A reasonable flood season delineation can effectively implement staged reservoir scheduling and improve water resource efficiency. Therefore, this study is aimed at analyzing the flood period segmentation and optimizing the staged flood limit water levels (FLWLs) for a multi-purpose reservoir, the Longtan Reservoir, China. The rainfall seasonality index (SIP) and the runoff seasonality index (SIR) are used to evaluate the feasibility and rationality of the flood period staging. The fractal method is then used to segment the flood season. Finally, the design flood is carried out to optimize the staged FLWLs. The results show that the SI is an effective indicator for judging the feasibility and verifying the rationality of flood segmentation. The flood period can be segmented into the pre-flood season (12 April–29 May), the main flood season (30 May–3 September), and the post-flood season (4 September–9 November). The FLWLs in the main flood and the post-flood season can be raised by 2.05 m and 3.45 m, and the effective reservoir capacity is increased by 5.810 billion m3 and 6.337 billion m3, according to the results of the flood season division.
Most ecological operation charts of hydropower stations have focused on the average ecological benefits over a long period of time, while the possible ecological damage caused by flood or drought is often overlooked or averaged out. This study proposed a new hydropower-ecological operation chart of cascade hydropower stations, in which limited ecological curves were introduced and optimized to alleviate the negative impacts caused by drought or flood events on fish habitat and to maintain the long-term average habitat quality without reducing the power generation. The optimal ecological discharge range at a given ecological conservation target was determined from the weighted usable area-discharge curve using the physical habitat simulation model, and then the upper and lower limited ecological curves were obtained by reverse calculation, which together with the conventional operation chart (COC) formed the ecological operation chart (EOC). The limited ecological curves were further optimized with the goal of reducing the ecological damage frequency in wet and dry extremes, and then incorporated into COC to form the optimized ecological operation chart (OEOC). A case study was performed with Jasajiang (JS) and Madushan (MDS) cascade reservoirs on the Yuan River in southwestern China. The results show that the EOC that takes into account the ecological benefits can reduce the ecological damage frequency compared to the COC, but potentially at the expense of the overall ecological benefit. However, further optimization of limited ecological curves in OEOC makes it possible to obtain higher short-term ecological benefit and lower ecological damage frequency with the loss of lower overall ecological benefit. Specifically, OEOC is helpful to reduce the ecological damage frequency and improve the power generation and overall ecological benefit at an ecological target of 60 ~ 80%. Notably, at an ecological target of 80%, OEOC results in a 4.1% increase in power generation and a 11.25% decrease in ecological damage frequency for JS-MDS cascade reservoirs compared with that of COC, respectively.
In order to solve the problem that the existing optimal operation model of reservoirs cannot coordinate the contradiction between long-term and short-term benefits, the paper nested the long-term optimal operation and mid-long-term optimal operations of reservoirs and established the multi-objective optimal operation nested model of reservoirs. At the same time, based on this model, the optimal control mode is determined when there are errors in the predicted runoff. In the optimal scheduling nested model, the dynamic programming algorithm is used to determine the long-term optimal scheduling solution, and the genetic algorithm is used to solve the mid-long-term optimal scheduling. The optimal control mode is determined by three indicators: power generation benefit, water level over limit risk rate and the not-exploited water volume. The results show that, on the premise of meeting the flood control objectives, the nested model optimal dispatching plan has higher benefits than the long-term optimal dispatching plan and the actual dispatching plan, which verifies the superiority of the nested model in the reservoir optimal dispatching problem. When there is error in predicting runoff, among the water level control mode, flow control mode and output control mode, the average power generation benefit of output control mode is 150.05 GW·h, the low-risk rate of water level overrun is 0.29, and the not-exploited water volume is 39,270 m3. Compared with the water level control mode and the flow control mode, the output control mode has the advantages of higher power generation efficiency, lower water level over limit risk rate and less not-exploited water volume. Therefore, from the perspective of economic benefit and risk balance, the output control mode in the optimization scheduling nested mode is the optimal control mode.
Global warming and the intensification of extreme temperature events have been major issues around the world in recent decades. Understanding changes in temperature extremes is critical to assessing and responding to the risks associated with regional temperature change. This paper takes the Longtan watershed as the research object, and 11 extreme temperature indices were calculated based on the meteorological observation data from 1959 to 2017. The Mann-Kendall trend mutation test, Empirical Orthogonal Function, and other methods were used to explore the spatial and temporal distribution characteristics of temperature extremes. Meanwhile, the simulation effects of temperature were analyzed based on 11 CMIP5 climate models, and the extreme temperature change in 2021–2050 under the high emission scenario RCP8.5 and low emission scenario RCP4.5 was estimated. The main results are as follows: both the warm-related indices and the extreme minimum temperature show an increasing trend. The cold-related frequency indices all show a decreasing trend. The spatial distribution of most temperature extremes increases or decreases from southwest to northeast, and the fluctuation is obvious with the alternation of positive and negative positions of the time. In the next 30 years, compared with the reference period 1961–1990, under the RCP4.5, the multiyear average of the Extreme Tmax and the multiyear average of the Extreme Tmin increase by 2.1°C and 0.4°C, respectively, and by 2.0°C and 0.3°C under the RCP8.5. Overall, the frequency of extreme cold events decreases, and the frequency of extreme warm events increases. There is a warming trend in temperature extremes.
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