Introduction to Real Time Rainfall

What is/are Real Time Rainfall?

Real Time Rainfall - An integrated urban flood model for Bengaluru city, Karnataka, India has been developed with a modular approach, which includes real-time rainfall and weather monitoring, and a rainfall forecast system feeding into a comprehensive hydrologic flood model. ^[1] The raw real-time rainfall data acquired was pertained to three regions of Karnataka North, South and Coastal. ^[2] However, the GSMaP Gauge cannot be used to provide real-time rainfall data and is, therefore, inadequate for real-time flood forecasting. ^[3] Near real-time rainfall monitoring at local scale is essential for urban flood risk mitigation. ^[4] The method presented in this study can be used not only to reasonably and efficiently select target sites for flood prevention facilities, but also to pre-detect areas vulnerable to flooding by using real-time rainfall forecasting. ^[5] Accurate and real-time rainfall estimation is a pressing need for forecasting the flood disaster and reducing the loss. ^[6] The provision of high resolution near real-time rainfall data has made satellite rainfall products very potential for monitoring hydrological hazards. ^[7] The flow analysis is conducted considering the shrink/swell behavior of the Yazoo clay with the real-time rainfall events, as observed in the rain gauges. ^[8] Both real-time rainfall data from next-generation radar (NEXRAD) and gaging stations, and forecasted rainfall are needed to make gate control decisions (reservoir releases) in real-time so that at time t, rainfall is known and rainfall over the future time-period (Δt) to time t + Δt can be forecasted. ^[9] In the domains dominated by complex topographies, quasi-periodicities, and non-linearities, deep learning (DL)–based methods provide an efficient solution in downscaling rainfall data for regional climate forecasting and real-time rainfall observation data at high spatial resolutions. ^[10] Real-time rainfall data can be used in conjunction with streamflow monitoring to determine when extreme precipitation has occurred within the ungauged watercourses catchment which may result in flooding. ^[11] Various forms of phosphorus and runoff process were monitored, and local real-time rainfall data were also collected. ^[12] In particular, due to rainfall concentrated in a short period of time during the flood season, it is necessary to plan the exact amount of dam discharge using real-time rainfall forecasting information. ^[13] In this paper, real-time rainfall conditions are incorporated into landslide prediction through a unique rainstorm-based database of reported landslides. ^[14] In this research, a real-time nowcasting system for regional landslide-hazard assessment under extreme-rainfall conditions was established by integrating a real-time rainfall data retrieving system, a landslide-susceptibility analysis program (TRISHAL), and a real-time display system to show the stability of regional slopes in real time and provide an alert index under rainstorm conditions for disaster prevention and mitigation. ^[15] In view of this, the effectiveness of integrating satellite-based near real-time rainfall, i. ^[16] The newly designed predictive model utilizes statistically significant lagged $I_{F}$ , improved by antecedent and real-time rainfall data to forecast the next daily $I_{F}$ value. ^[17] This study developed a real-time rainfall forecasting system that can predict rainfall in a particular area a few hours before a typhoon’s arrival. ^[18]   With this, rainfall-landslide correlation models have been established and updated regularly through statistical means to facilitate the prediction of the severity of landslide based on real-time rainfall recorded in the raingauge network and the rainfall forecast by the Hong Kong Observatory (HKO). ^[19] Therefore, a real-world case study was conducted in Wadi al Wala for real-time rainfall forecasting and flood control, using 38 years of daily data from 13 rain gauge stations in the region. ^[20] Obtaining near-real time rainfall data from rain gauge stations are not easy in most developing countries like Ethiopia. ^[21]