Optical and microwave images have been combined for land cover monitoring in different agriculture scenarios, providing useful information on qualitative and quantitative land cover changes. This study aims to assess the complementarity and interoperability of optical (SPOT-5 Take-5) and synthetic aperture radar (SAR) (Sentinel-1A) data for crop parameter (basal crop coefficient (K_cb) values and the length of the crop’s development stages) retrieval and crop type classification, with a focus on crop water requirements, for an irrigation perimeter in Angola. SPOT-5 Take-5 images are used as a proxy of Sentinel-2 data to evaluate the potential of their enhanced temporal resolution for agricultural applications. In situ data are also used to complement the Earth Observation (EO) data. The Normalized Difference Vegetation Index (NDVI) and dual (VV + VH) polarization backscattering time series are used to compute the K_cb curve for four crop types (maize, soybean, bean and pasture) and to estimate the length of each phenological growth stage. The K_cb values are then used to compute the crop’s evapotranspiration and to subsequently estimate the crop irrigation requirements based on a soil water balance model. A significant R² correlation between NDVI and backscatter time series was observed for all crops, demonstrating that optical data can be replaced by microwave data in the presence of cloud cover. However, it was not possible to properly identify each stage of the crop cycle due to the lack of EO data for the complete growing season.

The south of Portugal is one of the regions that will be most affected by the impacts of climate change (CC), with an expected increase in water scarcity. Irrigated super-intensive olive orchards occupy a large area of the used agricultural surface in the Alentejo region, south of Portugal, making it necessary to adapt this crop to the effects of CC. This study assessed the impacts of CC and defined adaptation measures concerning irrigation management of the super-intensive olive orchard. To compute the crop irrigation requirement (CIR), the soil water balance model ISAREG was combined with climate data relative to the reference period 1971–2000 and to the representative concentration pathways RCP4.5 and RCP8.5 for the periods 2011–2040, 2041–2070, and 2071–2100. The growing degree-days (GDD) approach was used to estimate olive phenology for these CC scenarios. Unchanged irrigation management with an average CIR increase up to 16% in RCP4.5 and 31% in RCP8.5 is expected. By adopting higher levels of water deficit, water savings of up to 22% can be realized. The results showed that the anticipated CIR increase for the CC scenarios can be mitigated through regulated deficit irrigation strategies.

Climate change is a challenging fact influencing diverse sectors in society including the agricultural one, which is heavily dependent on natural resources and climate. In the Mediterranean region, climate change-related increases in air temperature, and in the frequency and intensity of extreme weather events, such as droughts, boost the pressure on the agricultural systems and affect crop yield potential. The growth of the world population implies that production needs to increase in a sustainable manner. Therefore, this study focuses on the maize crop due to its importance for food security and because it is a crop with significant water consumption that occupies a large worldwide area. In order to study climate change impacts on crop production, plant water requirements, and provide farmers guidelines helping them to adapt, it is necessary to simultaneously evaluate a large number of factors. For this reason, modelling tools are normally used to measure the future impact of climate change on crop yield by using historical and future climate data. This review focuses on climate change impacts on maize crop irrigation requirements and compares—by means of critical analysis—existing approaches that allow for the building a set of mitigation and adaptation measures throughout the study of climate.

To improve water use efficiency and productivity, particularly in irrigated areas, reliable water accounting methodologies are essential, as they provide information on the status and trends in irrigation water availability/supply and consumption/demand. At the collective irrigation system level, irrigation water accounting (IWA) relies on the quantification of water fluxes from the diversion point to the plants, at both the conveyance and distribution network and the irrigated field level. Direct measurement is the most accurate method for IWA, but in most cases, there is limited metering of irrigation water despite the increasing pressure on both groundwater and surface water resources, hindering the water accounting procedures. However, various methodologies, tools, and indicators have been developed to estimate the IWA components, depending on the scale and the level of detail being considered. Another setback for the wide implementation of IWA is the vast terminology used in the literature for different scales and levels of application. Thus, the main objectives of this review, which focuses on IWA for collective irrigation services, are to (i) demonstrate the importance of IWA by showing its relationship with water productivity and water use efficiency; (ii) clarify the concepts and terminology related to IWA; and (iii) provide an overview of various approaches to obtain reliable data for the IWA, on the demand side, both at the distribution network and on-farm systems. From the review, it can be concluded that there is a need for reliable IWA, which provides a common information base for all stakeholders. Future work could include the development of user-friendly tools and methodologies to reduce the bridge between the technology available to collect and process the information on the various water accounting components and its effective use by stakeholders.