NDLI: Application of several artificial intelligence models and ARIMAX model for forecasting drought using the Standardized Precipitation Index

Content Provider	Springer Nature Link
Author	Jalalkamali, A. Moradi, N. Moradi, M.
Copyright Year	2014
Abstract	Drought is among the most important natural disasters influencing different aspects of human life. In recent decades, intelligent techniques have shown to be highly capable of modeling and forecasting nonlinear and dynamic time series. Hence, the present study aimed to forecast drought using and comparing the multilayer perceptron artificial neural network (MLP ANN), adaptive neuro-fuzzy inference systems (ANFIS), support vector machine (SVM) model, and the autoregressive integrated moving average (ARIMAX) multivariate time series. To this end, the precipitation data obtained from the Yazd synoptic station for a 51-year statistic period were used. Moreover, the humidity levels for short-term (3 and 6 months) and long-term (9, 12, 18, and 24 months) periods were calculated using the Standardized Precipitation Index (SPI). Next, based on the results of calculations, the 1961–2002 period was selected as the control group and the 2003–2012 period was selected as the experimental group. In order to forecast the SPI for the t + 1 period, values of SPI, precipitation, and temperature of previous eras were used. Results indicated that in a 9-months period (as the timescale), the ARIMAX model gives SPI values and forecast drought with more precision than the SVM, ANFIS, and MLP models.
Starting Page	1201
Ending Page	1210
Page Count	10
File Format	PDF
ISSN	17351472
Journal	International Journal of Environmental Science & Technology
Volume Number	12
Issue Number	4
e-ISSN	17352630
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-11-26
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	ANN Ecotoxicology SVM Water Management Forecasting SPI Waste Water Technology Aquatic Pollution Environment ANFIS Yazd Water Pollution Control Drought ARIMAX Environmental Chemistry Environmental Science and Engineering Soil Science & Conservation
Content Type	Text
Resource Type	Article
Subject	Environmental Chemistry Environmental Engineering Agricultural and Biological Sciences

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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