An approach for estimating mean monthly runoff at ungauged sites is presented. Speci.il attention is paid to include effects of local features such as karst and river regulation bv reservoirs. The developments introduced conform with hydrostochastic concepts in that simple physical and statistical laws are inherent in the methods used for mapping. Hence, the approach developed here is consistent v^rith the water balance along the river network. The suggested method combines an application of empirical orthogonal functions and an adapted sto( hastie interpolation scheme to match the runoff data. The observation data are handled in the frame of a hydrological information system. This allows the display of results either in the form cf the change in a statistical parameter along the river branches towards the basin outlet or as a map of the variation of the parameters across the basin or region space. The approach is demonstrated for France,
One of the most important consequences of future climate change may be an alteration of the surface hydrological balance, including changes in flow regimes, i.e. seasonal distribution of flow and especially the time of occurrence of high/low flow, which is of vital importance for environmental and economic policies. Classification of flow regimes still has an important role for the analyses of hydrological response to climate change as well as for validating climate models on present climatic and hydrologic data, however, with some modifications in the methodology. In this paper an approach for flow regime classification is developed in this context. Different ways of flow regime classification are discussed. The stability of flow regimes is studied in relation to changes in mean annual temperature and precipitation. The analyses have shown that even rather small changes in these variables can cause changes in river flow regimes. Different patterns of response have been traced for different regions of the Nordic countries.
An important characteristic of a river flow regime type is the time of year when high and low flows are likely to occur. How likely is it, however, to observe an identified seasonal pattern each individual year? Stability is an often neglected property of a flow regime, though shifts in the seasonal behaviour of flows affect both environmental and economic activities. An approach to characterize objectively the stability of a flow regime type, based on the concept of entropy, is presented. The stabilities of river flow maxima and minima are studied separately to investigate their respective contributions to the stability character of a particular regime type. A quantitative "instability index" permits a study of the development of a flow regime's stability in time, especially important in the context of a possible climate change. The method is presented using the example of a quantitative flow regime classification developed for Scandinavia and western Europe. Quantification de la stabilité du régime des rivièresRésumé Une importante caractéristique du régime des rivières est la période de l'année où il est probable que se produisent les crues ou les étiages. Cependant quelle est la probabilité d'observer le modèle saisonnier identifié au cours d'une année particulière? La stabilité est une propriété du régime souvent négligée, alors que des variations du comportement saisonnier de l'écoulement affectent à la fois l'environnement et les activités économiques. Nous proposons une approche fondée sur le concept d'entropie qui permet de caractériser objectivement la stabilité d'un régime. La stabilité des maxima et minima d'écoulement est étudiée séparément afin de rechercher leur contributions respectives à la stabilité caractéristique d'un régime particulier. Un "index de instabilité" quantitatif permet d'étudier l'évolution de la stabilité du régime au cours du temps, ce qui est particulièrement important dans la perspective d'éventuelles modifications climatiques. La méthode est présentée à partir d'une classification quantitative du régime des rivières réalisée pour la Scandinavie et l'Europe de l'ouest.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.