Soil moisture simulation at the local scale using satellite remote sensing data towards sustainable irrigation

Water plays a crucial role in food security. Currently, agriculture irrigation withdraws about 70% of the world’s fresh water. By 2050, the world population is estimated to increase to over 9 billion (UNDP, 2022). Together with climate change that is increasingly affecting the terrestrial ecosystem such as increasing the temperature, drought and extreme flood, all of which can lead to crop failure (IPCC et al., 2007) and water scarcity, the demand for food and irrigation water is expected to rise, dramatically. Accordingly, novel technologies for innovative, real-time water management for sustainable irrigation are necessary. In this regard, the main objective of this study is to simulate and predict the soil water content at the root zone, as a main factor of defining the irrigation time and quantity. Here, we have chosen a study area of 150km² which is located in west Europe, covering parts of Netherlands, Belgium, Luxemburg and west of Germany. Therewith, we have relied on the coupled land surface-subsurface CLM-Parflow model for hydrological simulations and the soil moisture data from on-site Cosmic-ray neutron sensor (CRNS) stations, as well as the SMAP (L3_SM_E_P), and high resolution C- and L-band Synthetic Aperture Radar (SAR) are used for data assessment. It is expected that the reliability of the soil moisture magnitude and dynamic will be examined.