Aim of the training

The training will enhance capacity of Egerton educational staff in accessing and using innovative data and tools in the public domain, to analyse crop performance and irrigation management. During the training, university participants will be specifically supported in developing course modules based on the skills gained. To maximize the impact in addressing the need for increased quality of higher education in the agricultural sector, representatives from other institutes, ministries and private sector companies will also be invited. The training will allow the staff to gain advanced skills in working with flying sensors (drones) and satellite-derived data to support agricultural and water-related challenges, such as pests and diseases, water efficiency in agriculture to enhance food security, and drought monitoring. They will acquire insight in and knowledge on analyzing the performance of crops, making the right intervention decisions and giving irrigation advice. For public sector representatives, the training objective is to obtain skills that can be directly and sustainably implemented in their respective organizations.

Overall, the Kenyan society at large will benefit from improved food security provided by well-educated agricultural researchers and professionals. This project forms an important step in the capacity building strategy as it focuses on strengthening the universities and preparing them to provide high quality education to the future generation agronomists and agricultural managers, as well as upgrading the knowledge of current professionals.

The training costs of four stages: an online training course, followed by an in-country training program, symposium and post-training support.

Stage 1: eTraining course

The first stage involved a weekly online training course that will start in January 2021, with a total of six sessions in six weeks. Participants will be consisting of University and TVET faculty members, university students, PhD candidates, researchers, Kenya Agricultural & Livestock Research Organization (KALRO) staff members, Agriculture Extension Staff from the County Government who are already involved in agricultural research and training and other private sector partners. Staff members from the university will be those that are involved in teaching agronomy, horticulture, agriculture engineering and agriculture extension courses and programs, i.e., soil, nutrient and water management, dryland farming, irrigated agriculture and crop protection. Non-university attendants will be technical staff who are close to the decision makers within their organizations. This will enhance the impact of the training by embedding the use of flying sensor and satellite-derived data for agriculture within these organizations and make sure that Kenya will pursue its activities in making use of this kind of information.

This first stage of the training course will be online and will focus on:

  1. Real Water Savings in Agricultural Systems including potential field interventions
  2. The use of WAPOR to access remotely sensed derived data
  3. The use of flying sensors (drones) in agriculture

The course will end with a test and evaluation and graduates will receive a certificate.

Stage 2: Targeted in-country training

After the first stage training a second in-country training will take place with a smaller group, focusing on the use of drones in agriculture. Here a selected group of 12 to 18 members will be trained. Focus will be on staff with lecturing responsibilities, to ensure impact on higher education provision and transfer of the new skills to students.

The in-depth training will consist of:

  1. Operating flying sensors manually and automatic, the processing of the collected data using open source software, interpretation and the subsequent decision making (recommendations to increase productivity) for (smallholder) farmers and actors
  2. Use satellite derived (precipitation) products to run crop growth models to provide advice on when and how much to irrigate in agricultural fields

Participants will work on hands-on exercises related to crop performance analyses, water demands and crop growth modelling. Application of the new skills will be further stimulated by assigning the participants clear, tailor-made goals at the end of the second training session, to be worked on during the distant-support period.

Stage 3: Symposium/knowledge sharing

Right after the second training session, a symposium will be organized for a larger audience including the superiors/managers (who most of the times are the final decision makers) of the training participants and representatives of similar organizations. During this knowledge sharing event, trainees and trainers will actively provide contributions to showcase the newly gained skills and their added value to the respective institutions and the Kenyan agricultural sector in general. By acquainting the responsible decision makers in these organizations with the potential applications of flying sensor and satellite-derived data relevant to them, this event will be crucial in ensuring a sustainable impact of the TMT.

Stage 4: Post-training support

In this period, progress will be actively monitored and the trainers will provide post-training support to the participants. The support will be both remotely (e.g. through Skype) by the Dutch training providers but also in-person by ThirdEye Kenya staff visiting the participants for Q&A sessions and to evaluate the implementation of the skills they obtained.

The Government of Angola is developing a policy to diversify the country’s economy, strongly dependent on the income of the oil sector. Agriculture is considered one of the priority sectors to be developed. A favorable climate and a relatively high availability of water resources and fertile soils, can lead Angola to become one of the leaders in agricultural production of the African continent.

With the objective of increasing agricultural production and productivity and favoring investment and innovation in related businesses, the present project arises: a nexus between policies, practice and knowledge. The project “Knowledge-to-Knowledge (K2K – Knowledge to Knowledge), funded by the Dutch government and managed by the University of Wageningen, aims to strengthen and enhance the capacity of the main Angolan knowledge institutions in agricultural sciences, to establish a strong relate between knowledge and practice. To do this, the development of skills in Geographic Information Technologies of the Faculty of Agricultural Sciences (FCA) of the José Eduardo dos Santos de Huambo University (UJES) is proposed.

