g., unwanted anthropogenic noise. In the presented work, these influences are automatically identified and removed to enable proper geoscientific analysis. The methods presented are based on machine learning and intentionally kept generic so that they can be equally applied in other (more generic) settings.
Christian Gruber, Sergei Rudenko, Andreas Groh, Dimitrios Ampatzidis, and Elisa Fagiolini
Earth Surf. Dynam., 6, 1203–1218, https://doi.org/10.5194/esurf-6-1203-2018, https://doi.org/10.5194/esurf-6-1203-2018, 2018
Short summary
Short summary
By using a set of evaluation methods involving GPS, ICESat, hydrological modelling and altimetry satellite orbits, we show that the novel radial basis function (RBF) processing technique can be used for processing the Gravity Recovery and Climate Experiment (GRACE) data yielding global gravity field models which fit independent reference values at the same level as commonly accepted global geopotential models based on spherical harmonics.
Michael Dietze
Earth Surf. Dynam., 6, 669–686, https://doi.org/10.5194/esurf-6-669-2018, https://doi.org/10.5194/esurf-6-669-2018, 2018
Short summary
Short summary
Environmental seismology is the study of the seismic signals emitted by Earth surface processes. This emerging research field is at the intersection of many Earth science disciplines. The overarching scope requires free integrative software that is accepted across scientific disciplines, such as R. The article introduces the R package "eseis" and illustrates its conceptual structure, available functions, and worked examples.
Eric Laloy, Koen Beerten, Veerle Vanacker, Marcus Christl, Bart Rogiers, and Laurent Wouters
Earth Surf. Dynam., 5, 331–345, https://doi.org/10.5194/esurf-5-331-2017, https://doi.org/10.5194/esurf-5-331-2017, 2017
Short summary
Short summary
Over very long timescales, 100 000 years or more, landscapes may drastically change. Sediments preserved in these landscapes have a cosmogenic radionuclide inventory that tell us when and how fast such changes took place. In this paper, we provide first evidence of an elevated long-term erosion rate of the northwestern Campine Plateau (lowland Europe), which can be explained by the loose nature of the subsoil.
Laurent Fouinat, Pierre Sabatier, Jérôme Poulenard, Jean-Louis Reyss, Xavier Montet, and Fabien Arnaud
Earth Surf. Dynam., 5, 199–209, https://doi.org/10.5194/esurf-5-199-2017, https://doi.org/10.5194/esurf-5-199-2017, 2017
Short summary
Short summary
This study focuses on the creation of a novel CT scan methodology at the crossroads between medical imagery and earth sciences. Using specific density signatures, pebbles and/or organic matter characterizing wet avalanche deposits can be quantified in lake sediments. Starting from AD 1880, we were able to identify eight periods of higher avalanche activity from sediment cores. The use of CT scans, alongside existing approaches, opens up new possibilities in a wide variety of geoscience studies.
Daniel E. J. Hobley, Jordan M. Adams, Sai Siddhartha Nudurupati, Eric W. H. Hutton, Nicole M. Gasparini, Erkan Istanbulluoglu, and Gregory E. Tucker
Earth Surf. Dynam., 5, 21–46, https://doi.org/10.5194/esurf-5-21-2017, https://doi.org/10.5194/esurf-5-21-2017, 2017
Short summary
Short summary
Many geoscientists use computer models to understand changes in the Earth's system. However, typically each scientist will build their own model from scratch. This paper describes Landlab, a new piece of open-source software designed to simplify creation and use of models of the Earth's surface. It provides off-the-shelf tools to work with models more efficiently, with less duplication of effort. The paper explains and justifies how Landlab works, and describes some models built with it.
Andrew Valentine and Lara Kalnins
Earth Surf. Dynam., 4, 445–460, https://doi.org/10.5194/esurf-4-445-2016, https://doi.org/10.5194/esurf-4-445-2016, 2016
Short summary
Short summary
Learning algorithms are powerful tools for understanding and working with large data sets, particularly in situations where any underlying physical models may be complex and poorly understood. Such situations are common in geomorphology. We provide an accessible overview of the various approaches that fall under the umbrella of "learning algorithms", discuss some potential applications within geomorphometry and/or geomorphology, and offer advice on practical considerations.
