The latter has proven to be most effective, since the bed slope parameter linearly increases downslope sediment transport and thereby directly affects channel depth and bar dimensions and therefore has the largest effect on large-scale morphology 8, 9. However, in practice, all large-scale models depend on model choices and need some form of calibration to converge to a stable morphology, for example by the choice in roughness predictor 4, 5, adding coarser grain sizes in the channels 6 or include a non-erodible layer that limits channel depth 7, and increasing the transverse bed slope parameter, which determines the amount of sediment transported on channel side slopes. Morphodynamic models are therefore widely used tools to study and forecast the development of these landscapes. Reliable forecasting of effects of combined measures requires morphodynamic models for rivers, estuaries, deltas, and coasts. Adaptation requires a system approach 1, 2 with combinations of hard engineering measures and sediment attrition 3. River valleys, coastal plains, and deltas are changeable landscapes with a large part of the human population that will be at risk from climate change effects and sea level rise. We discuss the major implications for model interpretation and a critical knowledge gap. We show how model design can be optimized for different applications. Consequently, present calibration practice may cause an order magnitude error in either morphology or morphological change. For five different models bracketing a range of scales and environments, we found that it is impossible to calibrate a model on both sediment transport magnitude and morphology. Here we show that such arbitrary calibrations dramatically bias sediment dynamics, channel patterns, and rate of morphological change. However, many existing morphodynamic models predict unrealistically high channel incision, which is often dampened by increased gravity-driven sediment transport on side-slopes by up to two orders of magnitude too high. The morphological development of fluvial and tidal systems is forecast more and more frequently by models in scientific and engineering studies for decision making regarding climate change mitigation, flood control, navigation and engineering works.
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