Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast

Joint Authors

Chen, Junfei
Li, Ming
Wang, Weiguang

Source

Mathematical Problems in Engineering

Issue

Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2012-09-24

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Civil Engineering

Abstract EN

Drought is part of natural climate variability and ranks the first natural disaster in the world.

Drought forecasting plays an important role in mitigating impacts on agriculture and water resources.

In this study, a drought forecast model based on the random forest method is proposed to predict the time series of monthly standardized precipitation index (SPI).

We demonstrate model application by four stations in the Haihe river basin, China.

The random-forest- (RF-) based forecast model has consistently shown better predictive skills than the ARIMA model for both long and short drought forecasting.

The confidence intervals derived from the proposed model generally have good coverage, but still tend to be conservative to predict some extreme drought events.

American Psychological Association (APA)

Chen, Junfei& Li, Ming& Wang, Weiguang. 2012. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1029834

Modern Language Association (MLA)

Chen, Junfei…[et al.]. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast. Mathematical Problems in Engineering No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-1029834

American Medical Association (AMA)

Chen, Junfei& Li, Ming& Wang, Weiguang. Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1029834

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1029834