[1] Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) is a satellite infrared-based algorithm that produces global estimates of rainfall at resolutions of 0.25 0.25 and a half-hour. In this study the model parameters of PERSIANN are routinely adjusted using coincident rainfall derived from the Tropical Rainfall Measurement Mission Microwave Im...

The study of the rainfall infiltration mechanism unsaturated soil has always been a hot issue in field geotechnical engineering. It is worth studying which parameters should be introduced to characterize characteristics calculation and analysis infiltration. In this paper, Fredlund–Xing model was quoted SEEP/W module Geostudio software, transient numerical under same duration T different intens...

Long lead rainfall prediction is important in the management and operation of water resources and many models have been developed for this purpose. Each of the developed models has its special strengths and weaknesses that must be considered in real time applications. In this paper, eld and General Circulation Models (GCM) data are used with the Statistical Downscaling Model (SDSM) and the Arti...

We use a basic stationary and isotropic spatial linear regression model to fit a rainfall dataset collected in central Venezuela. First order and partial second order trend explain the mean function. With a Matérn correlation function with smoothness fixed at one, unknown parameters are estimated through MCMC method. The variogram is also estimated based on the posterior samples. By examining p...

In drylands the soil water availability is a key factor ruling the architecture of the ecosystem. The soil water reflects the exchanges of water among soil, vegetation, and atmosphere. Here, a dryland ecosystem is investigated through the analysis of the local interactions between soil water and vegetation forced by rainfall having seasonal and stochastic occurrence. The evolution of dryland ec...

The majority of studies assessing aerosol effects on rainfall use coarse spatial scale (1° latitude/longitude or more) and multi-seasonal or decadal data sets. Here, we present results from a spatial correlation of aerosol size distribution and rain rate for selected stratiform and cumuliform precipitation events. The chemistry transport version of the Weather Research and Forecasting model was...

It is now widely acknowledged that climate variability modulates the frequency of extreme hydrological events. Traditional methodologies for hydrologic frequency analysis are not devised to account for variation in the exogenous teleconnections. Flood frequency analysis is further plagued by the assumptions of stationary in the causal structure as well as ergodicity. Here, we propose a dynamica...