In West Africa, climate change and variability are a major concern for sustainable development affecting agriculture and other key sectors with direct implications on the health and food security of rural populations. In the Sahel, major drought events caused famine in 1973–1974 and 1984 [1
] and, since then, rainfall variability has been a key stressor in agricultural activities and is projected to intensify with future climate change [2
]. Sahelian countries, such as Niger, where most of the population lives in rural areas and their main livelihood is rainfed agriculture, are particularly vulnerable to climate risks. In Niger, 84% of the population live in rural areas [5
], and 89% of them are considered multidimensionally poor [6
], experiencing “multiple deprivations at the household and individual level in health, education and standard of living” following the definition adopted by the UNDP for the multidimensional index of poverty [7
]. In Niger, the combination of rainfall variability and poverty dooms rural communities to a chronic vulnerability to food insecurity [8
For two decades, climate-smart agriculture (CSA) has been included in the development agenda with the aim of sustainably increasing agricultural productivity and building resilience of agricultural systems to climate change [10
]. Among CSA best practices, weather and climate services (WCSs) have been acknowledged as a key opportunity to reduce farmers’ vulnerability in Africa [10
]. Many authors [12
] provide evidence that agrometeorological information tailored to farmers can improve agricultural productivity and increase their income thereby reducing the impacts of climate change and minimizing the risk of food insecurity. However, at the farm level, agrometeorological services are often not really relevant, adapted, and usable for decision making in crop management. Indeed, national institutions are not well-equipped to respond to users’ needs in terms of both forecasting expertise and dissemination channels.
National meteorological services in West Africa usually concentrate their forecasting efforts on short term and seasonal lead times. Short-term weather forecasts, one up to three days, as usually provided by met services, are not sufficient to take some strategic decisions on crop management planning and risk reduction strategies, which require 10 days to seasonal lead times [10
]. Ten-day forecasts are not usually produced, even if they are particularly relevant for farmers and the benefit of their application in crop management, in terms of impact, is demonstrated to be even greater than seasonal forecasts [18
]. Moreover, 10-day forecasts can be used for integrating the information from seasonal forecasts with a major increase in their effective application for WCSs [19
Ten-day forecasts are generally considered a difficult time range, since the lead time is long enough for uncertainty from the initial conditions to arise and bias the numerical simulations [20
]. Meanwhile, the models do not have enough time to “warm up” and correctly reproduce the global atmospheric dynamics [21
]. The skill of such forecasts is often considered too low by met services and they do not often produce them. The main concern is to deal with the intrinsic uncertainty of medium-range weather forecasts. To properly communicate uncertainty, it is recommended that quantitative information be encoded in a way that fosters accurate decoding and prevents deterministic misinterpretations of uncertainty and the level of detail is chosen according to the forecast’s skill [22
]. Therefore, recognized good practices recommend translating quantitative values into categories through a participatory approach after an initial stage of testing and performance evaluation in the specific context.
A review on perceptions and use of WCSs in agricultural decision making [23
] highlights that farmers seek contextual and location-specific forecasts to aid decision making and “would like access to forecasts at the correct time to facilitate decisions (such as predicted harvest conditions) and predict impacts, so they can be mitigated before they become severe”.
The time-gap between issuing of the forecast and its reception by farmers has long been a critical challenge for agrometeorological warning systems, particularly in the least-developed countries, such as Niger, where information dissemination networks are weak, distances are large, and the extension service has suffered a chronic lack of financial resources for many years. The wide diffusion of mobile phone technology throughout sub-Saharan Africa offers the potential to reduce the time-gap and costs associated with the dissemination of forecasts to farmers [24
], changing the extension service paradigm. Indeed, the agriculture extension service has for a long time been characterized by, and often criticized because of, its linear knowledge transfer approach and its incapacity to use systematic approaches for service delivery [26
]. According to this approach, the proximity of agriculture extension officers to farmers was considered the main factor influencing the adoption of climate-informed cropping practices [18
]. Currently, the concept of proximity is changing from a geographical perception to a social one, mediated by social networks and the media. New Information and Communication Technologies (ICTs) are enhancing the interaction and information exchange within the agriculture innovation system and changing the relations between information providers, extension officers, and farmers [27
]. Moreover, digital technology could allow communities to provide timely feedback on information received and its performance, thereby improving their engagement in the whole agrometeorological monitoring system.
