To facilitate the needs of ZIPAK, this training aims to build data-driven capacities relevant to sustainable nature conservation practices and ecosystem-based natural resources management in Iran:

  • Leveraging the Climate Change Knowledge Portal (CCKP) for performing climate risk and vulnerability assessments
  • Leveraging the online dashboard Earth Map for environmental hazard mapping and socio-economic risk assessments
  • Applying the InVest model (Integrated Valuation of Ecosystem Services and Tradeoffs) for assessing ecosystem service provision

The training focuses on knowledge and skills development and how how to meaningfully integrate these capabilities into ZIPAK’s objectives on sustainable management of the environment and natural resources.

Last week, Martijn de Klerk, Corjan Nolet, and Tijmen Schults provided an in-person training on Climate Smart Agriculture and geodata and modeling tools for participants representing SMEs from the Egyptian agricultural sector. The training was part of the SASPEN (Sustainable Agriculture Service provision Enterprise Network in Egypt) project, implemented by Care Egypt

The training took place at Care Netherlands in The Hague and was initiated by Care Egypt Foundation (CEF) and funded by the Dutch Embassy in Egypt. The aim of the SAPSEN project is to connect Egyptian agribusiness professionals from small and medium enterprises to Dutch projects, companies, and other partners in the agricultural sector to strengthen collaboration and stimulate the exchange of knowledge.

During the training FutureWater provided, 11 enthusiastic participants from various agricultural companies listened to a variety of topics surrounding Climate Smart Agriculture (CSA). The participants acquired hands-on experience in the use of online portals for the retrieval of geodata for agriculture and were handed several tools to perform data analysis. The agribusiness professionals indulged in discussions and participated in interactive quizzes related to CSA, geodata tools, drones, and crop modeling. The day was successful in bringing ideas and businesses together.

The in-person training will be followed up by two online training sessions covering advanced topics such as an introduction to ‘Real Water Savings’ (REWAS), water productivity interventions, open data portals for climate change information, and open access data solutions for the agricultural sector.

 

Presentation provided by FutureWater colleague Tijmen Schults
Presentation provided by FutureWater colleague Corjan Nolet
The beneficiaries of this training, provided by FutureWater together with Solidaridad, belong to the Zambia Agricultural Research Institute (ZARI).
ZARI is a department within the Ministry of Agriculture of Zambia with the overall objective to provide a high quality, appropriate and cost-effective service to farmers, generating and adapting crop, soil and plant protection technologies. This department comprises a number of sections, one of which, for the purpose of this training request is the Soil and Water Management (SWM) division. ZARI and the SWM carry out demand-driven research, trying to find solutions to the problems faced by Zambian small-scale farmers, especially considering the near- and long-term impacts of climate change.
The training programme consists of a hybrid approach of e-learning and in-person training sessions and is structured around the following modules:
  1. Remote sensing-based analysis using Google Earth Engine to assess trends in land use, management, degradation and hotspots for intervention.
  2. Data collection and database management.
  3. GIS and remote sensing to assess suitability for SWC.
  4. Effectiveness and prioritization of SWC using open-source tools.
  5. Independent working on case study.
At the end of the training, it is expected that participants have achieved several objectives such as acquisition of technical skills for extracting relevant data from open access remote sensing products and improved knowledge of data collection and database management.

Last week, first module of the Nuffic TMT training course on Geo-spatial data skills development was kicked-off at Zambia Agricultural Research Institute (ZARI). 

Solidaridad is partnering with FutureWater to conduct a tailor-made training on ‘Geo-spatial data skills development for improved soil water
management and enhanced crop productivity at the national level in Zambia’.

The training project for ZARI is a Tailor-Made Training (TMT), as part of the Orange Knowledge Programme, funded by Nuffic and will enhance capacity in accessing and using innovative data and tools in the public domain, to analyse crop performance and improve soil water management.

This first module was focused on the use of Google Earth Engine (GEE).

