Redirigiendo al acceso original de articulo en 16 segundos...
Inicio  /  Water  /  Vol: 8 Núm: 3 Par: 0 (2016)  /  Artículo
ARTÍCULO
TITULO

Investigating Trends in Streamflow and Precipitation in Huangfuchuan Basin with Wavelet Analysis and the Mann-Kendall Test

Yuzhuang Chen    
Yiqing Guan    
Guangwen Shao    
Danrong Zhang    

Resumen

This study aims to investigate trends in streamflow and precipitation in the period 1954?2010 in a semiarid region of the Yellow River watershed, Huangfuchuan basin, China. The combination of the wavelet transform and different Mann-Kendall (MK) tests were employed to figure out the basic trends structure in streamflow and precipitation and what time scales are affecting the observed trends. The comparative analysis with five MK test methods showed that the modified MK tests with full serial correlation structure performed better when significant autocorrelations exhibited for more than one lag. Three criteria were used to determine the optimal smooth mother wavelet, the decomposition level and the extension mode used in the discrete wavelet transform (DWT) procedure. The first criteria referred to the relative error of the wavelet approximated component and the original series. The second one was the relative error of MK Z-values of approximation component and the original series. Additionally, a new criterion (Er), based on the relative error of energy between the approximate component and the original series, was proposed in this study, with better performance than the previous two criteria. Further, a new powerful index, the energy of the hydrological time series, was proposed to verify the dominant periodic components for the observed trends. The analysis indicated that all monthly, seasonal and annual streamflow showed significant decreasing trends, while no significant trends were found in precipitation. Results from the DWT and MK tests revealed that the main factors influencing the trends in the monthly and seasonal series in Huangfuchuan watershed are intra-annual cycles, while the leading factors affecting the trends in the annual series are decadal events. Different driving factors (e.g., seasonal cycles, solar activities, etc.) related to the periodicities identified in these data types resulted in this discrepancy.

 Artículos similares

       
 
Rafik Hamza and Hilmil Pradana    
Big Data applications have the potential to transform any digital business platform by enabling the analysis of vast amounts of data. However, the biggest problem with Big Data is breaking down the intellectual property barriers to using that data, espec... ver más
Revista: Algorithms

 
Sheilja Singh and Rabidyuti Biswas    
Rapid urbanization and haphazard development derive the changes in land uses and affect the naturally available resources which are essential for human development and other lives. Land use changes can undermine the environment and ecology of an urban ar... ver más
Revista: Urban Science

 
Blake G. Hudson and Sara E. Mason    
Complex metal oxides (CMOs) are used broadly in applications including electroreactive forms found in lithium-ion battery technology. Computational chemistry can provide unique information about how the properties of CMO cathode materials change in respo... ver más
Revista: Applied Sciences

 
Harsha Cheemakurthy, Zuheir Barsoum, Magnus Burman and Karl Garme    
The current study focuses on the impact loading phase characteristic of thin first year ice in inland waterways. We investigate metal grillages, fibre reinforced plastic (FRP) composites and nature-inspired composites using LS Dyna. The impact mode is mo... ver más

 
Najmeh Mozaffaree Pour and Tõnu Oja    
From 1990 to 2018, built-up areas in Tallinn, Estonia?s capital city, increased by 25.03%, while its population decreased by -10.19%. Investigating the factors affecting urban expansion and modeling it are critical steps to detect future expansion trends... ver más
Revista: Urban Science