A Data-Based Estimation of Power-Law Coefficients for Rainfall via Levenberg-Marquardt Algorithm: Results from the West African Testbed

Rainfall monitoring is of paramount importance for many applications, such as meteorology, hydrology, and flood prevention. In order to circumvent the expensive deployment of weather radar networks, many articles propose rainfall estimation by using the received signal power of microwave links as they are sensitive to precipitation at certain frequencies. In this context, the International Telecommunication Union (ITU) provides a power-law relationship that allows the computation of the precipitation rate from the attenuation due to rainfall. This physics-based approach uses scattering calculation to derive the power-law coefficients, which depend only on the frequency. However, the practical use of this equation faces other important parameters, such as the link length and the distance from the bucket gauge to the microwave link. These factors may significantly affect the prediction. In this article, it is proposed a data-based alternative for the estimation of the power-law coefficients, where the Levenberg-Marquardt algorithm is used to adjust them using several data collected from different radio links in West Africa. The estimation quality is assessed in terms of its correlation with rain rate measurements from bucket gauges spread across the African testbed.