Looking at global climate change patterns and its increased pressure on natural resources, West African countries like Ghana will be hit very hard. In particular, agriculture, which is the largest water user in Ghana, will be affected by high temperatures and changes in the variability of rainfall. This variability in climate makes crop production and yield more uncertain, as well as farm income. The periods of droughts in Ghana are getting longer and there is increased pressure on water availability from the river basins due to climate change, putting many people and farmers in risk of having too little water. Therefore in this project, we will develop and pilot in the field an innovative tool that will significantly enhance water security in Ghana by reducing the quantity of water needed for irrigation per hectare (up to about 40% less of current water use).

To support the Ghanaian farmers in making the transition to a water secure future, they expressed a need for locally adapted, climate smart irrigation technologies and innovative advice to improve their irrigation practices. To develop such a smart irrigation service, FutureWater is working together with knowledge institute TU Delft, horticulture company Holland Greentech, and social enterprise TAHMO to develop this innovative tool and implement it in the field. This smart irrigation service should be able to translate various weather parameters and data (historical but also real-time data) into crop specific irrigation advice in volumes, but also in minutes for small-scale farmers. The unique and innovative part of this smart irrigation service, called SOSIA+ (Small-scale Open source, Satellite based Irrigation Advice), will be the algorithm to provide advice on how many minutes a farmer should irrigate a specific crop – based on the combination of the TAHMO local weather data and real-time data (normally not taken into account), that will be tailor-made for small scale farmers (normally these services are only for large scale farmers while the predominant type of farmers in Ghana are small scale) and is linked to the innovative drip irrigation systems that Holland Greentech Ghana already sells to farmers (so closely linked to an existing customer base of farmers and a product).

SOSIA+ will initially focus on the city of Kumasi and the Ashanti region, targeting more than 500 farmers and a growing population of more than 4 million people that needs to be fed and are affected by the changing weather patterns and increased water demand. In the long-term, the goal is to transform the horticulture sector in Ghana towards a smart and sustainable practice. By developing the Irrigation Advisory Tool, we can prevent over-irrigation to reduce water use and hence work towards the desired situation of sustainable food production and water security. This project will focus on gathering better weather information, piloting an innovative irrigation tool that is linked to a drip irrigation system to reduce water losses and implement this in the field with lead farmers. This will change the current traditional practices of the farmers leading to less water and energy losses, hence increasing availability of water and the sustainability of food production in light of climate change.

Earlier this year FutureWater and Holland Greentech developed a very first draft of the irrigation advisory application ‘SOSIA’ for Rwanda, with promising results. As one of the main problems in many African countries is that there is no ground network of weather stations, making it very difficult to efficiently manage water resources or generate weather forecasts that are localised and essential for food production, the initial SOSIA project used satellite remote sensing data to overcome this problem. But given the rapidly changing weather patterns due to climate change, the collection of ground data is also essential. This is why TAHMO has been set-up to develop a dense network of weather stations all over Africa and using their data will be very valuable to use for the irrigation tool.

The video below gives a brief summary of the tool created in the previous SOSIA project.

“How long do you irrigate per day?” we asked Madame Christine, a small-holder farmer with an eye for business. “Well, I used to irrigate for up to three hours every day, but not anymore. I can now double my fields under cultivation and sell more crops while using the same amount of water!” 

We received this reaction during our field trials in Zambia for our newly developed Satellite Open-Source Irrigation Advisory (SOSIA) tool. This tool was developed within the two-stage call for innovations based on open-source geodata launched by the Netherlands Space Office (NSO), which aimed at positively impacting food security and sustainable land and water management in Africa. In response to this challenge, FutureWater and Holland Greentech developed the SOSIA tool to help small and medium farmers make informed decisions about their irrigation practices. Because – while irrigation is a crucial aspect of agriculture, over-irrigation can lead to significant environmental problems, and it reduces profits for farmers. Using less water can lead the farmer to spend less time irrigating, having a lower electricity/fuel and water bill, improving the water productivity of crops and contributing to a sustainable environment.  

