Merging weather radar and rain gauges for dryland agriculture

Abstract

The areal extent of rainfall remains one of the most challenging meteorological variables to model accurately due to its high spatial and temporal variability. Weather radar is a remote sensing instrument that is increasingly used to estimate rainfall by providing unique observations of precipitation events at fine spatial and temporal resolutions, which are difficult to obtain using conventional rain gauge networks. Dense rain gauge networks combined with operational weather radars are widely considered as the most reliable source of rainfall depth estimates. This paper compares the various sources of rainfall data available and explores the benefits of merging radar data with rain gauge data by reviewing the outcomes of a case study of a major agricultural cropping and pasture region. Comparison is made of rainfall measurements obtained from a dense rain gauge network covered by the output from a weather radar installation. We conclude that merging radar data with rain gauge data provides improved resolution of the spatial variability of rainfall, resulting in a significantly improved data source for agricultural water management and hydrological modelling. However, the use of weather radar merged with rain gauge data is generally underrated as a management tool.