Water management during drought emergency: high revisit SAR constellation architecture and potential synergy with airborne systems

In recent decades, the Earth witnessed a surge in severe atmospheric events attributed to climate change. Predictions indicate that such events will become even more frequent in the future. Among these, drought poses a particularly daunting challenge to agriculture, often subjecting crops to extended periods without access to essential water resources. Therefore, effective monitoring and decision-making processes are essential to mitigate its impact. In Italy, several systems have been deployed to address these challenges. While some of these systems are cost-effective, they are limited by their temporal and spatial resolutions. The study researches the main requirements imposed by customers (reclamation consortia and farmers) and proceeds to create a system that can satisfy them. Specifically, the focus is on establishing a system architecture designed to retrieve critical parameters for the management of irrigation water during drought emergencies across Italy's agricultural landscapes, which include evapotranspiration and soil moisture levels of the fields. Various configurations are explored, considering three types of remote sensing platforms: satellites, HAPS and UAVs. Preliminary trade-off studies indicate that a hybrid system primarily composed of SAR X band satellite constellation and thermal UAVs can be advantageous. The requirements flow-down is extended down to the constituent system level, allocating the majority of the functions to the space segment. The design of the satellite constellation is accomplished using a multiobjective optimization tool implemented in Matlab. The system is thought to be potentially operative in different years: 2023, 2024 or 2028. An innovative approach is proposed, which involves considering both existing and planned additional constellations, to ensure 50% coverage of Italy territory in a 24-hour timeframe and to improve the data quality. This methodology involves exploiting in an "auxiliary" role some constellations with payloads similar to the primary constellation (e.g., IRIDE) and others (e.g., Sentinel 1 and ROSE-L) which offer different radar bands, having a temporal distance between the complementary retrieved data that does not exceed two hours. In addition to ground sensor data, the system relies on UAVs to monitor the critical parameter of land surface temperature (LST), when it is unavailable to the end user. The results obtained indicate that the number of satellites in the constellation can be reduced by leveraging this innovative approach, while also allowing for diversification of the data and, consequently, improved final data quality. While UAVs may appear to play a marginal role in the overall system framework given their infrequent use, they can assume a critical function in achieving the desired data accuracy.