What is the SOSIA tool?  

SOSIA is a state-of-the-art, open source, satellite-based tool that provides both historical and near real-time information on irrigation water requirements for smallholder farmers, calculated based on open-source geodata and specific additional farmer and crop information. The tool was developed to overcome the often-limited ground data availability for calculating crop water requirements. The only data farmers can rely on are traditional weather stations, often far away from their fields. With the SOSIA tool, the farmer receives information based on open geodata for their location, by converting the spatial data into Virtual Weather Stations (VWS)!  

Seasonal and hindcasted irrigation information

The SOSIA tool provides a farmer with irrigation advice, expressed in minutes of irrigation duration, throughout the crop season. Before the farmer plants the crop, an extension officer of Holland Greentech uses the SOSIA tool to provide the farmer with their tailor-made seasonal crop schedule, which is an overview of expected irrigation minutes for the rest of the season, calculated based on the average evapotranspiration of WaPOR of the 10 years.

Figure 1. Graphical User Interface of the SOSIA tool, hosted on the Google Earth Engine platform.

As climate is changing, the average of the last 10 years does not always give an accurate depiction of what is happening in the field. Therefore, the SOSIA tool calculates the irrigation requirements for the last week based on open source geodata. The irrigation engineer uses this functionality on a weekly basis to make use of the actual climate data and informs the farmer only if additional irrigation is required, compared to the seasonal reference schedule.

Testing the SOSIA tool with farmers

To test the tool in the context of Sub-Saharan Africa, trials were set out in both Zambia and Rwanda with farmers from the Holland Greentech client base. The farmers were quite positive about the observed impact of using the tool. Many were surprised that the advice indicated less irrigation time than they were used to. While following the advice, the farmers also kept records of the realized number of minutes of irrigation, estimation of soil moisture and signs of drought stress. No farmer recorded any drought stress on the crops. The observations of the farmers showed that the crop performance of the SOSIA irrigated trial was visually the same as fields irrigated under their normal irrigation regime (Figure 3). The farmers were enthusiastic about this water saving, mainly because of the related decrease in electricity / fuel costs. For most of the farmers involved in the field trials, SOSIA reduced irrigation water requirements while optimizing yield.

Back to Madame Christine: she indicated that she usually irrigates her lettuce fields 1 hour in the morning and 1 hour at the end of the afternoon. She was surprised that the SOSIA advise only advised her to irrigate in the range of 50-57 minutes daily. When applying the advice, she did not notice any drought stress in her lettuce crop, and the harvest was visually the same for both the demo and control field.

Figure 2. Conducting an interview with farmers in Zambia.

Benefits for extension advisors

Extension officers are the primary intended users of the SOSIA tool on a daily basis. During the piloting phase, the extension officers from Holland Greentech received the tool with great enthusiasm. They praised the user-friendliness, quality and spatial detail of the information, and efficiency compared to traditional methods to provide advisory services.

Conclusion

In conclusion, SOSIA is a valuable tool for anyone involved in irrigation management for small and medium farmers, particularly in an African context. By providing near real-time information on irrigation water requirements, it helps farmers to irrigate more efficiently and thus to realize a more sustainable use of water resources. By leveraging the power of open source geodata, costs are kept relatively low while access to a wealth of localized information is achieved. Initial results from the Zambia and Rwanda trials indicate that application of the SOSIA tool saves farmers water, electricity/fuel, time and improves the water productivity and, potentially, income!

Figure 3. Difference between the SOSIA Demo and Control plot at Sunripe Farm, Rwanda (08/11/2023).

 

Early November Agência de Desenvolvimento do Vale do Zambeze (ADVZ) from Mozambique visited the FutureWater office in Wageningen, the Netherlands where a full day was planned with APSAN-Vale project partners Resilience, FutureWater and HiView. From FutureWater side Tijmen Schults and Lisa Verschuren provided an interesting presentation on the water productivity results of the passed season. Furthermore, a demonstration of the new Rapid Eye XS drone was provided in the floodplains of Wageningen. The day was concluded with a fruitful discussion on strengthening the future cooperation.

