Abstract. The understanding of runoff generation mechanisms is crucial for the sustainable management of river basins such as the allocation of water resources or the prediction of floods and droughts. However, identifying the mechanisms of runoff generation has been a challenging task, even more so in arid and semi-arid areas where high rainfall and streamflow variability, high evaporation rates, and deep groundwater reservoirs may increase the complexity of hydrological process dynamics. Isotope and hydrochemical tracers have proven to be useful in identifying runoff components and their characteristics. Moreover, although widely used in humid temperate regions, isotope hydrograph separations have not been studied in detail in arid and semiarid areas. Thus the purpose of this study is to determine whether isotope hydrograph separations are suitable for the quantification and characterization of runoff components in a semi-arid catchment considering the hydrological complexities of these regions. Through a hydrochemical characterization of the surface water and groundwater sources of the catchment and two-and three-component hydrograph separations, runoff components of the Kaap catchment in South Africa were quantified using both isotope and hydrochemical tracers. No major disadvantages while using isotope tracers over hydrochemical tracers were found. Hydrograph separation results showed that runoff in the Kaap catchment is mainly generated by groundwater sources. Two-component hydrograph separations revealed groundwater contributions of between 64 and 98 % of total runoff. By means of threecomponent hydrograph separations, runoff components were further separated into direct runoff, shallow and deep groundwater components. Direct runoff, defined as the direct precipitation on the stream channel and overland flow, contributed up to 41 % of total runoff during wet catchment conditions. Shallow groundwater defined as the soil water and nearsurface water component (and potentially surface runoff) contributed up to 45 % of total runoff, and deep groundwater contributed up to 84 % of total runoff. A strong correlation for the four studied events was found between the antecedent precipitation conditions and direct runoff. These findings suggest that direct runoff is enhanced by wetter conditions in the catchment that trigger saturation excess overland flow as observed in the hydrograph separations.

The description of intertwined ecological processes in surface waters requires a holistic approach that accounts for spatially distributed hydrological/water quality processes. This study describes a new approach to model dissolved oxygen (DO) based on linked hydrodynamic and closed nutrient cycle ecological models. Long term datasets from the River Dommel (Netherlands) are used to determine: 1) if this methodology is suitable for modelling DO concentrations, 2) the model sensitivity to various levels of nutrients input, and 3) the DO production and consumption processes and their response to nutrient input changes. Results show that seasonal dynamics of DO are well quantified at long timescales; the sensitivity of DO to different pollutant sources exhibits significant seasonal variation and the largest influences on DO are aeration and mineralization of organic material. The approach demonstrates an ability to consider the impacts of nutrient input and long term vegetation maintenance on ecological quality. Software Requirements • Wageningen Lowland Runoff Simulator (WALRUS) developed by Brauer et al.

The one‐dimensional advection dispersion equation (1D ADE) is commonly used in practice to simulate pollutant transport processes for assessment and improvement of water quality conditions in rivers. Various studies have shown that the longitudinal dispersion coefficient used within the 1D ADE is influenced by a range of hydraulic and geomorphological conditions. This study aims to quantify the impact and importance of the parameter uncertainty associated with the longitudinal dispersion coefficient on modeled pollutant time‐concentration profiles and its implications for meeting compliance with water quality regulations. Six regression equations for estimating longitudinal dispersion coefficients are evaluated, and commonly used evaluation criteria were assessed for their suitability. A statistical evaluation of the regression equations based on their original calibration data sets resulted in percent bias (PBIAS) values between −47.01% and 20.78%. For a case study, uncertainty associated with the longitudinal dispersion coefficient was propagated to time‐concentration profiles using 1D ADE and Monte Carlo simulations, and 75% confidence interval bands of the pollutant concentration versus time profiles were derived. For two studied equations, the measured peak concentration values were above the simulated 87.5th percentile, and for the other four equations it was close to the 87.5th percentile. Subsequent uncertainty propagation analysis of four diverse rivers show the potential considerable impact on concentration‐duration‐frequency‐based water quality studies, with 1D ADE modeling producing predictions of quality standard compliance which varied over hundreds of kilometers.