Biomass production and thus yield will need to be increased in a sustainable way. It is important to minimize the risks of yield loss even under more extreme environmental conditions, while making sure not to deplete or damage the available resources. Two measures are most important for this: irrigation and fertilization. Fertilisation is a bio-chemical process that can be controlled and optimized through agricultural management. It relies on (mostly) industrial goods and the resources for it can be transported if the necessary infrastructure is available. Irrigation on the other hand requires reliable water resources in the area that is being farmed, either from ground water or surface water. A large portion of the world’s fresh water is linked to snowfall, snow storage and seasonal release of the water. All these components are subject to increased variability due to climate change and the following increase in extreme events. In a large number of regions, the linkage of water availability provided by the seasonal snow melt is directly given. In growing areas in Europe up to 80 percent of the water used for irrigation is surface water, which is provided by rivers of nival or pluvio-nival regime. Beyond the total amount of water supply, shifts in precipitation patterns from snowfall in winter to heavy rain events in the drier season can lead to extreme events like floods, leaving agriculture doubly vulnerable – both to the drowning of crops in floods as well as the wilting of crops due to a lack of steady surface water supply for irrigation. Continuous monitoring of the water availability as well as the crop development and nutrient availability is needed to react quickly and find the most sustainable solutions for the future. For this, information from EO data together with modelling is the most promising solution, as it provides local data at high resolution but is globally available.

Assessment of the snow situation, especially the knowledge of the water stored in the snow cover and its dynamics in accumulation and release, and by use of physical models, its distribution via rivers, dams and reservoirs requires tools that exceed the use of single EO datasets or in-situ station observations. Time series of Copernicus Satellite Data, e.g. Sentinel-1, Sentinel-2 and potentially Sentinel-3, and their deeper analysis, are still underrepresented sources of the derivation of weekly/daily/hourly information on snow and the water sources. VISTA is offering snow monitoring and snow modelling for the flood forecast, energy producers and in an indirect way also for agricultural applications. As main parameters, snow covered area (using optical data) and the detection of melting snow (using SAR data) are derived from the EO sources. In combination with modelled values of the snow water equivalent, using the physically-based model PROMET (also applied agricultural process modelling) an controlled and corrected calculation of the water stored in the snow, its release and its availability in rivers, reservoirs or groundwater layer is provided. Since reliability of the modelled values is mainly depending on the quality of the forcing of such a model, a detailed monitoring of snow parameters is important. Especially in extreme areas (high and steep mountains) and with incomplete availability of meteorological measurements, external data sources are needful.

Continuous comparisons between modelled and EO observed snow parameters are the key to provide continuous and reliable information. With increasing areas, increasing spatial and temporal resolution (making use of e.g., Sentinel 1 A/B and Sentinel 2 A/B and Sentinel 3 A/B data (B is in preparation / launch in 2018) the big amount of data (volume, velocity and variety) is requiring effective methods of Big Data and extreme analytics techniques. Use of growing computing resources is one key element of gaining the opportunities of e.g., the Hops data platform, the TEPs and the DIAS activities. Improvements in scalable learning and analytics techniques are an additional factor that to avoid bottlenecks in information gain. Since the most relevant snow parameters (SWE – information on the water stored in the snow, and LWC – information on internal water / melting processes) could not directly be retrieved by single EO observations, the full analytics of time series and the small changes in snow covered area, snow albedo and snow backscatter, will be benefiting. Here the current techniques and algorithms reach their limitations.

For agriculture, VISTA is already offering biomass and yield estimation as well as irrigation recommendations on field-scale to individual farmers for their specific farms. For this service, VISTA combines the use of satellite information derived from high-resolution optical imagery (mainly Sentinel-2, but backed up by other relevant data like e.g. Landsat-8) with crop growth modelling. Information about current biomass is assimilated into the physically-based crop growth model PROMET, which in turn is driven by the current meteorological conditions, to deliver yield in a 10x10m raster. Yield estimations as offered by European services (e.g., Copernicus Land Service, GEOSS, MARS) use medium resolution data that does not allow a field-wise resolution. This limits its usability and accuracy. Additionally, VISTA continuously calculates crop parameters like LAI and chlorophyll for all incoming Sentinel-2 scenes on the Food Security-TEP for certain areas (currently Germany and parts of Zambia, to be extended in the next year) and stores them on the platform for further use as well as provides them for visualisation on the TEP.

The approach developed within ExtremeEarth taps the potential inherent in the Copernicus constellation to utilize the continuous big data stream of different satellite technologies - optical and radar, different spatial and temporal resolution - to bring together the best suited approaches for the monitoring of dynamic Earth processes like the water cycle and vegetation growth to provide a final product of the highest usefulness - water availability for irrigation use - to the users in the Food Security community. For this, the newly-developed infrastructure of ESA’s Thematic Exploitation Platforms is utilized to make the most efficient use of the available infrastructure, data, tools and methods for each thematic area.