The livelihood of the Maasai pastoral communities in Longido District of Northern Tanzania are impacted by droughts regularly, with expectations of increasing variability in rainfall patterns the coming years due to climate change. The goal of this research is to explore if weather forecast and remote sensing data can be tailored to existing coping strategies and decision-making. Furthermore, it is assessed if this tailored information provides enough skill to effectively complement local knowledge and drought management strategies. The study generated important methodological and theoretical findings, both of which have practical implications for policy and technological development. An ethnographic and participatory approach, including four months of immersion with local families, was used to document local knowledge and strategies, and understand what specific, weather information may benefit pastoralists. The study focused on alamei periods, which refers to times of drought and scarcity in the Maasai language. It revealed that weather information around particular important ‘decision junctures’ is most relevant. On the one hand, decisions to move livestock during vulnerable times are based on current water and grass availability; on the other hand, families also consider expectations of rainfall in their decisions. The research determined that at very specific junctures throughout respective seasons, key, timely decisions must be made to maintain household resiliency. It is at these junctures that rainfall predictions become crucial. Using NDVI data and the ECMWF weather model, it was assessed if the onset of rains at such junctures can be predicted with enough skill to support livestock movement decisions. It revealed both optimism and scepticism about the role of current remote sensing and weather prediction technologies vis-à-vis variable, dryland ecologies and pastoral livelihoods.

IHE-Delft in cooperation with the Asian Development Bank (ADB) conducts a pilot project on assessing Crop Water Productivity in Asia, aiming to contribute to sustainable development in Asia’s irrigation sector, and create more value from scarce water resources. Indonesia is one of the 6 pilot countries where advanced technologies to measure Water Productivity (WP) from satellite data were introduced. Indonesia is the third largest rice producer of the world. Given the challenges such as growing population, degrading land and increasing water scarcity in upcoming decades, the Indonesian government aims to rehabilitate its irrigation systems. More insights in the spatial distribution of irrigation water and water productivity of rice paddies could contribute to decision-making in future rehabilitation investments. This report describes the assessment of Water Productivity (WP) of paddy rice in Indonesia using the Surface Energy Balance Algorithm for Land (SEBAL). SEBAL is a tool that translates raw satellite measurements into maps of actual evapotranspiration and crop production, among others. The actual crop water consumption (i.e. actual evapotranspiration) and crop yield can now be estimated for every 30 m x 30 m, even if data on irrigation water application is not available. With this information, rice production per unit of land (kg/ha) as well as per unit of water consumed (kg/m3) can be computed. Focus of this study are sites in Bali, West Java and Lombok. Fieldwork is conducted in Bali and West Java to support the maps with ‘ground truth’ data. Data is collected from local governmental institutes and farmers to verify the remote sensing outputs. This research shows promising results linking SEBAL outputs with the ground truth even though the amount of fieldwork was limited. The inclusion of the new HANTS algorithm will create the technical opportunity to make daily WP reports for all rice fields in Indonesia, also under cloudy conditions. This could be a big information boost to support irrigation managers with their daily services of bringing water to farmers. Whereas some key explanatory reasons were detected (i.e. distance to canal, salt water intrusion, water quality, erosion), it is recommended to further explore relations between WP and influencing factors in the local context together with local irrigation officers. Even though the research revealed some limitations causing uncertainties, this new remote sensing technologies can support an efficient and effective investment purposes on modernization of irrigation. It is recommended that the Directorate of Irrigation and Lowlands recognize WP as a new policy instrument and implement it both at central level and irrigation district level.