The objective of this module was to build capacity of the participants in using the basic functionalities of GEE, by working on applications specifically relevant for land use management and identification of degradation hotspots. This objective has been achieved by participants by obtaining hands-on experience in script-building and interpretation of outcomes.

The first module has been conducted by:

And the rest of modules will take place during the incoming months, following the training project.

Introduction in classroom
Trainers and participants

InfoSequia is the Drought Early Warning and Forecasting System developed by FutureWater to support the decision-making and risk management of drought impacts. InfoSequia rests on an advanced cloud computing and geoprocessing architecture able to effectively integrate large volume of data from satellite, reanalysis and ground-observation networks, with machine learning techniques to generate local-tailored seasonal outlooks of drought risk failures at the river basin and agricultural district levels.

InfoSequia has been recently and effectively integrated into the TWIGA geoportal, a platform that offers to African users the possibility for accessing data from ground-observation networks, and climate or agro- services with monitoring and forecasting capabilities.

The new and enhanced InfoSequia indices and products are operationally delivered for the Inkomati River Basin, a transboundary basin which extends through South Africa, Eswatini and Mozambique.

This lite service includes a full suite of 3 dekad-based (10-days) meteorological drought indices and 3 dekad-based vegetative health indices, all of them timescale aggregated at 1, 3, 6 and 12 months, and updated every month. The service is easily scalable and user-tailored to other regions of Africa upon request and agreement with FutureWater. Thanks to the advanced front-end capabilities of the TWIGA portal, users can easily access InfoSequia data and incorporate them into dashboards specifically set up according to their information needs.

A video was made to highlight how InfoSequía has been implemented, watch it here:

More information about the FutureWater’s approach on Water Scarcity and Drought can be found here.

 

One-pager brochure of InfoSequia-TWIGA for Africa. Downloadable as PDF here.

 

The study will focus on selection of key traded crops between the EU and Africa and their key producing regions. The tasks will include overall analysis of current practices and the background in the regions, determination of key sensitive parameters in order to select key crops and food products and map hotspot regions. In addition, project team will assess climate risks for these hotspots on key crops and food products and link these risks with the importing countries. Climate risks will be assessed by identifying the multiple climate sensitivities on the food systems in each region, assessing changes predicted by a CMIP6 (latest) climate model ensemble on key agriculture-related climate indices, and analysing impacts on production-related indices, distinguishing between rainfed and irrigated production systems. It will be focused on country specific case studies in each partner country. The impacts of climate change on trade patterns will be evaluated to assess the carbon- and water footprints and virtual water profiles of key traded commodities of these countries. At the end, the project team will focus on policy relevance and assessment of adaptation strategies and identify interventions that will be needed, at which point in the system, and from which sector (or actor) is of interest.

The outcomes of CREATE will be used to increase awareness of the risks that climate change poses to the agro-food trade and the broader economy at large. They can contribute to efforts by the governments (macro-scale), the communities (meso-scale), as well as relevant agricultural producers (micro scale) in the case study countries, by providing essential information for promoting actions towards mitigating the negative consequences of climate change on agro-food trade.

The “Integrated Strategic Water Resources Planning and Management for Rwanda” consultancy project will assess and evaluate the availability and vulnerability of the country’s water resources up to around 2050 taking climate change into consideration.

Based on this, prioritization of investment options in grey and green infrastructure will take place, in order to formulate water resources investment plans. A revised water resources policy will be prepared that is in line with water security targets and SDG 6.

In more detail, the hydrological modelling assessment will result in update water accounts per sub-catchment up to 2050. Field work for assessing groundwater resources in key areas across the country is also performed. A detailed water allocation assessment will be performed using a water resources system model (WEAP), addressing water needs for the various users up to 2050. Water allocation plans will be developed from this modelling work, incorporating stakeholder inputs.

