Abstract

Study regionThe Nile River Basin Study focusThe lack of observed streamflow data at a short time scale poses a critical challenge for calibrating and validating hydrologic models. Therefore, many disaggregation methods were developed, resulting in various relative performances without a clear indication of the optimal choice. This study aims to iteratively assess eight monthly to daily streamflow disaggregation methods at 21 major subbasin outlets in the Nile River Basin (NRB) to identify the best-performing ones. These methods include one proportionality method and seven interpolation methods, i.e., linear, 2nd-order spline, 3rd-order spline, Piecewise Cubic Hermite Interpolating Polynomial (Pchip), Modified Akima (MAkima), mean preserved 2nd-order spline, and mean preserved 3rd-order spline. We assessed these methods using three metrics and visual investigations. New hydrologic insights for the regionThe results showed that the interpolation methods performed well, better than the proportionality method. However, their performances decreased at stations with high daily streamflow fluctuations. The interpolation methods’ performances were similar in mimicking the daily values but significantly different in preserving the mass balance. The mean preserving 3rd-order interpolation method (Lai 22) was the best in preserving the mass balance and capturing the low, moderate and high flows and, therefore, selected to generate the daily flow data in the NRB. The results of this study can guide a reliable method for obtaining daily streamflow data, which is important for the hydrologic and water management studies in the NRB.

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