## 1 Introduction  
Nowadays, the risks deriving from extreme weather conditions is constantly increasing and a growing number of people, as well as their available resources, are significantly exposed to flash flood events, all over the planet. Furthermore, the correct regulation of surface and subsurface rain waters must be considered a fundamental objective for the sustainable development of territories subjected to environmental transformation and reclamation processes, such as urban landfills. To cope with these events, it would be highly desirable to have an early warning [1] service that is able to validate meteorological data and promptly alert the civil protection offices, while providing real-time data on the progress of rainfall. The management of devices and systems for the transfer and collection of rainwater must follow criteria consistent with the principles of permanent site safety. To achieve reclamation, it is necessary to ensure, in particular, the isolation of any contaminating sources as well as the geotechnical stability of the soils and to have efficient environmental monitoring systems. In this sense, the fundamental parameters for the design and management of rainwater regeneration systems are the intensity and duration of rainfall. At present, the most often used rain sensors are the rain gauge (RG) with the tipping-bucket measuring technique [2] and the weather radar (WR) [3,4]. The first one provides a precise datum at given point-scale locations (how much rain has fallen in the place where it is installed) while the second one provides real data at low resolution (typically of the order of 1 km). The WRs have also significant constraints, concerning both implementation (as they need to be installed in isolated areas with particular features, usually on the top of a mountain) and functional operation (e.g., remote monitoring, shadow areas). Satellite-based remote sensing techniques based on passive microwave sensors and geosynchronous Earth orbit (geo) infrared (IR) estimates are becoming a relevant alternative in rainfall monitoring since they can provide global coverage and multi-satellite near real-time products. The satellite remote sensing precipitation datasets are made available by national services (e.g., the Integrated Multi-satellite Retrieval for GPM [5]) and results from combined estimation algorithms maps (such as those developed by NOAA/CPC for CMORPH) provide rainfall maps with a 30-min time resolution on a grid with a spacing of 8 km [6]. However, currently, the usage of such satellite remote sensing products for monitoring convective precipitation events over small-medium sized hydrologic basins and urban environments is still difficult, as finer spatial resolutions and updating time are needed. To deal with such issue, in recent years, research efforts have been dedicated to the evaluation of the optimal RGs density necessary to retrieve the high spatial variability of the rainfall field [7] through the development and testing of dedicated spatial interpolation techniques such as ordinary Kriging and conditional merging with WR products [8]. Once again, these studies highlighted the need for using high spatial resolution rainfall maps to correctly retrieve the strong variability of convective precipitation events that may occur in limited, and often highly populated, catchments for flash flood risk mitigation [9]. This is particularly necessary in a complex orography composed of small catchments that have to be monitored singularly for flash flood now-casting (it is the case in Mediterranean areas such as southeast France or Alps-Apennines catchments in Italy), in urban drainage waters management or for landfill runoff waters systems (the case showed in our letter) where the use of highly dense RG networks may not be a practicable solution because of its costs of deployment and maintenance. In this paper, a case study based on the application of an innovative system for rainfall monitoring in limited areas, such as small hydrologic basins and urban environments, is presented.