Estimation of sediment load for Himalayan Rivers: Case study of Kaligandaki in Nepal

2020 ◽  
Vol 129 (1) ◽  
Author(s):  
Pennan Chinnasamy ◽  
Aditya Sood
2021 ◽  
Vol 18 (6) ◽  
pp. 1591-1608
Author(s):  
Maryam Tajbakhshian ◽  
Abolfazl Mosaedi ◽  
Mohamad Hosein Mahmudy Gharaie ◽  
Sayyed Reza Moussavi Harami

2018 ◽  
Vol 3 (12) ◽  
pp. 1301
Author(s):  
Farhang Azarang ◽  
Ghazal Jafari ◽  
Maryam Karami Karami ◽  
Mahmood Shafaie Bejestan

Regarding the importance of rivers, appropriate management of aggregate mining is of great significance. Mining of river materials has a direct impact on environmental conditions of the river. Today, aggregate mining management represents a crucial topic in river engineering. Often selected based on the pattern of the considered river, matrix method provides a suitable approach to improve the river aggregate mining management. The present research aims at presenting the application of the matrix method in river material mining location evaluation. Given the capabilities of the matrix method for determining potential of mine area and aggregate mining method, this method can be seen as a suitable solution for reducing negative environmental impacts of river material mining. A'la River is one of the most important rivers streaming in Khouzestan Province (Iran), with its sediment load and mining potential being of critical importance. In this research, the reach of A'la River at the intersection of Rood-Zard River and Rahmhormoz diversion dam was studied for aggregate mining and application of matrix method. The main purpose of this work is to study the application of matrix method to A'la River. The results indicate braided pattern of the river and appropriateness of the matrix method. Available volume of aggregate for mining within the mentioned reach of A'la River was estimated as 50,000 m3, and scraping method at a maximum depth of 1 m was proposed for mining of the aggregates.


2021 ◽  
Vol 9 ◽  
Author(s):  
Yinjun Zhou ◽  
Zhijing Li ◽  
Shiming Yao ◽  
Miner Shan ◽  
Chao Guo

After the construction of the Three Gorges Dam (TGD) in China, the downstream has been affected by the reduction in sediment discharge and regulation of flow processes, which have resulted in severe scouring and changes hydrological regime. Consequently, the spawning ground of Chinese sturgeon distributed along the downstream Yichang reach could be affected. This study examined the effects of TGD on the streamflow, sediment load and channel morphology downstream based on in situ measured data. Results showed that, after the impoundment of the TGD, sediment load at the downstream Yichang hydrological station decreased significantly, and the Yichang reach continued to be scoured. The distribution of erosion was uneven, and the scouring mainly occurred in the branching channels. The channel gradient and riverbed roughness increased with the erosion of the river cross section. After more than 10 years of erosion, the riverbed scouring and armouring in the Yichang reach was basically completed, thus we expected that the spawning grounds of Chinese sturgeon could be retain as the riverbed tends to be stable. The findings in this work have implications in the protection of the critically endangered Chinese sturgeon.


2020 ◽  
Vol 24 (6) ◽  
pp. 1944-1957
Author(s):  
Sandeep Samantaray ◽  
Abinash Sahoo ◽  
Dillip K. Ghose
Keyword(s):  

2013 ◽  
Vol 3 (1) ◽  
pp. 09-25
Author(s):  
Vahid Nourani ◽  
Aida Yahyavi Rahimi ◽  
Farzad Hassan Nejad

Information on suspended sediment load (SSL) is fundamental for numerous water resources management and environmental protection projects. This phenomenon has the inherent complexity due to a large number of vague parameters and existence of both spatial variability of the basin characteristics and temporal climatic patterns. This complexity turns into a barrier to get accurate prediction by conventional linear methods. On the other hand, the extent of the noise on hydrological data reduces the performance of data-driven models like Artificial Neural Networks (ANNs). Although ANNs could capture the complex nonlinear relationship between input and output parameters, being data-driven method positioned it in a state of need to preprocessed data. In this paper, the application of ANN approach focusing on wavelet- based denoising method for modeling daily streamflow-sediment relationship was proposed. The daily streamflow and SSL data observed at outlet of the Potomac River in USA were used as the case study. Achieving this purpose, Daubechies (db) was used as mother wavelet to decompose both streamflow and sediment time series into detailed and approximation subseries. Decomposition at level ten via db3 and at level eight via db5 were examined for streamflow and SSL time series, respectively. At first, the appropriate input combination with raw data to estimate current SSL was determined and re-imposed to ANN with denoised data.  The comparison of results reveals that in term of determination coefficient, the obtained result by denoised data was improved up to 23.2% with raged to use noisy, raw data and this exhibits that denoised data can be employed productively in ANN-based daily SSL forecasting.


2015 ◽  
Vol 17 ◽  
pp. 24-33 ◽  
Author(s):  
Balendra Chhetry ◽  
Kumar Rana

In high sediment laden river projects or silt affected power stations, the frequency of repair and maintenance of underwater parts is comparatively higher which leads to increase the overall forced outages per year for repair The extent of the major maintenance will depend on the operating condition such as suspended sediment load passing through the turbine and how the machine was loaded during the operation. This paper illustrates the analysis of sediments, effect of sand erosion and maintenance of turbine of Kali Gandaki “A” Hydroelectric Plant (144 MW). The paper also describes the repair methods used for different turbine components to minimize the effects induced by sediment erosion. HYDRO Nepal JournalJournal of Water, Energy and EnvironmentIssue: 17, July 2015 


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