Evaluation of Crop Water Requirements estimated from Sentinel 2 MSI and Landsat 8 OLI Earth Observation data in MOSES DSS

Abstract

MOSES DSS web-platform aims to assist stakeholders such as governments and farmers in order to manage water irrigation distribution in a higher efficiency and sustainability. The constructed algorithms are focused on forecast using weather models, data, as well as satellite multispectral observations in such a way that a 7-day ahead crop water requirement estimation is generated. The current drawback of the system in using the available and free satellite products such as Landsat 8 and Sentinel 2, is that it assumes that the crops are under standard conditions, e.g. there is no water stress, diseases etc.. The current work investigates how possible errors due to this assumption can be potentially tackled in the future by comparing Crop Water Requirement (CWR) with S2REP VI and/or with water stress index and see the discriminative power of the latter. Furthermore, a comparison between several discrepancies between S2 and L8 (e.g. AC and co-registration) are studied since it is a crucial issue especially in temporal applications such as MOSES. On the one hand, the results showed that a harmonization of the two products is certainly needed. On the other hand, it seems that S2REP is capable of revealing crop stress information based on the methodologies of this work, thus it could potentially give more information compared to NDVI which is not sensitive to crop stress.