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DOI	10.3390/atmos12101248
	Forecasting of Drought: A Case Study of Water-Stressed Region of Pakistan
	Kumar, Prem; Shah, Syed Feroz; Uqaili, Mohammad Aslam; Kumar, Laveet; Zafar, Raja Fawad
通讯作者	Shah, SF (corresponding author), Mehran Univ Engn & Technol, Dept Basic Sci & Related Studies, Jamshoro 76090, Pakistan.
来源期刊	ATMOSPHERE
EISSN	2073-4433
出版年	2021
卷号	12 期号:10
英文摘要	Demand for water resources has increased dramatically due to the global increase in consumption of water, which has resulted in water depletion. Additionally, global climate change has further resulted as an impediment to human survival. Moreover, Pakistan is among the countries that have already crossed the water scarcity line, experiencing drought in the water-stressed Thar desert. Drought mitigation actions can be effectively achieved by forecasting techniques. This research describes the application of a linear stochastic model, i.e., Autoregressive Integrated Moving Average (ARIMA), to predict the drought pattern. The Standardized Precipitation Evapotranspiration Index (SPEI) is calculated to develop ARIMA models to forecast drought in a hyper-arid environment. In this study, drought forecast is demonstrated by results achieved from ARIMA models for various time periods. Result shows that the values of p, d, and q (non-seasonal model parameter) and P, D, and Q (seasonal model parameter) for the same SPEI period in the proposed models are analogous where p is the order of autoregressive lags, q is the order of moving average lags and d is the order of integration. Additionally, these parameters show the strong likeness for Moving Average (M.A) and Autoregressive (A.R) parameter values. From the various developed models for the Thar region, it has been concluded that the model (0,1,0)(1,0,2) is the best ARIMA model at 24 SPEI and could be considered as a generalized model. In the (0,1,0) model, the A.R term is 0, the difference/order of integration is 1 and the moving average is 0, and in the model (1,0,2) whose A.R has the 1st lag, the difference/order of integration is 0 and the moving average has 2 lags. Larger values for R-2 greater than 0.9 and smaller values of Mean Error (ME), Mean Absolute Error (MAE), Mean Percentile Error (MPE), Mean Absolute Percentile Error (MAPE), and Mean Absolute Square Error (MASE) provide the acceptance of the generalized model. Consequently, this research suggests that drought forecasting can be effectively fulfilled by using ARIMA models, which can be assist policy planners of water resources to place safeguards keeping in view the future severity of the drought.
英文关键词	forecasting ARIMA Standardized Precipitation Evapotranspiration Index (SPEI) mitigation drought
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000711909900001
WOS关键词	INDEX ; PRECIPITATION ; EVAPOTRANSPIRATION ; MODEL ; ARIMA ; CHALLENGES ; PREDICTION ; SCALE
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/368357
作者单位	[Kumar, Prem; Shah, Syed Feroz] Mehran Univ Engn & Technol, Dept Basic Sci & Related Studies, Jamshoro 76090, Pakistan; [Uqaili, Mohammad Aslam] Mehran Univ Engn & Technol, Dept Elect Engn, Jamshoro 76090, Pakistan; [Kumar, Laveet] Mehran Univ Engn & Technol, Dept Mech Engn, Jamshoro 76090, Pakistan; [Zafar, Raja Fawad] Sukkur Inst Business Adm Univ, Dept Math, Sukkur 65200, Pakistan
推荐引用方式 GB/T 7714	Kumar, Prem,Shah, Syed Feroz,Uqaili, Mohammad Aslam,et al. Forecasting of Drought: A Case Study of Water-Stressed Region of Pakistan[J],2021,12(10).
APA	Kumar, Prem,Shah, Syed Feroz,Uqaili, Mohammad Aslam,Kumar, Laveet,&Zafar, Raja Fawad.(2021).Forecasting of Drought: A Case Study of Water-Stressed Region of Pakistan.ATMOSPHERE,12(10).
MLA	Kumar, Prem,et al."Forecasting of Drought: A Case Study of Water-Stressed Region of Pakistan".ATMOSPHERE 12.10(2021).