Improving food security
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With water technology that we consistently develop to be safer and increasingly AI-embedded, we contribute to improve food security.
We help to stabilise agricultural yields, for example through irrigation systems based on weather data in water-scarce regions.
Agriculture worldwide is facing growing challenges. A rising global population and changing climatic conditions are increasing the pressure on agricultural systems. At the same time, food production needs to be linked with a responsible use of water and other resources.
Water is a key foundation in this context. What matters is not only how much water is available, but also how water use can be aligned with the irrigation needs of agricultural land.
With our water technology, we support different agricultural applications – from the extraction and distribution of water to the digital control of irrigation systems. The combination of operating data, weather data, and other environmental data creates additional opportunities to use water more in line with demand and to adapt irrigation processes to local conditions.
Using water more specifically for agriculture
Aligning irrigation systems with different requirements
Agricultural land places very different demands on water supply depending on region, soil, climate, and crop type. Especially in regions with limited water resources, it is important to deliver water as specifically as possible to where it is needed for cultivation.
Our water technology is used in different irrigation systems and supports the extraction, distribution, and provision of water in line with specific requirements. Digital control and the capture of operating data create additional opportunities to make the operation of irrigation systems more transparent and to manage them in a more targeted way. This makes it possible to adapt water supply for agricultural land to local conditions.
Supporting precision irrigation with data
Weather and operating data for demand-based irrigation
Digital technologies are also changing the management of agricultural land. Weather data, soil moisture information, and other operating data can be brought together to adapt irrigation decisions to current conditions.
Artificial intelligence can support the evaluation of large volumes of data and the identification of relationships between weather conditions, water demand, and system operation. The evaluated data can then be used for the management of irrigation processes.
Practical example: SolFrut olive oil production, Argentina
Argentina is one of the significant producers of olive oil. In the San Juan region, limited water resources create particular challenges for the cultivation of agricultural land.
At SolFrut, modern irrigation and pumping systems are therefore used to supply water to the olive plantations in a targeted way. The systems enable demand-based distribution of available water and thereby support the controlled operation of the irrigation infrastructure.
Digital control approaches and data-based irrigation strategies create additional opportunities to adapt water supply to local conditions.
Agriculture under challenging conditions
Water for dry regions and large cultivation areas
In regions with high temperatures, low rainfall, or difficult soil conditions, reliable water supply is an important prerequisite for agricultural use. The larger the cultivation areas and the more demanding the climatic conditions, the higher the requirements for water extraction and irrigation infrastructure.
Connected pumping and distribution systems can help transport water across the designed transfer distances and make it available for agricultural applications.
Practical example: Toshka project, Egypt
The Toshka project is one of Egypt’s large-scale agricultural development projects. Its aim is to make land that has so far been used only to a limited extent, or not at all, for agriculture available for cultivation through targeted irrigation.
Through an extensive water transfer system, water is transported from Lake Nasser to newly developed cultivation areas. There, connected irrigation systems take over the distribution of water across large areas.
The project illustrates the importance that water infrastructure can have for large-scale agricultural applications under demanding climatic conditions.
Intelligent water technology, intelligent agriculture
Operating data creates transparency
Agricultural operations and irrigation projects need to adapt to changing weather conditions, varying water availability, and complex operational requirements. Digital technologies can help bring together information on systems and water consumption and enable the remote monitoring of operating processes.
The combination of sensors, communication, and digital control makes it possible to continuously capture defined condition data from pumping stations and irrigation systems. This can make operating processes more transparent and allow them to be adjusted more specifically when needed.
Practical example: Nagalwadi irrigation project, India
In the Indian state of Madhya Pradesh, the Nagalwadi project supports the irrigation of around 47,000 hectares of agricultural land across more than 100 villages.
Modern pumping stations, digital control systems, and a LoRaWAN-based communication network enable the monitoring and control of the infrastructure. Relevant operating information can be captured remotely and used for the operation of the irrigation systems.
Mobile applications also support access to operating information and facilitate the coordination of water supply.
Advancing agricultural systems
Combining water technology, digitalization, and AI
The requirements placed on agriculture are changing, and with them the requirements for water supply. Especially where water is scarce or weather conditions fluctuate more strongly, digital information can provide an important basis for managing irrigation systems.
Our water technology is used in different agricultural applications. In combination with digital technologies and AI, this creates additional opportunities to evaluate operating data, manage irrigation processes more specifically, and align the use of available water resources with local conditions.
