In deltaic deposits, the largest volumes of sandy deposits occur at the delta top (as channel accretion, overbank deposits) and as distinct or amalgamated sandy mouth bars in the upper delta front. We use process-based models to study the sediment distribution in four evolving deltas, each with a different input sediment profile. We show how the mouthbar deposits can preserve a large proportion of the sand preserved in the sedimentary record of deltaic systems.@en

Geological models are generated by interpretation and interpolation of sparse data. To limit uncertainty, relevant analogues are used to extrapolate knowledge of previously studied, well understood systems. However, these analogues only provide a snapshot of deposition. During delta progradation, sediment will not only be deposited, but is also reworked resulting in unique preserved sediment distribution patterns for each delta. We show how process-based models can be used to study the evolution of deltaic sediment distribution in four dimensions. Grain-size distribution trends are extracted from preserved deposits in synthetic analogues of prograding deltas.@en

Abstract Understanding the processes and conditions at the time of deposition is key to the development of robust geological models which adequately approximate the heterogeneous delta morphology and stratigraphy they represent. We show how the mechanism of sediment transport (the proportion of the sediment supply transported as bed load vs. suspended load) impacts channel kinematics, delta morphology and stratigraphy, to at least the same extent as the proportion of cohesive sediment supply. This finding is derived from 15 synthetic delta analogues generated by processes-based simulations in Delft3D. The model parameter space varies sediment transport mechanism against proportions of cohesive sediment whilst keeping the total sediment mass input constant. Proximal morphology and kinematics previously associated with sediment cohesivity are also produced by decreasing the proportion of bed load sediment transport. However, distal depositional patterns are different for changes in sediment transport and sediment load cohesivity. Changes in sediment transport mechanisms are also shown to impact clinoform geometry as well as the spatiotemporal scale of autogenic reorganisation through channel avulsions. We conclude that improving insight into the ratio of bed load to suspended load is crucial to predicting the geometric evolution of a delta.@en

The process of constructing geological models is used on various scales in mining, oil and gas exploration, hydrology as well as in large construction projects. Development of geological models is a complex process consisting of various phases. A large degree of uncertainty is introduced from the interpretation of the data to the construction of the geological model. To arrive at the best approximation of the subsurface, relevant analogues are identified and consulted. Therefore, uncertainties originate from unknown depositional processes, but also from uncertain correlation between the study area and the analogues. We developed a set of tools to quantify the variability in deltaic geological models resulting from these uncertainties. These tools were applied to an ensemble of simulations generated in Delft3D by processed-based forward modelling. We show how a set of analyses can be used to quantify the differences in the resultant delta deposits. Analyses investigated channel networks, topographic profiles and sediment distribution in the delta. The tools make use of the unique advantages of numerical forward models, allowing single variables to be studied at high spacial and temporal resolution. @en

New developments are currently being undertaken to develop a new open source web-based modelling system based on the process-based model Delft3D. This modelling systems (Delft3D-GeoTool) aims to provide non-modeling specialists (as wel as specialists) in the field of sedimentary geology and reservoir geology with tools to easily set up their own model simulations and scenarios, perform post-processing analyses and store the results in a database. @en