Department of Civil Engineering, College of Engineering, King Khalid University, P.O. Box: 394, Abha, 61411, Kingdom of Saudi Arabia.
Department of Geography, Faculty of Natural Science Jamia Millia Islamia, New Delhi, India.
Environ Sci Pollut Res Int. 2022 Apr;29(17):25112-25137. doi: 10.1007/s11356-021-17609-w. Epub 2021 Nov 27.
In Saudi Arabia, identifying homogenous zones based on rainfall patterns is critical for ensuring a predictable and stable water resource and agriculture management strategy. As a result, the present research aims to identify Saudi Arabia's homogeneous rainfall zones and examine rainfall patterns in these areas. By proposing a novel trend analysis technique with a particular graphical representation, this study utilises and compares the traditional Mann-Kendall (MK) test, modified MK test, and basic Sen-innovative trend analysis (ITA) method. Another approach is to use the Pettit change point test to objectively identify subcategories as "low" or "high." The applications are based on 40-year rainfall records from 22 Saudi Arabian meteorological sites. K-means clustering and hierarchical clustering on principle component analysis (HCPC) were used to find homogeneous areas. The results of the homogeneous region identification revealed that the research area is divided into three clusters, each with three distinct climatic characteristics. Cluster 1 contains eight stations, whereas clusters 2 and 3 each have seven. The results of trend identification utilising the MK, MMK, and ITA tests revealed that cluster 1 had a falling rainfall trend, whereas cluster 2 had a very minor decreasing and increasing rainfall trend. Cluster 2 can be thought of as a transition zone. Cluster 3 observed an upward trend in rainfall. While the proposed new form of ITA produced similar results with more detailed analysis such as change point-based high and low value identification, and magnitude of decreasing and increasing trend, the proposed new form of ITA produced similar results with more detailed analysis such as change point-based high and low value identification. This study will serve as a foundation for future work by scientists and planners on the identification of climatic zones, the development of trend detection techniques, and the formulation of water resource management strategies.
在沙特阿拉伯，根据降雨模式识别同质区域对于确保可预测和稳定的水资源和农业管理策略至关重要。因此，本研究旨在识别沙特阿拉伯的同质降雨区，并研究这些地区的降雨模式。本研究提出了一种新颖的趋势分析技术，具有特定的图形表示，利用并比较了传统的 Mann-Kendall（MK）检验、修正的 MK 检验和基本 Sen 创新趋势分析（ITA）方法。另一种方法是使用 Pettit 变点检验来客观地识别“低”或“高”子类别。该应用基于 22 个沙特阿拉伯气象站的 40 年降雨记录。使用 K-均值聚类和主成分分析（HCPC）上的层次聚类来寻找同质区域。同质区域识别的结果表明，研究区域分为三个聚类，每个聚类有三个不同的气候特征。聚类 1 包含 8 个站，而聚类 2 和 3 各有 7 个站。利用 MK、MMK 和 ITA 检验进行的趋势识别结果表明，聚类 1 的降雨呈下降趋势，而聚类 2 的降雨呈明显的减少和增加趋势。聚类 2 可以看作是一个过渡区。聚类 3 的降雨量呈上升趋势。虽然所提出的 ITA 的新形式产生了类似的结果，但具有更详细的分析，如基于变点的高值和低值识别以及减少和增加趋势的幅度，但所提出的 ITA 的新形式产生了类似的结果，但具有更详细的分析，如基于变点的高值和低值识别以及减少和增加趋势的幅度。这项研究将为科学家和规划者在识别气候带、开发趋势检测技术和制定水资源管理策略方面的未来工作奠定基础。
