Flood Reconstruction Works – Recover, MARS, Konect, Spreadsheets or all of the above? Untangling the software mess under the DFRA.

Abstract

Does any of the following process mean anything to anyone in the room? “Use Recover to pick up the damage, then export to a spreadsheet and process the data to a point where MARS will accept it as an import, then process for submission in MARS for lodgement, then export as a spreadsheet, but knowing that the data has been manipulated in MARS, come up with a different method to peg out for delivery because it is unlikely that the data from MARS still matches what is in Recover. Also, the DRN’s may not be a match so the exported chainages are useless for reference. And, you have to keep taking completion photos in Recover because MARS does not have that function, but you will have to import them into MARS into the right damage line, which is referenced by chainage, that chainage that is not necessarily accurate.” If that has gone over your head, consider yourself one of the lucky ones. Having a program that provides funding to help councils fund the reconstruction of flood damaged infrastructure is an awesome privilege that we have on our first world island but navigating the process under the Queensland Reconstruction Authority’s DFRA program takes a bit of understanding. The DFRA was introduced as a replacement to the NDRRA program at the end of 2018. The fundamental differences between the two programs continue to be discussed in very much detail among flood works veterans. One of the major differences was the introduction of the QRA processing software “MARS” to help the QRA manage and process submissions. MARS is an extremely capable Esri based GIS tool with some brilliant processing functions, but it has glaring omission. It has no damage collection app. So how do we go about picking up, processing and moving large amounts of damage data from a handheld device to through various partially compatible software packages to submission and back onto the ground for delivery all while keeping the data accurate and maintaining efficiency? We have not found a perfect solution, yet, but here is what we have learned after five events for three different shires under the DFRA.