Waste management demands continuous enhancement of existing infrastructure in terms of newly designed facilities which have a lesser impact on the environment. The transportation of waste and its further treatment in the facility should be optimised according to the cost and environment policy. The future planning of new facilities and transportation routes require complex information about current state of the waste operation activities. The legislation of the Czech Republic (also other countries with well-developed waste management) forces waste operators to register production, treatment and handling of waste. Such an information, stored in large databases, provide authorities with at least basic knowledge about the waste flows in the area. Additionally, the annual data reporting decreases the information about producers’ waste flow due to the aggregation, inconsistency and/or inaccuracy (low quality of reported data). This paper presents an approach for flow and treatment identification based on the combination of data reconciliation with economic and environmental aspects. The approach uses mathematical programming techniques for identifying errors in the database with regards to the network flow preserving continuity and balances between and in the nodes. The objective is to make the amount of produced and delivered waste to each node equal to the amount that was there processed or removed. This is required with the minimum modification of the input data. Weights are introduced to distinguish high and low-quality data by assigning bigger values to arcs where sent amount correspond with quantity received. The results of this analysis provide an assessment of current waste handling for the particular node, which forms an essential information for future planning of processing facilities and their technologies. The multi-objective model considers environmental aspects as relations between treatment options and transportation distances (cost). Longer transportation distances are tolerated for higher treatment options in the waste hierarchy. The presented model has been tested through a case study on the database of waste management in the Czech Republic. The network was considered on the regional level. However, any commodity, which is included in supply chain models and has a reporting obligation, can be handled in a similar way. Further research might be focused on possible extensions such as influence from stakeholders in decision-making which provides proved flow inputs.