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Vlasina Lake in south-east Serbia is classified as an Area of Distinct Land Use and, as such, is subject to high environmental protection standards applied in the Master Plan. Two open channels for stormwater and sediment transportation to two large detention basins with pumping stations for water evacuation into the lake were envisaged in the Master Plan. In the preliminary design, the stormwater system was quite different: wherever possible, on-site natural features were used for allocation of ponds, and drainage channels were led through existing road culverts. The applied design concept has been low impact development (LID), which led to potential blue-green corridors, recognized by project stakeholders. The paper studies the possibility of using ponds as a key element of both the LID concept and the blue-green corridors approach. For that purpose, an initial Vlasina Lake site agent-based simulation model has been created. A realistic physical model is included, and simulation results for two hypothetical climatic and socio-economic scenarios are presented. From the experience in creating the agent-based model, and based on the simulation results, recommendations are given for further work. It is shown that ponds have potential for the investigated water re-use purposes.

Revision of existing methodologies for generating monthly-flow series at ungauged basins based on multivariate nonlinear correlation has led to a simple two-parameter model. While the existing methodology used hydrological, meteorological and geomorphologic input data, the proposed model requires hydrological and geomorphologic input data only. The proposed methodology requires formation of separate pools of donor catchments for model parameter estimates. The proposed two-parameter model and improvement in the sphere of homogeneous region identification were verified using 195 runoff data sets from hydrologic stations in Serbia in the 1961-2005 period, divided into three non-overlapping 15-year periods. Nash-Sutcliffe's model efficiency coefficient (NSE) was used to assess the: (1) quality of proposed model with identified model parameters; (2) quality of a nonlinear multivariate equation for standard normal variables estimation with identified model parameters; (3) quality of proposed model with model parameter estimates. Generated time-series statistics and nonlinear multivariate equation quality are also evaluated. Five model calibration and validation results are shown. Generated flow series variation coefficient is the best replicated statistics with relative absolute error less than 10%.