r a 200 .061 : +64 4 3 iwa.co.n Summary This study is devoted to simulation of the interannual variability of daily rainfall, such as the mean and variance of seasonal rainfall totals and the correlation between seasonal rainfall totals and a seasonal climate variable (e.g., an index of atmospheric or oceanic circulation). Prior work established that a mixture of chain-dependent processes, invo...

Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and rainfall are highly non-linear phenomena in nature exhibiting what is known as the "butterfly effect". While some regions of the world are noticing a systematic decrease in annual rainfall, others notice increases in fl...

Most runoff and soil erosion models take into account rainfall intensity, since higher storm intensities lead to greater runoff and losses of soil due to erosion. Accurate prediction of soil erosion requires rainfall intensity data with a high temporal resolution. This places a restriction on the simulation of soil erosion, since high temporal resolution data are usually not available. One way ...

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant an...

abstract agricultural scientists have developed considerable interest in modeling and generation of rainfall as new ways of analyzing rainfall data and assessing its impact on agriculture. a combination of markov chain and gamma distribution function is recognized as a simple approach and is demonstrated to be effective in generating daily rainfall data for many environments. thus the availabil...

Abstract This paper examines methodologies for the simulation of storms for the purpose of design flood generation in the Thames region. Existing methods are reviewed and two new approaches are proposed. One combines point profiles of storms extracted from long rainfall records with depth-duration-frequency statistics. The other uses a stochastic rainfall model based upon the Poisson point proc...

Two rainfall simulations of 30 mm h(-1), with 48-h interval between two simulations, were performed on rice lysimeters at 24, 48, and 72 h after being sprayed with tricyclazole. In the first simulated rainfall, wash-off concentration of tricyclazole was significant irrespective of the interval between the spray time and the rainfall simulation. And from 20.5% to 24.2% of tricyclazole deposited ...

Rainfall prediction is one of the most important and challenging task in the modern world. In general, climate and rainfall are highly non-linear and complicated phenomena, which require advanced computer modeling and simulation for their accurate prediction. An Artificial Neural Network (ANN) can be used to predict the behavior of such nonlinear systems. ANN has been successfully used by most ...

A single study was conducted in March 2004 on a Grenada silt loam (Fine-silty, mixed, active, thermic, Oxyaquic Fraglossudalfs) at the Roth Prairie and Harbecke Farms located near Stuttgart, Ark. Treatments consisted of three land uses: conventional till (CN), reduced till (RT), and native prairie (PR). The CN system had been tilled one month prior to rainfall simulation while the RT system had...