Best of both worlds : Co-producing climate services that integrate scientific and indigenous weather and seasonal climate forecast for water management and food production in Ghana

Climate variability and its impacts on the agriculture system is clearly evident in Ghana. Weather and seasonal climate forecast information service has been in operation for some time in the country. However, farmers generally do not find the information useful for their farm-level decision making. Forecast accuracy, untimeliness, and mismatch of forecast information and needs are often reported constraints for farmers to use weather and climate information. Consequently, the majority of farmers rely on their indigenous ecological knowledge to predict weather and seasonal climate patterns. At the same time, current weather and seasonal climate forecast information systems in Ghana face serious constraints in how they are used (if at all because of the one directional assumption behind its development; where only science produces new knowledge and makes it accessible for end-users with no or limited involvement of the end-users. In this context, this study addresses the central question: How can climate information services be improved through the coproduction of farmers and scientist? It aims at improving the reliability and acceptability of forecast information by integrating indigenous and scientific forecast. In this dissertation, I used a multi-method research approach, consisting of social participatory methods, mental modelling methods, forecast verification methods, and the principle of citizen science for data gathering and analysis. Initial diagnostics revealed certain issues that limit the uptake of climate information services in Northern Ghana: (1) the mismatch between forecast information provided and the farmers' information need (2) poor quality of forecast information, (3) the disconnect between forecast providers (researchers) and farmers, (4) management of unrealistic expectations of farmers. In response, I proposed a framework for second generation climate services that have the potential to facilitate co-production of relevant and accurate weather and seasonal climate forecast information and manages user expectation while strengthening the collaboration between information providers and users. Results of our analysis show that farmers’ information needs are linked to the type and timing of farm-level decision making. Also, model-based seasonal forecasts have the potential to provide relevant information at farmers most preferred lead time. Findings also show that in addition to historical rainfall patterns, farmers also use observational changes in certain indigenous ecological indicators to predict the coming season. In particular, there is a cognitive relationship between the observational changes and the predicted rainfall event. I observed that farmers’ indigenous forecasting skills and techniques are not intuitive but rationally developed and improve with age and experience. Results also show that farmers and Ghana Meteorological agency are on average able to accurately forecast one out of every three daily rainfall events. Similar results were obtained at the seasonal timescale. Furthermore, I recognized that forecast reliability and usefulness can be improved if indigenous forecast data are quantitatively collected and integrated with the scientific forecast using the proposed integrated probability forecast method. Finally, this dissertation contributes to the calls for a more integrated, co-learning, and co-production approach to climate services that move away from the current focus on science-driven and user-informed climate services. The approach developed in this dissertation is relevant for managing the impact of climate variability and change, particularly because it includes the knowledge of indigenous peoples which is often overlooked

Climate Variability Since 1970 and Farmers’ Observations in Northern Ghana

The study examines how farmers’ observations of climate variability and change correspond with 42 years (1970-2011) meteorological data of temperature and rainfall. It shows how farmers in the Northern Region of Ghana adjust to the changing climate and explore the various obstacles that hinder the implementation of their adaptation strategies. With the help of an extension officer, 200 farmers from 20 communities were randomly selected based on their farming records. Temperatures over the last four decades (1970-2009) increased at a rate of 0.04 (± 0.41) ˚C and 0.3(± 0.13)˚C from 2010-2011 which is consistent to the farmers (82.5%) observations. Rainfall within the districts are characterised by inter-annual and monthly variability. It experienced an increased rate of 0.66 (± 8.30) mm from 1970-2009, which was inconsistent with the farmers (81.5%) observation. It however decreased from 2010-2011 at a huge rate of -22.49 (±15.90) mm which probably was the reason majority of the respondents claim rainfall was decreasing. Only 64.5% of the respondents had adjusted their farming activities because of climate variability and change. They apply fertilizers and pesticides, practice soil and water conservation, and irrigation for communities close to dams. Respondents desire to continue their current adaptation methods but may in the future consider changing crop variety, water-harvesting techniques, change crop production to livestock keeping, and possibly migrate to urban centers. Lack of climate change education, low access to credit and agricultural inputs are some militating factors crippling the farmers’ effort to adapt to climate change

Indigenous knowledge and climate change adaptation in Africa: a systematic review

Indigenous people are often considered victims of climate change impact rather than agents of adaptation. Emerging studies in Africa have shifted the attention to indigenous knowledge (IK) to support the development of effective climate change adaptation strategies. This study adopted a systematic literature review methodology to analyse the following: (i) characterization of IK, (ii) potential of IK for knowledge co-production, (iii) IK for climate change causes and impact identification, (iv) IK for formulating and implementing climate change interventions, and (v) documentation and conservation of IK as a resource for climate change adaptation. Results show that there is no consensus on the definition of IK. However, certain identical elements in the available definitions are relevant for contextualization. IK has been useful in the formulation of different climate change adaptation strategies: management practices, early warning, and risk and disaster management. IK has the potential for knowledge co-production relevant for developing robust adaptation measures. Weather and climate services remain a critical area where IK and scientific knowledge (SK) are integrated to enhance forecast reliability and acceptability for local communities. IK is disappearing because of modernization and rural-urban migration, changing landscape and shifting religious beliefs. We suggest the need for more research into the complexity of the IK, proper documentation and storage of IK, and developing effective approaches to integrate IK with SK such that it is well received among researchers and policymakers. While doing this, it is important to maintain the unique features that distinguish IK from other forms of knowledge

