[1] A new model for the depth-averaged velocity for flow in presence of submerged vegetation is developed. The model is based on a two-layer approach, where flow above and through the vegetation layer is described separately. Vegetation is treated as a homogeneous field of identical cylindrical stems, and the flow field is considered stationary and uniform. It is demonstrated that scaling considerations of the bulk flow field can be used to avoid complications associated with smaller scale flow processes and that still the behavior of depth-averaged flow over vegetation is described accurately. The derived scaling expression of the average flow field is simple in form, it follows fundamental laws of fluid flow, and it shows very good agreement with laboratory flume experiments. The new model can be used for quick evaluation of a river's hydraulic response in cases where vegetated floodplains are inundated.

Abstract. Models with a fixed structure are widely used in hydrological studies and operational applications. For various reasons, these models do not always perform well. As an alternative, flexible modelling approaches allow the identification and refinement of the model structure as part of the modelling process. In this study, twelve different conceptual model structures from the SUPERFLEX framework are compared with the fixed model structure GR4H, using a large set of 237 French catchments and discharge-based performance metrics. The results show that, in general, the flexible approach performs better than the fixed approach. However, the flexible approach has a higher chance of inconsistent results when calibrated on two different periods. When analysing the subset of 116 catchments where the two approaches produce consistent performance over multiple time periods, their average performance relative to each other is almost equivalent. From the point of view of developing a well-performing fixed model structure, the findings favour models with parallel reservoirs and a power function to describe the reservoir outflow. In general, conceptual hydrological models perform better on larger and/or wetter catchments than on smaller and/or drier catchments. The model structures performed poorly when there were large climatic differences between the calibration and validation periods, in catchments with flashy flows, and in catchments with unexplained variations in low flow measurements.

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Solvent flushing is a potential technique for remediating a waste disposal/spill site contaminated with organic chemicals. This technique involves the injection of a solvent mixture (e.g., water plus alcohols) that enhances contaminant solubility, reduces the retardation factor, and increases the release rates of the contaminants. A simulation model is developed to predict contaminant elution curves during solvent flushing for the case of one-dimensional, steady flow through a contaminated medium. Column experiments are conducted with a Eustis fine sand that is initially equilibrated with an aqueous naphthalene solution, and then eluted with different methanol-water mixtures to remove the naphthalene. The model simulations, based on parameter values estimated from literature data, agree well with the measured elution profiles. Solvent flushing experiments, where the soil was initially equilibrated with a solution of naphthalene and anthracene, show that compounds with different retardation factors are separated at low cosolvent contents, while coelution of the compounds occurs at higher contents. In general, the smaller the retardation factor in water and the higher the cosolvent fraction, the faster the contaminant is recovered. The presence of nonequilibrium conditions, soil heterogeneity, and type of cosolvent will influence the time required to recover the contaminant.

The capability of the first-order, dual-porosity model, which explicitly accounts for non-ideal transport caused by the presence of 'immobile' water, to predict the non-ideal transport of nonsorbing solute in a constructed aggregated soil has been investigated. Miscible-displacement experiments performed with a well-characterized aggregated soil and a non-reactive tracer (pentafluorobenzoate) served as the source of the data. Values for the input parameters associated with physical non-equilibrium were determined independently and compared with values obtained by curve fitting of the experimental measurements. The calculated and optimized values compared well, suggesting that the non-equilibrium parameters represent actual physical phenomena.

The spatio-temporal dynamics of the trophic state of a lake are crucial in defining its water quality, as well as biodiversity. Accordingly, this study focused on the spatio-temporal variations of the trophic state, and the possible causes of the heterogeneous turbidity in Lake Naivasha, Kenya. The trophic state of the lake oscillated between a eutrophic and hypereutrophic condition, being found to be more eutrophic than reported in previous studies, indicating a progressive deterioration of its water quality. Inferences from the graphical representation of the deviations of total phosphorus and Secchi depth from the chlorophyll-a trophic state indices revealed that the lake is predominantly phosphorus limited. Furthermore, the turbidity in the northern part of the lake is dominated by suspended sediment and dissolved coloured material. Discriminant analysis resulted in identification of three distinct trophic state regions in Lake Naivasha, namely the northern region, the mid and southern part and the more or less isolated Crescent Lake. The results of this study provide a good basis for further investigation of the current loading magnitude of both nutrients and sediments, in order to facilitate sustainable management to ensure community integrity and ecosystem functions of the lake.

Water quality information in aquatic ecosystems is crucial in setting up guidelines for resource management. This study explores the water quality status and pollution sources in Lake Naivasha, Kenya. Analysis of water quality parameters at seven sampling sites was carried out from water samples collected weekly from January to June and biweekly from July to November in 2011. Principal component analysis (PCA) and cluster analysis (CA) were used to analyse the dataset. Principal component analysis showed that four principal components (PCA-1 to PCA-4) explained 94.2% of the water quality variability. PCA-1 and PCA-2 bi-plot suggested that turbidity in the lake correlated directly to nutrients and iron with close association with the sampling site close to the mouth of Malewa River. Three distinct clusters were discerned from the CA analysis: Crescent Lake, a more or less isolated crater lake, the northern region of the lake, and the main lake. The pollution threat in Lake Naivasha includes agricultural and domestic sources. This study provides a valuable dataset on the current water quality status of Lake Naivasha, which is useful for formulating effective management strategies to safeguard ecosystem services and secure the livelihoods of the riparian communities around Lake Naivasha, Kenya.

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