Agência de Desenvolvimento do Vale do Zambeze beneficiary of the APSAN-Vale project in central Mozambique. The project has as its overall aim to increase climate resilient agricultural productivity and food security, with a specific objective to increase the water productivity and profitability of smallholder farmers in Mozambique, prioritizing small (family sector) farmers to increase food and nutritional security.

This project will demonstrate what the best combinations are of adoption strategies and technological packages, with the largest overall impact in terms of water productivity, both at the plot, sub-basin as well as basin-level. The main role of FutureWater is monitoring water productivity in target areas (both spatial and seasonal/annual variation) using flying sensors (drones) in combination with a water productivity simulation model and field observations.

Visit of the Agência members to the Wageningen office

Field demonstation of the Rapid Drone XS in Wageningen

Currently, farmers rely on weather forecasts and advisories that are either general for a given, often wide, region of interest, or highly customized to the farmers’ needs (e.g. by combining large scale atmospheric variables into synthetic parameters of interest). In both cases, such forecasts and advisories often don’t rely at all on observations collected at or around the target cultivated areas, or they are limited to traditional observations provided only by weather stations, without exploiting the full extent of measurements and observations available through European space-based assets (e.g. Galileo GNSS, Copernicus Sentinels) and ground-based radar data.

MAGDA objectives go beyond the state-of-the-art by aiming at developing a modular system that can be deployed by owners of large farms directly at their premises, continuously feeding observations to dedicated and tailored weather forecast and hydrological models, with results displayed by a dashboard and/or within a Farm Management System.

FutureWater is leading the irrigation advisory service of MAGDA, making use of hydrological modelling using SPHY (Spatial Processes in Hydrology). The output expected consists of an operational irrigation service to provide advice on when and how much to irrigate at certain moments during the cropping season, using as input data improved weather forecasts.

During this task, the SPHY water balance model will be setup for three selected demonstrator farms in Romania, France and Italy. Finally, the irrigation advisory will be validated using performance indicators (e.g., water productivity, crop yield analysis, water use efficiency) using ground truth data (e.g., weather stations, moisture probes, crop biomass measurements)

The Lunyangwa Dam is the source of water supply for Mzuzu City, Ekwendi Town and surrounding areas. Currently, the yield of the dam is lower than the annual average daily water demand from the dam. A quick intervention for this problem is to raise the spillway of the Lunyangwe Dam.

In order to determine the height of the redesigned spillway, FutureWater conducted a hydrological study for the Lunyangwa Dam Catchment to determine flood extremes for several return periods. HEC-HMS was used for calculating the peak volumes and discharges. The input for the HEC-HMS model was retrieved using satellite-based datasets for rainfall and terrain. Furthermore, the flood routing was simulated with an elevation-storage curve. The output of this study will be used for the redesign of the spillway.

Agriculture is a key sector of the Rwandan economy; it contributes approximately 33% to the gross domestic product and employs more than 70% of the entire labour force. Although some farmers are already using water-efficient irrigation infrastructure, too much of the available water is still lost due to unsustainable use of existing irrigation systems, and/or maximum crop yields are not achieved due to under-irrigation.

Hence, small to medium-sized food producers in Rwanda do not have sufficient access to information regarding optimal irrigation practices. To close this information gap, FutureWater has devised an innovation that can calculate a location-specific irrigation advice based on Virtual Weather Stations, expressed in an irrigation duration (“SOSIA”). The use of the outdated CROPWAT 8.0 method, and the lack of good coverage of real-time weather stations in Rwanda, means that current advice falls short. In addition, existing advisory services are often too expensive for the scale on which small to medium-sized farmers produce. There is a potential to increase the productivity of the irrigation water by up to 25%. Initially, the innovation will be disseminated via the Holland Greentech network, with a pilot in Rwanda consisting of 40 customers. Aside from further refining the SOSIA tool, upscaling strategies will be explored in this second phase to identify other intermediaries that could benefit from the SOSIA service so to realize its optimal impact.

