The rainfall input is one of the main factors influencing the magnitude of the runoff response during a flood event. Its temporal and spatial distribution significantly contributes to the formation of hydrograph shape, peak discharge and flood volume. a novel approach to the evaluation of the role of the temporal rainfall pattern of hydrograph is presented in this contribution. The methodology ...

Radar rainfall data are affected by several types of error. Beside the error in the measurement of the rainfall reflectivity and its transformation into rainfall intensity, random errors can be generated by the temporal spacing of the radar scans. The aim of this work is to analize the sensitivity of the estimated rainfall maps to the radar sampling interval, i.e. the time interval between two ...

Pore water pressure, build up by recharge of hydrosystems, is one of the main triggering factors of deep seated landslides. Effective rainfall, which is the part of the rainfall which recharges the aquifer, is a significant parameter. Soil-water balance is an accurate way to estimate effective rainfall. Nevertheless this approach requires evapo5 transpiration, soil water storage and runoff char...

Precipitation is a major input in hydrological models. Radar rainfall data compared with rain gauge measurements provide higher spatial and temporal resolutions. However, radar data obtained form reflectivity patterns are subject to various errors such as errors in reflectivity-rainfall Z-R relationships, variation in vertical profile of reflectivity, and spatial and temporal sampling among oth...

This study sought to evaluate the utility of radar derived rainfall data as a unique resource for analysing the interplay between rainfall and ecosystem dynamics in the Kimberley region of Western Australia. The Bureau of Meteorology’s Weather Watch radar network was investigated as a potential source of spatially explicit radar data that could be processed to create estimates of accumulated ra...

East Asian summer monsoon (EASM) rainfall impacts the world’s most populous regions. Accurate EASM rainfall prediction necessitates robust paleoclimate reconstructions from proxy data and quantitative linkage to modern climatic conditions. Many precisely dated oxygen isotope records from Chinese stalagmites have been interpreted as directly reflecting past EASM rainfall amount variability, but ...

Introduction and Purpose: It is now apparent that the changing weather patterns are associated with climate change according to the UN Intergovernmental Panel on Climate Change. In the wake of relatively little work looking at rainfall pattern in tropical countries of developing nations, especially in Sierra Leone, we conducted a retrospective analysis on the amount of rainfall over the past fe...

Understanding rainfall variability, shifts and trends is of primary importance when considering the potential for biophysical, social and economic impacts. An increase in mean rainfall could enhance agricultural production and water supply. However, if this increase is associated with more extreme rainfall events, it can enhance flood frequency and intensity. Conversely, decreases in mean rainf...

This chapter also focusesaddresses on precipitation intensity measurements (in particular rate of rainfall or rainfall intensity) due to their rapidly increased need for the interpretation of rainfall patterns, rainfall event modeling and forecasts, everyday meteorological and engineering applications, the investigation of evolving events at the local to regional scale with potential tremendous...

Correlation in space between seasonality of malaria and seasonality of rainfall was studied in Sri Lanka. A simple seasonality index was developed by making use of the bimodal seasonality of both malaria and rainfall. The malaria seasonality index was regressed against the rainfall seasonality index taking spatial autocorrelation into account. Despite the presence of spatial autocorrelation, th...