Hydrograph separation and development of empirical relationships using single-parameter digital filters

A reliable hydrograph separation method is necessary for surface runoff modeling and hydrological studies. This paper investigates and compares the separation characteristics of two single-parameter digital filters, which are herein referred to as the one-parameter algorithm and the conceptual method. The application of the one-parameter algorithm was found to be restricted to low and medium baseflow separations, with a maximum separation limit of 50% of the total runoff hydrograph. The one-parameter algorithm was also observed to produce unrealistic sharp peaks under the peaks of the measured hydrograph when recession constant is smaller than 0.96. On the other hand, the conceptual method is applicable even for catchments fed largely by groundwater discharge. However, a reliable estimation of recession constant is a prerequisite for applying the conceptual method for large baseflow separations. Based on the hydrograph separation results, useful empirical relationships were developed for a partially urbanized watershed to estimate total runoff and direct runoff from the measured rainfall depth. The relationships between rainfall depth and total runoff depth and rainfall depth and direct runoff depth were found to be well represented by linear equations. The empirical relationships were then applied to estimate the long-term contribution of baseflow and surface runoff to total runoff at the study site. Baseflow was found to contribute about 58–61% of the annual total runoff.

New blind source estimation methods based on constant modulus criterion

This thesis presents two novel algorithms for blind chancel equalization (BCE) and blind source separation (BSS). Beside these, a general framework for global convergent analysis is proposed. Finally, the open problem of equalising a non-irreducible system is answered by the algorithm proposed in this thesis.

Generation of total runoff hydrographs using a method derived from a digital filter algorithm

A reliable prediction of the total runoff hydrograph is necessary for water resources management. This study investigates two approaches to generate total runoff hydrograph by adding baseflow to direct runoff hydrographs. The first approach uses a method, derived from a digital filter algorithm for hydrograph separation, to generate baseflow hydrographs from direct runoff hydrographs. The method appears to perform well in producing the overall shape of the total runoff hydrographs and the acceptable mass balance errors for a year of water cycle. For application, the recession baseflow constant needs to be estimated reliably and the initial baseflow could be approximated to the long-term mean dry weather flow. The second approach assumes a constant baseflow rate. Although this approach is still capable of producing the overall hydrograph shape, it yields high mass balance errors in the total runoff hydrographs for both monthly and long-term periods. Further analysis shows that two-third of the mass balance errors are contributed from periods with direct runoff, implying that the constant baseflow assumption could introduce significant errors into the computations of total runoff hydrograph