Logistic Regression Analysis for Spatial Patterns of Drought Persistence. (22nd November 2021)

• Record Type: Journal Article
• Authors: Niaz, Rizwan; Zhang, Xiang; Iqbal, Nouman; Almazah, Mohammed M.A.; Hussain, Tajammal; Hussain, Ijaz
• Other Names: Li Feng Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-11-22
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/3724919
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Drought is one of the natural hazards with potentially significant impacts on society, economy, and other natural resources over the globe. However, the understanding of drought characteristics and its persistence can significantly help to reduce the potential impacts of drought. Moreover, the knowledge about the spatiotemporal pattern of seasonal drought frequency and drought persistence is important for water resource management, agricultural development, energy consumption, and crop yields. Therefore, the present study is employed to examine the seasonal drought frequency and drought persistence in the region. In this regard, the standardized precipitation index (SPI) at the three-month time scale was used to determine meteorological drought. Furthermore, the logistic regression model is used to calculate the odds and probability of drought persistence from one season to the next for the selected stations by identifying the spatial pattern of seasonal drought frequency and persistence. The potential of the current analysis is validated on six selected stations of the northern area of Pakistan. The outcomes related to the current analysis provide the basis for taking more considerations on early warning systems and help to make the valuable decision for water resource management and agriculture sectors in Pakistan.