HS6.8 | Irrigation estimate and management from remote sensing and agro-hydrological modelling
EDI
Irrigation estimate and management from remote sensing and agro-hydrological modelling
Co-organized by SSS9
Convener: Chiara Corbari | Co-conveners: Jacopo Dari, kamal Labbassi, Francesco Morari, Pierre Laluet

Agriculture is the largest consumer of water worldwide and at the same time irrigation is a sector where huge differences between modern technology and traditional practices do exist. Furthermore, reliable and organized data about water withdrawals for agricultural purposes are generally lacking worldwide, thus making irrigation the missing variable to close the water budget over anthropized basins. As a result, building systems for improving water use efficiency in agriculture is not an easy task, even though it is an immediate requirement of human society for sustaining the global food security, rationally managing the resource and reducing causes of poverties, migrations and conflicts among states, which depend on trans-boundary river basins. Climate changes and increasing human pressure together with traditional wasteful irrigation practices are enhancing the conflictual problems in water use also in countries traditionally rich in water. Hence, saving irrigation water improving irrigation efficiency on large areas with modern techniques is an urgent action to do. In fact, it is well known that agriculture uses large volumes of water with low irrigation efficiency, accounting in Europe for around 24% of the total water use, with peak of 80% in the Southern Mediterranean part and may reach the same percentage in Mediterranean non-EU countries (EEA, 2009; Zucaro 2014). North Africa region has the lowest per-capita freshwater resource availability among all Regions of the world (FAO, 2018).
Several studies have recently explored the possibility of monitoring irrigation dynamics and by optimizing irrigation water management to achieve precision farming exploiting remote sensing information combined with ground data and/or water balance modelling.
In this session, we will focus on: the use of remote sensing data to estimate irrigation volumes and timing; management of irrigation using hydrological modeling combined with satellite data; improving irrigation water use efficiency based on remote sensing vegetation indices, hydrological modeling, satellite soil moisture or land surface temperature data; precision farming with high resolution satellite data or drones; farm and irrigation district irrigation management; improving the performance of irrigation schemes; estimates of irrigation water requirements from ground and satellite data; ICT tools for real-time irrigation management with remote sensing and ground data coupled with hydrological modelling.

Agriculture is the largest consumer of water worldwide and at the same time irrigation is a sector where huge differences between modern technology and traditional practices do exist. Furthermore, reliable and organized data about water withdrawals for agricultural purposes are generally lacking worldwide, thus making irrigation the missing variable to close the water budget over anthropized basins. As a result, building systems for improving water use efficiency in agriculture is not an easy task, even though it is an immediate requirement of human society for sustaining the global food security, rationally managing the resource and reducing causes of poverties, migrations and conflicts among states, which depend on trans-boundary river basins. Climate changes and increasing human pressure together with traditional wasteful irrigation practices are enhancing the conflictual problems in water use also in countries traditionally rich in water. Hence, saving irrigation water improving irrigation efficiency on large areas with modern techniques is an urgent action to do. In fact, it is well known that agriculture uses large volumes of water with low irrigation efficiency, accounting in Europe for around 24% of the total water use, with peak of 80% in the Southern Mediterranean part and may reach the same percentage in Mediterranean non-EU countries (EEA, 2009; Zucaro 2014). North Africa region has the lowest per-capita freshwater resource availability among all Regions of the world (FAO, 2018).
Several studies have recently explored the possibility of monitoring irrigation dynamics and by optimizing irrigation water management to achieve precision farming exploiting remote sensing information combined with ground data and/or water balance modelling.
In this session, we will focus on: the use of remote sensing data to estimate irrigation volumes and timing; management of irrigation using hydrological modeling combined with satellite data; improving irrigation water use efficiency based on remote sensing vegetation indices, hydrological modeling, satellite soil moisture or land surface temperature data; precision farming with high resolution satellite data or drones; farm and irrigation district irrigation management; improving the performance of irrigation schemes; estimates of irrigation water requirements from ground and satellite data; ICT tools for real-time irrigation management with remote sensing and ground data coupled with hydrological modelling.