Continuous daily hydrograph simulation using duration curves of a precipitation index

Abstract

The paper describes a parsimonious approach for generating continuous daily stream-¯ow time-series from observed daily rainfall data in a catchment. The key characteristic in the method is a duration curve. It is used to convert the daily rainfall information from source rain gauges into a continuous daily hydrograph at the destination river site. For each source rain gauge a time-series of rainfall related`current precipitation index' is generated and its duration curve is established. The current precipitation index re¯ects the current catchment wetness and is de®ned as a continuous function of precipitation, which accumulates on rainy days and exponentially decays during the periods of no rainfall. The process of rainfall-to-runo conversion is based on the assumption that daily current precipitation index values at rainfall site(s) in a catchment and the destination site's daily¯ows correspond to similar probabilities on their respective duration curves. The method is tested in several small catchments in South Africa. The method is designed primarily for application at ungauged sites in data-poor regions where the use of more complex and information consuming techniques of data generation may not be justi®ed.

Using hydro-chemograph analyses to reveal runoff generation processes in a Mediterranean catchment

“…Plot of the daily hydro-chemographical dataset recorded at the main monitoring station (BS16_01) and the 10-min rainfall plot at the Sanza rain gauge. Legend: Numbers indicate the selected events; horizontal lines are representative of the reference parameters ranges; black dashed-double dot lines are for EC maxima in the dry period; black dashed-dotted line is for EC minimum during the dry period; black dashed line is for EC maximum in the wet period; black dotted line is for EC minimum in the wet period; grey dashed line indicates the Q minima in the wet period; grey dotted line indicates the average Q maximum in the wet period; finally, the grey dashed-dotted curve indicates the theoretical annual baseflow curve of the catchment during the period under consideration; yellow box delimitates the wet period events; grey box delimitates the transition period events; red box delimitates the dry period According to Smakhtin and Masse (2000), the corrected antecedent precipitation indexes (CPI) is calculated by adopting the following equation:…”

Bias correction for hydrological impact studies – beyond the daily perspective

“…The correlation between maximum annual discharge and the precipitation in the preceding n days (including the day of maximum discharge as the last day in the series) was computed. Additionally, the current precipitation index (C PI ; Smakhtin and Masse, 2000), which corresponds to the better known antecedent precipitation index (A PI ) plus the precipitation on the current day, was computed iteratively as…”

Improved methods for daily streamflow estimates at ungauged sites

“…Also reliable rainfall gauges which provide inputs for these models do not always exist at the locations of interest. Smakhtin and Masse [2000] suggested that these types of complex and information consuming methods may not always be appropriate in data-poor regions, where comparable results can be achieved by applying the pragmatic techniques of data generation.…”

“…Smakhtin et al [1997] and Smakhtin [1999] illustrated the steps required to use the spatial interpolation technique and flow duration curves to generate complete streamflow time series. Smakhtin and Masse [2000] extended the FDC based spatial interpolation method to generate daily streamflow information at ungauged sites from observed rainfall data. Mohamoud [2008] used a FDC based sequential generation scheme, instead of the spatial interpolation method of Hughes and Smakhtin [1996], to construct daily streamflow series.…”