Zobrazeno 1 - 10
of 70
pro vyhledávání: '"U Ehret"'
Publikováno v:
Hydrology and Earth System Sciences, Vol 28, Pp 2705-2719 (2024)
Hydrological hybrid models have been proposed as an option to combine the enhanced performance of deep learning methods with the interpretability of process-based models. Among the various hybrid methods available, the dynamic parameterization of con
Externí odkaz:
https://doaj.org/article/e6ad5e741af146b18492acc2fd23231c
Publikováno v:
Hydrology and Earth System Sciences, Vol 27, Pp 2591-2605 (2023)
We propose and provide a proof of concept of a method to analyse, classify and compare dynamical systems of arbitrary dimensions by the two key features uncertainty and complexity. It starts by subdividing the system's time trajectory into a number o
Externí odkaz:
https://doaj.org/article/094ddc9d99654eadb7adb90a76f96625
Autor:
P. Ludwig, F. Ehmele, M. J. Franca, S. Mohr, A. Caldas-Alvarez, J. E. Daniell, U. Ehret, H. Feldmann, M. Hundhausen, P. Knippertz, K. Küpfer, M. Kunz, B. Mühr, J. G. Pinto, J. Quinting, A. M. Schäfer, F. Seidel, C. Wisotzky
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 23, Pp 1287-1311 (2023)
Heavy precipitation over western Germany and neighboring countries in July 2021 led to widespread floods, with the Ahr and Erft river catchments being particularly affected. Following the event characterization and process analysis in Part 1, here we
Externí odkaz:
https://doaj.org/article/2758b66a9ad44661b24be85be3163797
Autor:
S. Mohr, U. Ehret, M. Kunz, P. Ludwig, A. Caldas-Alvarez, J. E. Daniell, F. Ehmele, H. Feldmann, M. J. Franca, C. Gattke, M. Hundhausen, P. Knippertz, K. Küpfer, B. Mühr, J. G. Pinto, J. Quinting, A. M. Schäfer, M. Scheibel, F. Seidel, C. Wisotzky
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 23, Pp 525-551 (2023)
The July 2021 flood in central Europe was one of the five costliest disasters in Europe in the last half century, with an estimated total damage of EUR 32 billion. The aim of this study is to analyze and assess the flood within an interdisciplinary a
Externí odkaz:
https://doaj.org/article/f318fb3ac97e4ef8ae9aa6cc701861ce
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 1103-1115 (2021)
One of the main objectives of the scientific enterprise is the development of well-performing yet parsimonious models for all natural phenomena and systems. In the 21st century, scientists usually represent their models, hypotheses, and experimental
Externí odkaz:
https://doaj.org/article/70dfa8163a3948f8966ffb7fdd2c34bb
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 4389-4411 (2020)
In this paper we propose adaptive clustering as a new method for reducing the computational efforts of distributed modelling. It consists of identifying similar-acting model elements during runtime, clustering them, running the model for just a few r
Externí odkaz:
https://doaj.org/article/622b48dfa3d5458dae1887c053dd5de2
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 4523-4540 (2020)
Interpolation of spatial data has been regarded in many different forms, varying from deterministic to stochastic, parametric to nonparametric, and purely data-driven to geostatistical methods. In this study, we propose a nonparametric interpolator,
Externí odkaz:
https://doaj.org/article/d50bb6a9c07f4b1eba42ec28b30740a7
Publikováno v:
Hydrology and Earth System Sciences, Vol 23, Pp 3807-3821 (2019)
Surface topography is an important source of information about the functioning and form of a hydrological landscape. Because of its key role in explaining hydrological processes and structures, and also because of its wide availability at good resolu
Externí odkaz:
https://doaj.org/article/038b7e3d5d734215b213c4ae3902747b
Publikováno v:
Hydrology and Earth System Sciences, Vol 23, Pp 3711-3733 (2019)
In this study we propose and demonstrate a data-driven approach in an “information-theoretic” framework to quantitatively estimate precipitation. In this context, predictive relations are expressed by empirical discrete probability distributions
Externí odkaz:
https://doaj.org/article/35b3c60b9c2949fba106ec286a8d5e2b
Publikováno v:
Hydrology and Earth System Sciences, Vol 23, Pp 1015-1034 (2019)
In this study, we propose a data-driven approach for automatically identifying rainfall-runoff events in discharge time series. The core of the concept is to construct and apply discrete multivariate probability distributions to obtain probabilistic
Externí odkaz:
https://doaj.org/article/69e4ba0ab5bc427e9b77f84623fa3f64