Rainfall uncertainty in hydrological modelling: An evaluation of multiplicative error models

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GLUE: 20 years on (2014, background): “The first is to collect more detailed data, and there are projects currently addressing this at least in rainfall dominated regimes (Anagnostou et al., 2004; McMillan et al., 2011).”
Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities (2012, background): “, the sum of squared differences between simulated and observed streamflow), and the individual components of the model are rarely subject to scientific scrutiny (Kuczera and Franks, 2002; Gupta et al., 2008; McMillan et al., 2011).”
Use of an entropy‐based metric in multiobjective calibration to improve model performance (2014, background): “In late summer (February and March), remnants of tropical cyclones occasionally pass over northern New Zealand, producing intense bursts of rainfall [McMillan et al., 2011a].”