Regression analysis of rainfall-runoff data from an arid catchment in Oman

There is a pressing need to improve capability to predict the hydrological responses of arid and semi-arid catchments. The literature indicates that physically-based rain fall-runoff models are not yet able to meet this challenge. Simple empirical or semi-empirical models may perform equally well or better, and provide basic but important information into catchment functioning. In this context, hourly data from 36 rainfall-runoff events in Wadi Ahin, a 734 kill catchment in the Sultanate of Oman, are analysed. Runoff volumes and peaks are regressed against descriptors of rainfall characteristics and antecedent conditions. The controls on runoff are found to be: rainfall volume, rainfall peak, rainfall spatial location arid variability, and antecedent wetness. Simple linear relationships between runoff peak arid volume, and rainfall Volume produce the best predictions, and robust prediction confidence limits. We speculate that application of physically-based models will not produce better predictions, but will allow us to test hypotheses about the underlying hydrological processes.