الفهرس 
Development and evaluation of a rainfall estimation algorithm over the nile basin using remote sensing
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Abstract
The lack of data is a major problem considering that rainfall is the main input to the hydrological models used to forecast and simulate the flow at the hydrological stations located in the nile basin. So, it is essential and necessary to use remote sensing applications to estimate the expected rainfall over any selected area. The nile forecast system (NFS) of rainfall estimation algorithm is based on the cold cloud duration (CCD) technique which depends on single band technique of Thermal Infrared (IR) 10.8 om. This algorithm was improved in 2009 to take advantage of the METEOSAT second generation (MSG) satellite which provides more IR bands. The Improved NFS algorithm uses the multi-spectral IR technique which depends on the CCD and the brightness indices of other IR bands (10.8, 9.7, 12.0, and 13.4 om). In this study, we will be evaluating rainfall estimation algorithm, recently developed by bellerby (2009) to utilize the multi-spectral IR bands to improve the rainfall estimation. This will be achieved through evaluating the cold cloud duration (CCD) rainfall estimation technique over Nile sub-basins in the period (2010-2015) in order to quantify the performance of this technique over the Nile basin and evaluating multi-spectral satellite estimation algorithm over Nile Basin. We will compare the satellite estimates with the observed data in the Nile Basin and on the scale of the mean area precipitation. Results from the analysis showed that the multi-spectral IR rainfall product is better than single band product which means that the additional brightness indices for the IR bands enhance the rainfall estimation in NFS