Index Geophysics

ANN Model-Based Simulation of the Runoff Variation in Response to Climate Change on the Qinghai-Tibet Plateau, China

Precisely quantitative assessments of stream flow response to climatic change and permafrost thawing are highly challenging and urgent in cold regions. However, due to the notably harsh environmental conditions, there is little field monitoring data of runoff in permafrost regions, which has limited the development of physically based models in these regions. To identify the impacts of climate change in the runoff process in the Three-River Headwater Region (TRHR) on the Qinghai-Tibet Plateau, two artificial neural network (ANN) models, one with three input variables (previous runoff, air temperature, and precipitation) and another with two input variables (air temperature and precipitation only), were developed to simulate and predict the runoff variation in the TRHR. The results show that the three-input variable ANN model has a superior real-time prediction capability and performs well in the simulation and forecasting of the runoff variation in the TRHR. Under the different scenarios conditions, the forecasting results of ANN model indicated that climate change has a great effect on the runoff processes in the TRHR. The results of this study are of practical significance for water resources management and the evaluation of the impacts of climatic change on the hydrological regime in long-term considerations.

Chang Juan

Wang Genxu

Mao Tianxu

Sun Xiangyang

Meteorology. Climatology

QC851-999

Hindawi Limited

2017-01-01T00:00:00Z

article

1687-9309

1687-9317

10.1155/2017/9451802

https://doaj.org/article/41425a6be7c14a2ea676752374d1a6e4

Advances in Meteorology, Vol 2017 (2017)

EN

http://dx.doi.org/10.1155/2017/9451802

https://doaj.org/toc/1687-9309

https://doaj.org/toc/1687-9317

Journal Licence: CC BY