Issue |
E3S Web Conf.
Volume 97, 2019
XXII International Scientific Conference “Construction the Formation of Living Environment” (FORM-2019)
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Article Number | 05001 | |
Number of page(s) | 11 | |
Section | Hydrotechnical Construction and Melioration | |
DOI | https://doi.org/10.1051/e3sconf/20199705001 | |
Published online | 29 May 2019 |
GIUH-Nash based runoff prediction for Debarwa catchment in Eritrea
Moscow State University of Civil Engineering, Yaroslavskoe shosse, 26, Moscow, 129337, Russia
* Correspnding author: bahghi2012@gmail.com
Correct assessment of river flow is necessary to resolve a wide range of problems in the management and use of water resources. Recently, research towards the use of geomorphologic instantaneous unit hydrograph (GIUH) coupled with other conceptual models approach for flood prediction from ungauged catchments has been intensified. Widespread accessibility to geographic information system and remotely sensed imagery which are powerful tools for acquiring model inputs is one possible reason. This study, therefore, aims at direct surface runoff (DSRO) prediction using the geomorphologic instantaneous unit hydrograph based Nash model (GIUH-Nash) from ungauged catchment. DEM obtained from Shuttle Radar Topography Mission (SRTM) having 30 m resolution is used to generate the catchment’s physiographic and geomorphologic characteristics with the help of quantum geographic information system (QGIS). Based on this information, the GIUH-Nash model is used to simulate DSRO for different storm events. A visual comparison of observed values to predicted values of the runoff hydrographs as well as statistical indices shows that DSRO could be predicted with reasonable accuracy provided complete understanding of the model development and it’s evaluation procedures are properly followed. In respect of this, some key aspects that affect the performance of the model have been suggested.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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