There are at present two major governmental seasonal rainfall forecasting programs in Australia. The first of these programs is run by the Australian Government through the Bureau of Meteorology and commenced in 1989. The second is run by the Queensland Government (QG) through its Department of Environment and Resource Management (and its predecessors) and commenced in 1994. Both programs issue...

Climate and rainfall are highly non-linear and complicated phenomena, which require sophisticated computer modelling and simulation for accurate prediction. An artificial intelligence technology allows knowledge processing and can be used .as forecasting tool. For example, the application of Artificial Neural Networks (ANN), to predict the behaviors of nonlinear systems has become an attractive...

Mountain torrent disaster warning system is a significant non-engineering flood prevention measure for achieving the goals of flood prevention and disaster reduction in the related small rivers. After analyzing the design principle and objective of the system, we proposed a mountain torrent disaster warning system based on WEB GIS technology and the distributed hydrological model (DHM) of the r...

Annual series of three stochastic rainfall model parameters — the seasonal wet day amount (or intensity), the conditional dry–day probability (or dry–spell persistence), and the conditional wet-day probability (or wet-spell persistence) — were examined using daily rainfall records for ten UK stations for the period 1901–1995. The purpose was first, to determine the extent to which these indices...

Rainfall is important for food production plan, water resource management and all activity, plans in the nature. The occurrence of prolonged dry period or heavy rain at the critical stages of the crop growth and development may lead to significant reduce crop yield. Indian is an agricultural country and its economy is largely based upon crop productivity. Thus rainfall prediction becomes a sign...

Rainfall is important for food production plan, water resource management and all activity plans in the nature. The occurrence of prolonged dry period or heavy rain at the critical stages of the crop growth and development may lead to significant reduce crop yield. India is an agricultural country and its economy is largely based upon crop productivity. Thus rainfall prediction becomes a signif...

Power demand forecasting is a significant factor in the planning and economic and secure operation of modern power system. This research work has compared different forecasting techniques and opted to find out better technique in context of power generation, which varies rapidly from time to time. The dataset has been generated from yearly demand of electricity of Bangladesh for last five years...

A methodology for propagating and constraining the uncertainty inherent in real-time flood forecasting is presented and demonstrated on an application to the River Severn, UK. The flood forecasting system is based on a cascade of rainfall-runoff and flood routing models, developed using stochastic transfer functions with state dependent parameterisations to allow for nonlinearity. The nonlinear...

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation c...

Summer rainfall in the Sahel region of Africa exhibits one of the largest signals of climatic variability and with a population reliant on agricultural productivity, the Sahel is particularly vulnerable to major droughts such as occurred in the 1970s and 1980s. Rainfall levels have subsequently recovered, but future projections remain uncertain. Here we show that Sahel rainfall is skilfully pre...