Streamflow data are essential for the calibration of continuous rainfall-runoff (RR) models. The quantity and quality of streamflow data can significantly influence parameter calibration and thus model robustness. Most existing sensitivity analysis studies on the role of streamflow data have used continuous periods to calibrate model parameters, with a minimum of one year, though ideally much longer periods are generally advised. However, in practical model applications, streamflow data series available for model calibration may be rather short or non-continuous. This study aims at assessing the sensitivity of continuous RR models to the quantity of information used during model calibration when it is randomly sampled in the observed hydrograph, i.e. using non-continuous calibration periods. This sampling provides less auto-correlated streamflow information for model calibration than continuous records. Two daily RR models with four and six free parameters were tested on a sample of 12 basins in the USA to obtain more general conclusions. The results showed that, in general, 350 calibration days sampled out of a longer data set including dry and wet conditions are sufficient to obtain robust estimates of model parameters. The more parsimonious model requires fewer calibration data to obtain stable and robust parameter values. Stable parameter values prove more difficult to reach in the driest catchments.Key words rainfall-runoff modelling; calibration; sampling; sensitivity analysis; streamflow data Impact d'une limitation de données de débit sur l'efficacité et les paramètres de modèles pluie-débit Résumé Les données de débit sont essentielles pour caler les modèles pluie-débit continus. La quantité et la qualité des données peuvent influencer de manière significative le calage des paramètres et donc la robustesse du modèle. La plupart des analyses de sensibilité ayant abordé le rôle des données de débit ont utilisé des périodes continues pour le calage des paramètres des modèles, avec un minimum d'une année, bien qu'idéalement des chroniques beaucoup plus longues soient généralement conseillées. Cependant, dans des applications pratiques de modélisation, les séries de données disponibles pour le calage des modèles sont courtes ou non-continues. L'objectif de cette étude est d'évaluer la sensibilité des modèles pluie-débit continus à la quantité d'information utilisée pour leur calage lorsqu'elle est échantillonnée aléatoirement dans l'hydrogramme observé, c'est-à-dire en utilisant des périodes de calage non-continues. Cet échantillonnage fournit une information de débit moins corrélée qu'une série continue pour le calage. Nous avons utilisé ici deux modèles pluie-débit avec quatre et six paramètres, et nous les avons testés sur un échantillon de 12 bassins aux Etats-Unis, pour obtenir des conclusions plus générales. Les résultats montrent qu'en général, 350 jours de calage tirés dans une série plus longue comprenant des conditions sèches et humides sont suffisants pour obtenir des valeurs robustes des...

[1] This article describes an alternative to the optimization strategies classically adopted to calibrate the parameters of rainfall-runoff models. This new method, called discrete parameterization, relies on the sole use of the prior information on parameters gained on other catchments. The optimum parameter set is simply searched within a collection (a library) of predefined optima. This library is composed of parameter sets representing a large number of actual catchments. The method was tested on a set of 900 catchments (from Australia, France, and the United States) using two daily lumped rainfall-runoff models and was compared to more classical calibration approaches. Results are very similar for both models. Although the discrete parameterization method is not as efficient as a classical global search calibration approach when long time series are available for calibration, it provides more robust parameter sets when flow time series available for calibration becomes shorter than 2 years. This makes the method particularly interesting in the cases of poorly gauged catchments where available flow records are short. In case of limited data, the advantage of the proposed approach over the classical calibration approaches was more significant for the more complex model. On our set of 900 catchments, the optimum parameter set is generally selected among parameter sets from the library corresponding to catchments spatially close to the studied catchment. However other criteria of physical similarity may be relevant to select the donor catchment in the library.

This paper examines catchments that are almost ungauged, i.e., catchments for which only a small number of point flow measurements are available. In these catchments, hydrologists may still need to simulate continuous streamflow time series using a rainfall‐runoff model, and the methodology presented here allows using few point measurements for model parameterization. The method combines regional information (parameter sets of neighboring gauged stations) and local information (contributed by the point measurements) within a framework where the relative weight of each source of information is made dependent on the number of point measurements available. This approach is tested with two different hydrological models on a set of 609 catchments in France. The results show that on average a few flow measurements can significantly improve the simulation efficiency, and that 10 measurements can reduce the performance gap between the gauged and ungauged situations by more than 50%. The added value of regional information progressively decreases until being almost insignificant when sufficient flow measurements are available. Model parameters tend to come closer to the values obtained by calibration in fully gauged conditions as the number of point flow measurements increases.

Advances have been made in water resource investigation due to the implementation of mathematical models, the development of theoretical frameworks, and the evaluation of sustainability indices. Together, they improve and make integrated water resource management more efficient. In this paper, in the study area of the Duero River Basin, located in Michoacan, Mexico, we schematize a series of numerical indices of the Watershed Governance Prism to determine the quantitative status of water governance in a watershed. The results, presented as axes, perspectives, and prisms in the Axis Index, Water Governance Index, and Watershed Governance Prism Index, provide the conclusion that it is possible to establish and evaluate the Watershed Governance Prism Index using our numerical implementation of the Watershed Governance Prism theoretical framework. Thus, it is possible to define a quantitative status and evoke how water governance is being designed and implemented in a watershed.

The purpose of this study was to analyze water circulation in an estuary located in Boca del Río, Veracruz, Mexico. The diagnosis is based on the most representative flux records for the Jamapa River during the dry and rain seasons, that is, April and September, respectively. Tidal conditions, temperature, and water density were taken into account. For the diagnosis, a three-dimensional model (Delft3D) was applied. The seasonal circulation governing the estuary was evaluated using barotropic and baroclinic pressure levels. During the dry season, estuarine circulation was governed by the tides, and water circulation in the Mandinga lagoons was induced by baroclinic conditions. During the rainy season, the estuarine system was governed by discharge from the Jamapa River, and water circulation in the Mandinga lagoons is influenced by barotropic gradients.Resumen. Este estudio analiza la circulación de agua en el estuario de Boca del Río, Veracruz, México. El diagnóstico se basa en los registros disponibles de los flujos del río Jamapa durante las estaciones de estiaje y lluvia, es decir, durante abril y septiembre, respectivamente. Los regímenes de mareas, la temperatura y los valores de densidad del agua fueron tomados en cuenta. Para el dignóstico, se aplicó un modelo en 3 dimensiones (Delft3D). La circulación estacional del agua en el estuario se evaluó de acuerdo con los niveles de presión barotrópica y presión baroclínica. Durante la temporada de estiaje, la circulación en el estuario se rigió por las mareas, mientras que la circulación en las lagunas de Mandinga es inducida por condiciones baroclínicas. Durante la temporada de lluvias, el estuario se rigió por la descarga del río Jamapa, y la circulación del agua en las lagunas de Mandinga dependió de los gradientes barotrópicos.Palabras clave: estuario, Delft3D, barotrópico, baroclínico, salinidad.