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The number of wastewater treatment plants (WWTPs) in the Czech Republic is increasing. Wastewater, which was previously disposed of in other ways (e.g. septic tanks, cesspits etc), is now entering the surface water (after treatment at a WWTP). Billions of Czech crowns have been invested in the construction of new WWTPs or reconstruction and intensification of existing ones. This money had been invested to meet discharge standards for individual pollutants. However, the overall level of pollution associated with wastewater discharges has not been assessed. The indicator of grey water footprint was used to assess whether there was an increase in pollution load discharged from WWTPs between 2002 and 2018. Discharged pollution data from 4115 industrial and municipal WWTPs were analysed. The analysis of such a large data set has not been carried out yet and brings new knowledge concerning the effect of WWTP size on the grey water footprint. Overall, the total value of the grey water footprint (and thus of the discharged pollution level) decreased in the monitored period. Grey water footprint caused by the largest WWTPs decreased, while the grey water footprint of small WWTPs increased, due to the increase in their number. The decisive pollutants that determine the value of the grey water footprint are total phosphorus and ammonium nitrogen. Measures targeting these two main pollutants can significantly reduce the overall level of pollution load discharged from WWTPs.

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This study compares the Life Cycle Assessment based Water Scarcity Footprint of produced energy unit in two nuclear power plants in the Czech Republic between 2005 and 2015. Primary data has been used to allocate impacts to the core processing stage. Although the real total amount of water consumption in both power plants is similar, the water scarcity footprint in Temelín nuclear power plant is of approximately 8.9 m3 H2Oeq per MWh lower than in Dukovany power plant. The cooling water has the most significant contribution to the freshwater availability impact category. Evaporation from reservoirs which are a part of water management of the individual power plants has lower, but not inconsiderable, contribution to the water consumption. In the case of Temelín nuclear power plant, the loss caused by evaporation from Hněvkovice reservoir is of approximately 6.5% of the difference between withdrawal and discharge of the power plant. In the case of Dukovany nuclear power plant, evaporation from Dalešice - Mohelno reservoir is of even around 11%.

Evaporation and evapotranspiration is crucial part of hydrological and water resource management studies e.g. water footprinting. Proper methods for estimating evaporation/potential evapotranspiration using limited climatic data are critical if the availability of climatic data is extremely limited. In a large scale studies are very often used generalized (modelled or gridded) input data. For a large scale water footprint studies is also important to find methods as simple as possible with quantifiable error. In our study, nine simple temperature-based empirical equations were compared with a long term time series of real evaporation data from a 20 m2 tank at Hlasivo station. In the first step, we used real temperature measured at Hlasivo station for validation of equations. In the second step, the gridded temperature data (interpolated datasets) derived from the meteorological stations were used. For both datasets, the differences between observed and predicted values were categorized into three groups of accuracy and the statistical indices of each equation were calculated. Very good results were achieved with the Hamon equation from 1961 and the Oudin equation for both datasets with index of agreement (d) higher than 0.9, cross-correlation coefficient (R2) around 0.7 and root mean square error (RMSE) around 0.5 mm∙(24 h)−1 The Kharrufa equation, which was developed for semi-arid or arid areas, also provides results with sufficient accuracy. Comparison of the results with similar studies showed a lower accuracy of very simple equations against more complex equations, which have RMSE lower than 0.25 mm∙(24 h)−1. But for some kind of studies, quantifiable errors with sufficient accuracy can be more important than the absolute accuracy.