From Surf Wiki (app.surf) — the open knowledge base

Diyala Weir

Field	Value
name	Diyala Weir
image	Diyala Weir3 USACE NWD.jpg
location_map	Iraq
coordinates
dam_crosses	Diyala River
location	90km northeast of Baghdad, Iraq, Diyala Governorate, Iraq
operator	Ministry of Water Resources
construction_began	1966
opening	1969

Diyala Weir, also known as the Diyala Barrage, is a diversion dam on the Diyala River 90 km northeast of Baghdad, Iraq. It was constructed between 1966 and 1969. The main purpose of the dam is to divert outflow of the Hemrin Dam (11 km upstream) on the Diyala River to the Khalis and Sadr Al-Mushtarak canals for irrigation.

The weir and its associated extensive irrigation scheme, were designed in the 1960s by the Consulting Engineers Sir Murdoch McDonald and Partners, of High Holborn, London. At each end it incorporates irrigation canals. These and the weir are crossed by road bridges designed to take the heaviest loads, namely a tank on a wheeled transporter. The bridge works were designed by the then Captain B P Daly of Royal Engineers, who was attached to the Consultants. The weir was featured on a set of three Iraqi postage stamps.

References

[http://www.cig.ensmp.fr/~iahs/redbooks/a159/iahs_159_0225.pdf Suspended and solute loads on the Lower Diyala River]{{dead link. (December 2016)

Wikipedia Source

This article was imported from Wikipedia and is available under the Creative Commons Attribution-ShareAlike 4.0 License. Content has been adapted to SurfDoc format. Original contributors can be found on the article history page.

dams-in-iraq dams-on-the-diyala-(sirwan)-river dams-completed-in-1969 1969-establishments-in-iraq

Want to explore this topic further?

Ask Mako anything about Diyala Weir — get instant answers, deeper analysis, and related topics.

Research with Mako

Free with your Surf account

Content sourced from Wikipedia, available under CC BY-SA 4.0.

This content may have been generated or modified by AI. CloudSurf Software LLC is not responsible for the accuracy, completeness, or reliability of AI-generated content. Always verify important information from primary sources.

Report