FutureWater has found with Holland Greentech an ideal partner to roll-out this innovation due to their presence in and outside of Rwanda, where they provide irrigation kits and advice. This offers the opportunity to quickly scale-up the proposed innovation. With their expertise in agro-hydrological modeling and the African agricultural sector, FutureWater and Holland Greentech respectively have acquired ample experience to make this innovation project and its knowledge development to a success.

The tools can be accessed through online URLs for the Virtual Weather Stations and for the Irrigation Advisory Tool.

For smallholder farming systems, there is a huge potential to increase water productivity by improved (irrigated) water management, better access to inputs and agronomical knowledge and improved access to markets. An assessment of the opportunities to boost the water productivity of the various agricultural production systems in Mozambique is a fundamental precondition for informed planning and decision-making processes concerning these issues. Methodologies need to be employed that will result in an overall water productivity increase, by implementing tailored service delivery approaches, modulated into technological packages that can be easily adopted by Mozambican smallholder farmers. This will not only improve the agricultural (water) productivity and food security for the country on a macro level but will also empower and increase the livelihood of Mozambican smallholder farmers on a micro level through climate resilient production methods.

This pilot project aims at identifying, validating and implementing a full set of complementary Technological Packages (TP) in the Zambezi Valley, that can contribute to improve the overall performance of the smallholders’ farming business by increasing their productivity, that will be monitored at different scales (from field to basin). The TPs will cover a combination of improvement on water, irrigation, and agronomical management practices strengthened by improved input and market access. The goal is to design TPs that are tailored to the local context and bring the current family sector a step further in closing the currently existing yield gap. A road map will be developed to scale up the implementation of those TPs that are sustainable on the long run, and extract concrete guidance for monitoring effectiveness of interventions, supporting Dutch aid policy and national agricultural policy. The partnership consisting of Resilience BV, HUB, and FutureWater gives a broad spectrum of expertise and knowledge, giving the basis for an integrated approach in achieving improvements of water productivity.

The main role of FutureWater is monitoring water productivity in target areas using an innovative approach of Flying Sensors, a water productivity simulation model, and field observations. The flying sensors provide regular observations of the target areas, thereby giving insight in the crop conditions and stresses occurring. This information is used both for monitoring the water productivity of the selected fields and determining areas of high or low water productivity. Information on the spatial variation of water productivity can assist with the selection of technical packages to introduce and implement in the field. Flying sensors provide high resolution imagery, which is suitable for distinguishing the different fields and management practices existent in smallholder farming.

In May 2020, FutureWater launched an online portal where all flying sensor imagery from Mozambique, taken as part of the APSAN-Vale project, can be found: futurewater.eu/apsanvaleportal

Project video: Portrait of the activities on water productivity

In Sub-Saharan Africa, population growth, associated food demand and pressure on natural areas have all increased greatly. Agricultural intensification – more production from the same acreage – remains a key solution to these challenges. One of the cornerstones of intensification is that of a higher and more productive use of inputs, such as fertilizer and water. So far, the average production has remained low and a significant yield gap still exists, mainly among small scale producers (SSPs). The limiting factors are (partly) caused by weather and climatic changes but also by a lack of agronomical knowledge, proper inputs, fertilizers and (climate smart) irrigation techniques. Thanks to the digital revolution Africa is going through, many commercial farmers already have access to a wide range of agricultural services. However, such solutions are not yet accessible to SSPs due to their costs.

