Calibration of the Parameters of a Rainfall-Runoff Model in Ungauged Basins Using Synthetic Flow Duration Curves as Estimated by Regional Analysis

Pinheiro, Viviane Borda; Naghettini, Mauro

doi:10.1061/(asce)he.1943-5584.0000737

Cited by 7 publications

(2 citation statements)

References 13 publications

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“…Finally, all qualified parameter sets would be further evaluated for prediction in ungauged catchments. At the early post‐PUB decade, there were some studies which applied this method (Costa, Fernandes, & Naghettini, 2014; Pinheiro & Naghettini, 2013; Shu & Ouarda, 2012; Westerberg et al, 2014). However, this research has been relatively rare in the post‐PUB decade since it is more complex and might be limited by the accuracy of meteorological data compared with direct regionalization of hydrological signatures (H. E. Beck et al, 2016).…”

Section: Hydrological Regionalization Methodsmentioning

confidence: 99%

Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review

et al. 2020

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Runoff prediction in ungauged and scarcely gauged catchments is a key research field in surface water hydrology. There have been numerous studies before and since the launch of the predictions in ungauged basins (PUB) initiative by the International Association of Hydrological Sciences in 2003. This study critically reviews and assesses the decadal progress in the regionalization of hydrological modeling, which is the major tool for PUB, from 2000 to 2019. This paper found that the journal publications have noticeably increased in terms of PUB in the past 7 years, and research countries have been expanded dramatically since 2013. The regionalization methods are grouped into three categories including similarity-based, regression-based, and hydrological signature-based. There are more detailed researches focusing on the interdisciplinary and profound improvement of each regionalization method. Namely, tremendous efforts have been made and lots of improvements have been carried out in the parameterization domain for the post-PUB period. However, there is still plenty of room to improve the prediction capability in data-sparse regions (e.g., further verification and proof of multi-modeling adaptation and uncertainties description). This paper also discusses possible research directions in the future, including PUB in a changing environment and better utilization of multi-source remote-sensing information.

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Section: Hydrological Regionalization Methodsmentioning

confidence: 99%

Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review

et al. 2020

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“…Overall, the results suggest that the global maps of Q characteristics derived in this study can be employed to refine the parameterization or structure of the examined models in order to obtain better Q behavior (cf. Yadav et al 2007;Zhang et al 2008;Castiglioni et al 2010;Wagener and Montanari 2011;Lombardi et al 2012;Pinheiro and Naghettini 2013).…”

Section: Example Applicationmentioning

confidence: 99%

Global Maps of Streamflow Characteristics Based on Observations from Several Thousand Catchments*

Beck

Roo

Dijk

2015

Journal of Hydrometeorology

152

179

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Streamflow Q estimation in ungauged catchments is one of the greatest challenges facing hydrologists. Observed Q from 3000 to 4000 small-to-medium-sized catchments (10–10 000 km2) around the globe were used to train neural network ensembles to estimate Q characteristics based on climate and physiographic characteristics of the catchments. In total, 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Testing coefficients of determination for the estimation of the Q characteristics ranged from 0.55 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were relatively unimportant, perhaps because of their data quality. The trained neural network ensembles were subsequently applied spatially over the entire ice-free land surface, resulting in global maps of the Q characteristics (at 0.125° resolution). These maps possess several unique features: they represent observation-driven estimates, they are based on an unprecedentedly large set of catchments, and they have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macroscale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of four macroscale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available online (http://water.jrc.ec.europa.eu/GSCD).

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Parameters Optimization using Fuzzy Rule Based Multi-Objective Genetic Algorithm for an Event Based Rainfall-Runoff Model

Reshma

Reddy

Pratap

et al. 2018

Water Resour Manage

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Calibration of the Parameters of a Rainfall-Runoff Model in Ungauged Basins Using Synthetic Flow Duration Curves as Estimated by Regional Analysis

Cited by 7 publications

References 13 publications

Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review

Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review

Global Maps of Streamflow Characteristics Based on Observations from Several Thousand Catchments*

Parameters Optimization using Fuzzy Rule Based Multi-Objective Genetic Algorithm for an Event Based Rainfall-Runoff Model

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