Then, a scenario analysis is performed to evaluate the potential of additional storage in the landscape: grey (reservoirs) and green (through Nature-based Solutions). This analysis will be complemented by field work and a pre-feasibility analysis will be performed on the prioritized options. A SWOT analysis will then lead to a number of possible flagship projects which of which a concept note is prepared.
Support to the revised national policy for water resources management will also be provided by defining new policy statements and actions informed by the results from the previous tasks and developing a new water resources policy that will guide the country towards achieving the NST1 and Vision 2050 targets.

Water and food security are at risk in many places in the world: now and most likely even more in the future, having large economic and humanitarian consequences. Risk managers and decision-makers, such as water management authorities and humanitarian-aid agencies/NGOs, can prevent harmful consequences more efficiently if information is available on-time on (1) the impact on the system, economy or society, and also (2) the probabilities for a failure in the system. EO information has proven to be extremely useful for (1). For looking into the future, considering the uncertainties, novel machine learning techniques are becoming available.

The proposed development is incorporated into an existing solution for providing Drought and Early Warning Systems (DEWS), called InfoSequia. InfoSequia is a modular and flexible toolbox for the operational assessment of drought patterns and drought severity. Currently, the InfoSequia toolbox provides a comprehensive picture of current drought status, based mainly on EO data, through its InfoSequia-MONITOR module. The proposed additional module, called InfoSequia-4CAST, is a major extension of current InfoSequia capabilities, responding to needs that have been assessed in several previous experiences.

InfoSequia-4CAST provides the user with timely, future outlooks of drought impacts on crop yield and water supply. These forecasts are provided on the seasonal scale, i.e. 3-6 months ahead. Seasonal outlooks are computed by a novel state-of-the-art Machine Learning technique. This technique has already been tested for applications related to crop production forecasting and agricultural drought risk financing. The FFTrees algorithm uses predictor datasets (in this case, a range of climate variability indices alongside other climatic and vegetative indices) to generate FFTs predicting a binary outcome – crop yields or water supply-demand balance above or below a given threshold (failure: yes/no).

The activity includes intensive collaboration with stakeholders in Spain, Colombia and Mozambique, in order to establish user requirements, inform system design, and achieve pilot implementation of the system in the second project year. Generic machine learning procedures for training the required FFTs will be developed, and configured for these pilot areas. An intuitive user interface is developed for disseminating the output information to the end users. In addition to development of the forecasting functionality, InfoSequia-MONITOR will be upgraded by integrating state-of-the art ESA satellite data and creating multi-sensor blended drought indices.

Frost damage has been a frequent hazard for fruit growers in the Netherlands, getting worse with shifts in the growing season due to climate change. Wind machines can be a more sustainable alternative than sprinkling freshwater for frost protection, especially in regions where freshwater is limited or too brackish.

Last spring, FutureWater and HiView conducted flying sensor flights equipped with a thermal camera to map the temperature effects of wind machines for protecting fruit orchards against frost damage. The work was done in a larger research project with TUDelft aiming at capturing the effect of the wind machines on fruit frost protection at a fruit grower in Krabbedijke, the Netherlands. Read more about this project here.

A video was made to give an impression of the flying sensor activities, watch it here:

FutureWater, with TWIGA project partners HiView, Hydrologic and UFZ Helmholtz, have developed the farm extension service ‘MapYourCrop’. The MapYourCrop service uses drones, or flying sensors, to collect crop information with an unprecedented level of detail. What makes MapYourCrop unique is that flying sensor data is enriched with detailed crop status information collected by the smartphone app called ‘VegMon’.

After making the flying sensor crop stress maps, the VegMon app is used to zoom in to problem areas. Based on measurements, visual inspection, photographic evidence, and expert knowledge, the crop stress is identified and recorded with the app and a farm management advice is developed. The final advice is provided using the TWIGA platform. The farmer can choose to receive the advice in-person or electronically. MapYourCrop is currently tested by Mozambican drone and extension company. The company has a team of farm extension officers that are professionally trained as drone operators and have all the tools and knowledge to give advice to improve farming practices.

A video was made to highlight how MapYourCrop has been implemented, watch it here: