All Outputs (2)

The need for operational reasoning in data-driven rating curve prediction of suspended sediment (2012)
Journal Article
Mount, N. J., Abrahart, R., Dawson, C., & Ab Ghani, N. (2012). The need for operational reasoning in data-driven rating curve prediction of suspended sediment. Hydrological Processes, 26(26), https://doi.org/10.1002/hyp.8439

The use of data-driven modelling techniques to deliver improved suspended sediment rating curves has received considerable interest in recent years. Studies indicate an increased level of performance over traditional approaches when such techniques a... Read More about The need for operational reasoning in data-driven rating curve prediction of suspended sediment.

Ideal point error for model assessment in data-driven river flow forecasting (2012)
Journal Article
Dawson, C., Mount, N. J., Abrahart, R., & Shamseldin, A. (2012). Ideal point error for model assessment in data-driven river flow forecasting. Hydrology and Earth System Sciences, 16(8), https://doi.org/10.5194/hess-16-3049-2012

When analysing the performance of hydrological models in river forecasting, researchers use a number of diverse statistics. Although some statistics appear to be used more regularly in such analyses than others, there is a distinct lack of consisten... Read More about Ideal point error for model assessment in data-driven river flow forecasting.