Among other tasks, a program is established with an approach based on “Train the Trainers -TtT” (train the trainers), in which FutureWater has collaborated, with the aim of developing the knowledge and skills of the FCA staff. UJES in Geoinformatics and Remote Sensing. After the development of the TtT program, the staff of the University should be able to:

  1. Establish a University program of training in Remote Sensing
  2. Develop and maintain the necessary teaching material
  3. Initiate and carry out its own research program
  4. Develop small courses aimed at the agricultural sector

The Sierra Nevada de Santa Marta, a UNESCO-declared Biosphere Reserve, is an isolated mountain complex encompassing approximately 17,000 km², set apart from the Andes chain that runs through Colombia. The Sierra Nevada has the world’s highest coastal peak (5,775 m above sea level) just 42 kilometres from the Caribbean coast. The Sierra Nevada is the source of 36 basins, making it the major regional ‘water factory’ supplying 1.5 million inhabitants as well as vast farming areas in the surrounding plains used mainly for the cultivation of banana and oil palm. The main problems to be solved in these basins are: i) Declining availability of water for irrigation, ii) Declining availability and quality of water for human consumption, iii) Increasing salinization of ground water and soils, iv) Increasing incidence of floods.

This is a feasibility study on the adoption of more efficient irrigation techniques by oil palm farmers in the Sevilla basin (713 km²), one of the key basins in the Sierra Nevada. The general objective is to identify the local environment at basin scale, the limiting factors and suitable field interventions in oil palm areas to improve the water use. A preparation and implementation phase was developed including an initial baseline assessment of the basin on climate, water availability, drought hazard, soil characteristics, land use, and topography. The agronomy (e.g. cultivars) and current field practices (e.g. nutrient management and irrigation practices) of the oil palm areas were characterized, and the crop water requirements determined. In addition, costs and benefits associated to the implementation of efficient irrigation technologies such as fertigation and water harvesting were assessed. Potential locations, risks and opportunities for water harvesting were evaluated with the idea to store water in the wet season to be able to use the resource in an efficient way in the dry season. A range of GIS and satellite-based datasets (e.g. CHIRPS, MODIS-ET, MODIS-NDVI, HiHydroSoil) were used to evaluate the environmental conditions, and local data and information was provided by local partners Cenipalma and Solidaridad to generate a comprehensive assessment at basin and field scale. The expectation is that fertigation and water harvesting techniques can be adopted in the Sevilla basin, but also in other basins in the Sierra Nevada de Santa Marta to reduce the environmental impact of oil palm production.

The Asian Development Bank supports Tajikistan in achieving increased climate resilience and food security through investments in modernization of Irrigation and Drainage (I&D) projects. A Technical Assistance is preparing modernization projects for two I&D systems in the Lower Vaksh river basin in Tajikistan. In line with this, the TA will prepare a holistic feasibility study and project design for the system (38,000 ha), as well as advanced designs and bidding documents for selected works.

FutureWater is part of the team of international experts, working together with the local consultant on the climate risk and adaptation assessment that accompanies the feasibility projects. For this purpose, past climate trends will be analyzed, climate model projections processed, and a climate impact model will be used to assess how the project performs under a wide range of future conditions, to assess the robustness of the proposed I&D investments, and identify possible climate adaptation measures.

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.

The project should increase agricultural water use productivity in the selected agricultural districts in Uzbekistan through a threefold approach: (i) climate resilient and modernized I&D infrastructure to improve measurement, control and conveyance within existing systems; (ii) enhanced and reliable onfarm water management including capacity building of water consumers’ associations (WCAs), physical improvements for land and water management at the farm level and application of high level technologies for increased water productivity; and (iii) policy and institutional strengthening for sustainable water resources management. This will include strategic support to the Ministry of Water Resources (MWR) and its provincial, basin and district agencies.

The project supports the Strategy of Actions on Further Development of Uzbekistan (2017), which includes: (i) introduction of water saving technologies and measures to mitigate the negative impact of climate change and drying of the Aral Sea; (ii) further improvement of irrigated lands and reclamation and irrigation facilities; and (iii) modernization of agriculture by educating areas of cotton and cereal crops to expand horticulture production.

FutureWater focuses on the climate risk and adaptation assessment that accompanies the feasibility projects, and will analyze climate trends, climate model projections, climate impacts on the projects and assess adaptation options.

Watch the video below to learn more about the management of Climate Adaptive Water Resources in the Aral Sea Basin in Uzbekistan (source: ADB)

Cambodia is currently improving in economic standing, however the benefits of this are largely contained to urban areas. As a major contributor to GDP, ensuring the sustainability of Cambodia’s agricultural sector is highly important, especially when coupled with the increasing awareness of the dangers of climate change. Access to water for agriculture, fisheries and domestic supply is an issue, with many rural communities competing for resources. Coupled with the effects of flood and drought activity in recent years, the need for adequate and reliable water resource management in rural, agricultural areas is prominent. This project focuses on the North- Western Cambodian provinces of Oddar Meanchey (OMC) and Banteay Meanchey (BMC) and the neighbouring North-Eastern Thai provinces of Surin and Sisaket.

