Data Collection through Local Involvement
RELEVANCE OF NON-TRADITIONAL DATA
The iMoMo Project was incubated by the Global Programme Water of the Swiss Agency for Development and Cooperation from 2012 through 2017. The project had two main goals:
Fostering innovation in low-cost, high-tech, non-traditional, people-centered observations and monitoring.
Modernizing pathways from observation to decision-support for effective and sustainable water resources management.
The projects focus was in the global context of irrigation agriculture.
Nowadays, 25 % of the global crop area is irrigated, producing 40 % of all crops and 60 % of all cereals while irrigation accounts for 70 % of water withdrawals and 90 % of consumptive water use globally. Rising population numbers and changing nutritional demand will push agriculture towards increasing irrigation as projected food production will double in the 21st century. Together with climate uncertainty, these developments will exacerbate water stress, especially in the global drylands. As a result, stakeholders at all levels will be impacted as traditional water monitoring and management approaches have failed to answer most of the multi-scale water challenges.
Knowledge about runoff formation, water distribution as well as effective management is often hampered by the lack of sufficient data. One key reason is that traditional monitoring does not scale because of prohibitive investment and operation/maintenance costs as well as due to vandalism. Even where data are available, stakeholders often lack knowledge and technology on how to make best use of data in tactical and strategic terms. It often leaves them with the practice of informed guessing, e.g. by gambling on rains for agricultural production. Suboptimal and unsustainable outcomes result. They translate into water insecurity with adverse impacts on communities, their livelihoods and ecosystems.
The ultimate goal of data collection in water resources, is to provide a set of sufficient good quality data that can be used in decision-making in all aspects of planning and management, in the wide range of possible applications, including for research. Decisions may be made directly from raw data measurements or based on derived statistics or on the results of many stages of modelling beyond the raw data stage. But in all circumstances, it is the collected data that form the basis for these decisions.
The paucity of good water-related supply and use data is an expression of decades of stakeholders neglect to invest adequately in data acquisition but also often caused by weak enforceability of national water legislation or the absence thereof. This often also translates into lack of awareness by local communities about the challenges associated with proper water resources management. Despite significant focus from donors and the acknowledgment that the modernization of monitoring and measurement networks could bring large benefits to countries and their populations, the situation remains dire even today. On a local level, water users often perceive monitoring as a step towards increasing water use tariffs or constraining use rather than a mean to improve efficiency and secure reliable access. It is therefore crucial that measurement is supported by robust institutions to effectively engage vested interests, monitor and control water use and resolve disputes.