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LISFLOOD: a GIS‐based distributed model for river basin scale water balance and flood simulation

Van Der Knijff, J. M., Younis, J., De Roo, A. P. J.·2010·International Journal of Geographical Information Science

Abstract

In this paper we describe the spatially distributed LISFLOOD model, which is a hydrological model specifically developed for the simulation of hydrological processes in large European river basins. The model was designed to make the best possible use of existing data sets on soils, land cover, topography and meteorology. We give a detailed description of the simulation of hydrological processes in LISFLOOD, and discuss how the model is parameterized. We also describe how the model was implemented technically using a combination of the PCRaster GIS system and the Python programming language, and discuss the management of in‐ and output data. Finally, we review some recent applications of LISFLOOD, and we present a case study for the Elbe river.

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Crossref · 10.1080/13658810802549154

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Metadata

Authors
Van Der Knijff, J. M., Younis, J., & De Roo, A. P. J.
Venue
International Journal of Geographical Information Science
Published
2010-02
Volume
24
Issue
2
Pages
189-212
ISSN
  • 0269-3798 (ISSN-L)
  • 1365-8816
  • 1362-3087
OpenAlex
W1981410107
Cited by
637
References
2
FWCI
12.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: LISFLOOD: a GIS‐based distributed model for river basin scale water balance and flood simulation. https://app.cochat.ai/papers/10.1080/13658810802549154
The paper
Van Der Knijff, J. M., Younis, J., & De Roo, A. P. J. (2010). LISFLOOD: a GIS‐based distributed model for river basin scale water balance and flood simulation. International Journal of Geographical Information Science. https://doi.org/10.1080/13658810802549154

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.