2023
DOI: 10.1080/23249676.2023.2230892
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Estimation of rainfall and streamflow missing data under uncertainty for Nile basin headwaters: the case of Ghba catchments

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Cited by 2 publications
(2 citation statements)
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“…Water demand forecasting is a difficult task, because data is often limited and there are many variables that could affect demand [3,23,24]. For example, the data may be inaccurate because of the nature and quality of the data, and the variables that are thought to affect water demand can be very different from one forecast to the next [25][26][27]. Additionally, the forecast horizon and periodicities can also vary.…”
Section: Introductionmentioning
confidence: 99%
“…Water demand forecasting is a difficult task, because data is often limited and there are many variables that could affect demand [3,23,24]. For example, the data may be inaccurate because of the nature and quality of the data, and the variables that are thought to affect water demand can be very different from one forecast to the next [25][26][27]. Additionally, the forecast horizon and periodicities can also vary.…”
Section: Introductionmentioning
confidence: 99%
“…to properly characterize the catchments properties using target parameter prediction depending on data input [20,21]. Furthermore, models that have good measured and simulated data agreement can be applied to a variety of purposes, including assessing the effects of changing input factors like climate change, land-use/land cover (LULC) change, intervention of structures in the river system, and so on which will give a chance to set scenarios and analysis for different adaptation options [22,[23][24][25]. Different regions have used hydrological models, ranging from conceptual to fully physically based distributed models.…”
Section: Introductionmentioning
confidence: 99%