Evaluating the eutrophication risk of a receiving reservoir is crucial for scientific water
transfer schemes. However mega water transfer projects would greatly affect both water …

Input error is one of the main sources of uncertainty in hydrological models. It mainly comes
from the uncertainty of precipitation data, which is caused by inaccurate measurement at the …

In the process of hydrological forecasting, there are uncertainties in data input, model
parameters, and model structure, which cause a deterministic forecasting to fail to provide …

Low-quality input data (such as sparse rainfall gauges, low spatial resolution soil type and
land use maps) have limited the application of physically-based distributed hydrological …

The outputs of Rainfall-runoff models are inherently uncertain and quantifying the
associated uncertainty is crucial for water resources management activities. This study …

Urbanization in the Haihe River Basin in northern China, particularly the upstream
mountainous basin of Baiyangdian, has significantly altered land use and runoff processes …

This research develops an extension of the Model Conditional Processor (MCP), which
merges clusters with Gaussian mixture models to offer an alternative solution to manage …

The hydrological model requires precise parameter calibration to reflect the basin
characteristicsproperly. The optimum parameter values depend highly on the runoff …

Early warning of safety risks downstream of small reservoirs is directly related to the safety of
people's lives and property and the economic and social development of the region. The …

Hydrological forecasting plays an important role in basin flood control systems, and the
uncertainty of hydrological forecasting is helpful to reveal basin hydrological characteristics …