## 1 Introduction
### Rainfall Estimation Methods  
For the study of precipitation, in particular rainfall quantification, several methods are used, e.g., rain gauges, ground-based radar, and satellites [4]. Traditionally, the most used instrument for measuring rainfall on the ground is the rain gauge. This technique has the disadvantage of low spatial representativeness. In addition, rain gauges require regular maintenance visits. Furthermore, there is often a significant delay in the rain gauge data delivery for post-processing, e.g., at the Global Precipitation Climatology Centre, leading to low sensor density in station-based rainfall products [5]. Weather radar, applied to rainfall estimation, appears to be more accurate in time and space than rain gauges [6]. It allows for the determining of the position, intensity, and displacement of the rain event, within a coverage radius typically between 100 km and 150 km [6]. The weather radar is a high-tech device that requires significant financial investment for its acquisition and human resources of high technical expertise for operation and maintenance. In addition, one needs several radars in order to cover the territory of a given country. For a country such as Burkina Faso, with an area of 274.200 km\({}^{2}\), nine weather radars with a range of 100 km would be needed. Satellite-based remote sensing is another important technique for monitoring rainfall [7, 8]. The advantage of remote sensing with low earth orbit satellites is the very good global, or almost global, coverage--depending on the orbit-spatial coverage. However, satellite data are subject to uncertainties and have low temporal resolution for continuously estimating the precipitation at a given location [7, 8]. The use of CMLs to quantify precipitation is an alternative that is increasingly being explored by many researchers [9, 10, 11, 12]. When a microwave signal propagates between a transmitting and a receiving antenna, its signal strength decreases due to free space loss [13], atmospheric gases, and associated effects [14]. If the signal passes through rainfall, it is attenuated significantly due to the phenomena of absorption and scattering of electromagnetic radiation by water drops. This additional attenuation can be used to determine the amount of rainwater falling between the two antennas [10, 15, 16]. Using the CML technology to quantify rainwater has the following advantages:  
1. it is possible to cover very large areas;
2. there is no need for major new investments;
3. it is fully automatic and does not require experienced service personnel to operate it;
4. there is the possibility of having the data in real time. Another advantage of the CML data technique is that the quantifications take place at a maximum altitude of 100 m, above the ground, unlike other remote sensing techniques, such as radar or satellites, which scan precipitation at higher altitudes. There is therefore more precision at small spatial and temporal scales with this technique. This technology using telecommunication commercial microwave link networks for precipitation quantification was first initiated and implemented in Israel 2006 [9]. The correlation between precipitation intensity measured by the CML and the rain gauge was 0.86 for a 15 min interval and 0.9 for an hourly interval. In 2008, in Israel, by using a great number of CMLs, [PERSON] et al. [17] inferred the spatial evolution of precipitation. Subsequently, it was applied in several other countries:  
* Netherlands: in 2007, [PERSON] et al. [18] performed the first analysis of data from two CMLs in the Netherlands. Eight rainfall events were evaluated over two CMLs with a resolution of 15 min, and the results are consistent with the rainfall retrieved by the rain gauges and the C-band radar. In 2013, [PERSON] et al. (2013), by increasing the number of CMLs, were able to deduce the spatial evolution of rainfall. * Germany: in 2012, [PERSON] et al. [19] processed the first CML data that they recorded first using data loggers.