Fractal Dimensional Analysis of Runoff in Jinsha River Basin, China

2013 ◽  
Vol 405-408 ◽  
pp. 2181-2184 ◽  
Author(s):  
Yun Xia Xie ◽  
Shang Chun Zeng ◽  
Wen Sheng Wang
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
Dimensional Analysis ◽  
River Basin ◽  
Hydrological Processes ◽  
Jinsha River ◽  
Runoff Series ◽  
Transform Coefficients ◽  
Wavelets Transform

The hydrological processes are becoming more and more complex. Fractal dimension is one of the important measurements of complexity. This paper utilizes wavelets transform technique to calculate the fractal dimension of runoff for eight stations (Zhimenda, Shigu, Ganzi, Yajiang, Guili, Luning, Xiaodeshi, Pingshan ) in the Jinsha River Basin. The results show: the runoff series in the Jinsha River Basin is fractal; the approach for estimating the fractal dimension by using wavelet transform coefficients is feasible and effective; the fractal dimension of runoff reflect the influence of factors on the runoff.

Complexity Analysis of Rainfall in Jinsha River Basin, China

2014 ◽  
Vol 530-531 ◽  
pp. 586-590
Author(s):  
Yun Xia Xie ◽  
Shang Chun Zeng ◽  
Dong Long Li ◽  
Jun Wang
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
River Basin ◽  
Complexity Analysis ◽  
Rainfall Series ◽  
Hydrological Processes ◽  
Jinsha River ◽  
Transform Coefficients ◽  
Wavelets Transform

The hydrological processes are becoming more and more complex. Fractal dimension is one of the important measurements of complexity. This paper utilizes wavelets transform technique to calculate the fractal dimension of rainfall in July for eight stations (Yushu, Xichang, Pingshan, Lijiang, Kunming, Huili, Deqin, Lnage ) in the Jinsha River Basin. The results show: the rainfall series in the Jinsha River Basin is fractal; the approach for estimating the fractal dimension by using wavelet transform coefficients is feasible and effective; the fractal dimension of rainfall reflect the influence of factors on the rainfall.

scholarly journals Impacts of climate change and LULC change on runoff in the Jinsha River Basin

2020 ◽  
Vol 30 (1) ◽  
pp. 85-102 ◽  
Author(s):  
Qihui Chen ◽  
Hua Chen ◽  
Jun Zhang ◽  
Yukun Hou ◽  
Mingxi Shen ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Jinsha River ◽  
Lulc Change ◽  
Impacts Of Climate Change

scholarly journals Superiority of Hybrid Soft Computing Models in Daily Suspended Sediment Estimation in Highly Dynamic Rivers

2021 ◽  
Vol 13 (2) ◽  
pp. 542
Author(s):  
Tarate Suryakant Bajirao ◽  
Pravendra Kumar ◽  
Manish Kumar ◽  
Ahmed Elbeltagi ◽  
Alban Kuriqi
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Suspended Sediment ◽  
River Basin ◽  
Time Series Data ◽  
Series Data ◽  
Discrete Wavelet ◽  
Original Time Series ◽  
Inference System ◽  
Original Time

Estimating sediment flow rate from a drainage area plays an essential role in better watershed planning and management. In this study, the validity of simple and wavelet-coupled Artificial Intelligence (AI) models was analyzed for daily Suspended Sediment (SSC) estimation of highly dynamic Koyna River basin of India. Simple AI models such as the Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were developed by supplying the original time series data as an input without pre-processing through a Wavelet (W) transform. The hybrid wavelet-coupled W-ANN and W-ANFIS models were developed by supplying the decomposed time series sub-signals using Discrete Wavelet Transform (DWT). In total, three mother wavelets, namely Haar, Daubechies, and Coiflets were employed to decompose original time series data into different multi-frequency sub-signals at an appropriate decomposition level. Quantitative and qualitative performance evaluation criteria were used to select the best model for daily SSC estimation. The reliability of the developed models was also assessed using uncertainty analysis. Finally, it was revealed that the data pre-processing using wavelet transform improves the model’s predictive efficiency and reliability significantly. In this study, it was observed that the performance of the Coiflet wavelet-coupled ANFIS model is superior to other models and can be applied for daily SSC estimation of the highly dynamic rivers. As per sensitivity analysis, previous one-day SSC (St-1) is the most crucial input variable for daily SSC estimation of the Koyna River basin.