During the last decade, several pilot initiatives, by national and international bodies, have been set up to provide WCSs to farmers in West Africa, mainly based on short-term weather forecasts or climate seasonal forecasts addressing the main hazards that affect agricultural activities such as a delay in the onset of the rainy season, dry spells, and an early end of the rainy season. Nevertheless, none of these initiatives addresses the issue of producing and disseminating medium-range weather forecasts and related agrometeorological information for smallholder farmers.
Given the hypothesis that 10-day agrometeorological forecasts can effectively enhance a WCS’s capability to improve agricultural productivity and increase farmers’ incomes, this study aimed to answer the following research questions:
How can a national met service produce and disseminate 10-day agrometeorological forecasts in remote rural areas in a timely and sustainable way?
Do 10-day agrometeorological forecasts meet the needs of farmers in supporting their decision-making process?
How can the encoding of agrometeorological information disseminated to farmers be improved?
In order to answer these questions, this paper describes the service developed within the ANADIA (adaptation to climate change and disaster risk reduction in agriculture for food security) project in Niger. The project, funded by the Italian Agency for Development Cooperation, provided technical support to the Niger National Meteorological Directorate (DMN) to improve its capacity to reduce climate risk at the local level. The project included eight municipalities in Tillaberi and Dosso regions. Within this initiative, a case study was set up aiming to (i) fill the gap in agrometeorological medium-range forecasting at DMN, (ii) improve the usability of such information by the local communities and (iii) tailor information dissemination at the municipality level. The results coming from this experience demonstrated that, even if some improvements are needed to make this process fully operational, the forecasts issued are globally appreciated by the local communities, who judged them useful for their decision-making processes.
The paper is organized in five sections. After this introduction, Section 2
describes the materials and methods and Section 3
presents the main results. In Section 4
, we discuss the findings according to the three research questions and, lastly, in Section 5
, some conclusions and indications on the way forward are provided.
The quantitative results of the performance analysis of the 10-day forecast indexes were not very different from the results already published in the literature on the skills of medium-range weather forecasts [39
]. The hypothesis we made at the beginning was that in a context where any weather forecast with a lead time longer than one day exists, 10-day agrometeorological forecasts, even with low accuracy, can sustain local decision making if appropriately applied. Therefore, assuming that the skill of the forecasts is good enough to guide cropping practices, some answers to our research questions are discussed hereinafter.
4.1. How Can a National Met Service Produce and Disseminate 10-Day Agrometeorological Forecasts in Remote Rural Areas in a Timely and Sustainable Way?
The question contains two different aspects concerning the availability of dissemination technology and technical expertise. Both challenges were tackled adopting simple solutions, contributing to the sustainability of the process. Very simple dissemination technology could be used effectively. Even in remote rural areas, mobile phones are widely used and even smartphones are common. The dissemination mechanism worked quite well during the two years. We had some issues at the beginning of 2019 related to internet connectivity in a few municipalities. This showed that the mechanism is more sustainable if users work with their own smartphone rather than providing new ones for the purpose of dissemination. Prepaid internet credit can simplify and encourage users to be connected but it is not strictly necessary.
The choice of plain text messages simplified the process of communication from the central to the local level. Dissemination was then ensured by local media and social networks. A key role in agrometeorological information dissemination to the public was therefore played by rural radios, which are the main information media in Niger rural areas and identified by farmers as the preferred channel to access WCSs [43
]. For this reason, radio stations were fully engaged in the dissemination process since the beginning of the initiative.
The agrometeorological indexes were actually disseminated at the beginning of each 10 days (1st, 11th, and 21st days of the month) while the 10-day forecasts were produced each day by GFS. It would be possible to produce the agrometeorological indexes daily and send them to farmers. However, sending indexes with a daily frequency to farmers would not be sustainable, and probably also not useful. The communication mechanism was designed according to the existing DMN chain of information dissemination, so that during the two years of experimentation, the forecasts were produced and disseminated with the decadal bulletins sent by DMN each 1st, 11th, and 21st days of the month. Nonetheless, the dissemination of updates with a shorter delay, i.e., 5 days, should be considered as a possible improvement in the whole process.
