Hydrological models are important tools for flood forecasting and for the assessment of
water resources under current and changing climate. However, the accuracy of hydrological …

Most lumped hydrological models use areal average precipitation data as model input.
Though weather-radar-based and satellite-based precipitation estimation methods have …

The Bayesian model averaging (BMA), hydrological uncertainty processor (HUP), and HUP-
BMA methods have been widely used to quantify flood forecast uncertainty. This study …

Disinformation as a result of epistemic error is an issue in hydrological modelling. In
particular the way in which the colour in model residuals resulting from epistemic errors …

The assessment of future impacts of climate change is associated with a cascade of
uncertainty linked to the modelling chain employed in assessing local-scale changes …

Abstract Study Region Four subbasins in the Gandaki River Basin in the southern
Himalayan region. Study Focus In the southern Himalayan region, gridded precipitation …

In this study, we explore the effect of uncertainty and poor observation quality on
hydrological model calibration and predictions. The Osali catchment in Western Norway was …

A growing number of investigations on uncertainty quantification for hydrological models
have been widely reported in past years. However, limited studies are found on uncertainty …

Detailed sowing and harvesting (S&H) information is crucial for climate-coupled crop models
to accurately simulate dynamic crop growth. The timing of intra-annual crop growth not only …

For capturing spatial variations of runoff and nutrient fluxes attributed to catchment
heterogeneity, multi-site hydrological water quality monitoring strategies are increasingly put …