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Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation

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2018
Authors
Ivković, Marija
Todorović, Andrijana
Plavšić, Jasna
Article (Published version)
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Abstract
Flood forecasting relies on good quality of observed and forecasted rainfall. In Serbia, the recording rain gauge network is sparse and rainfall data mainly come from dense non-recording rain gauges. This is not beneficial for flood forecasting in smaller catchments and short-duration events, when hydrologic models operating on subdaily scale are applied. Moreover, differences in rainfall amounts from two types of gauges can be considerable, which is common in operational hydrological practice. This paper examines the possibility of including daily rainfall data from dense observation networks in flood forecasting based on subdaily data, using the extreme flood event in the Kolubara catchment in May 2014 as a case study. Daily rainfall from a dense observation network is disaggregated to hourly scale using the MuDRain multivariate disaggregation software. The disaggregation procedure results in well-reproduced rainfall dynamics and adjusts rainfall volume to the values from the non-rec...ording gauges. The fully distributed wflow_hbv model, which is under development as a forecasting tool for the Kolubara catchment, is used for flood simulations with two alternative hourly rainfall data. The results show an improvement when the disaggregated rainfall from denser network is used, thus indicating the significance of better representation of rainfall temporal and spatial variability for flood forecasting.

Keywords:
flood forecasting / HBV model / rainfall-runoff model / rainfall spatial distribution / sparse network / subdaily rainfall disaggregation
Source:
Journal of Hydroinformatics, 2018, 20, 4, 784-797
Funding / projects:
  • Urban Drainage Systems as Key Infrastructure in Cities and Towns (RS-37010)
  • Assessment of Climate Change Impact on Water Resources of Serbia (RS-37005)

DOI: 10.2166/hydro.2018.053

ISSN: 1464-7141

WoS: 000436621300004

Scopus: 2-s2.0-85051377870
[ Google Scholar ]
5
4
URI
https://grafar.grf.bg.ac.rs/handle/123456789/935
Collections
  • Radovi istraživača / Researcher's publications
  • Катедра за хидротехнику и водно-еколошко инжењерство
Institution/Community
GraFar
TY  - JOUR
AU  - Ivković, Marija
AU  - Todorović, Andrijana
AU  - Plavšić, Jasna
PY  - 2018
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/935
AB  - Flood forecasting relies on good quality of observed and forecasted rainfall. In Serbia, the recording rain gauge network is sparse and rainfall data mainly come from dense non-recording rain gauges. This is not beneficial for flood forecasting in smaller catchments and short-duration events, when hydrologic models operating on subdaily scale are applied. Moreover, differences in rainfall amounts from two types of gauges can be considerable, which is common in operational hydrological practice. This paper examines the possibility of including daily rainfall data from dense observation networks in flood forecasting based on subdaily data, using the extreme flood event in the Kolubara catchment in May 2014 as a case study. Daily rainfall from a dense observation network is disaggregated to hourly scale using the MuDRain multivariate disaggregation software. The disaggregation procedure results in well-reproduced rainfall dynamics and adjusts rainfall volume to the values from the non-recording gauges. The fully distributed wflow_hbv model, which is under development as a forecasting tool for the Kolubara catchment, is used for flood simulations with two alternative hourly rainfall data. The results show an improvement when the disaggregated rainfall from denser network is used, thus indicating the significance of better representation of rainfall temporal and spatial variability for flood forecasting.
T2  - Journal of Hydroinformatics
T1  - Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation
EP  - 797
IS  - 4
SP  - 784
VL  - 20
DO  - 10.2166/hydro.2018.053
ER  - 
@article{
author = "Ivković, Marija and Todorović, Andrijana and Plavšić, Jasna",
year = "2018",
abstract = "Flood forecasting relies on good quality of observed and forecasted rainfall. In Serbia, the recording rain gauge network is sparse and rainfall data mainly come from dense non-recording rain gauges. This is not beneficial for flood forecasting in smaller catchments and short-duration events, when hydrologic models operating on subdaily scale are applied. Moreover, differences in rainfall amounts from two types of gauges can be considerable, which is common in operational hydrological practice. This paper examines the possibility of including daily rainfall data from dense observation networks in flood forecasting based on subdaily data, using the extreme flood event in the Kolubara catchment in May 2014 as a case study. Daily rainfall from a dense observation network is disaggregated to hourly scale using the MuDRain multivariate disaggregation software. The disaggregation procedure results in well-reproduced rainfall dynamics and adjusts rainfall volume to the values from the non-recording gauges. The fully distributed wflow_hbv model, which is under development as a forecasting tool for the Kolubara catchment, is used for flood simulations with two alternative hourly rainfall data. The results show an improvement when the disaggregated rainfall from denser network is used, thus indicating the significance of better representation of rainfall temporal and spatial variability for flood forecasting.",
journal = "Journal of Hydroinformatics",
title = "Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation",
pages = "797-784",
number = "4",
volume = "20",
doi = "10.2166/hydro.2018.053"
}
Ivković, M., Todorović, A.,& Plavšić, J.. (2018). Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation. in Journal of Hydroinformatics, 20(4), 784-797.
https://doi.org/10.2166/hydro.2018.053
Ivković M, Todorović A, Plavšić J. Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation. in Journal of Hydroinformatics. 2018;20(4):784-797.
doi:10.2166/hydro.2018.053 .
Ivković, Marija, Todorović, Andrijana, Plavšić, Jasna, "Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation" in Journal of Hydroinformatics, 20, no. 4 (2018):784-797,
https://doi.org/10.2166/hydro.2018.053 . .

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