The project focused on the flood/drought related problems in Mali and the impact on food production. The innovation works by big data analysis, using different sources of data: online media, remote sensing, historical and actual data and user generated data sources. The data is used to improve (predictions on) drought models. Mali Meteo, the meteorological agency in Mali, has easy access to analysed data, thus better helping their clients. By doing this Mali Meteo can help governments and NGOs improve IWRM and disaster measures. It can also help input suppliers, credit suppliers and crop insurance companies tailor their product offer.
The project accomplished:
- Availability at Mali Meteo of data combined from weather stations, online media, historical and satellite data
- Seasonal forecast support by using the difference sources of data, including online media
- Training at Mali Meteo of the use of the drought model
- Letter of the consortium to Mali Meteo on how to prepare the next step and use the data in other business and user cases, also at externatl organisations to which Mali Meteo currently delievers forescasts.
Tips for the future
- Only start a project if there is clear ownership on the local side. The divergence between the local expectation and what the project could deliver, was too big. If you start a joint project, clearly define expectations of each of the partners.
- Writing a ‘closing letter’ to the local partner proved to be a nice and more personalised way of formulating results and recommendations for the future.
Potential for growth
There is potential for growth if Mali Meteo – in addition to the meteorological side (what the weather will be) – also works and contributes to the impact (what the weather will do) of the weather. It can then become a valuable partner for many different actors.
MaliMeteo, Floodtags, Akvo, Satelligence, Deltares
August 2017 – June 2019
Last project updates
The country for example suffers from frequent floods of the river Niger, who’s watershed covers 47% of the country. These floods regularly cause large damages, such destruction of property or destroyed roads, inhibiting transport in the rural region of Mali. On the opposite also frequent droughts hit the country, not only causing drinking water scarcity, but leaving its mark on Mali’s agricultural sector, that is responsible for 90% of the water use in Mali. Another issue negatively impacting the agricultural performance in Mali , which is well behind its neighbouring countries (Aidenvironment, 2015), is related to the difficulties of small farmers getting access to funding, which means they can’t invest in more efficient agricultural practices (Beaman et al., 2015). Also land degradation, in part due to large scale deforestation of up to 6% per year (FAO, 2013), mismanagement of upstream dams in the river Niger, and irrigation potential not being exploited (Dietz et al., 2014), holds back agricultural production, limiting Mali’s GDP and contributing to the severity of famines (FAO, 2013). Also, more than 30% of Mali’s population still does not have access to safe drinking water (WorldBank, 2013), a figure that has hardly changed over the last decades (UNICEF & WHO, 2015). Additionally, water availability is negatively impacted by the ongoing pollution of ground water in Mali (Dietz et al., 2014). Set against this background, the project that we propose will address the Niger River basin in Mali, covering 47% of the country and specifically the impact of development in the Basin on the urban areas of the Bamako, Mopti, Sikasso, Gao, Timbouctou and Ségou.
To phase and execute the activities, we will use Rational Unified Processing (RUP is an iterative framework for software development) which consists of the phases Inception, Definition, Elaboration, Production and Transition. Within each phase there will be iterations based on input from project team and stakeholders. The iterations in the phase “Production” will be guided by Agile Development Principles. The phases are: * Inception: In this phase we determine the scope of the project, relation to other programs, project region, sub-consultant contracts etc. and do the inventory. * Definition (distinguish Back-End Architecture and Development from Graphic and UI design front-end). All high level requirements (business, technical, functional, content) are gathered and formalized and are the reference requirements for next steps. * Elaboration: the requirements are elaborated into deliverables like test plan, technical design, graphic designs, use cases and content plan. * Production: The Software will be developed using agile software development principles. * Test and Transition: the tested software is transferred to the production environment, users are trained, start of regular maintenance. Secondly, in each of the phases, five domains are considered: * Societal: What is the societal problem and is it being solved? * Functional: What does the software do, to solve the problem * Technical: How does the software work, to solve the problem * Graphical: What does the software look like * Content: What does the software contain in terms of data
The target group initially involves multiple organisations, which will be reduced throughout the project: * Direction Nationale de l’Hydraulique (DNH) * Disaster response organisations * Agricultural credit suppliers and insurance firms * Agricultural input supply companies * Farmers * Non-governmental Organisations
We are aiming for Impact by enabling a number of organisations to benefit from new data. These organisations include the local counterpart and we will explore a number of further use cases for commercial stakeholders. For these use cases in Mali, we will determine time/budget need to (post-project) business as usual. At the round-up of the project (preparing for transition) we will make a new list of top risks for the sustainable continuation of the changes foreseen at the local counterpart, and a plan for further scaling to commercial use cases. Conclusively, the work of PCA-GIRE, Watershed and other programmes in supporting stakeholders to be data driven (the assumptions from the Theory of Change) will continue after the end of this project. We acknowledge these programmes for the good work they do, helping countries and stakeholders benefit maximally from the resources available.
Overview of Goals
Hereunder the change of behaviour would contribute to achieving those impacts (in random order): * Viable Financial Arrangements in the Agricultural Sector: Credit suppliers have more data to bare decisions on, leading to more credits. By improving access of farmers to investments, loans and insurances, they can invest in better practices, leading to a higher agricultural efficiency, less water use and increased crop production (See e.g. Beaman et al., 2015). * Access to knowledge and information among farmers: Farmers use impact forecasting data (aligned with OPIDIN data) to warn them about disasters happening in their area. As a result, the make better decisions about times of seeding, applying pesticides and harvesting * Improved Efficiency of Agricultural Input Supply Companies: Agricultural Input Supply companies use data to determine demand variation. This makes their distribution more efficient, finally translating to a better product offer and reduced costs for farmers. * Governments use risk data in flood and drought management: Accurate information about past water events, such as floods and water scarcity, helps in understanding disaster risks, and thereby guides decisions on mitigating risks and boosting disaster preparedness, both important stages of the disaster risk reduction cycle (Carter, 2008). * Disaster response organisations: In the preparation and response to a disaster like floods and water scarcity, organizations such as the Red Cross use actionable (near) real-time data to request funds, shape their response and prioritize action (IFRC). * Governments optimize water resource planning based on long-term trends: Accurate information about past water events, such as floods and water scarcity, helps in understanding disaster risks, and guides decisions on mitigating risks and boosting disaster preparedness, both important stages of the disaster risk reduction cycle (Carter, 2008). * Evidence-based advocacy by NGOs: Following evidence-based advocacy by organizations and programmes such as UNICEF, WHO and UNEP, NGOs use data about occurrences of deforestation, erosion, peat fires, point disposals, waste disposals, and other malpractices that are reported in news media, to advocate for a better environment. * Changing behaviour of organizations that negatively impact sustainability: Evidence based advocacy of NGOs and optimized water allocation policies of government, drives organizations to adopt practices that are water efficient and reduce environmental harm.