scholarly journals Identification of the Impacts of Climate Changes and Human Activities on Runoff in the Jinsha River Basin, China

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaowan Liu ◽  
Dingzhi Peng ◽  
Zongxue Xu
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Human Activities ◽  
Climate Changes ◽  
Balance Method ◽  
Variation Method ◽  
Rainfall Runoff ◽  
Jinsha River ◽  
Water Balance Method ◽  
Double Mass

Quantifying the impacts of climate changes and human activities on runoff has received extensive attention, especially for the regions with significant elevation difference. The contributions of climate changes and human activities to runoff were analyzed using rainfall-runoff relationship, double mass curve, slope variation, and water balance method during 1961–2010 at the Jinsha River basin, China. Results indicate that runoff at upstream and runoff at midstream are both dominated by climate changes, and the contributions of climate changes to runoff are 63%~72% and 53%~68%, respectively. At downstream, climate changes account for only 13%~18%, and runoff is mainly controlled by human activities, contributing 82%~87%. The availability and stability of results were compared and analyzed in the four methods. Results in slope variation, double mass curve, and water balance method except rainfall-runoff relationship method are of good agreement. And the rainfall-runoff relationship, double mass curve, and slope variation method are all of great stability. The four methods and availability evaluation of them could provide a reference to quantification in the contributions of climate changes and human activities to runoff at similar basins in the future.

Study on Damage Detection of Bridge Based on Wavelet Multi-Scale Analysis

2013 ◽  
Vol 639-640 ◽  
pp. 1010-1014 ◽  
Author(s):  
Ke Ding ◽  
Ting Peng Chen
Keyword(s):  
Wavelet Transform ◽  
Damage Detection ◽  
Detection Method ◽  
Mode Shapes ◽  
Scale Analysis ◽  
Multi Scale ◽  
Damage Location ◽  
Transform Coefficients ◽  
Beam Bridge ◽  
Multi Scale Analysis

The damage detection method based on wavelet multi-scale analysis is presented in the paper. The damage location can be identified by analyzing the multi-scale wavelet transform coefficients of curvatures of mode shapes. The extreme value of wavelet transform coefficients indicates the damage location. But it is difficult to detect the location of defect if the defect is near to the equilibrium position of vibration. In order to solve this problem, we put forward a method which is to add the wavelet transform coefficients of multi modals together. The method can effectively overcome the above problem. Three damage situations of simply supported beam bridge are discussed in the paper. The results show that the peaks of wavelet transform coefficients indicate the damage location of structural. It is possible to pinpoint the damage location based on wavelet multi-scale analysis on curvatures of mode shapes.

Runoff Fractal Dimension of Songhua River Basin in Harbin Station Based on Db4 Wavelet

2012 ◽  
Vol 550-553 ◽  
pp. 2537-2540
Author(s):  
Hai Yan Gu ◽  
Yong Wang ◽  
Lei Yu
Keyword(s):  
Time Series ◽  
Fractal Dimension ◽  
River Basin ◽  
Fractal Theory ◽  
Measurement Methods ◽  
Self Similarity ◽  
Songhua River ◽  
Songhua River Basin ◽  
The Songhua River Basin ◽  
The Songhua River

The wavelet analysis and fractal theory into the analysis of hydrological time series, fluctuations in hydrological runoff sequence given the complexity of the measurement methods--- fractal dimension. The real monthly runoffs of 28 years from Songhua River basin in Harbin station are selected as research target. Wavelet transform combined with spectrum method is used to calculate the fractal dimension of runoff. Moreover, the result demonstrates that the runoff in Songhua River basin has the characteristic of self-similarity, and the complexity of runoff in the Songhua River basin in Harbin station is described quantificationally.

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