Ebru Eris

Laboratory experiments of sediment transport from bare soil with a rill

Abstract Mathematical models developed for quantification of sediment transport in hydrological watersheds require data collected through field or laboratory experiments, but these are still very rare in the literature. This study aims to collect such data at the laboratory scale. To this end, a rainfall simulator equipped with nozzles to spray rainfall was constructed, together with an erosion flume that can be given longitudinal and lateral slopes. Eighty experiments were performed, considering microtopographical features by pre-forming a rill on the soil surface before the start of each experiment. Medium and fine sands were used as soil, and four rainfall intensities (45, 65, 85 and 105 mm h-1) were applied in the experiments. Rainfall characteristics such as uniformity, granulometry, drop velocity and kinetic energy were evaluated; flow and sediment discharge data were collected and analysed. The analysis shows that the sediment transport rate is directly proportional to rainfall intensity and slope. In contrast, the volumetric sediment concentration stays constant and does not change with rainfall intensity unless the slope changes. These conclusions are restricted to the conditions of experiments performed under rainfall intensities between and 105 mm h-1 for medium and fine sands in a 136-cm-wide, 650-cm-long and 17-cm-deep erosion flume with longitudinal and lateral slopes varying between 5 and 20%. Editor Z.W. Kundzewicz; Associate editor G. Mahé Citation Aksoy, H., Unal, N.E., Cokgor, S., Gedikli, A., Yoon, J., Koca, K., Inci, S.B., Eris, E., and Pak, G., 2013. Laboratory experiments of sediment transport from bare soil with a rill. Hydrological Sciences Journal, 58 (7), 1505–1518.

Evaluation of an erosion-sediment transport model for a hillslope using laboratory flume data

Climate change can escalate rainfall intensity and cause further increase in sediment transport in arid lands which in turn can adversely affect water quality. Hence, there is a strong need to predict the fate of sediments in order to provide measures for sound erosion control and water quality management. The presence of microtopography on hillslopes influences processes of runoff generation and erosion, which should be taken into account to achieve more accurate modelling results. This study presents a physically based mathematical model for erosion and sediment transport coupled to one-dimensional overland flow equations that simulate rainfall-runoff generation on the rill and interrill areas of a bare hillslope. Modelling effort at such a fine resolution considering the flow connection between interrill areas and rills is rarely verified. The developed model was applied on a set of data gathered from an experimental setup where a 650 cm×136 cm erosion flume was pre-formed with a longitudinal rill and interrill having a plane geometry and was equipped with a rainfall simulator that reproduces natural rainfall characteristics. The flume can be given both longitudinal and lateral slope directions. For calibration and validation, the model was applied on the experimental results obtained from the setup of the flume having 5% lateral and 10% longitudinal slope directions under rainfall intensities of 105 and 45 mm/h, respectively. Calibration showed that the model was able to produce good results based on the R2 (0.84) and NSE (0.80) values. The model performance was further tested through validation which also produced good statistics (R2=0.83, NSE=0.72). Results in terms of the sedigraphs, cumulative mass curves and performance statistics suggest that the model can be a useful and an important step towards verifying and improving mathematical models of erosion and sediment transport.

