Deriving Optimal Daily Reservoir Operation Scheme with Consideration of Downstream Ecological Hydrograph Through A Time-Nested Approach

Deriving Optimal Daily Reservoir Operation Scheme with Consideration of Downstream Ecological Hydrograph Through A Time-Nested Approach
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DOI:
10.1007/s11269-015-1005-z
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发表时间:
2015-04
影响因子:
4.3
通讯作者:
Duan Chen;Ruonan Li;Qiuwen Chen;Desuo Cai
Duan Chen;Ruonan Li;Qiuwen Chen;Desuo Cai
中科院分区:
环境科学与生态学3区
文献类型:
--
作者:
Duan Chen;Ruonan Li;Qiuwen Chen;Desuo Cai

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在鱼类的特殊生命阶段,如产卵期,生态流量需求(EFR)不仅与流量有关,而且与流量的日变化有关。因此,在日常基础上优化水库生态友好运行更为合适。直接制定和求解基于日常的优化模型会涉及大量的决策变量和约束,这可能会导致不利的时间消耗和不可靠的解决方案。本文提出了一种考虑下游生态水文曲线的时间嵌套方法,推导出水库日调度的最优方案。它将决策变量从以月为基础缩小到以10天为基础,最后缩小到以日为基础。提出的方法应用于中国西南雅砻江的两个梯级水库,在那里需要每天的生态流量来保护当地鱼类的栖息地。chongi)。结果表明,该方法可以有效地推导出考虑下游EFR的鱼类栖息地保护日优化操作方案。此外,该方法在处理复杂优化问题时,大大提高了全局搜索能力。
The ecological flow requirement (EFR) during special life stages of species, for instance the fish spawning period, concerns not only the flow rate, but also daily changes in the flow rate. Therefore, it is more appropriate to optimize ecologically-friendly reservoir operation on a daily base. Directly formulating and solving a daily-based optimization model would involve a large number of decision variables as well as constraints, which may lead to unfavourable time consumption and unreliable solutions. This study proposes a time-nested approach to derive an optimal daily reservoir operation scheme with consideration of the downstream ecological hydrograph. It scales down the decision variables from monthly-base to 10-day base and finally to daily-base. The proposed method was applied to two cascaded reservoirs in the Yalong River in southwest China, where a daily ecological flow is required to conserve the habitats of an indigenous fishSchizothorax chongi(S. chongi). The results showed that the developed method could efficiently derive a daily optimal operational scheme with the consideration of downstream EFR for fish habitat conservation. In addition, the method greatly improves global searching ability in dealing with complex optimization problems.