Impact of the substitution of reference annual streamflow by monthly streamflow on the potential use of water resources

The consideration of the streamflow seasonality has a high potential to improve the water use. In order to give subsidies to the optimization of water use, it was evaluated the impact of the change of reference annual streamflow by the monthly streamflows in the potential water use throughout the hydrography of Paracatu sub-Basin. It was evaluated the impact on Q7,10 (lowest average streamflow during a 7-day period with an average recurrence of 10 years) and on Q95 (permanent flow present 95% of the time). The use of monthly streamflow to substitute the annual streamflow had a high potential of improvement of water resources use in the sub-Basin studied. The use of monthly Q 7,10 in substitution of annual Q 7,10 increases the potential water use that vary from about 10% in the months of lower water availability to values exceeding 200% in the months with higher availability of surface water resources. The use of monthly Q95 in substitution of the annual Q95 implies in changes oscillating from reduction of 37% in months of higher water restriction to values exceeding 100% in the months of higher availability, so the use of monthly Q95 instead of the annual Q95 enables the more rational and safe use of water resources.

Multivariate statistical analysis to support the minimum streamflow regionalization

ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall of the dry and of the rainy season – Pss and Psc; watershed drainage area – Ad; length of the main river – Lp; total length of the rivers – Lt; and average watershed slope – SL). The results of the principal component analysis pointed out that the variable SL was the least representative for the study, and so it was discarded. The most representative independent variables were Ad and Psc. The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin.

Low-flow estimates in regions of extrapolation of the regionalization equations: a new concept

ABSTRACT Knowledge of natural water availability, which is characterized by low flows, is essential for planning and management of water resources. One of the most widely used hydrological techniques to determine streamflow is regionalization, but the extrapolation of regionalization equations beyond the limits of sample data is not recommended. This paper proposes a new method for reducing overestimation errors associated with the extrapolation of regionalization equations for low flows. The method is based on the use of a threshold value for the maximum specific low flow discharge estimated at the gauging sites that are used in the regionalization. When a specific low flow, which has been estimated using the regionalization equation, exceeds the threshold value, the low flow can be obtained by multiplying the drainage area by the threshold value. This restriction imposes a physical limit to the low flow, which reduces the error of overestimating flows in regions of extrapolation. A case study was done in the Urucuia river basin, in Brazil, and the results showed the regionalization equation to perform positively in reducing the risk of extrapolation.