A new microwave tomography approach for rainfall monitoring over limited areas

Abstract

Exploiting the relationship between microwave attenuation and rainfall intensity in a microwave tomography approach was demonstrated in the past to be a valid alternative to weather radar measurements for the reconstruction of rainfall fields in limited areas. This is useful in areas (e.g. valleys or small basins), where radar data are not available due to beam blocking or, in general, for real time monitoring of rainfall events occurring over zones characterized by a high hydrological risk. At each time step, path-integrated attenuation measurements are provided by a set of microwave transmitter-receiver pairs, and two-dimensional Gaussian basis functions are utilized to reconstruct the space-time distribution of the rainfall intensity field. The inversion problem to be solved is highly ill-conditioned, due to the practical (and economical) impossibility to set up an adequate network for performing classical tomography. Therefore a Global Optimization Stochastic Technique has been developed to obtain valid results in quasi real time. Some search parameters of the algorithm must be chosen depending on the network characteristics: this allows a kind of calibration depending on the adopted quality (complexity) of the network. Some investigations have been performed both on simulated rain fields and on radar monitored rainfall events. Some significant examples are presented, showing computational speed and flexibility of the technique, and that a network based on 10 stations can provide a estimate of the mean rainfall intensity over a basin of nearly 400 Km 2 with an error less than 10% even with a monitoring time of 30 seconds. Under the same conditions, it is possible to guess the rainfall distribution pattern. We show that, utilizing a longer observation time, more reliable estimates are obtained.