4.7 Article

Soft-cooperation via data sharing eases transboundary conflicts in the Lancang-Mekong River Basin

期刊

JOURNAL OF HYDROLOGY
卷 606, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.jhydrol.2022.127464

关键词

Lancang-Mekong River; Data sharing; Information selection; Cascade multi-objective reservoir operation

资金

  1. National Natural Science Foundation of China [92047302, 51861125102]

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Water resources management in the Lancang-Mekong River Basin faces challenges due to geopolitical factors, hydropower dam expansion, and increasing demands for energy, food, and riverine ecosystem preservation. This paper proposes the concept of soft cooperation through data sharing to enhance the adaptive and reliable operation of the water system. The study shows that conflicts mainly exist between sectors rather than among countries, and sharing water storage data significantly improves hydropower production.
Water resources management in the Lancang-Mekong River Basin (LMRB) is challenging in face of the complex trans-national geopolitical context, the acceleration of hydropower dam expansion, and the growing demands for energy, food, and riverine ecosystem preservation across the basin. Centralised management through coordinated operation of all the basin water infrastructures (hard cooperation) across the river basin is ideal but hard to achieve given the existing geopolitical context of the region. To overcome these barriers and facilitate a more adaptive and reliable operation of the LMRB's water system, this paper focuses on the concept of soft -cooperation, i.e. the idea of indirectly fostering cooperation by sharing data across countries to inform the noncooperative (or independent) operation of their systems. Here, we first quantify existing riparian conflicts and synergies for the non-cooperative scenario, where upstream and downstream act independently without any form of cooperation, and for the hard cooperation configuration, where an ideal centralised operator jointly operates all the infrastructures. Then a soft cooperation scheme assuming data sharing across riparian countries is evaluated. The most effective and informative data is selected via machine learning and used to inform the design of the river reservoir system operation via evolutionary multiobjective direct policy search. Results show that the riparian conflicts around water mainly exist between the sectors, i.e. hydropower production vs ecosystem conservation, rather than among countries. For reservoirs with various capacities and locations, the value of information varies. Generally, sharing data about the water currently available in the different river storages results in a large improvement in hydropower production. This study highlights the value of appropriate data sharing and selection in water system operation as an indirect way of promoting cooperation in trans boundary river management.

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