Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/12137
Title: Aplicabilidade do método CN-SCS a uma bacia hidrográfica representativa dos latossolos no Sul de MG
Other Titles: Applicability ot the cn-scs method at a watershed representative of the oxisols in Southern Minas Gerais
Authors: Mello, Carlos Rogério de
Beskow, Samuel
Diotto, Adriano Valentim
Beskow, Samuel
Keywords: Hidrologia – Métodos estatísticos
Águas pluviais – Escoamento
Bacias hidrográficas – Escoamento
Hydrology – Statistical methods
Rain-water – Runoff
Watersheds – Runoff
Issue Date: 27-Dec-2016
Publisher: Universidade Federal de Lavras
Citation: ALVES, G. J. Aplicabilidade do método CN-SCS a uma bacia hidrográfica representativa dos latossolos no Sul de MG. 2016. 156 p. Dissertação (Mestrado em Recursos Hídricos)-Universidade Federal de Lavras, Lavras, 2016.
Abstract: The CN-SCS (Curve Number - Soil Conservation Service) method is a rainfall-runoff model that considers an empirical approximation between a given rainfall event and the surface conditions of a hydrologic unit. It has been used to estimate the direct surface runoff (Q) from total rainfall (P) ,taking into account soil classes and their uses. It was developed considering a relationship between the initial rainfall abstraction (Ia) and the maximum soil-water storage potential (S) that was defined equal to 0.2. Ia parameter has been largely studied by many authors, and most of them have found values lower than 0.2, being this one of the main sources of error associated with the method. Another parameter of paramount importance for the Q estimation is the current value of CN, which is difficult to establish with precision, since it depends on the combination between soil class, vegetation cover and antecedent soil moisture, besides the physical characteristics of the rain. The objective of this study was to evaluate the estimated Q values for JaguaraCreek Watershed(JCW), using the CN-SCS method, in which CN values were determined based on 29 methods. JCW is located in the Upper Grande River region, southern Minas Gerais, whose weather and streamflow datasets have been monitored since 2006. The first procedure for CN was based on the combination between the use and soil classesmaps, generating a CN map in the moisture condition II (CNII) for JCW. Based on the weighted average of each value of CN and its respective area, and considering the 3 existing soil moisture antecedent conditions (defined by the antencedent amount of rainfall), 3 values of average CN were obtained. Otherwise, with the observed Q data the respective S value was calculated, and then, the estimatedCNfor each event. Similar methodology was applied for the rainfall-runoffevents which were ordered in a decreasing and independent way. Based on the minimum square method, an asymptotic CN value was determined, which, in turn, resulted in an equation in function of rainfall. Other methodologies applied in the CN determination are also based on ordered rainfall-runoffevents, however, this procedure was carried out to identify the spatial distribution of CN, taking into account the geomorphological characteristics of the watershed. At first, only two CN values were considered, then CN numbers were set equal to those obtained through the combination between soil classes and soil use maps. For all the methods, 3 values of λ (Ia/S relationship) were considered: 0.2, 0.05, 0.02, all of them used for S calculation, and further Q estimation, thus allowing to infer about their behavior. Finally, by means the application of three precision statistics, it was evaluated the best method for CN determination, as well as the λvalues more closely approximates the Q estimated to the observed one. For that, 166 rainfall-runoff events were taken into consideration. It was also observed that some methods were effective in the Q estimation, especially those based on rainfall-runoff events. CN determination based only on the land use and soil classesmaps did not show good results, even considering the 3 soil moisture antecedent conditions. Finally, the best estimates resulted from the methods based on the λvalues of 0.02 and 0.05.
URI: http://repositorio.ufla.br/jspui/handle/1/12137
Appears in Collections:Recursos Hídricos - Mestrado (Dissertações)



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