Climate change and variability greatly affect many human activities particularly agriculture. Various adaptation strategies to climate variability have been used over the years with little attention to the vital role played by seasonal climate forecast (SCF) in providing information on the expected climatic conditions to adapt to. Despite dissemination of SCF information to varied users by Kenya Meteorological services (KMS) before rain seasons, it still remains unclear whether the information is used in agricultural decision-making among smallholder farmers in semi-arid areas.This study sought to contribute towards improved use of SCF in response to climate variability by assessing perception, use and constraints to use of seasonal climate forecast in agricultural decision-making by smallholder farmers in semi-arid Voi sub-County, Kenya. SCF for October-November-December (OND) 2015 was obtained from KMSand compared to observed climatic conditions for the season. Climatic data of the study area for the period 1985- 2014 was obtained from Voi Meteorological station and used to calculate the OND mean rainfall. Questionnaires were administered to 246 household heads randomly selected from two Locations and interview schedule administered to five purposively selected Key Informants. Primary data collected were analyzed using descriptive statistics, one sample Chi-square and Pearson Correlation tests. The results showed that majority of smallholder farmers’ perception of SCF information was somewhat good with a significance of p=0.000 in their perception.The study also established that 41.7% of smallholder farmers used OND 2015 SCF in agricultural decision- making. Key constraints to use of seasonal climate forecast were lack of trust in the forecasts and inadequate extension support. The household socio-economic characteristics that were found to have a significant influence on use of SCF were education level and reason for farming. The study concludes that the perception of OND 2015 SCF by smallholder farmers was a limitation to use of the information in agricultural decision-making. The study recommends enhancement of awareness of SCF information, provision of short-term forecasts and training on use of forecasted seasonal climate information in agricultural decision-making.

Background to the Study
Climate plays an essential role in many human activities and in particular agriculture (Ogen, 2007). Despite improvements in agricultural technologies such as plant breeding, soil fertility and weed science, climate still remains a primary determinant of agricultural productivity due to the biophysical relationship between crops and the dynamic atmospheric environment (Meza &Wilks, 2008). The agricultural sector remains a key contributor to the socio-economic development of many countries, especially in the developing regions largely due to its multi-functional nature as the main source of food and employment to most of the people especially among rural population (Calzadilla, Zhu, Rehdanz, Tol&Ringler, 2009; Ogen, 2007).

Climate change and variability has been witnessed world over with its impact largely felt in the agricultural sector due to its sensitivity to as well as its strong dependence on climate (Coelho & Costa, 2010; Mendelsohn, 2009). Climate change and variability affects farming as a result of changes in rainfall amounts and distribution, extreme low or high temperatures and occurrence of flooding, drought and severe wind storms (Oyekale, 2015). Seasonal climate variation is caused by the interaction between the atmosphere and the ocean with some modifications by other physical phenomena such as relief and altitude. Globally, the teleconnections of ocean-atmosphere leads to occurrence of major synoptic systems such as El- Nino South Oscillation (ENSO), Northern Atlantic Oscillation (NAO) and Antarctica Oscillation (AO) which bring about climate variability (Hayman, Whitbread &Gobbett, 2010). Climate change and variability became an issue of international concern after it was given a closer attention at the United Nations Conference on Environment and Development (UNCED) summit in 1992 where causes and mitigation measures were addressed (Kpanodou, Adegbola&Tovignan, 2012). Climate variability, which is the manifestation of changing climatic conditions from one place to another, from year to year or within the same year, is mainly attributed to natural causes (IPCC, 2014).

Climate variability brings about changes in the seasonal climate characteristics especially onset, amount and cessation of rainfall which have a great impact on agriculture. In Europe, for example, climate variability is responsible for the shift in the occurrence times of hail, frost, snow and drought which adversely affect agriculture (Gimenez&Lanfranco, 2012). In sub- Saharan Africa, climate change and variability has greatly affected food production due to prolonged droughts which have become severe in recent years (Funk et al., 2008). Climate change and variability in Eastern and the Horn of Africa has also been manifested in the frequent occurrence of droughts and shift in growing seasons. For instance in Kenya, rain seasons have become unpredictable and unreliable with many regions such as the semi-arid South-eastern parts of the country experiencing long dry spells (Macharia, Thuranira, Ng’ang’a&Wakori, 2012). Today, more rain occur during OND seasons in semi-arid regions as compared to MAM seasons and therefore essence of “short” and “long” rains has lost its meaning in these regions. This is because the traditional short rains (OND) have for long been the most reliable for agricultural activities as compared to MAM seasons in Eastern Kenya (Hansen &Indeje, 2004).

