Flow Prediction in Ungauged Catchments Using Probabilistic Random Forests Regionalization and New Statistical Adequacy Tests-Reference-Cited by-同舟云学术

Flow Prediction in Ungauged Catchments Using Probabilistic Random Forests Regionalization and New Statistical Adequacy Tests

Published:2019-05 Issue:5 Volume:55 Page:4364-4392
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Prieto Cristina¹²³^ORCID,Le Vine Nataliya²⁴^ORCID,Kavetski Dmitri⁵^ORCID,García Eduardo¹^ORCID,Medina Raúl¹^ORCID

Affiliation:

1. Environmental Hydraulics Institute “IHCantabria”Universidad de Cantabria Santander Spain

2. Department of Civil and Environmental EngineeringImperial College London London UK

3. Department of Civil EngineeringBristol University Bristol UK

4. Swiss Re Armonk NY USA

5. School of Civil, Environmental and Mining EngineeringUniversity of Adelaide Adelaide South Australia Australia

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2018WR023254

Reference112 articles.

1. Agencia Vasca del Agua(2003).Estudio de evaluación de los recursos hídricos totales en el ámbito de la CAPV. Report prepared by INTECSA‐INARSA. Retrieved fromhttp://www.uragentzia.euskadi.eus/contenidos/documentacion/evaluacion_recursos_hidricos/es_rh/adjuntos/memoria.pdf 02/02/2019.

2. Improving parameter priors for data-scarce estimation problems

3. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

4. Almeida S. L. Bulygina N. McIntyre N. Wagener T.&Buytaert W.(2012).Predicting flows in ungauged catchments using correlated information sources. In:British Hydrological Society's Eleventh National Hydrology Symposium Hydrology for a Changing World Dundee 2012

5. Almeida S. M. C. L.(2014).The value of regionalised information for hydrological modelling (PhD thesis). Imperial College London London UK.

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