A consortium led by FutureWater will collaborate with ETG agronomists and the Empowering Farmers Foundation (EFF) to work together with 60 selected maize, coffee, and tea farmers from around the country to implement Climate Smart Agricultural practices, such as crop rotation to rejuvenate soil nutrients, or mulching to reduce weeds and water erosion. By using drones to monitor the application of these sustainable crop interventions from the selected farms, the project team will also be able to use the data to assess crop productivity improvements, create crop calendars to increase harvest yields, and understand land use changes to protect encroachment into biodiverse areas. Soil samples will also be collected and analyzed to identify soil nutrition deficiencies and design appropriate soil enhancement measures that will be implemented on demo farms. The success of this pilot project will provide learnings on how it can be scaled up to reach more farmers and assess its replicability across different geographic locations.

Over the past years FutureWater and HiView managed to develop a low-cost agricultural drone technology which revolutionized the applicability of geo-information services for African farmers: ThirdEye. With the flying sensor service successful local enterprises were established that provide a low-cost drone service to small- and largescale farmers, both in Mozambique and Kenya. ThirdEye’s young agronomist-drone operators support farm decisions based on the flying sensor crop mapping that is viewed on a tablet. Integrating crop nutrition advisory and other improved agronomic practices into the ThirdEye service will bring the (extension) service up to the next level. In this project, we complement the work of flying sensors by ThirdEye with the agronomic service model of Holland Greentech including input distribution, demonstrations and field days, farmer training and coaching and soil testing.

By merging agronomic advisory services making use of low-cost flying sensors, soil testing, climate smart inputs, farmer coaching and an interactive online planning & monitoring portal, the farmer is able to improve his/her:

  • Planning: What crop to grow in the season based on expected weather, crop prices and market demand;
  • Cropping: When to sow the seed based on the type of crop and predicted weather
  • Management: When and where to irrigate, fertilize and apply pesticide. This can help reduce the amount of inputs used in the farm and increase yields, thus helping with profitability.
  • Harvest: When to harvest the crop based on market prices and predicted weather.
  • Market linkage: The ability to make informed decisions on where to sell their produce, which may increase their income.
  • Climate resilience: Option to order climate smart inputs and technologies from different suppliers. These technologies include hybrid seeds, propagation units and greenhouses, (drip) irrigation equipment, soil analysis, biological soil enhancers and biological pest control products.

This project is a collaboration between ETG Kenya, Empowering Farmers Foundation, Eco-Business II Sub-Fund Development Facility, HiView, FutureWater, Holland Greentech and ThirdEye Kenya. For more information visit: https://www.ecobusiness.fund/

In Angola, more and better-quality data is required to improve crop suitability assessments over large extensions of arable land to ensure sustainable food and income security. For example, environmental data on soil texture, soil water storage capacity, vegetation growth, terrain slopes, rainfall and air temperature are key to develop reliable crop suitability assessments. These datasets are available from state-of-the-art satellite-based products and machine learning observations (de Boer, 2016; Funk et al., 2015; Hengl et al., 2014, 2017). The benefit of these data products is that data can be obtained for any province, municipality, or farm in Angola. On top of that, data can be shown in maps to easily visualize spatial variation and identify the most suitable location and area to grow desired crops. Land-crop suitability maps are obtained by calculating a weighted average of the environmental variables that influence crop growth (e.g. rainfall, air temperature, soil water storage capacity), providing an integrated and complete assessment on where to plant. Also, potential crop yields are determined for desired cropping seasons using the FAO AquaCrop model to provide more information about potential income.

Irrigated agriculture in Angola has been developed in commercial farms using mainly central pivot and drip irrigation systems. The installation of new irrigation systems is foreseen in large extensions of land over 5000 hectares. Irrigated agriculture results in higher crop yields and allows higher incomes to farmers. However, commercial farms must invest in high energy supply to operate irrigation systems with water pumping stations. The challenge for irrigation system operators is to know exactly when and how much to irrigate during the cropping season. If better information about irrigation volumes and intervals are provided a significal reduction in energy costs could be achieved. The objective is to predict irrigation demand volumes during the cropping season and provide a user-friendly decision tool to irrigation operators. To achieve this, weather forecasts, remote sensing, and the SPHY model will be used.