Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations.

Climate change will likely increase the frequency and magnitude of extreme precipitation events and floods, increasing design peak flows that could lead to underestimates in current spillway capacity. Therefore, new methodologies for hydrological dam safety assessment considering climate change are required. This study presents a methodology that considers the impact of climate change on both inflow hydrographs and initial reservoir water levels. Moreover, the uncertainty in the procedure is assessed. The methodology is applied to the Eugui Dam in the River Arga catchment (Spain). An ensemble of 12 climate models is used. The results show an increase in the maximum reservoir water level during flood events and in the overtopping probability in the Representative Concentration Pathway 8.5 (RCP 8.5 scenario), especially in the 2071–2100 time window. The proposed methodology can be useful to assess future hydrological dam safety, fulfilling the requirements of recent regulations to consider the impact of climate change on dams.

Whey is a highly polluting by-product obtained from the elaboration of cheese. Its high content in organic matter, mainly proteins and lactose, makes it a valuable candidate for multiple applications in the food industry. However, mineral salts have to be previously eliminated. The main objective of this work was to eliminate mineral salts from model solutions with different nanofiltration membranes: NF200, NF270, Ds-5 DK and Ds-5 DL polyamide. Although all four membranes showed fairly good results in the demineralisation of the used samples, the most promising results in terms of good permeate flux and low solute retention were obtained with the NF200 and Ds-5 DL membranes, respectively. The effect of the salt mixture concentration on permeate flux and solute retention was further evaluated for Ds-5 DL membrane.

Annual maximum daily rainfalls will change in the future because of climate change, according to climate projections provided by EURO-CORDEX. This study aims at understanding how the expected changes in precipitation extremes will affect the flood behavior in the future. Hydrological modeling is required to characterize the rainfall-runoff process adequately in a changing climate to estimate flood changes. Precipitation and temperature projections given by climate models in the control period usually do not fit the observations in the same period exactly from a statistical point of view. To correct such errors, bias correction methods are used. This paper aims at finding the most adequate bias correction method for both temperature and precipitation projections, minimizing the errors between observed and simulated precipitation and flood frequency curves. Four catchments located in central western Spain have been selected as case studies. The HBV hydrological model has been calibrated, using the observed precipitation, temperature, and streamflow data available at a daily scale. Expected changes in precipitation extremes are usually smoothed by the reduction of soil moisture content due to expected increases in temperatures and decreases in mean annual precipitation. Consequently, rainfall is the most significant input to the model and polynomial quantile mapping is the best bias correction method.