Multi-model ensemble hydrological simulation of Yalong River Basin based on artificial neural network
- Article
- Figures
- Metrics
- Preview PDF
- Reference
- Related
- Cited by
- Materials
Abstract:
In order to reduce the influence of the uncertainty of hydrological models on hydrological simulation and improve the actual application effect of the models, we took the Yalong River basin as an example, and constructed four commonly used hydrological models: SWAT model, BTOPMC model, VIC model, and DTVG model. We conducted independent simulation using these models with the same input data and simulation time range. Then, we calculated the simulation results of the four models using the Multi-model Ensemble Out put System independently developed by Beijing Normal University based on the artificial neural net work method to obtain the flow hydrograph and error, and compared them with the results of the four models. The results indicated that the correlation coefficient and Nash efficiency coefficient of the multi-model ensemble simulation were both above 0.90, which was a great improvement in accuracy than the independent models. The results were stable and consistent with the actual runoff process. These indicated that the multi-model ensemble hydrological simulation had good applicability in this river basin.
Keywords:
Project Supported:
Clc Number:
Mobile website
® 2024 All Rights Reserved
冀公网安备13010502002656号
冀公网安备13010502002656号