Assessing the Effect of Streamflow Estimation at Potential Station Locations In Entropy-Based Hydrometric Network Design

7 pages•Published: September 20, 2018

Jongho Keum, Paulin Coulibaly and Alain Pietroniro

Abstract

Having an efficient hydrometric network is important not only for successful water resources management but also for dealing with the economic cost of maintaining the network. One of the challenging tasks is to have a reliable dataset at candidate locations of additional monitoring stations. While many have applied regionalization methods, such as spatial interpolation, this study introduced a spatially distributed hydrologic model for generating data at potential locations. The determined optimal networks are compared with those from the use of spatial interpolation. The optimal networks are also evaluated using the outcome of transinformation analysis. The results showed that the optimal results using a spatially distributed model performed better than those using a spatial interpolation method.

Keyphrases: hydrologic model, hydrometric network, information theory, network design, shannon entropy, spatial interpolation

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1048-1054.

Links:	https://easychair.org/publications/paper/tB3k
	https://doi.org/10.29007/xlv7

BibTeX entry

@inproceedings{HIC2018:Assessing_Effect_Streamflow_Estimation,
  author    = {Jongho Keum and Paulin Coulibaly and Alain Pietroniro},
  title     = {Assessing the Effect of Streamflow Estimation at Potential Station Locations In Entropy-Based Hydrometric Network Design},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/tB3k},
  doi       = {10.29007/xlv7},
  pages     = {1048-1054},
  year      = {2018}}

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