Estimation of rainfall and streamflow missing data under uncertainty for Nile basin headwaters: the case of Ghba catchments

The datasets in semi-arid and arid regions of developing countries are known for their long period of missing data. To approximate any missing data interpolation or estimation techniques are frequently used. The current study focuses on applying the concept of data uncertainty by setting out different percentages of missing data from the known dataset at all target stations calibrated and validated against the ensemble simulation interpolation and reconstitution approach by contrasting findings with voluntarily excluded data that will be re-estimated using the various approaches selected. While testing the nearby stations (6 to 50 km) for filling the missing data were used. The tests on the selected stations shows that the better estimates of precipitation and streamflow are the ID and the NR methods. Thus, the methods that revealed a better estimation were used for filling in missing data of the respective stations to undergo a water resource study.