Shaukat Muhammad Haroon, Al-Dousari Ahmad, Hussain Ijaz, Faisal Muhammad, Ismail Muhammad, Mohamd Shoukry Alaa, Elashkar Elsayed Elsherbini, Gani Showkat
Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
Department of Geography, Kuwait University, Kuwait, Kuwait.
PeerJ. 2020 Aug 24;8:e9729. doi: 10.7717/peerj.9729. eCollection 2020.
A temporal imbalance in the water availability, which is consistently below average or more than average rainfall, can lead to extremely dry or wet conditions. This impacts on agricultural yields, water resources and human activities. Weather instabilities and trends of wet/dry events have not yet been explored in Pakistan. In this study, we have two-fold objectives: (1) evaluate the weather instabilities, and (2) the trend of dry/wet events of selected stations of Pakistan. To observe weather instabilities, we used Mean Marginal Hilbert Spectrum (MMHS) and Continuous Wavelet Power Spectrum (CWPS) as meteorological series are mostly non-linear and non-stationary. We used Ensemble Empirical Mode Decomposition (EEMD) for the analysis of temporal characteristics of dry/wet events. We found that all stations are facing severe weather instabilities during the short period of 5 and 10 months using MMHS method and CWPS has shown the weather instabilities during 4 to 32 months of periodicity for all stations. Ultimately, the achieved short-term weather instabilities indicated by MMHS is consistent with CWPS. In summary, these findings might be useful for water resource management and policymakers.
水资源可用性的时间失衡，即降雨量持续低于或高于平均水平，可能导致极端干燥或潮湿的状况。这会影响农业产量、水资源和人类活动。巴基斯坦尚未对天气不稳定以及干湿事件的趋势进行研究。在本研究中，我们有两个目标：（1）评估天气不稳定情况，（2）研究巴基斯坦选定站点的干湿事件趋势。为了观测天气不稳定情况，我们使用了平均边际希尔伯特谱（MMHS）和连续小波功率谱（CWPS），因为气象序列大多是非线性和非平稳的。我们使用集合经验模态分解（EEMD）来分析干湿事件的时间特征。我们发现，使用MMHS方法时，所有站点在5个月和10个月的短时间内都面临严重的天气不稳定，而CWPS显示所有站点在4至32个月的周期内存在天气不稳定情况。最终，MMHS所显示的短期天气不稳定情况与CWPS一致。总之，这些发现可能对水资源管理和政策制定者有用。