In order to protect rural livelihoods and maintain agricultural production, communities must be supplied with permanent and regulated water year-round. Analysis of recent flood and drought histories and their effects in the provinces are first necessary to determine the most vulnerable areas both in terms of agriculture and households. In addition, water resource assessments of supplies and demand will identify the most crucial areas to ensure supplies are increased and sustained both for crops and domestic use. Socio-economic studies will also ensure ‘cross- cutting’ issues are considered in WR planning, such as: gender, economic vulnerability and cultural factors related to WRM. Furthermore, meetings with stakeholders at multiple levels can address issues in water infrastructure, alongside assessment of the capacities of those managing monitoring systems for example. From this, future recommendations for improvements in infrastructure can be made with an awareness of the necessary knowledge capacities to ensure proper maintenance and sustainability.

Initially, an analysis of the current water resource situation in the study area will be conducted through collection of available data on water resources, flood and drought histories and socioeconomic issues in the area. Following this, areas for more detailed analysis will be established and strategies to improve WRM supporting agricultural livelihoods can be developed. FutureWater is involved in the implementation of the WEAP model, for evaluation of various water resources management strategies in the catchments under baseline and projected future conditions.

The scope of the project work is as follows:

  • Train selected NCBA Clusa PROMAC staff on drone operation, imagery processing software, and crop monitoring;
  • Provide technical assistance to trained NCBA Clusa staff on drone operation, imagery processing, and interpretation of crop monitoring data;
  • Present technical reports on crop development and land productivity (i.e. crop yield) at the end of the rainy and dry season

The trainings and technical assistance for the NCBA Clusa staff are provided in collaboration with project partners HiView (The Netherlands) and ThirdEye Limitada (Central Mozambique). Technical staff of the NCBA Clusa are trained in using the Flying Sensors (drones) in making flights, processing and interpreting the vegetation status camera images. This camera makes use of the Near-Infrared wavelength to detect stressed conditions in the vegetation. Maps of the vegetation status are used in the field (with an app) to determine the causes of the stressed conditions: water shortage, nutrient shortage, pests or diseases, etc. This information provides the NCBA Clusa technical staff and extension workers with relevant spatial information to assist their work in providing tailored information to local farmers.

At the end of the growing season the flying sensor images are compiled to report on the crop development. The imagery in combination with a crop growth simulation model is used to calculate the crop yield and determine the magnitude of impact the conservation agriculture interventions have in contrast with traditional agricultural practices.

The detection of on-site farm reservoirs and ponds in large areas is a complex task that can be addressed through the combination of visual inspection of orthophotos and the application of automatic pixel classification algorithms.

This analysis applied a general workflow to detect and quantify the area and density of on-farm reservoirs and water bodies in three representative Mediterranean irrigated oases in Sicily-Italy, Northern of Morocco, and Israel. For each area of analysis, the most recent orthophotos available were collected from Google Earth, and the ilastik algorithms were implemented for the pixel classification (Random Forest -RF-) and semantic-segmentation. The RF classifier, which is previously applied to a set of filtered imagery and iteratively trained, provides probability maps of different classes that are finally used for quantitative analysis, or the retrieval of a segmentation-categorical (water vs non-water) maps.

In irrigated agriculture options to save water tend to focus on improved irrigation techniques such as drip and sprinkler irrigation. These irrigation techniques are promoted as legitimate means of increasing water efficiency and “saving water” for other uses (such as domestic use and the environment). However, a growing body of evidence, including a key report by FAO (Perry and Steduto, 2017) shows that in most cases, water “savings” at field scale translate into an increase in water consumption at system and basin scale. Yet despite the growing and irrefutable body of evidence, false “water savings” technologies continue to be promoted, subsidized and implemented as a solution to water scarcity in agriculture.

The goal is to stop false “water savings” technologies to be promoted, subsidized and implemented. To achieve this, it is important to quantify the hydrologic impacts of any new investment or policy in the water sector. Normally, irrigation engineers and planners are trained to look at field scale efficiencies or irrigation system efficiencies at the most. Also, many of the tools used by irrigation engineers are field scale oriented (e.g. FAO AquaCrop model). The serious consequences of these actions are to worsen water scarcity, increase vulnerability to drought, and threaten food security.

There is an urgent need to develop simple and pragmatic tools that can evaluate the impact of field scale crop-water interventions at larger scales (e.g. irrigation systems and basins). Although basin scale hydrological models exist, many of these are either overly complex and unable to be used by practitioners, or not specifically designed for the upscaling from field interventions to basin scale impacts. Moreover, achieving results from the widely-used FAO models such as AquaCrop into a basin-wide impact model is time-consuming, complex and expensive. Therefore, FutureWater is developing a simple but robust tool to enhance usability and reach, transparency, transferability in data input and output. The tool is based on proven concepts of water productivity, water accounting and the appropriate water terminology, as promoted by FAO globally (FAO, 2013). Hence, the water use is separated in consumptive use, non-consumptive use, and change in storage (Figure 1).

Separation of water use according to the FAO terminology.

A complete training package is developed which includes a training manual and an inventory of possible field level interventions. The training manual includes the following aspects: 1) introduce and present the real water savings tool, 2) Describe the theory underlying the tool and demonstrating some typical applications, 3) Learn how-to prepare the data required for the tool for your own area of interest, 4) Learn when real water savings occur at system and basin scale with field interventions.