Estimation of 'drainable' storage – A geomorphological approach. (March 2015) - Biswal, Basudev; Nagesh Kumar, D.
Highlights: Traditional approaches generally suggest that drainable storage in a basin is infinite. Drainable storage–discharge curve is controlled by basin geomorphology. Drainable storage–discharge curve exhibits a transition point. An analytical model is proposed to estimate drainable storage in basins. Abstract: Storage of water within a river basin is often estimated by analyzing recession flow curves as it cannot be 'instantly' estimated with the aid of available technologies. In this study we explicitly deal with the issue of estimation of 'drainable' storage, which is equal to the area under the 'complete' recession flow curve (i.e. a discharge vs. time curve where discharge continuously decreases till it approaches zero). But a major challenge in this regard is that recession curves are rarely 'complete' due to short inter-storm time intervals. Therefore, it is essential to analyze and model recession flows meaningfully. We adopt the well-known Brutsaert and Nieber analytical method that expresses time derivative of discharge ( dQ / dt ) as a power law function of Q : - dQ / dt = kQ α . However, the problem with dQ / dt – Q analysis is that it is not suitable for late recession flows. Traditional studies often compute α considering early recession flows and assume that its value is constant for the whole recession event. But this approach gives unrealistic results when α ⩾ 2, a common case. We address this issue here by using the recently proposed geomorphological recession flow model (GRFM) that exploits the dynamics of active drainage networks. According to the model, α is close to 2 for early recession flows and 0 for late recession flows. We then derive a simple expression for drainable storage in terms the power law coefficient k, obtained by considering early recession flows only, and basin area. Using 121 complete recession curves from 27 USGS basins we show that predicted drainable storage matches well with observed drainable storage, indicating that the model can also reliably estimate drainable storage for 'incomplete' recession events to address many challenges related to water resources.