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The medium and long-term runoff simulation can provide a scientific basis for the rational allocation of water resources, which is of great significance to the high-quality development of the basin. Based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and singular spectrum analysis (SSA) two-stage decomposition strategy, the monthly runoff simulation model ICEEMDAN-SSA-WOA-LSTM was constructed by using the long short-term memory network model (LSTM) optimized by the whale optimization algorithm (WOA). It was applied to the simulation of monthly runoff in Stone River Reservoir and compared with the single decomposed ICEEMDAN-WOA-LSTM, SSA-WOA-LSTM and the undecomposed WOA-LSTM models. The results show that the ICEEMDAN-SSA-WOA-LSTM model has the best simulation effect, and the three evaluation indexes in the calibration period and validation period are better than other models, with the root mean square error of 1.278 m3/s, the average absolute error of 0.893 m3/s, and the Nash efficiency coefficient of 0.985 in the validation period. The two-stage decomposition strategy model can significantly improve the accuracy of monthly runoff simulation and can be used for year-round incoming runoff simulation.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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