Taking Stock of Climate Change Induced Sea Level Rise across the West African Coast

The impact of climate induced sea level rise (SLR) is a major threat, likely to continue even if greenhouse gas concentrations were stabilized. SLR will not be geographically uniform. Developing countries are most impacted because of their low adaptive capacity. This study reviewed the most recent scientific evidence of the impact, vulnerability and adaptation of coastal areas in West Africa to climate induced SLR. The results show an increasing rate in SLR for the near and further future. Coastal communities in West Africa are vulnerable to erosion, flooding and inundation resulting in the loss of many coastal lands and ensuing socio-economic consequences. Therefore adaptation is a matter of urgency. Given that relatively little and unbalanced information exists on this subject for those areas, we call for the need to invest resources into studying and protecting coastal communities in West Africa against current and future impacts of climate change and SLR.</p

Techniques and skills of indigenous weather and seasonal climate forecast in Northern Ghana

There are strong calls to integrate scientific and indigenous forecasts to help farmers adapt to climate variability and change. Some studies used qualitative approaches to investigate indigenous people's techniques for forecasting weather and seasonal climate. In this study, we demonstrate how to quantitatively collect indigenous forecast and connect this to scientific forecasts. We identified and characterized the main indigenous ecological indicators (IEIs) local farmers in Northern Ghana use for forecasting. Mental model was constructed to establish the relationship between IEIs and their forecasts. Local farmers were trained to send their rainfall forecast with mobile apps and record observed rainfall with rain gauges. Results show that farmers forecast techniques are based on established cognitive relationship between IEIs and forecast events. Skill assessment shows that on the average both farmers and Ghana Meteorological Agency (GMet) were able to accurately forecast one out of every three daily rainfall events. Performance at the seasonal scale showed that unlike farmers, GMet was unable to predict rainfall cessation in all communities. We conclude that it is possible to determine the techniques and skills of indigenous forecasts in quantitative terms and that indigenous forecasts are not just intuitive but a skill developed over time and with practice.</p

Towards weather and climate services that integrate indigenous and scientific forecasts to improve forecast reliability and acceptability in Ghana

The livelihood of many farmers across the globe is affected by climate variability and change. Providing weather and seasonal climate information is expected to support farmers to make adaptive farming decisions. Yet, for many farmers, scientific forecast information provided remains unreliable for decision-making. Scholars have called for the need to integrate indigenous and scientific forecasts to improve forecast information at the local level. In Northern Ghana, scientific forecast information from meteorological agency is unacceptable to farmers, making them rely on indigenous forecasts for adaptive decisions. This study proposed an integrated probability forecasting (IPF) method that integrates indigenous and scientific forecasts into a single forecast. As a proof of concept, we tested the reliability of IPF using binary forecast verification method and evaluated its acceptability to farmers through internally consistent multiple-response questions. Results of the reliability test show that IPF performed on average better than indigenous and scientific forecasts at a daily timescale. At the seasonal timescale, IPF and indigenous forecast performed better than Scientific forecast, although in terms of probability IF showed better results overall. Majority of the farmers (93%) prefer the IPF method as this provides a reliable forecast, requires less time, and at the same time resolves the contradictions arising from forecast information from different sources. The results also show that farmers already integrate (complementary) scientific and indigenous forecasts to make farming decisions. However, their complementary approach does not resolve the issue of contradictory forecast information. From our proof of concept, we conclude that integrating indigenous and scientific forecasts can potentially increase forecast reliability and uptake

Hydro-climatic and land use/cover changes in Nasia catchment of the White Volta basin in Ghana

The Nasia catchment is the reservoir with significant surface water resources in Northern Ghana and home to numerous subsistence farmers engaged in rainfed and dry season irrigation farming. Yet, there is little understanding of the hydro-climatic and land use/cover conditions of this basin. This study investigated trends, relationships and changes in hydro-climatic variables and land use/cover in addition to implications of the observable changes in the Nasia catchment over a period of 50 years. Parameters used for the study were minimum (Tmin) and maximum temperature (Tmax), wind speed (WS), sunshine duration (S), rainfall (R), relative humidity (RH), discharge (D) and potential evapotranspiration (PET) data, 15 years of remotely sensed normalized difference vegetation index (NDVI) data and 30 years of land use/cover image data. Results show that Tmin, Tmax, WS and PET have increased significantly (p 0.05). A significant abrupt change in almost all hydro-climatic variables started in the 1980s, a period that coincides with the occurrence of drought events in the region, except WS in 2001, R in 1968 and D in 1975, respectively. Also, D showed a positive significant correlation with RH, R and PET, but an insignificant positive relationship with S. D also showed a negative insignificant correlation with Tmin, Tmax and WS. Areas covered with shrubland and settlement/bare lands have increased to the disadvantage of cropland, forest, grassland and water bodies. It was concluded that climate change impact is quite noticeable in the basin, indicating water scarcity and possibilities of droughts. The analysis performed herein is a vital foundation for further studies to simulate and predict the effect of climate change on the water resources, agriculture and livelihoods in the Nasia catchment

