Preface—Special Issue: Facets of Uncertainty     

Alin Carsteanu  Ebru Eris  Elena Volpi  Steven Weijs Guest Editors 《水文科学杂志》2016,61(9):1555-1556

  相似文献   

Validation and use of rainfall radar data to simulate water flows in the Rio Escondido basin   总被引：2，自引：1，他引：1  

Sami Eleuch  Alin Carsteanu  Khalidou Bâ  Ramata Magagi  Kalifa Goïta  Carlos Diaz 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(5):559-565

This paper presents a combined validation method of radar-sensed rainfall, using rain gauge data and hydrologic closure, with an application to the Rio Escondido basin (North-East of Mexico). The space–time scaling behavior of rainfall between rain gauge and radar scales is compared with the intrinsic variability of rainfall, for a statistical validation of space–time variability. For hydrological validation purposes, the CEQUEAU model is used to perform rainfall-runoff routing. It provides a basin-wide water balance, to be compared with the measured water flow at the Villa de Fuentes hydrometric station, for mean-value gauging closure. A good qualitative agreement in terms of hydrograph shape and timing is obtained between the simulated and the observed water flows, and a multiplicative correction factor of an initially proposed Z–R relationship is adopted for the watershed under study, which agrees approximately with other authors’ findings about that relationship. The results are considered particularly useful as a validation-and-correction methodology of radar rainfall estimates for areas sparsely covered by rain gauges.  相似文献   

Long-range dependence in the time series of Taiţa River discharges     

Carmen Maftei  Alina Barbulescu  Alin Andrei Carsteanu 《水文科学杂志》2016,61(9):1740-1747

ABSTRACT

The aim of this article is to offer an insight into the hydrology of southeast Romanian catchments, which have not been studied systematically. The complex behaviour of the Tai?a, one of the most important rivers situated in the northern part of Dobrogea, is demonstrated. Long-range dependence (LRD) in the time series of its streamflow, including the presence of trends, is supported by an estimated Hurst exponent of approximately 0.8, as well as statistical tests.