HS6.8 | Advancing Water Cycle Analysis and Irrigation estimate and management By Integrating Remote Sensing, Hydrological Modelling, and In-Situ Data
EDI
Advancing Water Cycle Analysis and Irrigation estimate and management By Integrating Remote Sensing, Hydrological Modelling, and In-Situ Data
Co-organized by SSS9
Convener: Chiara Corbari | Co-conveners: Pierre LaluetECSECS, Zheng Duan, Christina Anna OrieschnigECSECS, Jacopo DariECSECS, kamal Labbassi, John W. Jones

Accurate monitoring of various hydrological cycle components (e.g., precipitation, evaporation, water storage, and runoff) and the anthropogenic fluxes which modify them, as well as the development of models to reproduce them are important for improving our understanding of hydrological processes. Acquiring this understanding is a crucial prerequisite to ameliorate resource management, optimize the development of infrastructure, and adjust land use practices to changing climate conditions and hazards such as floods and droughts, in particular irrigation management.
Agriculture is the largest consumer of water worldwide and huge differences exist between modern irrigation technology and traditional practices. However, reliable and organized data about water withdrawals for agricultural purposes are generally lacking worldwide, thus making irrigation a key missing variable to close the water budget over anthropized basins. Climate changes and increasing human pressure, together with traditional wasteful irrigation practices are enhancing the conflictual potential in water use, even in countries traditionally rich in water. Hence, saving irrigation water and improving irrigation efficiency on large areas with modern techniques is an urgent required action.
Several studies have recently explored the possibility of monitoring the natural and anthropogenic components of the water cycle by leveraging remote sensing information in combination with ground-based observations and/or hydrological modelling.
In this session, we will focus on:
-the use of approaches combining remote sensing data, hydrological modelling, and in-situ data to estimate variables in natural, agricultural, and anthropized systems (such as irrigation volumes and timing); and to analyse hydrological extremes
-the combination of satellite data and hydrological modelling to improve water management approaches such as irrigation water use efficiency and precision farming
- the performance of remotely sensed data in multi-variable calibration and spatial evaluation of hydrological and agricultural models

Please note: This is a merged session with multiple topics.