Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–Č Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-301 PEER REVIEWED ARTICLE 2011 Matteo Tregnaghi Modelling time varying scouring at bed sills 10.1002/esp.2198 Hydrological modeling Groundwater ABSTRACTIn this paper a modelling approach is presented to predict local scour under time varying flow conditions. The approach is validated using experimental data of unsteady scour at bed sills. The model is based on a number of hypotheses concerning the characteristics of the flow hydrograph, the temporal evolution of the scour and the geometry of the scour hole. A key assumption is that, at any time, the scour depth evolves at the same rate as in an equivalent steady flow. The assumption is supported by existing evidence of geometrical affinity and similarity of scour holes formed under different steady hydraulic conditions. Experimental data are presented that show the scour hole development downstream of bed sills due to flood hydrographs follow a predictable pattern. Numerical simulations are performed with the same input parameters used in the experimental tests but with no post‐simulation calibration. Comparison between the experimental and model results indicates good correspondence, especially in the rising limb of the flow hydrograph. This suggests that the underlying assumptions used in the modelling approach are appropriate. In principle, the approach is general and can be applied to a wide range of environments (e.g. bed sills, step‐pool systems) in which scouring at rapid bed elevation changes caused by time varying flows occurs, provided appropriate scaling information is available, and the scour response to steady flow conditions can be estimated. Copyright © 2011 John Wiley & Sons, Ltd. 235755
publications-302 PEER REVIEWED ARTICLE 2011 Andrea Busolin Bottacin Evidence of distinct transport patterns contaminant in rivers using tracer tests and a multiple domain retention model 10.1016/j.advwatres.2011.03.005 Hydrological modeling River Basins No abstract available 235755
publications-303 PEER REVIEWED ARTICLE Matteo Tregnaghi Risk of entrainment in uniformly sized sediment beds at low transport stages I: Theory Uncategorized River Basins No abstract available 235755
publications-304 PEER REVIEWED ARTICLE 2012 Matteo Tregnaghi Risk of entrainment in uniformly sized sediment beds at low transport stages II: Experiments 10.1029/2011jf002135 Uncategorized Groundwater Fluvial sediment transport is caused by a complex interaction of interdependent grain and fluid processes many of which are stochastic in nature and cannot be adequately represented by deterministic equations. Random variable analysis has been used previously but limited data are available to describe the variability of grain resistance combined with particle arrangements, and thus validate such analysis. In this study low to medium bed load transport tests were carried out in a flume where sediment movement was monitored using a three‐camera 3D PIV system. Simultaneous grain motion and flow velocity measurements were made on a plane located slightly above and parallel to the sediment bed. Detailed statistical velocity information was acquired to model the velocity distribution at the bed level. This was combined with the joint probabilistic distribution of particle exposures and grain resistance to motion, which were obtained from discrete particle modeling (DPM) simulations. DPM simulations were used to provide a stochastic mathematical description of the risk that a stationary particle is entrained by the flow. Predictions from the stochastic model equations replicated the observed pulsation in sediment transport. This demonstrates that it is possible to simulate sediment entrainment and transport at a high resolution by adequately modeling all the sub‐processes. A number of flow patterns were identified that caused large fluctuations of the entrainment rate. These all exhibit high velocity flow structures, but they selectively cause the dislodgement of individual particles located at different positions. This selective behavior follows from the variability of the interaction between the near‐bed flow and the particles having different exposure. 235755
publications-305 PEER REVIEWED ARTICLE 2011 Gowen, A., Tsenkova, R., Bruen, M., O’Donnell, C. Vibrational spectroscopy for water?quality analysis: a review. Critical Reviews in Environmental Science and Technology? 10.1080/10643389.2011.592758 Simulation & Modeling River Basins No abstract available 237819
publications-306 PEER REVIEWED ARTICLE 2010 Gowen, A., Downey, G., Esquerre, C., O’Donnell, C. Preventing over-fitting in PLS?calibration models of near infrared (NIR) spectroscopy data using regression coefficients? 10.1002/cem.1349 Simulation & Modeling River Basins AbstractSelection of the number of latent variables (LVs) to include in a partial least squares (PLS) model is an important step in the data analysis. Inclusion of too few or too many LVs may lead to, respectively, under or over‐fitting of the data and subsequently result in poor future model performance. One well‐known sign of over‐fitting is the appearance of noise in regression coefficients; this often takes the form of a reduction in apparent structure and the presence of sharp peaks with a high degree of directional oscillation, features which are usually estimated subjectively. In this work, a simple method for quantifying the shape and size of a regression coefficient is presented. This measure can be combined with an indicator of model bias (e.g. root mean square error) to aid in estimation of the appropriate number of LVs to include in a PLS model. The performance of the proposed method is evaluated on simulated and and real NIR spectroscopy datasets sets and compared with several existing methods. Copyright © 2010 John Wiley & Sons, Ltd. 237819
publications-307 PEER REVIEWED ARTICLE 2011 Gowen, A., Marini, F., Esquerre, C., O’Donnell, C., Downey, G., Burger, J. Time series?hyperspectral chemical imaging data: challenges, solutions and applications? 10.1016/j.aca.2011.06.031 Simulation & Modeling Irrigation Systems No abstract available 237819
publications-308 PEER REVIEWED ARTICLE 2011 Esquerre, C., Gowen, A.A., O’Donnell, C., Downey, G Selection of variables based on most stable normalised partial least squares regression coefficients in an ensemble Monte Carlo procedure 10.1255/jnirs.962 Uncategorized Uncategorized A modification of ensemble Monte Carlo uninformative variable elimination (EMCUVE) is proposed, which does not involve the use of random variables, with the aim of improving the performance of partial least squares (PLS) regression models, increasing the consistency of results and reducing processing time by selecting the most informative variables in a spectral dataset. The proposed method (ensemble Monte Carlo variable selection—EMCVS) and the robust version (REMCVS) were compared to PLS models and with the existing EMCUVE method using three near infrared (NIR) datasets, i.e. prediction of n-butanol in a five-solvent mixture, moisture in corn and glucosinolates in rapeseed. The proposed methods were more consistent, produced models with better predictive accuracy (lower root mean squared error of prediction) and required less computational time than the conventional EMCUVE method on these datasets. In this application, the proposed method was applied to PLS regression coefficients but it may, in principle, be used on any regression vector. 237819
publications-309 PEER REVIEWED ARTICLE 2011 Burger, J., Gowen, A. Data handling in Hyperspectral Image Analysis 10.1016/j.chemolab.2011.04.001 Data Management & Analytics Natural Water Bodies No abstract available 237819
publications-310 PEER REVIEWED ARTICLE 2013 A.A. Gowen, J.M. Amigo, R. Tsenkova Characterisation of hydrogen bond perturbations?in aqueous systems using aquaphotomics and multivariate curve resolution 10.1016/j.aca.2012.10.007 Uncategorized Groundwater No abstract available 237819