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Open AccessArticle

Optimization of the Multi-Start Strategy of a Direct-Search Algorithm for the Calibration of Rainfall–Runoff Models for Water-Resource Assessment

1
Research Institute of Water Environmental Engineering (IIAMA), Universitat Politècnica de València, 46022 Valencia, Spain
2
Faculty of Civil Engineering, Universidad Michoacana de San Nicolás de Hidalgo, Morelia 58030, Mexico
*
Authors to whom correspondence should be addressed.
Water 2019, 11(9), 1876; https://doi.org/10.3390/w11091876
Received: 2 August 2019 / Revised: 22 August 2019 / Accepted: 5 September 2019 / Published: 9 September 2019
(This article belongs to the Section Water Resources Management and Governance)
Calibration of conceptual rainfall–runoff models (CRRM) for water-resource assessment (WRA) is a complicated task that contributes to the reliability of results obtained from catchments. In recent decades, the application of automatic calibration techniques has been frequently used because of the increasing complexity of models and the considerable time savings gained at this phase. In this work, the traditional Rosenbrock (RNB) algorithm is combined with a random sampling method and the Latin hypercube (LH) to optimize a multi-start strategy and test the efficiency in the calibration of CRRMs. Three models (the French rural-engineering-with-four-daily-parameters (GR4J) model, the Swedish Hydrological Office Water-balance Department (HBV) model and the Sacramento Soil Moisture Accounting (SAC-SMA) model) are selected for WRA at nine headwaters in Spain in zones prone to long and severe droughts. To assess the results, the University of Arizona’s shuffled complex evolution (SCE-UA) algorithm was selected as a benchmark, because, until now, it has been one of the most robust techniques used to solve calibration problems with rainfall–runoff models. This comparison shows that the traditional algorithm can find optimal solutions at least as good as the SCE-UA algorithm. In fact, with the calibration of the SAC-SMA model, the results are significantly different: The RNB algorithm found better solutions than the SCE-UA for all basins. Finally, the combination created between the LH and RNB methods is detailed thoroughly, and a sensitivity analysis of its parameters is used to define the set of optimal values for its efficient performance. View Full-Text
Keywords: calibration; rainfall–runoff models; multi-start; Latin hypercube; Rosenbrock; water-resource assessment calibration; rainfall–runoff models; multi-start; Latin hypercube; Rosenbrock; water-resource assessment
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García-Romero, L.; Paredes-Arquiola, J.; Solera, A.; Belda, E.; Andreu, J.; Sánchez-Quispe, S.T. Optimization of the Multi-Start Strategy of a Direct-Search Algorithm for the Calibration of Rainfall–Runoff Models for Water-Resource Assessment. Water 2019, 11, 1876.

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