Markus Casper

Universität Trier

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Oliver Gronz

Universität Trier

Rita Ley

Universität Trier

Manuel Seeger

Universität Trier

Philipp Reiter

Forschungsanstalt für Waldökologie und Forstwirtschaft Rheinland-Pfalz

H. Hellebrand

Universität Trier

Oliver Gutjahr

Max Planck Institute for Meteorology

Günther Heinemann

Universität Trier

Johannes B. Ries

Universität Trier

V. Butzen

Universität Trier

Hadis Mohajerani

Universität Trier

Cooperative Institutions

Universität Trier

Norsk Hydro (Germany)

Karlsruhe Institute of Technology

Trier University of Applied Sciences

University of Basel

Wageningen University & Research

University of Freiburg

Universidad de Málaga

Delft University of Technology

University of Tübingen

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

The potential of Smartstone probes in landslide experiments: how to read motion data

Natural hazards and earth system sciences (2020)

J. Bastian Dost Oliver Gronz Markus Casper Andréas Krein

Abstract. Laboratory landslide experiments enable the observation of specific properties of these natural hazards. However, these observations are limited by traditional techniques: frequently used high-speed video analysis and wired sensors (e.g. displacement). These techniques lead to the drawback that either only the surface and 2D profiles can be observed or wires confine the motion behaviour. In contrast, an unconfined observation of the total spatiotemporal dynamics of landslides is needed for an adequate understanding of these natural hazards. The present study introduces an autonomous and wireless probe to characterize motion features of single clasts within laboratory-scale landslides. The Smartstone probe is based on an inertial measurement unit (IMU) and records acceleration and rotation at a sampling rate of 100 Hz. The recording ranges are ±16 g (accelerometer) and ±2000∘ s−1 (gyroscope). The plastic tube housing is 55 mm long with a diameter of 10 mm. The probe is controlled, and data are read out via active radio frequency identification (active RFID) technology. Due to this technique, the probe works under low-power conditions, enabling the use of small button cell batteries and minimizing its size. Using the Smartstone probe, the motion of single clasts (gravel size, median particle diameter d50 of 42 mm) within approx. 520 kg of a uniformly graded pebble material was observed in a laboratory experiment. Single pebbles were equipped with probes and placed embedded and superficially in or on the material. In a first analysis step, the data of one pebble are interpreted qualitatively, allowing for the determination of different transport modes, such as translation, rotation and saltation. In a second step, the motion is quantified by means of derived movement characteristics: the analysed pebble moves mainly in the vertical direction during the first motion phase with a maximal vertical velocity of approx. 1.7 m s−1. A strong acceleration peak of approx. 36 m s−2 is interpreted as a pronounced hit and leads to a complex rotational-motion pattern. In a third step, displacement is derived and amounts to approx. 1.0 m in the vertical direction. The deviation compared to laser distance measurements was approx. −10 %. Furthermore, a full 3D spatiotemporal trajectory of the pebble is reconstructed and visualized supporting the interpretations. Finally, it is demonstrated that multiple pebbles can be analysed simultaneously within one experiment. Compared to other observation methods Smartstone probes allow for the quantification of internal movement characteristics and, consequently, a motion sampling in landslide experiments.

Pebble

10.5194/nhess-20-3501-2020

Cite

Citations (16)

Smartstone probe data of a landslide experiment

Zenodo (CERN European Organization for Nuclear Research) (2020)

J. Bastian Dost Oliver Gronz Markus Casper Andréas Krein

The files contain data of four Smartstone probes recorded during a landslide experiment. The MATLAB data files are named after the particular pebbles (1 to 4), which were equipped with the probes. The files contain acceleration (acc) and gyroscope (gyr) data as well as a time code (time).

10.5281/zenodo.4316597

Cite

Citations (1)

Data driven model generation based on computational intelligence

EGUGA (2010)

Peter Gemmar Oliver Gronz Christophe Faust Markus Casper

Source

Cite

Citations (0)

Analysis of projected hydrological behavior of catchments based on signature indices

Hydrology and earth system sciences (2012)

Markus Casper Gayane Grigoryan Oliver Gronz Oliver Gutjahr Günther Heinemann

Abstract. To precisely map the changes in hydrologic response of catchments (e.g. water balance, reactivity or extremes), we need sensitive and interpretable indicators. In this study we defined nine hydrologically meaningful signature indices: five indices were sampled on the flow duration curve, four indices were closely linked to the distribution of event runoff coefficients. We applied these signature indices to the output from a hydrologic catchment model for three different catchments located in the Nahe basin (Western Germany) to detect differences in runoff behavior resulting from different meteorological input data. The models were driven by measured and simulated (COSMO-CLM) meteorological data. It could be shown that the application of signature indices is a very sensitive tool to assess differences in simulated runoff behavior resulting from climatic data sets of different sources. Specifically, the selected signature indices allow assessing changes in water balance, vertical water distribution, reactivity, seasonality and runoff generation. These indices showed that the hydrological model is very sensitive to biases in mean and spatio-temporal distribution of precipitation and temperature because it acts as a filter for the meteorological input. Besides model calibration and model structural deficits, we found that bias correction of temperature fields and further adjustment of bias correction of precipitation fields is absolutely essential. We conclude that signature indices can act as indirect "efficiency measures" or "similarity measures" for output from regional or local climate models.

Water balance

Signature (topology)

10.5194/hess-16-409-2012

Cite

Citations (32)

Do sub-annual bias corrections improve the quantile mapping results for daily precipitation?

