ADV measurements of velocity distributions in a gravel‐bed flume

Velocity measurements carried out by an acoustic doppler velocimeter (ADV) in a rectangular laboratory ?ume having a gravel bed are presented. The velocity pro?les are measured in six verticals of the channel cross‐section having an increasing distance (from 4 to 38·5 cm) from the ?ume wall. The experimental runs are carried out for ?ve different bed arrangements, characterized by different concentrations of coarser elements, and for the two conditions of small‐ and large‐scale roughness. For both hydraulic conditions, the velocity measurements are ?rst used to test the applicability of the Dean pro?le and of the logarithmic pro?le corrected by a divergence function proposed in this paper. Then, for each value of the depth sediment ratio h/d₈₄, the non‐dimensional friction factor parameter is calculated by integration of the measured velocity distributions in the different verticals of the cross‐section. Finally a semi‐logarithmic ?ow resistance equation is empirically deduced. Copyright © 2003 John Wiley & Sons, Ltd.     

A verification framework for interannual-to-decadal predictions experiments

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.     

Evaluating overland flow sediment transport capacity

An equation for evaluating the sediment transport capacity of overland flow is a necessary part of a physically based soil erosion model describing sediment detachment and transport as distributed processes. At first, for the hydraulic conditions of small-scale and large-scale roughness, the sediment transport capacity relationship used in the WEPP model is calibrated by Yalin and Govers' equation. The analysis shows that the transport coefficient K_t depends on the Shields parameter, Y, according to a semi-logarithmic (Yalin) or a linear (Govers) equation. The reliability of the semi-logarithmic equation is verified by Smart's, and Aziz and Scott's experimental data. Then the Low's formula, whose applicability is also proved by Smart's, and Aziz and Scott's data, is transformed as a stream power equation in which a stream power coefficient, K_SP, depending on Shields parameter, slope, sediment and water-specific weight, appears. A relationship between transport capacity and effective stream power is also proposed. Finally, the influence of rainfall on sediment transport capacity and the prediction of critical shear stress corresponding to overland flow are examined. © 1998 John Wiley & Sons, Ltd.     

Measuring hydrological connectivity inside a soil by low field nuclear magnetic resonance relaxometry

Hydrological connectivity inside the soil is related to the spatial patterns inside the soil (i.e., the structural connectivity). This, in turn, is directly associated with the physical and the chemical processes at a molecular level (i.e., the functional connectivity). Nuclear magnetic resonance (NMR) relaxometry can be successfully applied to reveal both structural and functional components of soil hydrological connectivity. In the present study, the low field NMR relaxometry was applied on water suspended soils sampled at the upstream‐ and downstream‐end of three different length plots. Also the sediments collected from the storage tanks at the end of each plot were water suspended and monitored by NMR relaxometry. The results from the NMR investigations were elaborated by using a mathematical approach in order to quantify both the functional and structural connectivity components. In particular, following integration of the T₁ distribution curve, an S‐shaped curve was obtained. It revealed two plateaus corresponding to the shortest (low component) and the longest (high component) intervals of relaxation times, respectively. According to relaxometry theory, the two T₁ intervals, associated to the different plateaus, were attributed to micro and macro soil pores, respectively. The two T₁ intervals were used to define a functional connectivity index, while the central part of the S‐shaped distribution was used to define a structural connectivity index. Here we provide the physical meaning of the our mathematical approach, thereby revealing that functional connectivity index increases with plot length, as a result of a selective eroded particle transport. Moreover, the relationship structural connectivity index versus plot length resulted quasi‐independent of grainsize distribution, whereas the values of the structural connectivity index for the sediment samples resulted lower than those obtained for the corresponding soils.     

Evaluation of the SEDD model for predicting sediment yield at the Sicilian experimental SPA2 basin

In this paper a spatially distributed model of the hillslope sediment delivery processes, named the sediment delivery distributed (SEDD) model, is initially reviewed; the model takes into account the sediment delivery processes due to both the hillslope sediment transport and the effects of slope curvature. Then the rainfall and sediment yield events measured at the experimental SPA2 basin, in Sicily, are used both to calibrate the SEDD model and to verify the predictive capability of the distributed sediment delivery approach at event scale. For the SPA2 basin discretized into morphological units and stream tubes, the SEDD model is calibrated at event scale using the measurements carried out at the outlet of the experimental basin in the period December 2000–January 2001. The model calibration is used to determine a relationship useful for estimating the unique coefficient β_e of the model by rainfall erosivity factor R_e at event scale. To test the predictive capability of the β_e = f(R_e) relationship, 20 events measured in the period September 2002–December 2005 are used; the comparison between measured sediment yield values and calculated ones for all monitored events shows that the sediment delivery distributed approach has a good predictive ability at event scale. The analysis also shows that estimating β_e by the relationship β_e = f(R_e) gives a better agreement between measured and calculated sediment yields than obtained with the median value β_e,m of all 27 calculated β_e values. Finally the analysis at annual scale, for the period 2000–2005, allows the estimation of the median value β_a,m representative of the annual behaviour. This analysis shows that the sediment delivery distributed approach also has a good predictive ability at annual scale. Copyright © 2006 John Wiley & Sons, Ltd.