Mount Doongul Track is a 2.2 km Medium 4WD trail in Doongul, Queensland, Australia. Average drive time is 8 minutes.
Mount Doongul Track offers 4WD enthusiasts a fantastic short drive through Queensland's diverse bushland with genuine character and accessibility. You'll navigate 2.2 kilometres of well-formed track that showcases the region's natural features without demanding extreme technical skill, making it perfect for intermediate drivers looking to build confidence or those seeking a quick adventure near Doongul.
The terrain combines gentle woodland driving with occasional rocky sections that keep things interesting without becoming intimidating. You'll experience the satisfaction of genuine off-road driving as you wind through native vegetation, with stunning views opening up as you progress. The landscape transitions between dense scrub and more open areas, giving you variety throughout the short journey. With no steep grades to negotiate, you can focus on line selection and enjoying the Queensland outback experience at a comfortable pace.
Before heading out, ensure your vehicle is in good working order and carry essential supplies including water and a first aid kit. The track is suitable for most 4WD vehicles, and with 13 confirmed successful drives logged on Newtracs, you'll benefit from real-world route information. Early morning or late afternoon visits offer the best lighting for both driving safety and photography. This is the ideal trail when you want authentic off-road adventure without overcommitting your time or pushing your limits.
Explore Mount Doongul Track in the app
Offline maps, live conditions & more
2.2 km
Distance
8 min
Avg Time
17 km/h
Avg Speed
--
Steep Grade
See how many vehicles have driven this trail
Already have an account?
See who's driving this trail and when
Already have an account?
16°C
Patchy rain nearby
9 km/h SSE
91%
16°C
0
7-Day Forecast
Patchy rain nearby
Patchy rain nearby
Patchy rain nearby
Heavy rain
Heavy rain
Heavy rain
Patchy rain nearby
Get offline topo maps, live conditions, and data-driven difficulty ratings.