DEVELOPING AN EXCELLENT SEDIMENT RATING CURVE FROM ONE HYDROLOGICAL YEAR SAMPLING PROGRAMME DATA: APPROACH (doi: 10.4090/juee.2008.v2n1.021027)

Preksedis Marco Ndomba, Felix W. Mtalo, Ånund Killingtveit

Abstract


This paper presents preliminary findings on the adequacy of one hydrological year sampling programme data in developing an excellent sediment rating curve. The study case is a 1DD1 subcatchment in the upstream of Pangani River Basin (PRB), located in the North Eastern part of Tanzania. 1DD1 is the major runoff-sediment contributing tributary to the downstream hydropower reservoir, the Nyumba Ya Mungu (NYM). In literature sediment rating curve method is known to underestimate the actual sediment load. In the case of developing countries long-term sediment sampling monitoring or conservation campaigns have been reported as unworkable options. Besides, to the best knowledge of the authors, to date there is no consensus on how to develop an excellent rating curve. Daily-midway and intermittent-cross section sediment samples from Depth Integrating sampler (D-74) were used to calibrate the subdaily automatic sediment pumping sampler (ISCO 6712) near bank point samples for developing the rating curve. Sediment load correction factors were derived from both statistical bias estimators and actual sediment load approaches. It should be noted that the ongoing study is guided by findings of other studies in the same catchment. For instance, long term sediment yield rate estimated based on reservoir survey validated the performance of the developed rating curve. The result suggests that excellent rating curve could be developed from one hydrological year sediment sampling programme data. This study has also found that uncorrected rating curve underestimates sediment load. The degree of underestimation depends on the type of rating curve developed and data used.

Keywords


Actual sediment load, Sediment rating curve, Sediment sampling programme, Statistical bias estimator, Sediment load correction factor

Full Text:

PDF


DOI: https://doi.org/10.4090/juee.2013.v2n1.

Locations of visitors to this page
SCImago Journal & Country Rank

ISSN 1982-3932
DOI: 10.4090/juee


Sponsor: