Niger's economy is mainly based on agriculture with 75% of the working population and 40% of GDP depending considerably on the availability of water resources. However, in recent decades, agricultural production in the Sahel region and particularly that of Niger has experienced a general downward trend caused by an increase of drought and floods. The rainfall on which the agricultural sector and livestock largely depend is highly irregular. The most recent climate change projections show a trend towards further intensification of rainfall and an increase in the duration of dry episodes during the agricultural season. These environmental and climatic changes have profoundly changed the hydrology of artificial ponds and natural reservoirs that play an important role in hosting vegetable crops, rice cultivation, fruit trees and providing water to livestock and migratory birds. Despite this situation, there are no quantitative estimates of the sedimentation rate of Niger’s ponds and reservoirs, and no predictive model of their storage capacity and lifespan in the dry season. It is also unknown how soil moisture changes according to rainfall in different types of soils. Due to this, Niger seeks to increase its knowledge on soil moisture dynamics and pond dynamics to prepare climate change adaptation policies and increase agricultural resilience.
Niger’s national adaptation priorities focus on improving the resilience of the agriculture, livestock and forestry subsectors. The CTCN shall support Niger in its objective to generate 18 months’ worth of data to develop predictive models of the hydrological and sedimentary dynamics of temporary ponds and small reservoirs in the Sahel to improve climate smart agriculture models. This includes the identification of a set of about fifty ponds and temporary reservoirs of different sizes in watersheds with various characteristics and acquiring a high-resolution topography of these ponds during the dry season and before and after each rain to analyze water dynamics and generate predictive models.
The project shall ultimately serve decision-makers, farmers and herders to make important decisions for the short-, medium- and long-term productivity of livestock and agriculture in Niger. Examples include predictions at the end of the rainy season, whether a pond or a reservoir will be able to meet the usual needs of the population and ecosystems during the dry season and whether the level of services provided by pond or reservoir are likely to decrease significantly in the medium or long term due to rainfall or sedimentation. Furthermore, it shall also help to identify necessary interventions (over-digging, watershed treatment) required to maintain the level of service of an artificial pond or reservoir and identify the best place to create an artificial reservoir that can provide a given amount of water during a given period of time. This Technical Assistance ultimately supports Niger’s NDC to reach its adaptation and food security goals, as well as its focus on climate-smart agriculture by improving the expertise on climate information, early warning and risk and disaster management. It also contributes to the preservation and partial restoration of biodiversity hit by droughts.