This paper presents an improved bivariate mixed distribution, which is capable of modeling
the dependence of daily rainfall from two distinct sources (eg, rainfall from two stations, two …

Floods are the natural hazards that are causing the most deaths worldwide. Flood early
warning systems are one of the most cost-efficient methods to reduce death rates, triggering …

The spatial structure of climatic variables synthesized by a weather generator has
considerable impact on the modeling of hydrological variability; however, in most cases, it …

Projected hydrological variability is important for future resource and hazard management of
water supplies because changes in hydrological variability can cause more disasters than …

Dams are ubiquitous in the United States, with more than 87,000 influencing streamflow
across the nation. The significant majority of these dams are small and are often ignored in …

The generation of hydrometeorological time series that exhibit a given probabilistic and
stochastic behavior across multiple temporal levels, traditionally expressed in terms of …

Precipitation is influential in determining runoff at different scales of analysis, whether in
minutes, hours, or days. This paper proposes the use of a multisite multivariate model of …

Extreme precipitation occurs frequently because of hydrological variability, resulting in
humid cities facing serious waterlogging problems. Previous studies about rainstorms had …

Delineating a homogeneous region is a standard procedure for rainfall frequency analysis in
predicting precipitation in ungauged basins (PUB) in vast unpopulated areas. However, for …

Stochastic rainfall models are commonly used in practice for long-term flood risk
management. One of the most widely used model types is based on point processes …