Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Evaluation of precipitation input for SWAT modeling in Alpine catchment : A case study in the Adige river basin (Italy)

Tuo, Ye ; Duan, Zheng LU ; Disse, Markus and Chiogna, Gabriele (2016) In Science of the Total Environment 573. p.66-82
Abstract

Precipitation is often the most important input data in hydrological models when simulating streamflow. The Soil and Water Assessment Tool (SWAT), a widely used hydrological model, only makes use of data from one precipitation gauge station that is nearest to the centroid of each subbasin, which is eventually corrected using the elevation band method. This leads in general to inaccurate representation of subbasin precipitation input data, particularly in catchments with complex topography. To investigate the impact of different precipitation inputs on the SWAT model simulations in Alpine catchments, 13 years (1998–2010) of daily precipitation data from four datasets including OP (Observed precipitation), IDW (Inverse Distance Weighting... (More)

Precipitation is often the most important input data in hydrological models when simulating streamflow. The Soil and Water Assessment Tool (SWAT), a widely used hydrological model, only makes use of data from one precipitation gauge station that is nearest to the centroid of each subbasin, which is eventually corrected using the elevation band method. This leads in general to inaccurate representation of subbasin precipitation input data, particularly in catchments with complex topography. To investigate the impact of different precipitation inputs on the SWAT model simulations in Alpine catchments, 13 years (1998–2010) of daily precipitation data from four datasets including OP (Observed precipitation), IDW (Inverse Distance Weighting data), CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and TRMM (Tropical Rainfall Measuring Mission) has been considered. Both model performances (comparing simulated and measured streamflow data at the catchment outlet) as well as parameter and prediction uncertainties have been quantified. For all three subbasins, the use of elevation bands is fundamental to match the water budget. Streamflow predictions obtained using IDW inputs are better than those obtained using the other datasets in terms of both model performance and prediction uncertainty. Models using the CHIRPS product as input provide satisfactory streamflow estimation, suggesting that this satellite product can be applied to this data-scarce Alpine region. Comparing the performance of SWAT models using different precipitation datasets is therefore important in data-scarce regions. This study has shown that, precipitation is the main source of uncertainty, and different precipitation datasets in SWAT models lead to different best estimate ranges for the calibrated parameters. This has important implications for the interpretation of the simulated hydrological processes.

(Less)
Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Adige, Alpine catchment, CHIRPS, IDW, SWAT model, TRMM
in
Science of the Total Environment
volume
573
pages
17 pages
publisher
Elsevier
external identifiers
  • scopus:84983057061
ISSN
0048-9697
DOI
10.1016/j.scitotenv.2016.08.034
language
English
LU publication?
no
id
ab163f19-a318-4ced-8321-7593d392c65e
date added to LUP
2019-12-22 20:25:16
date last changed
2022-03-26 01:11:33
@article{ab163f19-a318-4ced-8321-7593d392c65e,
  abstract     = {{<p>Precipitation is often the most important input data in hydrological models when simulating streamflow. The Soil and Water Assessment Tool (SWAT), a widely used hydrological model, only makes use of data from one precipitation gauge station that is nearest to the centroid of each subbasin, which is eventually corrected using the elevation band method. This leads in general to inaccurate representation of subbasin precipitation input data, particularly in catchments with complex topography. To investigate the impact of different precipitation inputs on the SWAT model simulations in Alpine catchments, 13 years (1998–2010) of daily precipitation data from four datasets including OP (Observed precipitation), IDW (Inverse Distance Weighting data), CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and TRMM (Tropical Rainfall Measuring Mission) has been considered. Both model performances (comparing simulated and measured streamflow data at the catchment outlet) as well as parameter and prediction uncertainties have been quantified. For all three subbasins, the use of elevation bands is fundamental to match the water budget. Streamflow predictions obtained using IDW inputs are better than those obtained using the other datasets in terms of both model performance and prediction uncertainty. Models using the CHIRPS product as input provide satisfactory streamflow estimation, suggesting that this satellite product can be applied to this data-scarce Alpine region. Comparing the performance of SWAT models using different precipitation datasets is therefore important in data-scarce regions. This study has shown that, precipitation is the main source of uncertainty, and different precipitation datasets in SWAT models lead to different best estimate ranges for the calibrated parameters. This has important implications for the interpretation of the simulated hydrological processes.</p>}},
  author       = {{Tuo, Ye and Duan, Zheng and Disse, Markus and Chiogna, Gabriele}},
  issn         = {{0048-9697}},
  keywords     = {{Adige; Alpine catchment; CHIRPS; IDW; SWAT model; TRMM}},
  language     = {{eng}},
  month        = {{12}},
  pages        = {{66--82}},
  publisher    = {{Elsevier}},
  series       = {{Science of the Total Environment}},
  title        = {{Evaluation of precipitation input for SWAT modeling in Alpine catchment : A case study in the Adige river basin (Italy)}},
  url          = {{http://dx.doi.org/10.1016/j.scitotenv.2016.08.034}},
  doi          = {{10.1016/j.scitotenv.2016.08.034}},
  volume       = {{573}},
  year         = {{2016}},
}