Assessing water-limited crop production with a scatterometer based crop growth monitoring system

Soil moisture is one of the most important parameters influencing crop yield. In current crop growth monitoring systems (CGMS) soil moisture is simulated using water budget models that require as input meteorological observations such as rainfall, temperature, and cloud cover. The collection of the meteorological data is expensive and often the station density is low. This poses a problem because, particularly for rainfall, large errors may occur when interpolating the station data to area means. In this paper a new approach for monitoring water-limited crop production is proposed that combines the advantages of conventional crop growth models and a novel remote sensing technique. The system builds upon a CGMS that has been developed by Alterra (formerly DLO Staring Center) and is used operationally in the MARS Project (Monitoring Agriculture with Remote Sensing) by the Joint Research Center of the European Commission to monitor agricultural production in Europe and adjoining countries. However, instead of using simulated soil moisture data based on rainfall observations, the proposed system uses as input soil moisture data retrieved from ERS Scatterometer data, a low resolution active microwave instrument