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P. A. Kagoda, et al., “Application of Radial Basis Function Neural Networks to Short-Term Streamflow Forecasting,” Physics and Chemistry of the Earth, Parts A/B/C, Vol. 35, No. 13-14, 2010, pp. 571-581. doi:10.1016/j.pce.2010.07.021

has been cited by the following article:

• TITLE: Estimation of Extreme Flows in Nkana River to Verify the Adequacy of Naming’ongo Bridge Waterway

  AUTHORS: Zacharia Katambara, Joseph J. Msambichaka, Joseph Mkisi

  KEYWORDS: Extreme Flow; Australian Water Balance Model; Stream Flow Simulations; Catchment Delineation; Parameter Estimation

  JOURNAL NAME: Engineering, Vol.5 No.3, March 19, 2013

  ABSTRACT: The response by the government of Tanzania to food security and poverty alleviation in the Naming’ongo area in Mbozi District has been to develop Naming’ongo irrigation scheme as well as construct a bridge across River Nkana to connect the farms and other parts of the district to facilitate a reliable transportation of the produce to the market. The Australian Water Balance Model that was calibrated by using 10 years data from a nearby sub-catchment of Mbarali. The Naming’ongo Sub-catchment was delineated form a 30 m digital elevation model. The observed rainfall was obtained from Mbozi Meteorological station. The study approximated the peak flows in River Nkana for a return period of 50 years to be slightly above 560 m3/s. This was considered to be adequate for the proposed structure. The study recommends that when undertaking human activities such as deforestation and cultivation an account for soil and environmental conservation should be considered. While it is necessary to establish a monitoring system within the catchment, the designs of future hydraulic structures should incorporate stream flow measuring facilities.