Ensemble flood simulation for the typical catchment in humid climatic zone by using multiple hydrological models
<p>A good performance of hydrological model for flood simulation is of critical importance for flood forecasting. Taking Yandu River catchment, as the study area, three hydrological models (i.e. Xin'anjiang model, TOPMODEL, artificial neural network model) and a multi-model ensemble simul...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-09-01
|
| Series: | Proceedings of the International Association of Hydrological Sciences |
| Online Access: | https://piahs.copernicus.org/articles/383/213/2020/piahs-383-213-2020.pdf |
| Summary: | <p>A good performance of hydrological model for flood simulation is
of critical importance for flood forecasting. Taking Yandu River catchment,
as the study area, three hydrological models (i.e. Xin'anjiang model,
TOPMODEL, artificial neural network model) and a multi-model ensemble
simulation method (i.e. entropy-based method) were applied to simulate the
hydrological processes of 30 flood events occurring in 1981–1987. The
performance of the ensemble members and multi-model ensemble simulation
method was evaluated by comparing indicators of Nash-Efficiency coefficient,
errors in root mean square, peak occurrence time, and relative errors of
flood peak discharge, event runoff depth. Results show that the
three hydrological models perform well for hydrological simulation of all 30
storm floods with Nash and Sutcliffe Efficiency coefficient of above 0.75
and relative error of less than 10 %. However, different model exhibits a
difference in simulation errors of peak discharge and peak occurrence time.
For example, BP model has the smallest error of 3.78 % for peak discharge
simulation while that of Xin'anjiang model and TOPMODEL are 20.9 % and
24.7 % respectively. The entropy-based ensemble simulation method improved
flood simulation accuracy to some extent for all evaluation criteria
comparing to the three hydrological models. It is feasible to apply
entropy-based ensemble approach for improving accuracy of flood forecasting
in humid regions of China.</p> |
|---|---|
| ISSN: | 2199-8981 2199-899X |