The innovation of agricultural systems management is a determinant factor that guarantees adaptation to a new paradigm of global economy, environmental protection, and social requirements. The conventional concepts of innovation, applicable to new products and processes, do not consider many characteristics of the agricultural sector, such as social innovation and innovation resulting from new or renewed processes. Nevertheless, the overall impact of innovation on yields, competitiveness, and value can be hampered by the limited understanding or misinterpretation of Agriculture Innovation paradigms. For instance, the Rural Development Program (RDP) applies a restrict concept of innovation, being unable to embrace the full range of activities intended to implement new practices within the framework of the Agricultural Knowledge and Innovation System (AKIS). Stimulating innovation in agriculture demands a change in policy innovation of RDP in order to preserve natural resources and combine agricultural priorities and the rural environment with the concepts of innovation. This paper focuses on the different views of the concept of innovation within the Program of Operational Groups (OGs) of the European Innovation Partnership for Agricultural Productivity and Sustainability (EIP-AGRI), analyzing the Portuguese case study of the Lis Valley Irrigation District whose main innovation objective was to achieve and implement new processes of water management aiming at the conservation of natural resources as well as sustainable social and economic agricultural development. The Portuguese experience highlights why the application of innovation in agriculture may not reach the desirable outcomes.

Organic farming can play an important role in rural development and food production, by reinforcing the trend toward sustainable agriculture and its purpose of ecosystem conservation. The agribusiness of organic farming is particularly relevant in family farming, given the labor availability and the short marketing circuits. The innovative techniques of organic farming, namely with soil fertility, weed and pest control, opens a wide range of possibilities in its development and extension. The expectation of organic farming profitability in small-scale family farming, supported by known successful examples, were the theme of a field study on Lis Valley Irrigation District to assess the constraints to its expansion in order to outline the procedures for the acquisition of technical knowledge, the adaptation of technologies, the support for the conversion of production models, and the specialized training of farmers for action. Results revealed that the: (i) farmer’s land structure, (ii) their mature age, (iii) low education level, and (iv) markets, are the main constrains for organic farming development. Furthermore, other uncertainties were identified, namely: (i) the certification process, (ii) the knowledge of new technologies, especially of crop protection, and (iii) the marketing problems to guaranteeing profitability. This study concludes that organic farming has significant potential for development in the Lis Valley and that the efforts and resources of the various stakeholders, namely the state, need to be harmonized to deliver effective support to farmers to promote organic farming that prioritizes: (i) rural development policies, (ii) supporting land restructuring, (iii) modernization of irrigation, (iv) stimulation of young farmers, (v) conversion and implementation of innovative technologies, (vi) the organization of farmers for better productive efficiency, and (vii) to facilitate market access.

Irrigation districts play a decisive role in Portuguese agriculture and require the adaptation to the new water management paradigm through a change in technology and practices compatible with farmers’ technical know-how and economic sustainability. Therefore, improvement of water management, focusing on water savings and increasing farmers’ income, is a priority. In this perspective, an applied research study is being carried out on the gravity-fed Lis Valley Irrigation District to assess the performance of collective water supply, effectiveness of water pumping, and safety of crop production due to the practice of reuse of drainage water. The water balance method was applied at irrigation supply sectors, including gravity and Pumping Irrigation Allocation. The average 2018 irrigation water allocated was 7400 m³/ha, being 9.3% by pumping recharge, with a global efficiency of about 67%. The water quality analysis allowed identifying some risk situations regarding salinization and microbiological issues, justifying action to solve or mitigate the problems, especially at the level of the farmers’ fields, according to the crops and the irrigation systems. Results point to priority actions to consolidate improved water management: better maintenance and conservation of infrastructure of hydraulic infrastructures to reduce water losses and better flow control; implementation of optimal operational plans, to adjust the water demand with distribution; improvement of the on-farm systems with better water application control and maintenance procedures; and improvement of the control of water quality on the water reuse from drainage ditches. The technological innovation is an element of the modernization of irrigation districts that justifies the development of multiple efforts and synergies among stakeholders, namely farmers, water users association, and researchers.

Rice irrigation by continuous flooding is highly water demanding in comparison with most methods applied in the irrigation of other crops, due to a significant deep percolation and surface drainage of paddies. The pollution of water resources and methane emissions are other environmental problems of rice agroecosystems, which require effective agronomic changes to safeguard its sustainable production. To contribute to this solution, an experimental study of alternate wetting and drying flooding (AWD) was carried out in the Center of Portugal in farmer’s paddies, using the methodology of field irrigation evaluation. The AWD results showed that there is a relevant potential to save about 10% of irrigation water with a reduced yield impact, allowing an additional period of about 10 to 29 days of dry soil. The guidelines to promote the on-farm scale AWD automation were outlined, integrating multiple data sources, to get a safe control of soil water and crop productivity. The conclusions point out the advantages of a significant change in the irrigation procedures, the use of water level sensors to assess the right irrigation scheduling to manage the soil deficit and the mild crop stress during the dry periods, and the development of paddy irrigation supplies, to allow a safe and smart AWD.

Rice culture is one of the most important crops in the world, being the most consumed cereal grain (755 million tons in 2020). Since rice is usually produced under flooding conditions and water performs several essential functions for the crop, estimating its water needs is essential. Remote sensing techniques have shown effectiveness in estimating and monitoring the water use in crop fields. An estimation from satellite data is a challenge, but could be very useful, in order to spatialize local estimates and operationalize production models. This study intended to derive an approach to estimate the actual crop evapotranspiration (ET_a) in rice paddies from a temporal series of satellite images. The experimental data were obtained in the Lis Valley Irrigation District (central coast of Portugal), during the 2019 to 2021 rice growing seasons. The average seasonal ET_a (FAO56) resulted 586 ± 23 mm and the water productivity (WP) was 0.47 ± 0.03 kg m⁻³. Good correlations were found between the crop coefficients (K_c) proposed by FAO and the NDVI evolution in the control rice fields, with R² ranging between 0.71 and 0.82 for stages II+III (development + middle) and between 0.76 and 0.82 for stage IV (late). The results from the derived RS-assisted method were compared to the ET_a values obtained from the surface energy balance model METRIC, showing an average estimation error of ±0.8 mm d⁻¹, with a negligible bias. The findings in this work are promising and show the potential of the RS-assisted method for monitoring ET_a and water productivity, capturing the local and seasonal variability in rice growing, and then predicting the rice yield, being a useful and free tool available to farmers.