Hysteresis sensitive neural network for modeling rating curves

Hysteresis is sometimes exhibited in rating curves representing the stage-discharge relationships at stream gauging locations. In practice, this creates a problem for hydrologists and makes the deduction of discharges, from regularly measured stages, rather difficult. Different approaches have been proposed for modeling such rating curves. A commonly used approach in the Nile river gauging stations is to develop two rating curves for the rising and falling phases of flood waves. However, this approach involves subjective judgment and may produce separation in the deduced discharge hydrograph. This paper proposes an artificial neural network methodology for providing a more accurate and practical solution to this problem. The aim of the study is to investigate the potential employing neural networks for modeling stage-discharge relationships at specific stream locations, A simple three-layer back propagation neural network is introduced for developing rating curves at two Nile gauging stations. The proposed technique avoids drawbacks in current practice such as subjectivity in classifying observations into failing and rising sets, and separation in the deduced discharge hydrograph.