Streamflow simulation methods for ungauged and poorly gauged watersheds
Rainfall–runoff modelling procedures for ungauged and poorly gauged watersheds are developed in this study. A well-established hydrological model, the University of British Columbia (UBC) watershed model, is selected and applied in five different river basins located in Canada, Cyprus, and Pakistan....
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Copernicus Publications
2014-07-01
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doaj-9645ded702b1439ab38c51270d34a4502020-11-24T23:08:41ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812014-07-011471641166110.5194/nhess-14-1641-2014Streamflow simulation methods for ungauged and poorly gauged watershedsA. Loukas0L. Vasiliades1Department of Civil Engineering, University of Thessaly, Pedion Areos, 38334 Volos, GreeceDepartment of Civil Engineering, University of Thessaly, Pedion Areos, 38334 Volos, GreeceRainfall–runoff modelling procedures for ungauged and poorly gauged watersheds are developed in this study. A well-established hydrological model, the University of British Columbia (UBC) watershed model, is selected and applied in five different river basins located in Canada, Cyprus, and Pakistan. Catchments from cold, temperate, continental, and semiarid climate zones are included to demonstrate the procedures developed. Two methodologies for streamflow modelling are proposed and analysed. The first method uses the UBC watershed model with a universal set of parameters for water allocation and flow routing, and precipitation gradients estimated from the available annual precipitation data as well as from regional information on the distribution of orographic precipitation. This method is proposed for watersheds without streamflow gauge data and limited meteorological station data. The second hybrid method proposes the coupling of UBC watershed model with artificial neural networks (ANNs) and is intended for use in poorly gauged watersheds which have limited streamflow measurements. The two proposed methods have been applied to five mountainous watersheds with largely varying climatic, physiographic, and hydrological characteristics. The evaluation of the applied methods is based on the combination of graphical results, statistical evaluation metrics, and normalized goodness-of-fit statistics. The results show that the first method satisfactorily simulates the observed hydrograph assuming that the basins are ungauged. When limited streamflow measurements are available, the coupling of ANNs with the regional, non-calibrated UBC flow model components is considered a successful alternative method to the conventional calibration of a hydrological model based on the evaluation criteria employed for streamflow modelling and flood frequency estimation.http://www.nat-hazards-earth-syst-sci.net/14/1641/2014/nhess-14-1641-2014.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. Loukas L. Vasiliades |
spellingShingle |
A. Loukas L. Vasiliades Streamflow simulation methods for ungauged and poorly gauged watersheds Natural Hazards and Earth System Sciences |
author_facet |
A. Loukas L. Vasiliades |
author_sort |
A. Loukas |
title |
Streamflow simulation methods for ungauged and poorly gauged watersheds |
title_short |
Streamflow simulation methods for ungauged and poorly gauged watersheds |
title_full |
Streamflow simulation methods for ungauged and poorly gauged watersheds |
title_fullStr |
Streamflow simulation methods for ungauged and poorly gauged watersheds |
title_full_unstemmed |
Streamflow simulation methods for ungauged and poorly gauged watersheds |
title_sort |
streamflow simulation methods for ungauged and poorly gauged watersheds |
publisher |
Copernicus Publications |
series |
Natural Hazards and Earth System Sciences |
issn |
1561-8633 1684-9981 |
publishDate |
2014-07-01 |
description |
Rainfall–runoff modelling procedures for ungauged and poorly gauged
watersheds are developed in this study. A well-established hydrological
model, the University of British Columbia (UBC) watershed model, is selected
and applied in five different river basins located in Canada, Cyprus, and
Pakistan. Catchments from cold, temperate, continental, and semiarid climate
zones are included to demonstrate the procedures developed. Two methodologies
for streamflow modelling are proposed and analysed. The first method uses
the UBC watershed model with a universal set of parameters for water
allocation and flow routing, and precipitation gradients estimated from the
available annual precipitation data as well as from regional information on
the distribution of orographic precipitation. This method is proposed for
watersheds without streamflow gauge data and limited meteorological station
data. The second hybrid method proposes the coupling of UBC watershed model
with artificial neural networks (ANNs) and is intended for use in poorly
gauged watersheds which have limited streamflow measurements. The two
proposed methods have been applied to five mountainous watersheds with
largely varying climatic, physiographic, and hydrological characteristics.
The evaluation of the applied methods is based on the combination of graphical
results, statistical evaluation metrics, and normalized goodness-of-fit
statistics. The results show that the first method satisfactorily simulates
the observed hydrograph assuming that the basins are ungauged. When limited
streamflow measurements are available, the coupling of ANNs with the
regional, non-calibrated UBC flow model components is considered a successful
alternative method to the conventional calibration of a hydrological model
based on the evaluation criteria employed for streamflow modelling and flood
frequency estimation. |
url |
http://www.nat-hazards-earth-syst-sci.net/14/1641/2014/nhess-14-1641-2014.pdf |
work_keys_str_mv |
AT aloukas streamflowsimulationmethodsforungaugedandpoorlygaugedwatersheds AT lvasiliades streamflowsimulationmethodsforungaugedandpoorlygaugedwatersheds |
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