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Automatic calibration of arid rainfall-runoff model for Wadi Thara Western Kingdom of Saudi Arabia

Input parameter calibration to rainfall-runoff models is the most critical stage of the overall flood modeling processes, where the input parameters values are adjusted to make the simulated flood hydrographs fit the corresponding records. Wadi Thara (275 km2) in the Western Kingdom of Saudi Arabia (KSA) is selected and hourly rainfall data are extracted from the paper charts. Five-minute observed runoffs are analysed and ASTER Digital Elevation Model (DEM) with 30-m pixel size is processed to compute automatically the morphometric parameters and to extract the geometric features of the catchment. hydrological soil group map and land cover/land use (LCLU) map are developed to estimate the excess rainfall using composite SCS curve number (SCS-CN). Clark unit hydrograph (Clark-UH) time of concentration approach is used to transform the excess rainfall to flood hydrograph. Four parameters are chosen for calibration, which are SCS-CN, initial abstraction (Ia), Clark-UH time of concentration (Tc) and Clark storage coefficient (R). Nine observed runoff events are selected for modeling; seven different events are chosen for parameter calibration and two for parameter validation. This study focuses on calibrating the peak flow only, which is one of the most critical hydrograph characteristics in rainfall-runoff modeling in arid regions. Calibration process produced exact peak flow for five out of seven events and one event with very close match (–2.6% of change). On the average parameters, calibrations for SCS-CN, Ia, Tc and R are 81.6, 11.0 mm, 3.81 h and 1.88 h, respectively, where R is the most highly variable parameter with 139% coefficient of variation. The reason behind this variation may be because of the local search algorithms usage, which produce local minimum objective function and assign optimized value to the parameter that is not in existence, also the selected hydrological methods are lumped, where the spatial rainfall variation and the other input parameters are not taken into consideration. In the validation process, the four average calibrated parameters are used to validate two events, the first event produced a peak flow with –50% change, which can be considered as relatively high, while the second event resulted in a peak flow with –6.0% change). The value of calibrated parameters is very valuable and can be used in the future for the same and similar catchments. More optimization module applications may be needed with global search algorithm and multiple objective functions to enhance the estimated parameters in future studies.