EGU General Assembly Conference Abstracts (2016)

Philipp Reiter Oliver Gutjahr Lukas Schefczyk Günther Heinemann Markus Casper

Quantile

Source

Cite

Citations (0)

Catchment classification by runoff behaviour with self-organizing maps (SOM)

Hydrology and earth system sciences (2011)

Rita Ley Markus Casper H. Hellebrand Ralf Merz

Abstract. Catchments show a wide range of response behaviour, even if they are adjacent. For many purposes it is necessary to characterise and classify them, e.g. for regionalisation, prediction in ungauged catchments, model parameterisation. In this study, we investigate hydrological similarity of catchments with respect to their response behaviour. We analyse more than 8200 event runoff coefficients (ERCs) and flow duration curves of 53 gauged catchments in Rhineland-Palatinate, Germany, for the period from 1993 to 2008, covering a huge variability of weather and runoff conditions. The spatio-temporal variability of event-runoff coefficients and flow duration curves are assumed to represent how different catchments "transform" rainfall into runoff. From the runoff coefficients and flow duration curves we derive 12 signature indices describing various aspects of catchment response behaviour to characterise each catchment. Hydrological similarity of catchments is defined by high similarities of their indices. We identify, analyse and describe hydrologically similar catchments by cluster analysis using Self-Organizing Maps (SOM). As a result of the cluster analysis we get five clusters of similarly behaving catchments where each cluster represents one differentiated class of catchments. As catchment response behaviour is supposed to be dependent on its physiographic and climatic characteristics, we compare groups of catchments clustered by response behaviour with clusters of catchments based on catchment properties. Results show an overlap of 67% between these two pools of clustered catchments which can be improved using the topologic correctness of SOMs.

Regionalisation

Catchment hydrology

10.5194/hess-15-2947-2011

Cite

Citations (124)

Towards model evaluation and identification using Self-Organizing Maps

Hydrology and earth system sciences (2008)

M. Herbst Markus Casper

Abstract. The reduction of information contained in model time series through the use of aggregating statistical performance measures is very high compared to the amount of information that one would like to draw from it for model identification and calibration purposes. It has been readily shown that this loss imposes important limitations on model identification and -diagnostics and thus constitutes an element of the overall model uncertainty. In this contribution we present an approach using a Self-Organizing Map (SOM) to circumvent the identifiability problem induced by the low discriminatory power of aggregating performance measures. Instead, a Self-Organizing Map is used to differentiate the spectrum of model realizations, obtained from Monte-Carlo simulations with a distributed conceptual watershed model, based on the recognition of different patterns in time series. Further, the SOM is used instead of a classical optimization algorithm to identify those model realizations among the Monte-Carlo simulation results that most closely approximate the pattern of the measured discharge time series. The results are analyzed and compared with the manually calibrated model as well as with the results of the Shuffled Complex Evolution algorithm (SCE-UA). In our study the latter slightly outperformed the SOM results. The SOM method, however, yields a set of equivalent model parameterizations and therefore also allows for confining the parameter space to a region that closely represents a measured data set. This particular feature renders the SOM potentially useful for future model identification applications.

Identifiability

Identification

Feature (linguistics)

Self-organizing map

Data set

10.5194/hess-12-657-2008

Cite

Citations (30)

Identifying State Variables in Multivariate Hydrological Time Series Using Time Series Knowledge Mining

Oliver Gronz Markus Casper Peter Gemmar

Source

Cite

Citations (0)

Is Catchment Classification Possible by Means of Multiple Model Structures? A Case Study Based on 99 Catchments in Germany

Hydrology (2016)

Rita Ley H. Hellebrand Markus Casper Fabrizio Fenicia

This study investigates how the performance of a set of models depends on the catchments to which these models are applied. It examines (i) whether it is possible to identify a single best model for each of the catchments, or whether results are dominated by equifinality; and (ii) whether the ranking of model performance can be related to a set of predictors, such as climate and catchment characteristics. In order to explore these questions, we applied 12 model structures to 99 catchments in Germany, ranging in size from 10 km2 to 1826 km2. We examined model performance in terms of streamflow predictions, based on various indices. Our results indicate that for some catchments many structures perform equally well, whereas for other catchments a single structure clearly outperforms the others. We could not identify clear relationships between relative model performance and catchment characteristics. This result led us to conclude that for the spatial scales considered, it is difficult to base the selection of a lumped conceptual model based on a priori assessment, and we recommend a posteriori selection based on model comparisons.

Equifinality

Conceptual model

Catchment hydrology

10.3390/hydrology3020022

Cite

Citations (8)

Does applying quantile mapping to subsamples improve the bias correction of daily precipitation?

International Journal of Climatology (2017)

Philipp Reiter Oliver Gutjahr Lukas Schefczyk Günther Heinemann Markus Casper

ABSTRACT Quantile mapping (QM) is routinely applied in many climate change impact studies for the bias correction (BC) of daily precipitation data. It corrects the complete distribution, but does not correct for errors in the annual cycle. Therefore, QM is often applied separately to temporal subsamples of the data (e.g. each calendar month), which reduces the calibration sample size. The question arises whether this sample size reduction negates the benefit from applying QM to temporal subsamples. We applied four QM methods in a cross‐validation approach to 40 years of daily precipitation data from 10 regional climate model (RCM) hindcast runs, without and with (semi‐annual, seasonal, and monthly) subsampling. QM subsampling improved the BC of daily RCM precipitation; less distinct for independent data but considerably for the calibration data. The optimal subsampling timescale for the correction of independent data depended on the chosen QM method and ranged between semi‐annual and monthly. Overall, a sub‐annual QM improves the forcing for climate change impact studies and thus their reliability.

Quantile

Hindcast

Forcing (mathematics)

10.1002/joc.5283

Cite

Citations (64)