Preface—Special Issue: Facets of Uncertainty

Uncertainty is the only certainty we have, taught Pliny the Elder 20 centuries ago. How far have we come today, in that modern science would confirm or contradict this classical conundrum? This Special Issue of Hydrological Sciences Journal is dedicated particularly to contributions that could shed some light on any of the many facets of uncertainty. The title of the Special Issue has been inspired by the name of a triple conference held on Kos Island (Greece) in October of 2013, which also represents its main source of contributions. The triple conference, convened by Demetris Koutsoyiannis, hosted the Statistical Hydrology (STAHY) Workshop of the International Association of Hydrological Sciences (IAHS), the Leonardo Conference of the European Geosciences Union (EGU), and the third edition of the Hydrofractals Conference, all of which focused, this time, on the most diverse aspects of uncertainty in natural processes. The different facets involving the role of uncertainty in modelling natural processes include the heuristics of its presence (regarded by many as an opponent of science, eventually to-be-eliminated, but perhaps being intrinsic to nature, as stated by the standard view of quantum mechanics or implied by statistical thermophysics and the theory of dynamical systems), its pragmatic treatment (estimation and ways to include it into mathematical models), as well as its propagation in model predictions. The paper by Dimitriadis et al. (2016a) compares the predictability of a die’s motion with that of hydrometeorological processes, and challenges the false dichotomy between determinism and randomness, showing how deterministic approaches can be combined with uncertainty estimation. A particular section (Sutcliffe et al. 2016, O’Connell et al. 2016) celebrates the legacy of Harold Edwin Hurst, the empirical discoverer of long-range dependence in natural processes. It is not surprising that this discovery occurred precisely in the field of hydrology, where it managed to grant a parsimonious description to an otherwise complex process. The fertility of the seed that Hurst planted is shown by the variety of areas in which similar scaling behaviours with statistically estimated exponents are being employed, from structure functions in turbulence to climatic processes, as well as by the great minds who have concerned themselves with its study, Kolmogorov, Wiener, Mandelbrot and many others. Historically, it has been precisely the existence of such, initially regarded as “anomalous”, exponents characterizing the behaviour of many natural processes that prompted the development of the notions of fractal sets and fractal measures. These eventually grew into the more general theory of monofractal and multifractal scaling, whose contribution to the development of hydroscience has largely yet to be written. This Special Issue adds to the body of knowledge on this topic with three papers. The first contribution (Tsonis, 2016) is a concept paper introducing randomness as a property of nature, while the stochastic representation with uncertainty of the self-similarity structures of turbulence and hydrometeorological processes, e.g. fractal dimension and Hurst coefficient, is covered by Dimitriadis et al. (2016b). Finally, Gires et al. (2016) discuss the use of the theory of multifractals as a tool to improve knowledge and understanding of hydrometeorological processes (specifically, rainfall as a space−time process). The Leonardo Conference, in turn, offered an opportunity for the development of applications and new methodology, as well as revisiting the underlying philosophical basis for uncertainty analysis. The contribution by Beven (2016), inspired by his Leonardo Lecture, highlights the rich history and current challenges of uncertainty analysis, having to deal with various types of uncertainty that he defines. Nearing et al. (2016) put the debate about hydrological uncertainty analysis into the context of the historical literature on epistemology and the contemporary axiomatically derived interpretation of probability theory as extended logic. Tyralla and Schumann (2016) present a new approach for dealing with model structural uncertainty. Mylopoulos and Sidiropoulos (2016) consider the management of an aquifer under uncertain hydrogeology of the subsurface and propose a stochastic optimization approach, while Mukolwe et al. (2016) deal with uncertainties on the surface, studying the influence of various elevation datasets on accuracy of flooding models. Kabeya et al. (2016) quantify the effects of forest harvesting versus climate on streamflow variability and trend, while Koga et al. (2016) present an urban-scale hydrological application accounting for the uncertainty in land-use delineation. Maftei et al. (2016) investigate the presence of long-range dependence in flow time series from a sparsely studied region in Romania. Finally, Di Baldassarre et al. (2016) consider the seventh facet of uncertainty, unknown unknowns, and the surprises that can arise in coupled socio-hydrological systems. As work on this Special Issue comes to a close, we cannot avoid a look back to the island of Kos, venue of the “Facets of Uncertainty” triple conference and homeland of Hippocrates, the pioneer of Western Medicine and a paragon of mitigating human suffering, only to find that the paradise we came to know during the conference, has since been overshadowed by the uncountable tragedies of those who, having been uprooted from their homeland by war, have come to seek shelter on the island. As researchers in the realm of uncertainty, it is precisely the latter that allows us to be hopeful for an end to the humanitarian crisis, as it is uncertainty itself that allows for unexpected change (Koutsoyiannis 2010, 2013), and enables the existence of such marvellous human HYDROLOGICAL SCIENCES JOURNAL – JOURNAL DES SCIENCES HYDROLOGIQUES, 2016 VOL. 61, NO. 9, 1555–1556 http://dx.doi.org/10.1080/02626667.2016.1186919 Special issue: Facets of Uncertainty