Real time rainfall estimation using microwave signals of cellular communication networks: a case study of Faisalabad, Pakistan

Abstract. Water balance estimate requires high spatio-temporal water balance components and rainfall is one of them. Rainfall is stochastic variable, which varies with respect to space and time. There are different methods for rainfall estimation such as rain gauge, satellite data but the resolution of these methods are very low, which cause over and underestimation of rainfall. A real time rainfall estimation mechanism is tested using commercial cellular networks in Faisalabad, district of Pakistan. The microwave links are used to quantify rainfall intensities and estimate rainfall at high spatio-temporal resolution. The attenuation in electromagnetic signals due to varying rainfall intensities is measured by taking difference between the power transmitted and power received during rainy period and is the measure of the path-averaged rainfall intensity. This rainfall related distortion is converted into rainfall intensity. This technique is applied on a standard microwave communication network used by a cellular communication system, comprising 35 microwave links, and it allow for observation of near-surface rainfall at the temporal resolutions of 15 min. Signal data-set of year 2012–2014 and 2015–2017 is used for calibration and validation respectively with three rain gauge data-set. The accuracy of the method is demonstrated by comparing the daily cumulative rainfall depth of University of Agriculture Faisalabad rain gauge (UAF-RG), Ayub Agriculture Research rain gauge(AR-RG) and Water and Sanitation Authority rain gauge (WASA-RG) with link based rainfall depths estimated from L2, L28 and L34 respectively, reaching r² up to 0.97. UAF-RG is considered reference to study the spatial variability of rainfall of all the selected links within the study area, observed 10 %–60 % average spatial error of all links with the reference UAF-RG. All the results show that microwave links are potentially useful compared to the low resolution methods of rainfall estimation and can be used for effective water resources management.