Earth-Science Reviews xxx (2014) xxx EARTH-01959; No of Pages 1 The authors would like to correct some of the numbers in Table 2 in the article by de Vente et al. (2013) referring to the performance of linear regression models applied to Italian catchments. The corrected numbers are indicated in the Table below and concern 1) correction of catchment areas, 2) addition of Model Efficiency for validation data reported Grauso et al. (2008), and, 3) addition of reference to the study where the model calibration was reported (Ciccacci et al., 1987).

Understanding the sediment delivery process at the drainage basin scale remains a challenge in erosion and sedimentation research. In the absence of reliable spatially distributed process-based models for the prediction of sediment transport at the drainage basin scale, area-specific sediment yield (SSY; t km—2 y—1) is often assumed to decrease with increasing drainage basin area (A). As the measurement of A is relatively simple, this assumption is frequently used for prediction of SSY in ungauged basins. However, over the last two decades several studies reported a positive or non-linear relation between A and SSY. Various authors have suggested diverse explanations for these opposing trends. This paper provides an overview of the different observed trends and summarizes the explanations for each trend. Furthermore, three typical trends are identified to conceptualize the main driving forces of the relation between A and SSY. First of all, it is emphasized that erosion and sediment deposition processes are scale dependent, and going from small (<m2) to larger areas (km2) more erosion processes become active leading to a rise in SSY with increasing A. However, for larger areas (>km2) erosion rates generally decrease and deposition in sediment sinks increases due to decreasing slope gradients, and so SSY decreases with increasing A. Next, land-cover conditions and human impact determine if hillslope erosion is dominant over channel erosion or vice versa. In the first case, SSY is expected to decrease with increasing A, while in the latter case SSY will show a continuous positive relation with A. Only for very large areas (A > ~104 km2) a decrease in SSY is observed when drainage density decreases or channel banks are stabilized. Finally, spatial patterns in lithology, land cover, climate or topography can cause SSY to increase or decrease at any basin area and can therefore result in non-linear relations with A. Altogether, with increasing A often first a rise and then a decrease in SSY is observed. The decrease can be absent or can be postponed within a region due to local factors of which lithology, land cover, climate and topography are the most important ones. The large regional, local and even temporal variability in the trend between A and SSY implies that prediction of SSY based on A alone is troublesome and preferably spatially distributed information on land use, climate, lithology, topography and dominant erosion processes is required.

The bulk of eroded soils measured at the outlets of plots, slopes and watersheds are suspended sediments, splash-induced sheet erosion. It is depending on rainfall intensity and antecedent soil moisture contents and contributes to a significant proportion of soil loss that usually is ignored in soil erosion and sediment studies. A digital image processing method for tracing and measuring non-suspended soil particles detached/transported by splash/runoff was therefore used in the present study. Accordingly, fine mineral pumice grains aggregated with white cement and coloured with yellow pigment powder, with the same size, shape and specific gravity as those of natural soil aggregates, called synthetic color-contrast aggregates, were used as tracers for detecting soil particle movement. Subsequently, the amount of non-suspended soil particles detached and moved downward the slope was inferred with the help of digital image processing techniques using MATLAB R2010B software (Mathworks, Natick, Massachusetts, USA). The present study was conducted under laboratory conditions with four simulated rainfall intensities between 30-90 mm h -1 , five antecedent soil moisture contents between 12-44 % v v -1 and a slope of 30%, using sandy loam soils taken from a summer rangeland in the Alborz Mountains, Northern Iran. A range of total transported soil between 90.34 and 1360.93 g m -2 and net splash erosion between 36.82 and 295.78 g m -2 were observed. The results also showed the sediment redeposition ratio ranging from 87.27% [sediment delivery ratio (SDR) = 12.73%] to 96.39% (SDR = 3.61%) in various antecedent soil moisture contents of rainfall intensity of 30 mm h -1 and from 80.55% (SDR = 19.45%) to 89.42% (SDR = 10.58%) in rainfall intensity of 90 mm h -1 .

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Suspended sediment transport in river for a particular period is a timescale finite population. This population shows natural aggregation tendencies in sediment concentration particularly during floods. Adaptive cluster sampling (ACS) can be potentially conducted for sampling from this rare clustered population and estimating total load. To illustrate the performance of ACS in sediment estimation, a comparative study was carried out in the Gorgan-Rood River, Iran, with around a 5 year daily concentration record. The total sediment loads estimated by ACS were statistically compared to the observed load, estimations of selection at list time (SALT) and conventional sediment rating curve with and without correction factors. The results suggest that none of the sediment rating curves produced accurate estimates, while both ACS and SALT showed satisfactory results at a semi-weekly sampling frequency. The best estimation obtained by the rating curves did not show a percent error better than −40%; however, ACS and SALT underestimated the load at less than 5%. The results of this study suggest ACS could improve river monitoring programs.

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