Inicio  /  Water  /  Vol: 10 Par: 1 (2018)  /  Artículo
ARTÍCULO
TITULO

Detection of Anomalies and Changes of Rainfall in the Yellow River Basin, China, through Two Graphical Methods

Hao Wu    
Xinyan Li and Hui Qian    

Resumen

This study aims to reveal rainfall anomalies and changes over the Yellow River Basin due to the fragile ecosystem and rainfall-related disasters. Common trend analyses relate to overall trends in mean values. Therefore, we used two graphical methods: the quantile perturbation method (QPM) was used to investigate anomalies over time in extreme rainfall, and the partial trend method (PTM) was used to analyze rainfall changes at different intensities. A nonparametric bootstrap procedure is proposed in order to identify significant PTM indices. The QPM indicated prevailing positive anomalies in extreme daily rainfall 50 years ago and in the middle reaches during the 1970s and 1980s. The PTM detected significant decreases in annual rainfall mainly in the latter half of the middle reaches, two-thirds of which occurred in high and heavy rainfall. Most stations in the middle and lower reaches showed significant decreases in rainy days. Daily rainfall intensity had a significant increase at 13 stations, where rainy days were generally decreasing. The combined effect of these opposing changes explains the prevailing absence of change in annual rainfall, and the observed decreases in annual rainfall can be attributed to the decreasing number of rainy days. The changes in rainy days and rainfall intensity were dominated by the wet season and dry season, respectively.

 Artículos similares

       
 
George Papageorgiou, Vangelis Sarlis and Christos Tjortjis    
This study utilized advanced data mining and machine learning to examine player injuries in the National Basketball Association (NBA) from 2000?01 to 2022?23. By analyzing a dataset of 2296 players, including sociodemographics, injury records, and financ... ver más
Revista: Information

 
Dominic Lightbody, Duc-Minh Ngo, Andriy Temko, Colin C. Murphy and Emanuel Popovici    
The growth of the Internet of Things (IoT) has led to a significant rise in cyber attacks and an expanded attack surface for the average consumer. In order to protect consumers and infrastructure, research into detecting malicious IoT activity must be of... ver más
Revista: Future Internet

 
Kyle DeMedeiros, Chan Young Koh and Abdeltawab Hendawi    
The Chicago Array of Things (AoT) is a robust dataset taken from over 100 nodes over four years. Each node contains over a dozen sensors. The array contains a series of Internet of Things (IoT) devices with multiple heterogeneous sensors connected to a p... ver más
Revista: Future Internet

 
Ji-Woon Lee and Hyun-Soo Kang    
The escalating use of security cameras has resulted in a surge in images requiring analysis, a task hindered by the inefficiency and error-prone nature of manual monitoring. In response, this study delves into the domain of anomaly detection in CCTV secu... ver más
Revista: Applied Sciences

 
Jaehan Jeon and Gerasimos Theotokatos    
Digital twins (DTs) are gradually employed in the maritime industry to represent the physical systems and generate datasets, among others. However, the trustworthiness of both the digital twins and datasets must be assured. This study aims at developing ... ver más