Abstract
Abstract Ensemble hydrologic forecasting which takes advantages of multiple hydrologic models has made much contribution to water resource management. In this study, four hydrological models (the Xin’anjiang model (XAJ), Simhyd, GR4J, and artificial neural network (ANN) models) and three ensemble methods (the simple average, black box-based, and binomial-based methods) were applied and compared to simulate the hydrological process during 1979–1983 in three representative catchments (Daixi, Hengtangcun, and Qiaodongcun). The results indicate that for a single model, the XAJ model and the GR4J model performed relatively well with averaged Nash and Sutcliffe efficiency coefficient (NSE) values of 0.78 and 0.83, respectively. For the ensemble models, the results show that the binomial-based ensemble method (dynamic weight) outperformed with water volume error reduced by 0.8% and NSE value increased by 0.218. The best performance on runoff forecasting occurs in the Hengtang catchment by integrating four hydrologic models based on binomial ensemble method, achieving the water volume error of 2.73% and NSE value of 0.923. Finding would provide scientific support to water engineering design and water resources management in the study areas.
Highlights
Hydrological models have played essential roles in many applications such as flood-control and disaster reduction [1], water resources utilization [2], hydraulic engineering construction [3], and pollution evaluation [4]
The results showed that the artificial neural network (ANN) performed better on the monthly scale and the other two models are more applicable on the daily scale
Statistical results for data series from 1979 to 1983 in this study show that the annual runoff ranges from 200 to 1,300 mm which approximately covers most of the range of annual variability in previous studies
Summary
Hydrological models have played essential roles in many applications such as flood-control and disaster reduction [1], water resources utilization [2], hydraulic engineering construction [3], and pollution evaluation [4]. Different hydrological models consider different emphases in water cycle simulation, which results in different simulation results. Different models have different applicabilities in different climatic zones and underlying surface conditions (such as terrain, vegetation, urbanization) due to the calculation methods in hydrological processes [9,10,11]. Liu et al compared the applicability of the Xinanjiang model [12], the unsaturated runoff model, and time-variant gain model (TVGM) in arid and semiarid region of China. The results indicated that the TVGM model considering rainfall intensity was the most applicable model in the area. Wang et al compared the applications of the Xinanjiang, Topmodel, This work is licensed under the Creative Commons Attribution 4.0 International
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