Improving Information-Based Coordinated Operations in Interbasin Water Transfer Megaprojects: Case Study in Southern India
Publication: Journal of Water Resources Planning and Management
Volume 147, Issue 11
Abstract
Globally, interbasin water transfer (IBWT) projects worth $2.7 trillion seek to address existing and potential future water scarcity concerns. IBWTs present a challenging decision context with complex operational dynamics and conflicting objectives. Information-based coordination between donor and recipient basins is likely to play a role in the success of these large-scale projects, so it is important to explore its potential impact. We developed an IBWT design framework to quantify the multiobjective gains from information coordination between participating basins. For a large-scale IBWT in Southern India, we compared four design paradigms in which transfer decisions are based on (1) the storage states of both reservoirs (cooperative), (2) the storage state of the donor reservoir only (noncooperative), (3) the rule proposed by regional authorities, and (4) status quo (no transfer). The evolutionary multiobjective direct policy search (EMODPS) framework was used to discover the state-aware control strategies that compose the trade-offs between flood protection, demand satisfaction, and environmental flow maintenance. We found that cooperative strategies are substantially more efficient in balancing conflicting objectives, utilizing much lower annual transfers () compared with noncooperative strategies (), and both outperform the proposed regional rule ().
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The observed inflow time series for Perur gauge station was obtained from the India-WRIS website (https://indiawris.gov.in/wris/#/). The observed inflow time series for the Nagarjuna Sagar reservoir was provided with sharing restrictions. However, the synthetic inflow time series was generated from that data can be shared. Other codes generated or used for IBWT model simulation-optimization and plotting codes are available from corresponding author by request. Data related to demand calculation are provided in the section “Description of Participating Basins and IBWT.”
Acknowledgments
The authors acknowledge the support of DST-SERB early career research award number ECR/2015/000355. The authors thank the Central Water Commission (CWC) and the Irrigation and CAD Department, Telangana, for providing the data. Ajay Bhave is funded by the Water Security and Sustainable Development Hub funded by the UK Research and Innovation’s Global Challenges Research Fund (GCRF), Grant No. ES/S008179/1.
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Journal of Water Resources Planning and Management
Volume 147 • Issue 11 • November 2021
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Received: Nov 14, 2020
Accepted: Jun 1, 2021
Published online: Aug 25, 2021
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