The training program and further knowledge transfer were demonstrated to be critical to successfully set up and maintain a semi-automatic procedure and replicate it in other areas. We found that new technical problems could arise daily, such as changes in the data distribution and format by the NOAA, which failed to undermine the sustainability of the system. However, strong collaboration and on-the-job training allowed the procedure to be modified and fixed in a reasonable time.
In the context of weak national institutions, another important aspect of sustainability is the cost to maintain the system. The use of open and freely available programming languages and simple procedures not demanding high calculating power ensured low cost, as well as the use of GFS products that were freely available. A final aspect is the replicability and sustainability of extension to other areas, even to the whole country. The entire procedure took 30 min to run even on obsolete Pentium hardware, but the time was not proportional to the number of localities because the bottleneck is internet access (data download from GFS), not the calculating time for processing the forecasts. The system is therefore easily extendable to the whole country without a significant increase in running time.
4.2. Do 10-Day Agrometeorological Forecasts Meet the Needs of Farmers in Supporting Their Decision-Making Process?
Users perceived the agrometeorological 10-day forecasts as important for their decision-making processes, even if they were not quantitatively accurate. Indeed, the feedback received from users underlined that they are able to manage forecast uncertainties in their daily activities. Although this should not be an excuse for not improving the forecast (the forecasting skills could be improved by using a regional model and intensifying the network of observation stations to allow a better initialization of the model), it seemed to us more profitable and pertinent to tailor existing information to specific end-users’ needs.
The service was generally and unanimously perceived as positive and useful for local communities, even if some problems related to the forecast accuracy were real. The bidirectional exchange of information, strengthening collaboration between the national and local levels, was a positive outcome of the initiative. The participatory approach made local communities feel that they were engaged in a process and therefore contributed to building trust and credibility. Indeed, according to Wall [45
], the process is often as important as the outcome.
According to the feedback from users, further development will concern new forecast information, such as strong winds and temperatures, which farmers perceive as useful for crop management.
4.3. How Can the Encoding of Agrometeorological Information Disseminated to Farmers Be Improved?
Forecast skill can be improved by using quantile–quantile categorized classification of the forecast dekadal rainfall amount. This approach allows misunderstanding due to the provision of quantitative values to be reduced and also to introduce a simple bias correction. It was not possible to adopt such an approach from the beginning because of the lack of forecasts time series. In the coming years, it will be possible to train the system to recalculate the centile every year in order to obtain more robust statistics for translating quantitative into qualitative information. However, the opportunity to translate quantitative information into qualitative (i.e., very wet, wet, almost dry, dry, etc.) must be verified with users because the language gap could become a real barrier. In many cases, the translation of the categories concept into local languages (Hausa and Djerma) could be misleading. Moreover, it is important to underline that the classified information does not have an absolute meaning for farmers because different crops and cropping systems have different needs in different periods that drive specific strategic choices. For this reason, further studies should explore the most effective way to communicate such forecasts maintaining a high level of usability.
The overall evaluation by users of the service provided was positive because, for the first time, they could access agrometeorological forecasts tailored to their own municipality. Users were really interested in accessing 10-day forecasts and were aware of their utility for crop management, particularly for extreme meteorological phenomena that could have a strong impact on their crops. Despite the uneven accuracy of the forecast, which is a common issue of 10-day forecasts, the main meteorological trends were detected and the information was perceived as useful for local decision-making processes. Indeed, farmers are used to dealing with weather uncertainties and they do not feel uncomfortable about the difference between forecast and observation. They particularly appreciated the forecast of very intense phenomena and dry spells during the next 10 days. Moreover, the local communities liked to be engaged in such a participatory process and they actively contributed to the progressive improvement of the service. This is particularly encouraging given that they were in charge of spreading the information to the wider farming community. The involvement of rural radio stations in the dissemination was shown to be really effective, thanks also to the strong collaboration between the DMN, extension officers, and journalists for the translation of information into local languages.
According to the feedback received from users, a further development of this WCS for smallholders will be to test the performance of temperature and strong wind forecasts during the 2020 rainy season. Moreover, the results showed that the adoption of categorized indexes could be very profitable for correcting biases. Nevertheless, before the setting up of an operational service, further investigation is needed to understand the most efficient way to communicate this information to smallholders in order to avoid misunderstandings.