Mitigation and adaptation are the two main approaches used in dealing with climate change and variability. Mitigation is a global long-term approach to address the problem of greenhouse gases emission while adaptation is a short-term local measure of coping with the climate situation which involves avoiding its adverse effects or taking advantage of positive changes (Bawakyillenuo, Yoro &Teye, 2014). Adaptation to climate change has entailed measures put in place to cope with the changing climatic conditions as well as taking advantages of opportunities created by such changes. In sub-Saharan Africa, adaptation takes the centre stage in dealing with climate change and variability since the region is more vulnerable due to its limited skills and financial resources as well as weak institutions concerned with climate change mitigation efforts (Bagamba, Bashaasha, Claesens&Antle, 2012). Nevertheless, some countries for example Ghana and Zimbabwe have experimented with adaptation efforts such as irrigation and growing of drought tolerant crops (Bawakyillenuoet al., 2014; Moyoet al., 2012). In Kenya, climate change and variability adaptation policies have been put in place by the National Climate Change Response Strategy (NCCRS),a national policy document that proposes a range of adaptation measures ranging from water and soil resource management to adaptation policy formulation and review (RoK, 2010a). In addition, the Kenya Climate Change Action Plan (KCCAP) gives specific and elaborate time-bound steps towards adaptation to climate change and variability (RoK, 2013a).

Causes of climate change and variability and its effects have been well understood with timing and degree of the change and variability now being a major concern (Crist, 2007). Large-scale predictions of climate world over through modelling and scenario building have been used with little certainty achieved (McGrail, 2013). In response to this, regional climate forecasting centres have been established in many parts of the world. In sub-Saharan Africa, the Southern African Regional Climate Outlook Forum (SARCOF) brings together producers and consumers of climate information from the entire Southern Africa Development Community (SADC) region to discuss, generate and disseminate seasonal climate forecast to many end-users in the region. The Intergovernmental Authority on Development (IGAD) Climate Prediction and Application Centre (ICPAC) also provide climate forecast information to the Horn of Africa countries.

In Kenya, the Kenya Meteorological services (KMS) issues seasonal climate forecasts about one month before onset of the rainfall seasons. Perception of these forecasts by farmers in most cases has been perceived as negative (Machariaet al., 2012). Despite this perception, seasonal climate forecasts have been used by farmers, especially the large-scale ones in making on-farm decisions (Klopper, Vogel &Landman, 2006). However, there are many constraints which may arise in the use of these forecasts in agricultural decision-making right from their generation to their application. Seasonal climate forecasts provide information on expected seasonal rainfall conditions in terms of its onset, amount and cessation which is vital in making on-farm decisions on adaptation strategies in semi-arid areas (Recha, Shisanya, Makokha&Kinuthia, 2008; Klopperet al., 2006). Voi sub-County is a semi-arid area where smallholder farmers mainly rely on OND rainfall season for crop farming (RoK, 2013b). In light of this, it is important to establish how smallholder farmers perceive these forecasts and whether they use them in agricultural decision-making at farm level.

Statement of the Problem
Use of seasonal climate forecast is an adaptation strategy to climate variability, especially in semi-arid lands. In Kenya, the Kenya Meteorological services (KMS) disseminates seasonal climate forecast before onset of March-April-May (MAM) and October-November-December (OND) rainfall seasons. Despite this, it remains unclear whether this has translated into agricultural risk reduction especially among smallholder farmers in low agricultural potential semi-arid areas such as Voi sub-County. The study, therefore, sought to assess the extent of perception of SCF and its effectiveness in agricultural decision-making process as adaption strategy to climate variability among smallholder farmers in semi-arid Voi sub-County.

