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GLOBAQUA is a European Union (EU)-funded project aiming to identify the prevalence of, and interaction between, stressors under water scarcity in order to improve water management practices and policies. River water temperature (RWT) plays a pivotal role in aquatic freshwater ecosystems, impacting the distribution of aquatic species and water quality. In this study, we aimed at assessing RWT in three data-poor, water scarce basin of the European Mediterranean region to enable projections of RWT as one of the multiple stressors that aquatic habitats face currently and likely more in the future. Given that water thermal inertia regulates RWT response to Ta, stream discharge (Q) should be considered in predicting RWT in water scarce basins. To be pragmatic, we opted for applying a published empirical regression of RWT as a function of Ta and Q for application in three European basins, namely the Adige (Italy, 28 stations), the Ebro (Spain, 39 stations), and the Sava (Western Balkans, 10 stations). Time series comprised data observed from 1967 to 2014; observed RWT ranged from -5 to 34 °C, Ta ranged from -50 to 39 °C and stream discharge ranged from 0 to 5000 m3/s. For each basin, the regression coefficients were estimated with Bayesian inference using a calibration dataset that comprised about 75% of basin stations. Initial collinearity analysis showed that correlation between regression coefficients reduced identifiability of all empirical parameters, thence the asymptotic minimum RWT was set at zero while the asymptotic maximum was set according to the distribution of the highest 4% of recorded RWT. MCMC runs converged to acceptable solutions in all basins. The root mean square error (RMSE) in the calibration and in the validation datasets varied from 2 to 3.15 °C, which was deemed acceptable for application at basin scale. However, while statistic results were acceptable, the projected impact of stream discharge on RWT resulted to be either negligible (in the Sava basin) or unrealistic, e.g. in the Adige basin. Furthermore, the empirical equation seemed conceptually flaw at low temperatures, where low discharge would increase rather than decrease RWT. Repeating the analysis after dropping the stream discharge variable allowed reaching the same estimation errors, i.e. neglecting the hypothesized discharge impact did not degrade the empirical RWT estimation. In view of data limitations, the logistic regression of RWT as a function of Ta was considered sufficient to assess RWT changes in foreseeable future in the three studied basins. We further conclude that despite statistical convergence and acceptable goodness of fit, the hypothesized empirical relationship of RWT and Q should be revised. Alternatively, in data richer environments, stream discharge could be used in regionalization schemes to extend regression parameters in between observation stations.

Empirical modelling of river water temperature in water scarce European basins