H
Harald Klempe
Researcher at University College of Southeast Norway
Publications - 6
Citations - 1016
Harald Klempe is an academic researcher from University College of Southeast Norway. The author has contributed to research in topics: Landslide & Aquifer. The author has an hindex of 4, co-authored 5 publications receiving 744 citations. Previous affiliations of Harald Klempe include Telemark University College.
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Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree
TL;DR: This study introduces a framework for training and validation of shallow landslide susceptibility models by using the latest statistical methods and demonstrates the benefit of selecting the optimal machine learning techniques with proper conditioning selection method in shallow landslide susceptible mapping.
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A novel fuzzy K -nearest neighbor inference model with differential evolution for spatial prediction of rainfall-induced shallow landslides in a tropical hilly area using GIS
TL;DR: The fuzzy k-NN model is a promising prediction tool that should be used for susceptibility mapping in landslide-prone areas and performs better than the support vector machines and the J48 decision trees models.
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The hydrogeological and cultural background for two sacred springs, Bø, Telemark County, Norway
TL;DR: Two of the most sacred springs in Norway are located in Bo in Telemark, Southern Norway, and have been surveyed for their sedimentology and hydrology as mentioned in this paper, and both of them have been mapped by drilling, monitoring wells, and ground penetrating radar and analyzed by GIS models.
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Effect of catchment properties and flood generation regime on copula selection for bivariate flood frequency analysis
TL;DR: In this paper, the authors present a study of 27 catchments located throughout Norway, in which they assess whether catchment properties, flood generation processes and flood regime have an effect on the correlation between flood peak and volume and, in turn, on the selection of copulas.
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Regionalisation of the parameters of the rainfall–runoff model PQRUT
TL;DR: In this article, the PQRUT model is used for the analysis of peak flows for which a sub-daily temporal resolution is required, and the results for the weighted regression indicate a decrease in the median Kling-Gupta efficiency from 0.64 to 0.51 for calibration and regionalisation.