Accurate rainfall data are of prime importance for many environmental applications. To
provide spatially distributed rainfall data, point measurements are interpolated. However, in …

Spatially continuous data products are essential for a number of applications including
climate and hydrologic modeling, weather prediction, and water resource management. In …

Quantifying the rainfall-runoff-pollutant (RRP) process is key to regulating non-point source
(NPS) pollution; however, the impacts of scarce measured data on RRP simulations have …

Extreme rainfall events are associated with large negative consequences to human society,
primarily as they may cause floods and other environmental problems such as erosions and …

Hydrological process modelling consistency is associated with long available gauged data
and reliable parameters, which is often limited. Multi-sensors and satellite-based products …

A representative of meteorological data-constrained basin, Ayeyarwady, in Myanmar,
Southeast Asia, is set for flow simulation and forecasting at 15 locations using a range of …

Daily rainfall data are one of the basic inputs in hydrological and ecological modeling and in
assessing water quality. However, most data series are too short to perform reliable and …

Abstract Daniau Village in Daniau Creek Watershed, Taitung County, Taiwan, sustained
damages from landslides and mudflows during Typhoon Morakot in 2009. The purpose of …

The impact of future climate change on streamflow in the Brahmani River basin, India has
been assessed using a distributed parameter hydrological model Precipitation Runoff …

Understanding the runout of slope failures is important for hazard identification, risk
assessments, and disaster prevention. This study evaluates the accuracy of three runout …