DONATE

IAHR Document Library


« Back to Library Homepage « Proceedings of the 37th IAHR World Congress (Kuala Lumpur, 2...

Water Allocation Modelling: A Comparison of Ranking and Penalty Approaches in Mike Hydro Basin

Author(s): Bertrand Richaud, Roar Jensen, Eduardo Munoz, Keiko Yamagata, Michael Butts

Linked Author(s): Michael Brian Butts

Keywords: Water allocation, optimization, global ranking, linear programming, penalty function approach

Abstract: The global demand for water continues to grow, driven by population growth, urbanization and rising standards of living, food and energy security. To achieve and maintain sustainable water resources under these unprecedented demands requires both careful management and protection of the resource and efficient allocation of water to match the demands in both space and time. In this paper, we compare two methods of modelling water allocation for water resources management, applying MIKE HYDRO Basin to a highly modified and simplified system based on an actual case study in Sri Lanka. The first is a commonly used global ranking algorithm, based on the assumption that the water user demands can be assigned a priority, irrespective of their location in the river basin and water is distributed according to this global priority. The second uses penalties rather than ranks. Penalties are assigned to units of water user and hydropower deficit as well as the reservoir storage depletion and the water allocation problem solved using linear programming. The initial results show that both methods appear to be efficient in solving the water allocation problem posed. The global ranking approach is easily understood and can be applied in a straightforward manner, once the priorities amongst the different users are identified. The penalty approach requires calibration of the penalties, which may be tedious for practitioners and may well influence the overall results. We propose using the ranking approach to perform an initial screening of water allocation options and constraints that could then be refined by using an optimization method such as the linear approach with penalties evaluated in this study

DOI:

Year: 2017

Copyright © 2024 International Association for Hydro-Environment Engineering and Research. All rights reserved. | Terms and Conditions