E. Pohl, M. Knoche, R. Gloaguen, C. Andermann, and P. Krause
Earth Surf. Dynam., 3, 333–362, https://doi.org/10.5194/esurf-3-333-2015, https://doi.org/10.5194/esurf-3-333-2015, 2015
Short summary
Short summary
A semi-distributed hydrological model is used to analyse the hydrological cycle of a glaciated high-mountain catchment in the Pamirs.
We overcome data scarcity by utilising various raster data sets as meteorological input. Temperature in combination with the amount of snow provided in winter play the key role in the annual cycle.
This implies that expected Earth surface processes along precipitation and altitude gradients differ substantially.
T. Croissant and J. Braun
Earth Surf. Dynam., 2, 155–166, https://doi.org/10.5194/esurf-2-155-2014, https://doi.org/10.5194/esurf-2-155-2014, 2014
Cited articles
Angulo-Martínez, M., López-Vicente, M., Vicente-Serrano, S. M., and Beguería, S.: Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain), Hydrol. Earth Syst. Sci., 13, 1907–1920, https://doi.org/10.5194/hess-13-1907-2009, 2009.
Ballabio, C., Borrelli, P., Spinoni, J., Meusburger, K., Michaelides, S., Beguería, S., Klik, A., Petan, S., Janeček, M., Olsen, P., Aalto, J., Lakatos, M., Rymszewicz, A., Dumitrescu, A., Tadić, M. P., Diodato, N., Kostalova, J., Rousseva, S., Banasik, K., Alewell, C., and Panagos, P.: Mapping monthly rainfall erosivity in Europe, Sci. Total Environ., 579, 1298–1315, https://doi.org/10.1016/j.scitotenv.2016.11.123, 2017.
Bezak, N., Ballabio, C., Mikoš, M., Petan, S., Borreli, P., and Panagos, P.: Reconstruction of past rainfall erosivity and trend detection based on the REDES database and reanalysis rainfall, J. Hydrol., 590, 125372, https://doi.org/10.1016/j.jhydrol.2020.125372, 2020.
Bezak, N., Borrelli, P., and Panagos, P.: A first assessment of rainfall erosivity synchrony scale at pan-European scale, Catena, 198, 105060, https://doi.org/10.1016/j.catena.2020.105060, 2021a.
Bezak, N., Mikoš, M., Borrelli, P., Liakos, L., and Panagos, P.: An in-depth statistical analysis of the rainstorms erosivity in Europe, Catena, 206, 105577, https://doi.org/10.1016/j.catena.2021.105577, 2021b.
Bezak, N., Petan, S., and Mikoš, M.: Spatial and temporal variability in rainfall erosivity under Alpine climate: a Slovenian case study using optical disdrometer data, Front. Environ. Sci., 423, 735492, https://doi.org/10.3389/fenvs.2021.735492, 2021c.
Bezak, N., Borrelli, P., and Panagos, P.: Exploring the possible role of satellite-based rainfall data in estimating inter- and intra-annual global rainfall erosivity, Hydrol. Earth Syst. Sci., 26, 1907–1924, https://doi.org/10.5194/hess-26-1907-2022, 2022.
Breinl, K. and Di Baldassarre, G.: Space-time disaggregation of precipitation and temperature across different climates and spatial scales, Journal of Hydrology: Regional Studies, 21, 126–146, 2019.
Brown, L. C. and Foster, G. R.: Storm Erosivity Using Idealized Intensity Distributions, Am. Soc. Agric. Biol. Eng., 30, 0379–0386, https://doi.org/10.13031/2013.31957, 1987.
Callau Poduje, A. C. and Haberlandt, U.: Short time step continuous rainfall modeling and simulation of extreme events, J. Hydrol., 552, 182–197, 2017.
CDC: Climate Data Center, https://www.dwd.de/EN/climate_environment/cdc/cdc_node_en.html, last access: 15 December 2020.
De Oliveira, J. P. B., Cecilio, R. A., Pruski, F. F., Zanetti, S. S., and Moreira, M. C.: Assessing the use of rainfall synthetic series to estimate rainfall erosivity in Brazil, Catena, 171, 327–336, 2018.
Dunkerley, D. L.: Rainfall intensity bursts and the erosion of soils: an analysis highlighting the need for high temporal resolution rainfall data for research under current and future climates, Earth Surf. Dynam., 7, 345–360, https://doi.org/10.5194/esurf-7-345-2019, 2019.
