Next Article in Journal
Non-Point Source Nitrogen and Phosphorus Assessment and Management Plan with an Improved Method in Data-Poor Regions
Previous Article in Journal
Detection of Anomalies and Changes of Rainfall in the Yellow River Basin, China, through Two Graphical Methods
Article

Variability and Trend Detection in the Sediment Load of the Upper Indus River

Chair of Hydraulic and Water Resources Engineering, Technical University of Munich, Arcisstr. 21, D-80333 Munich, Germany
*
Author to whom correspondence should be addressed.
Water 2018, 10(1), 16; https://doi.org/10.3390/w10010016
Received: 14 November 2017 / Revised: 21 December 2017 / Accepted: 21 December 2017 / Published: 25 December 2017
Water reservoirs planned or constructed to meet the burgeoning energy and irrigation demands in Pakistan face a significant loss of storage capacity due to heavy sediment load from the upper Indus basin (UIB). Given their importance and the huge investment, assessments of current UIB sediment load and possible future changes are crucial for informed decisions on planning of optimal dams’ operation and ensuring their prolonged lifespan. In this regard, the daily suspended sediment loads (SSLs) and their changes are analyzed for the meltwater-dominated zone up to the Partab Bridge and the whole UIB up to Besham Qila, which is additionally influenced by monsoonal rainfall. The gaps between intermittent suspended sediment concentration (SSC) samples are filled by wavelet neural networks (WA-ANNs) using discharges for each site. The temporal dynamics of SSLs and discharges are analyzed using a suite of three non-parametric trend tests while the slope is identified using Sen’s slope estimator. We found disproportional spatio-temporal trends between SSLs and discharges caused primarily by intra-annual shifts in flows, which can lead to increased trap efficiency in planned reservoirs, especially upstream of Besham Qila. Moreover, a discernible increase in SSLs recorded at Partab Bridge during summer is being deposited downstream in the river channel. This is due to a decrease in river transport capacity in the monsoonal zone. These findings will not only help to identify these morphological problems, but also accurately anticipate the spatio-temporal changes in the sediment budget of the upper Indus River. Our results will help improve reservoir operational rules and sediment management strategies for existing and 30,000-MW planned dams in the UIB. View Full-Text
Keywords: sediment pattern; sediment load trend; sediment transport estimation; upper Indus River; wavelet neural network; Mann–Kendall test; Sen’s slop test; April sediment load sediment pattern; sediment load trend; sediment transport estimation; upper Indus River; wavelet neural network; Mann–Kendall test; Sen’s slop test; April sediment load
Show Figures

Figure 1

MDPI and ACS Style

Ateeq-Ur-Rehman, S.; Bui, M.D.; Rutschmann, P. Variability and Trend Detection in the Sediment Load of the Upper Indus River. Water 2018, 10, 16. https://doi.org/10.3390/w10010016

AMA Style

Ateeq-Ur-Rehman S, Bui MD, Rutschmann P. Variability and Trend Detection in the Sediment Load of the Upper Indus River. Water. 2018; 10(1):16. https://doi.org/10.3390/w10010016

Chicago/Turabian Style

Ateeq-Ur-Rehman, Sardar; Bui, Minh D.; Rutschmann, Peter. 2018. "Variability and Trend Detection in the Sediment Load of the Upper Indus River" Water 10, no. 1: 16. https://doi.org/10.3390/w10010016

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop