Irrigation Estimation from Soil Water Balance and the Water Cloud Model by leveraging Sentinel-1 and Sentinel-2 observations

• DOI: 10.5194/egusphere-egu24-18745
• Publication Date: 2024-03-11T11:16:49Z
• Authors: Martina Natali; Sara Modanesi; Domenico De Santis; Luca Brocca; Fabio Mantovani; Andrea Maino; Gabrielle De Lannoy; Christian Massari
• Keywords: Water balance

Irrigation plays a pivotal role in the hydrological cycle, representing about 70% of freshwater withdrawals. However, its representation Earth System models is characterized by significant uncertainties terms amount, timing and spatial distribution. Observation data offer viable way to reduce this uncertainty thanks their ability sense the soil vegetation real condition with few-days revisit high resolution (~ 10 m), e.g. new Sentinel missions.  In contribution, we use remote sensing observations from Sentinel-1 Sentinel-2 satellite missions constrain simple Soil Water Balance (SWB) model coupled semi-empirical Cloud Model (WCM) obtain irrigation estimates via an inverse modelling solution. The WCM, which simulating backscatter (σ0) moisture descriptor, forced indexes simulated SWB that includes sprinkler scheme. outputs are then matched estimates. tested over irrigated field Po River valley, one most intensively European areas. Results show can capture signal relatively good accuracy. It also provides estimate field.  Nonetheless time platforms simplicity model, especially component, constitute two main limitations model. This tool be easily applied context precision agriculture optimize practices conserve water resources even when in-situ measurements not available.