The study was guided by the following objectives:

Broad Objective
The broad objective of this study was to contribute towards improved use of seasonal climate forecast among smallholder farmers in Voi sub-County with a view of enhancing agricultural productivity in light of climate variability especially in semi-arid areas.

Specific Objectives
i. To evaluate the perception of the quality of seasonal climate forecasts from Kenya Meteorological services among smallholder farmers in Voi sub-County.

ii. To establish smallholder farmers’ use of seasonal climate forecasts in agricultural decision-making in Voi sub-County.

iii. To determine constraints to use of seasonal climate forecasts in agricultural decision- making among smallholder farmers in Voi sub-County.

Research Questions
i. How do smallholder farmers in Voi sub-County perceive the quality of seasonal climate forecasts from Kenya Meteorological services?

ii. How do smallholder farmers in Voi sub-County use seasonal climate forecasts from Kenya Meteorological services in agricultural decision-making?

iii. What constraints affect use of seasonal climate forecasts among smallholder farmers in agricultural decision-making in Voi sub-County?

Justification/Significance of the Study
One of the strategic objectives of National Climate Change Response Strategy (NCCRS) policy framework is to recommend measures aimed at minimizing climate change risks with downscaling of weather information suggested as an appropriate adaptation strategy in agriculture (RoK, 2010a). The study findings are, therefore, aimed at making a contribution to the suggested pathways in the NCCRS on improving adaptation to climate variability. The findings are to further suggest ways of improving dissemination of seasonal climate forecasts among smallholder farmers so as to enhance adaptation to climate variability. Finally, the findings also aim at providing knowledge to smallholder farmers on the importance of response strategies to seasonal climate forecasts.

Scope of the Study
The study focused on evaluation of perception of quality and use of seasonal climate forecasts in agricultural decision-making in Voi sub-County. The study was carried in Voi sub- County because it is found in semi arid Southeastern Kenya andwas limited to Mbololo and Sagalla Locations due to their proximity to Voi meteorological station - important for collecting reliable rainfall data. In addition, the two study sites are predominantly occupied by smallholder farmers.

The study also focused on rainfall as one of the elements of climate because of its significance in agricultural production in semi-arid areas. Seasonal climate forecasts may vary based on the tools and institutions involved in generation. Parameters of seasonal climate forecast for this study was limited to the forecast given by Kenya Meteorological services since it is the designated national authority in Kenya.Farmers’ perception, use and constraints to use of seasonal climate forecast were limited to the experience and KMS forecast of OND 2015 rainfall season. Although traditionally in Kenya MAM represents the long rains and OND the short rains, OND was used since it is the most reliable season for rain-fed agriculture in South East Kenya (Cooper et al., 2008; Hansen &Indeje, 2004).

The researcher encountered several challenges during data collection. One of the challenges was language barrier as the study was conducted in a rural setup where some respondents could only communicate in the local language -Taita. As a remedy, the researcher used field assistants on the basis of their knowledge of the local language. Another limitation was the expansiveness of the study area which made the researcher travel long distances by foot or on motorbike. This was due to sparsely distributed households and lack of access roads in some areas. Despite this challenge all sampled households were contacted and provided the necessary information.

The study relied on one meteorological station; Voi. This may not have taken care of the expansiveness and varied topographical characteristics of the study area. However, Voi meteorological station was used since it is the only synoptic station in the study area with reliable rainfall data. Likewise models of seasonal climate prediction are also based on regional scale (Dessai, Hulme, Lempert&Pilke, 2009).

The study assumed that KMS will have released seasonal climate forecast for OND 2015 rainfall season before the start of the season. It also assumed that the seasonal climate forecast information from KMS will be disseminated through various channels such as extension services, radio, television and internet and all respondents will have an opportunity of getting the information.The study further anticipated that the entire sampled households’ heads and Key Informants will be able to provide objective and reliable information.

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Item Type: Kenyan Topic  |  Size: 70 pages  |  Chapters: 1-5
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