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 The use of the outdated CROPWAT 8.0 method, and the lack of good coverage of real-time weather stations in Rwanda, means that current advice falls short.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.
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.
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 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.