Citation: Niebuhr, C.M.; Hill, C.; Van Dijk, M.; Smith, L. Development of a Hydrokinetic Turbine Backwater Prediction Model for Inland Flow through Validated CFD Models. Processes 2022, 10, 1310. https:// doi.org/10.3390/pr10071310 Academic Editors: Santiago Lain and Omar Dario Lopez Mejia Received: 23 May 2022 Accepted: 20 June 2022 Published: 4 July 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). processes Article Development of a Hydrokinetic Turbine Backwater Prediction Model for Inland Flow through Validated CFD Models Chantel Monica Niebuhr 1, * , Craig Hill 2 , Marco Van Dijk 1 and Lelanie Smith 3 1 Department of Civil Engineering, University of Pretoria, Pretoria 0001, South Africa; marco.vandijk@up.ac.za 2 Mechanical and Industrial Engineering Department, University of Minnesota-Duluth, Duluth, MN 55812, USA; cshill@d.umn.edu 3 Department of Mechanical Engineering, University of Pretoria, Pretoria 0001, South Africa; lelanie.smith@up.ac.za * Correspondence: chantel.niebuhr@up.ac.za; Tel.: +27-79-427-5190 Abstract: Hydrokinetic turbine deployment in inland water reticulation systems such as irrigation canals has potential for future renewable energy development. Although research and development analysing the hydrodynamic effects of these turbines in tidal applications has been carried out, inland canal system applications with spatial constraints leading to possible blockage and backwater effects resulting from turbine deployment have not been considered. Some attempts have been made to develop backwater models, but these were site-specific and performed under constant operational conditions. Therefore, the aim of this work was to develop a generic and simplified method for calculating the backwater effect of HK turbines in inland systems. An analytical backwater approximation based on assumptions of performance metrics and inflow conditions was tested using validated computational fluid dynamics (CFD) models. For detailed prediction of the turbine effect on the flow field, CFD models based on Reynolds-averaged Navier–Stokes equations with Reynolds stress closure models were employed. Additionally, a multiphase model was validated through experimental results to capture the water surface profile and backwater effect with reasonable accuracy. The developed analytical backwater model showed good correlation with the experimental results. The model’s energy-based approach provides a simplified tool that is easily incorporated into simple backwater approximations, while also allowing the inclusion of retaining structures as additional blockages. The model utilizes only the flow velocity and the thrust coefficient, providing a useful tool for first-order analysis of the backwater from the deployment of inland turbine systems. Keywords: hydrokinetic; computational fluid dynamics; backwater; inland hydrokinetic; axial flow turbines 1. Introduction Research and development of hydrokinetic (HK) devices in canal systems is increasing in popularity due to increasing electricity costs and the drive towards finding renewable energy sources with unconventional applications [1–3]. Although most development has focussed on tidal applications, multiple opportunities exist for the deployment of HK systems within inland water infrastructure (e.g., canal systems) [1]. However, the placement of such a device can have significant water level and hydrodynamic energy loss effects [4]. Prediction of the hydrodynamic effects of hydrokinetic turbines in canal systems remains an important pre-development objective. Due to the nature of canal design, these systems usually have flat slopes and subcritical flow regimes. Therefore, the analysis of backwater effects from blockages is critical for the prevention of flooding and water loss. This is especially important in array schemes where the cumulative effect of multiple devices can exceed the top of the channel and cause it to overtop. Processes 2022, 10, 1310. https://doi.org/10.3390/pr10071310 https://www.mdpi.com/journal/processes