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N.C. Van de Giesen
Researcher at Delft University of Technology
Publications - 108
Citations - 3075
N.C. Van de Giesen is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Environmental science & Geology. The author has an hindex of 30, co-authored 91 publications receiving 2679 citations. Previous affiliations of N.C. Van de Giesen include University of Bonn.
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Journal ArticleDOI
A distributed stream temperature model using high resolution temperature observations
Martijn Westhoff,Hubert H. G. Savenije,Wim Luxemburg,Guus S. Stelling,N.C. Van de Giesen,John S. Selker,Laurent Pfister,Stefan Uhlenbrook +7 more
TL;DR: In this article, a DTS (Distributed Temperature Sensing) system with a fiber optic cable of 1500 m was used to measure stream water temperature with 1 m resolution each 2 min.
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Estimation of small reservoir storage capacities in a semi-arid environment: A case study in the Upper East Region of Ghana
TL;DR: In this article, the authors developed a simple method that allows the estimation of reservoir storage volumes as a function of their surface areas, based on an extensive bathymetrical survey that was conducted in the Upper East Region of Ghana.
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Feasibility of soil moisture estimation using passive distributed temperature sensing
Susan C. Steele-Dunne,Martine Rutten,Dominika Krzeminska,Mark B. Hausner,Scott W. Tyler,John S. Selker,Thom Bogaard,N.C. Van de Giesen +7 more
TL;DR: In this paper, a passive soil distributed temperature sensing (DTS) method is introduced as an experimental method of measuring soil moisture on the basis of DTS and several fiberoptic cables in a vertical profile are used as thermal sensors, measuring propagation of temperature changes due to the diurnal cycle.
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Model complexity control for hydrologic prediction
TL;DR: In this paper, the authors compare three model complexity control methods for hydrologic prediction, namely, cross validation (CV), Akaike's information criterion (AIC), and structural risk minimization (SRM).
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Why hydrological predictions should be evaluated using information theory
TL;DR: In this paper, the authors propose to use information theory as the central framework to evaluate predictions and propose that calibration of models representing a hydrological system should be based on information-theoretical scores, because this allows extracting all information from the observations and avoids learning from information that is not there.