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Refinado por: Nome da Publicação: Journal Of Hydrology remover
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1
Influence of rainfall spatial variability on rainfall–runoff modelling: Benefit of a simulation approach?
Influence of rainfall spatial variability on rainfall–runoff modelling: Benefit of a simulation approach?
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Influence of rainfall spatial variability on rainfall–runoff modelling: Benefit of a simulation approach?

Emmanuel, I. ; Andrieu, H. ; Leblois, E. ; Janey, N. ; Payrastre, O.

Journal of hydrology (Amsterdam), 2015-12, Vol.531, p.337-348 [Periódico revisado por pares]

Elsevier B.V

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2
The influence of sugarcane crop development on rainfall interception losses
The influence of sugarcane crop development on rainfall interception losses
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The influence of sugarcane crop development on rainfall interception losses

Rafael Pires Fernandes Robson Willians da Costa Silva; Luiz Felippe Salemi; Tatiana Morgan Berteli de Andrade; Jorge Marcos de Moraes; Albert I. J. M Van Dijk; Luiz Antonio Martinelli

Journal of Hydrology Amsterdam v. 551, p. 532-539, 2017

Amsterdam 2017

Item não circula. Consulte sua biblioteca.(Acessar)

3
Using long-term daily satellite based rainfall data (1983–2015) to analyze spatio-temporal changes in the sahelian rainfall regime
Using long-term daily satellite based rainfall data (1983–2015) to analyze spatio-temporal changes in the sahelian rainfall regime
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Using long-term daily satellite based rainfall data (1983–2015) to analyze spatio-temporal changes in the sahelian rainfall regime

Zhang, Wenmin ; Brandt, Martin ; Guichard, Francoise ; Tian, Qingjiu ; Fensholt, Rasmus

Journal of hydrology (Amsterdam), 2017-07, Vol.550, p.427-440 [Periódico revisado por pares]

Elsevier B.V

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4
Stochastic generation of daily rainfall events: A single-site rainfall model with Copula-based joint simulation of rainfall characteristics and classification and simulation of rainfall patterns
Stochastic generation of daily rainfall events: A single-site rainfall model with Copula-based joint simulation of rainfall characteristics and classification and simulation of rainfall patterns
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Stochastic generation of daily rainfall events: A single-site rainfall model with Copula-based joint simulation of rainfall characteristics and classification and simulation of rainfall patterns

Gao, Chao ; Xu, Yue-Ping ; Zhu, Qian ; Bai, Zhixu ; Liu, Li

Journal of hydrology (Amsterdam), 2018-09, Vol.564, p.41-58 [Periódico revisado por pares]

Elsevier B.V

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5
Which potential evapotranspiration input for a lumped rainfall-runoff model?. Part 2: Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling
Which potential evapotranspiration input for a lumped rainfall-runoff model?. Part 2: Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling
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Which potential evapotranspiration input for a lumped rainfall-runoff model?. Part 2: Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling

OUDIN, Ludovic ; HERVIEU, Frédéric ; MICHEL, Claude ; PERRIN, Charles ; ANDREASSIAN, Vazken ; ANCTIL, Francois ; LOUMAGNE, Cécile

Journal of hydrology (Amsterdam), 2005-03, Vol.303 (1-4), p.290-306 [Periódico revisado por pares]

Amsterdam: Elsevier Science

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6
Space–time organization of debris flows-triggering rainfall and its effect on the identification of the rainfall threshold relationship
Space–time organization of debris flows-triggering rainfall and its effect on the identification of the rainfall threshold relationship
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Space–time organization of debris flows-triggering rainfall and its effect on the identification of the rainfall threshold relationship

Marra, F. ; Nikolopoulos, E.I. ; Creutin, J.D. ; Borga, M.

Journal of hydrology (Amsterdam), 2016-10, Vol.541, p.246-255 [Periódico revisado por pares]

Elsevier B.V

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7
Data-driven input variable selection for rainfall–runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines
Data-driven input variable selection for rainfall–runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines
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Data-driven input variable selection for rainfall–runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines

Taormina, Riccardo ; Chau, Kwok-Wing

Journal of hydrology (Amsterdam), 2015-10, Vol.529, p.1617-1632 [Periódico revisado por pares]

Elsevier B.V

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8
The rainfall kinetic energy–intensity relationship for rainfall erosivity estimation in the mediterranean part of Slovenia
The rainfall kinetic energy–intensity relationship for rainfall erosivity estimation in the mediterranean part of Slovenia
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The rainfall kinetic energy–intensity relationship for rainfall erosivity estimation in the mediterranean part of Slovenia

Petan, Sašo ; Rusjan, Simon ; Vidmar, Andrej ; Mikoš, Matjaž

Journal of hydrology (Amsterdam), 2010-09, Vol.391 (3), p.314-321 [Periódico revisado por pares]

Kidlington: Elsevier B.V

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9
A rule based quality control method for hourly rainfall data and a 1 km resolution gridded hourly rainfall dataset for Great Britain: CEH-GEAR1hr
A rule based quality control method for hourly rainfall data and a 1 km resolution gridded hourly rainfall dataset for Great Britain: CEH-GEAR1hr
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A rule based quality control method for hourly rainfall data and a 1 km resolution gridded hourly rainfall dataset for Great Britain: CEH-GEAR1hr

Lewis, Elizabeth ; Quinn, Niall ; Blenkinsop, Stephen ; Fowler, Hayley J. ; Freer, Jim ; Tanguy, Maliko ; Hitt, Olivia ; Coxon, Gemma ; Bates, Paul ; Woods, Ross

Journal of hydrology (Amsterdam), 2018-09, Vol.564, p.930-943 [Periódico revisado por pares]

Elsevier B.V

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10
Rainfall trends in Nigeria, 1901–2000
Rainfall trends in Nigeria, 1901–2000
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Rainfall trends in Nigeria, 1901–2000

Oguntunde, Philip G. ; Abiodun, Babatunde J. ; Lischeid, Gunnar

Journal of hydrology (Amsterdam), 2011-12, Vol.411 (3), p.207-218 [Periódico revisado por pares]

Kidlington: Elsevier B.V

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Deste Autor:

  1. Martinelli, L
  2. Fernandes, R
  3. Silva, R
  4. Moraes, J
  5. van Dijk, A

Neste Assunto:

  1. Water Resources
  2. Geology
  3. Engineering
  4. Physical Sciences
  5. Science & Technology

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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