The Queensland Land Court has heard evidence that Adani’s Carmichael coal mine is likely to generate royalties between $3.7 to $4.8 billion in the current market, significantly less than the $22 billion that Adani has publicly claimed, Lock the Gate said.

It has also heard the coal mine will create about 1464 direct and indirect jobs – 8536 jobs fewer than the company’s inflated estimates.

Lock the Gate Alliance spokesperson Georgina Woods said special treatment of the industry by credulous governments hinders oversight of the claims made by companies when applying for licences and testing of their claims.

“These revelations about inflated job numbers and overstatement of potential royalties are symptomatic of a more general lack of rigour in the assessment process for coal mines in Queensland that is leading to very poor outcomes,” Woods said.

“Large new mining projects are putting public assets like rivers, aquifers and endangered wildlife at risk for financial benefits that are at best short-lived and in this case, actually false.

“There's a similar pattern in NSW, where the Planning and Assessment Commission has criticised the Government for uncritically accepting the inflated economic claims made by coal mining companies.

“The public has a lot to lose when huge new mines like Carmichael that will deplete groundwater and radically alter bush landscapes are approved by governments on the basis of information supplied by mining companies and not rigorously scrutinised.

“In NSW, the former planning minister promised last year to improve the standards of economic assessments for mines, but that has not happened and the premier is today visiting the site of two controversial projects that are making economic claims to justify quite devastating impacts on local industries and communities.

“With the stakes this high, it is crucial that impartial information is gathered and analysed, but until Queensland and New South Wales bring back balance to the mining and planning process, we're afraid that this kind of gross error is likely to be repeated.”