Increased seasonal rainfall in the twenty-first century over Ghana and its potential implications for agriculture productivity

The slightest change in rainfall could have a significant impact on rain-fed agriculture in countries like Ghana. This study evaluated for the first time the performance of the statistical downscaling model (SDSM-DC) at 2m spatial resolution in simulating rainfall in Ghana for the base period 1981–2010. It further analysed the projected changes in seasonal rainfall pattern across different agro-ecological zones for the twenty-first century under RCP 4.5 and 8.5 emission scenarios over Ghana. Ensemble mean of simulated rainfall data (2011–2099) generated by 43 GCMs in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used as base factors for local future climate scenarios generation. Performance analysis of SDSM-DC shows a Nash–Sutcliffe efficiency, percent bias and RMSE observations standard deviation ratio of 0.88, −19 and 0.34, respectively. Generally, seasonal rainfall amount is expected to increase between 10 and 40% in all the agro-ecological zones in Ghana by the end of the twenty-first century. Off-season rainfall in December–February shows more than 100% increase in the Guinea Savannah zone. Rainfall projected under RCP 4.5 was on average 2% higher than RCP 8.5 in all the seasons throughout the century. Based on these results, it is appropriate to suggest a high incidence of flooding across Ghana in the twenty-first century. This could have dire consequences on agriculture which contribute to a large proportion of Ghana’s GDP. Therefore, for sustainable food production and security in the twenty-first century, Ghana needs climate adaptation policies and programmes that encourage the design and implementation of early warning systems of meteorological hazards and the introduction of new crop varieties that are flood tolerant.</p

Verification of Seasonal Climate Forecast Towards Hydro-Climatic Information Needs of Rice Farmers in Northern Ghana

Farmers in sub-Saharan Africa face many difficulties when making farming decisions due to unexpected changes in weather and climate. Access to hydroclimatic information can potentially assist farmers to adapt. This study explores the extent to which seasonal climate forecasts can meet hydroclimatic information needs of rice farmers in northern Ghana. First, 62 rice farmers across 12 communities were interviewed about their information needs. Results showed that importance of hydroclimatic information depends on the frequency of use and farming type (rain-fed, irrigated, or both). Generally, farmers perceived rainfall distribution, dam water level, and temperature as very important information, followed by total rainfall amount and onset ranked as important. These findings informed our skills assessment of rainfall (Prcp), minimum temperature (Tmin), and maximum temperature (Tmax) from the European Centre for Medium-Range Weather Forecasts (ECMWF-S4) and at lead times of 0 to 2 months. Forecast bias, correlation, and skills for all variables vary with season and location but are generally unsystematic and relatively constant with forecast lead time. Making it possible to meet farmers’ needs at their most preferred lead time of 1 month before the farming season. ECMWF-S4 exhibited skill in Prcp, Tmin, and Tmax in northern Ghana except for a few grid cells in MAM for Prcp and SON for Tmin and Tmax. Tmin and Tmax forecasts were more skillful than Prcp. We conclude that the participatory coproduction approach used in this study provides better insight for understanding demand-driven climate information services and that the ECMWF-S4 seasonal forecast system has the potential to provide actionable hydroclimatic information that may support farmers’ decisions

Forecast probability, lead time and farmer decision-making in rice farming systems in Northern Ghana

Rice farmers in Northern Ghana are susceptible to climate variability and change with its effects in the form of drought, water scarcity, erratic rainfall and high temperatures. In response, farmers resort to weather and seasonal forecast to manage uncertainties in decision-making. However, there is limited empirical research on how forecast lead time and probabilities influence farmer decision-making. In this study, we posed the overall question: how do rice farmers respond to forecast information with different probabilities and lead times? We purposively engaged 36 rice farmers (12 rainfed, 12 irrigated and 12 practising both) in Visually Facilitated Scenario Mapping Workshops (VFSMW) to explore how probabilities and lead times inform their decision-making. Results of the VFSMW showed rainfed rice farmers are most sensitive to forecast probabilities because of their over-reliance on rainfall. Also, an increase in forecast probability does not necessarily mean farmers will act. The decision to act based on forecast probability is dependent on the stage of the farming cycle. Also, seasonal forecast information provided at a 1 month lead time significantly informed farmer decision-making compared to a lead time of 2 or 3 months. Also, weather forecast provided at a lead time of 1 week is more useful for decision-making than at a 3 day or 1 day lead time. We conclude that communicating forecast information with their probabilities and at an appropriate lead time has the potential to help farmers manage risks and improve decision-making. We propose that climate services in Northern Ghana should aim at communicating weather and seasonal climate forecast information at 1 week and 1 month lead times respectively. Farmers should also adapt their decisions to the timing and probabilities of the forecast provided.</p