Eekhout, J. P. C., Millares-Valenzuela, A., Martinez-Salvador, A., Garcia-Lorenzo, R., Perez-Cutillas, P., Conesa-Garcia, V., and de Vente, J.: A process-based soil erosion model ensemble to assess model uncertainty in climate-change impact assessments, Land Degrad. Dev., 32, 2409–2422, 2021.
Goovaerts, P.: Geostatistics for Natural Resources Evaluation, Oxford University Press, 483 pp., ISBN 9780195115383, 1997.
Haas, J., Schack-Kirchner, H., and Lang, F.: Adjustment of a weather generator to represent actual rain erosivity in the northern Black Forest – Germany, Catena, 163, 42–53, 2018.
Haberlandt, U., Ebner von Eschenbach, A.-D., and Buchwald, I.: A space-time hybrid hourly rainfall model for derived flood frequency analysis, Hydrol. Earth Syst. Sci., 12, 1353–1367, https://doi.org/10.5194/hess-12-1353-2008, 2008.
Isaaks, E. H. and Srivastava, R. M.: An Introduction to Applied Geostatistics, Oxford University Press, 592 pp., ISBN 9780195050134, 1990.
Jebari, S., Berndtsson, R., Olsson, J., and Bahri, A.: Soil erosion estimation based on rainfall disaggregation, J. Hydrol., 436–437, 102–110, 2012.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World Map of the Köppen-Geiger climate classification updated, Meteorol. Z., 15, 259–263, https://doi.org/10.1127/0941-2948/2006/0130, 2006.
Lobo, G. P., Frankenberger, J. R., Flanagan, D. C., and Bonilla, C. A.: Evaluation and improvement of the CLIGEN model for storm and rainfall erosivity generation in Central Chile, Catena, 127, 206–213, 2015.
Meyer, C. R., Renschler, C. S., and Vining, R. C.: Implementing quality control on a random number stream to improve a stochastic weather generator, Hydrol. Process., 22, 1069–1079, 2008.
Molnar, P. and Burlando, P.: Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model, Atmos. Res., 77, 137–151, 2005.
Müller, H. and Haberlandt, U.: Temporal rainfall disaggregation using a multiplicative cascade model for spatial application in urban hydrology, in: Rainfall in urban and natural Systems, Proceedings of the 10th International Workshop on Precipitation in Urban Areas (UrbanRain15), edited by: Molnar, P. and Peleg, N., Pontresina, 1–5 December 2015, Paper UR15-43, ETH-Zürich, Institute of Environmental Engineering, https://doi.org/10.3929/ethz-a-010549004, 2015.
Müller, H. and Haberlandt, U.: Temporal rainfall disaggregation using a multiplicative cascade model for spatial application in urban hydrology, J. Hydrol., 556, 847–864, https://doi.org/10.1016/j.jhydrol.2016.01.031, 2018.
Müller-Thomy, H.: Improving the autocorrelation in disaggregated time series for urban hydrological applications, in: 11th Workshop on Precipitation in Urban Areas (UrbanRain18), edited by: Peleg, N. and Molnar, P., 5–7 December 2018, Pontresina, Switzerland, 75–76, https://doi.org/10.3929/ethz-b-000347485, 2019.
Müller-Thomy, H.: Temporal rainfall disaggregation using a micro-canonical cascade model: possibilities to improve the autocorrelation, Hydrol. Earth Syst. Sci., 24, 169–188, https://doi.org/10.5194/hess-24-169-2020, 2020.
NLWKN: Globaler Klimawandel – Wasserwirtschaftliche Folgen für das Binnenland (KliBiW), Abschlussbericht Phase V, Niedersächsischer Landesbetrieb für Wasserwirtschaft, Küsten- und Naturschutz, Norden, 2019.
Onof, C. and Wang, L.-P.: Modelling rainfall with a Bartlett–Lewis process: new developments, Hydrol. Earth Syst. Sci., 24, 2791–2815, https://doi.org/10.5194/hess-24-2791-2020, 2020.
Onof, C., Chandler, R. E., Kakou, A., Northrop, P., Wheater, H. S., and Isham, V.: Rainfall modelling using Poisson-cluster processes: A review of developments, Stoch. Env. Res. Risk A., 14, 384–411, 2000.
Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., Tadić, M. P., Michaelides, S., Hrabalíková, M., Olsen, P., Aalto, J., Lakatos, M., Rymszewicz, A., Dumitrescu, A., Beguería, S., and Alewell, C.: Rainfall erosivity in Europe, Sci. Total Environ., 511, 801–814, https://doi.org/10.1016/j.scitotenv.2015.01.008, 2015.
Panagos, P., Ballabio, C., Borrelli, P., and Meusburger, K.: Spatio-temporal analysis of rainfall erosivity and erosivity density in Greece, Catena, 137, 161–172, 2016.
Panagos, P., Borrelli, P., Meusburger, K., Yu, B., Klik, A., Lim, K. J., Yang, J. E., Ni, J., Miao, C., Chattopadhyay, N., Hamidreza Sadeghi, S., Hazbavi, Z., Zabihi, M., Larionov, G. A., Krasnov, S. F., Gorobets, A. V., Levi, Y., Erpul, G., Birkel, C., Hoyos, N., Naipal, V., Oliveira, P. T. S., Bonilla, C. A., Meddi, M., Nel, W., Al Dashti, H., Boni, M., Diodato, N., Van Oost, K., Nearing, M., and Ballabio, C.: Global rainfall erosivity assessment based on high-temporal resolution rainfall records, Nat. Sci. Rep., 7, 4175, https://doi.org/10.1038/s41598-017-04282-8, 2017.
Pebesma, E. J.: Multivariable geostatistics in S: the gstat package, Comput. Geosci., 30, 683–691, 2004.
Peleg, N., Fatichi, S. Paschalis, A., Molnar, P., and Burlando, P.: An advanced stochastic weather generator for simulating 2-D high-resolution climate variables, J. Adv. Model. Earth Sy., 9, 1595–1627, 2017.
Peleg, N., Skinner, C., Ramirez, J. A., and Molnar, P.: Rainfall spatial-heterogeneity accelerates landscape evolution processes, Geomorphology, 390, 107863, https://doi.org/10.1016/j.geomorph.2021.107863, 2021.
Petan, S., Rusjan, S., Vidmar, A., and Mikoš, M.: The rainfall kinetic energy-intensity relationship for rainfall erosivity estimation in the Mediterranean part of Slovenia, J. Hydrol., 391, 314–321, 2010.
Petek, M., Mikoš, M., and Bezak, N.: Rainfall erosivity in Slovenia: Sensitivity estimation and trend detection, Environ. Res., 167, 528–535, 2018.
Pohle, I., Niebisch, M., Müller, H., Schümberg, S., Zha, T., Maurer, T., and Hinz, C.: Coupling Poisson rectangular pulse and multiplicative micro-canonical random cascade models to generate sub-daily precipitation time series, J. Hydrol., 562, 50–70, 2018.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org/ (last access: 4 October 2017), 2015.
Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., and Yoder, D. C.: Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE), Agricultural Handbook no. 703, USDA ARS, Washington, DC, 65–100, ISBN 0-16-048938-5, 1997.
Thiessen, A. H.: Precipitation averages for large areas, Mon. Weather Rev., 39, 1082–1809, 1911.
Vandenberghe, S., Verhoest, N. E. C., Onof, C., and De Baets, B.: A comparative copula-based bivariate frequency analysis of observed and simulated storm events: a case study on Bartlett-Lewis modeled rainfall, Water Resour. Res., 47, W07529, https://doi.org/10.1029/2009WR008388, 2011.
Vernieuwe, H., Vandenberghe, S., De Baets, B., and Verhoest, N. E. C.: A continuous rainfall model based on vine copulas, Hydrol. Earth Syst. Sci., 19, 2685–2699, https://doi.org/10.5194/hess-19-2685-2015, 2015.
Wang, W., Flanagan, D. C., Yin, S., and Yu, B.: Assessment of CLIGEN precipitation and storm pattern generation in China, Catena, 69, 96–106, 2018.
Short summary
Erosion is a threat for soils with rainfall as the driving force. The annual rainfall erosivity factor quantifies rainfall impact by analysing high-resolution rainfall time series (~ 5 min). Due to a lack of measuring stations, alternatives for its estimation are analysed in this study. The best results are obtained for regionalisation of the erosivity factor itself. However, the identified minimum of 60-year time series length suggests using rainfall generators as in this study as well.
Erosion is a threat for soils with rainfall as the driving force. The annual rainfall erosivity...
