Variance decomposition of forecasted sediment transport in a lowland watershed using global climate model ensembles.

• Hydrologic model parameterization produces greatest uncertainty for sediment transport forecasts via GCMs. • Water and sediment forecasts are under-predicted 49% and 35% when only precipitation and temperature are included. • Streamflow and sediment yield forecasts increase by 19% and 14% for the shear-limited landscape and transport-limited stream. Forecasting change in sediment transport using global climate model ensembles is under-developed in the hydrology community due to a lack of knowledge regarding the variance structure of predictions. We investigate the uncertainty of forecast sediment transport from sources, including global climate model realizations, global climate model ensemble design, forecasted hydrologic inputs, and hydrologic modeling parameterizations. We then forecast sediment transport for the gently rolling watershed in Kentucky, USA. Contrary to past research forecasting hydrology with global climate models, hydrologic model parameterization was the most significant source of variance impacting forecasted sediment transport variables. Forecast of sediment transport responses shows the propagation of uncertainty from the hydrologic model parameterization was over two times greater than the uncertainty from the selected global climate model realizations. This result emphasizes researchers focused on forecasting sediment transport with global climate models may need to give as much, or more, consideration to their water–sediment linkages as climate-water–sediment linkages. Hydrologic inputs from climate change, including forecast precipitation, temperature, relative humidity, solar radiation, and wind speed, impacted sediment transport. Considering changes in precipitation and temperature alone under-predicts streamflow and sediment transport by 49% and 35%, respectively, compared to including all meteorological variables inputs. Variance introduced across the three different global climate model ensembles was a relatively small source of variance impacting forecasted streamflow or sediment yield. The results suggest a quantitative effort by the researcher to design the global climate model ensemble by considering representativeness, historical performance, and independency will lead to robust results. Ensemble average forecasts forecast streamflow and sediment yield to increase by 19% and 14%, respectively, for the lowland watershed. The sediment transport forecasts reflect the shear-limited landscape of the watershed and the transport-limited conditions in the stream channel. [ABSTRACT FROM AUTHOR]