Meteorological Services Department Research Articles

Incorporating indigenous knowledge systems-based climate services in anticipatory action in Zimbabwe: an ex-ante assessment

IntroductionThe success of anticipatory action (AA) in climate change related disaster risk reduction depends largely on the ability to accurately predict adverse weather events and to subsequently take appropriate and timely action. The current seasonal climate forecasts obtained through national and global forecasting centers such as the Zimbabwe Meteorological Services Department (MSD) and the European Center for Medium-Range Weather Forecasts (ECMWF) have been found to have several limitations including limited skill in intra-seasonal variability which is vital in most processes, lack of accessibility, difficult interpretability and applicability to local communities. As a result, calls for the integration of Indigenous Knowledge Systems (IKS)-based climate services in seasonal climate forecasting to bolster the efficacy and accuracy of forecasts are increasing.MethodologyThe study employed a mixed methods approach combining a survey of 200 household heads, document reviews and key informant interviews with IKS specialists, AA community of practice members and disaster risk reduction specialists.ResultsThis article presents the findings of a study carried out in four semi-arid districts of Zimbabwe (Mbire, Matobo, Binga, and Mudzi) to assess the feasibility of integrating IKS into the drought AA mechanism at national, district, and ward level. We find that 82% of the surveyed households used indigenous knowledge systems for seasonal climate forecasting and extreme weather forecasting combined with scientific forecasts. Respondents demonstrated preference for triangulated forecasting to increase reliability. Both the meteorological approaches to seasonal climate forecasting and the IKS based forecasting had different strengths and weaknesses.DiscussionBased on the found gaps in current seasonal forecasting techniques, local applicability, and limited quantitative analysis in IKS, this study provides a guideline on how scientific and IKS forecasting can be triangulated for leveraging forecasting information in Zimbabwe. The use of IKS may be of utmost relevance to agencies and entities seeking the achievement of drought risk reduction through AA programmes.

Effect of Rainfall and Temperature Variability on Green Gram Yield in Tharaka South Sub County, Tharaka Nithi County, Kenya

Globally, green gram is a significant legume particularly in Arid and Semiarid Lands (ASALs), as a source of food, income, and soil enhancement. Despite this importance, green gram yield in Tharaka South Sub County is still too low at 560 kg/ha far below the crop’s estimated national potential of 1500 kg/ha and compares unfavorably with the global and national average of 730 kg/ha and 670 kg/ha, respectively. Green gram production is primarily rain-fed and variability in rainfall and temperature affects the ideal conditions favourable for the crop growth. This study aimed at quantifying the effect of rainfall and temperature variability, separately and jointly on green gram yield in Tharaka South Sub County, Tharaka Nithi County, Kenya for the period 2002-2021. Secondary data on seasonal rainfall, temperature, and green gram yield was collected from the Meteorological Services and County Department of Agriculture. Data was analysed using qualitative and quantitative methods by use of coefficient of determination, Analysis of Variance (ANOVA), correlation, and regression analysis. The study found that rainfall variability explained 30.4% of the variables affecting green gram yield. The findings of the model showed that a 1% increase in rainfall in March-April- May (MAM) season increased yield of green gram by 49.3% but no effect was observed in OND (October-November-December) season. Temperature variability explained 28.5% of the variables affecting green gram yield. Further, the model findings revealed that a 1% increase in temperature in OND season decreased yield of green gram by 48.5% and no effect was observed in MAM season. A combination of rainfall and temperature variability explained 34.2% of the variables affecting green gram yield. The model coefficients showed that a 1% increase in rainfall and temperature during the OND season increased yield of green gram by 16.2%. In addition, it was noted that a 1% rise in temperature and rainfall during MAM season reduced the output of green gram by 13.2%. The study concluded that rainfall and temperature had an effect on green gram yield and recommended that green gram farmers need to adapt to the changing climate to lessen the effects of climate change and for sustainable green gram production.

Spatiotemporal variation of rainfall and its implications on water resources management: The case of Manyame River catchment in Zimbabwe

AbstractRainfall is an important hydrometeorological variable that affects river flow regimes and the amount of water flowing into surface water bodies and underground aquifers. Changing rainfall patterns and magnitudes contribute to extreme events including floods, droughts, and landslides. Thus, understanding of rainfall distribution is vital to sound water resources planning and allocation to users. Owing to the shortage of evenly distributed of rainfall stations in the arid and semiarid catchments, satellite rainfall products are regarded as reliable alternatives. This study therefore analyzes the long‐term spatiotemporal variation of rainfall in Manyame River catchment in Zimbabwe. Monthly rainfall data spanning from 1982 to 2019 were retrieved from the Climate Hazards Group Infra‐Red Precipitation with Station (CHIRPS). In situ rainfall data obtained from the country's two Meteorological Services Department were used to determine the accuracy of satellite data. Rainfall trends were tested using the Mann–Kendall trend test. The results showed goodness of fit between in situ and remotely sensed rainfall data. There is no significant increasing and decreasing trends in quarterly, monthly, and wet season rainfall. Statistically significant decreasing trends were observed in the central parts of the catchment during the dry season. The changing rainfall trends highlight the need for integrated and adaptive water resource management strategies to avoid adverse effects of floods and droughts in the catchment.

Challenges and Opportunities in Communicating Weather and Climate Information to Rural Farming Communities in Central Zimbabwe

Abstract Sustainability of rain-fed agriculture in semiarid regions is being threatened by climate variability and change. Weather and climate information (WCI) can be used to reduce the effects of this threat on agricultural production. WCI may be available, but is it readily accessible and communicated/disseminated efficiently to intended end users? Are stakeholders able to interpret the information to correctly inform decision-making? To answer these questions, in view of intermediate stakeholders (service providers to farmers), a study was carried out in two districts of the Midlands Province of Zimbabwe to identify the type and sources of WCI received by these stakeholders as well as constraints and opportunities to access, interpretation, and use of WCI. The study sample was drawn from the Midlands Provincial Drought Relief Committee, a link between the sources of WCI and the smallholder farmers. A questionnaire pretested for clarity and checked for internal consistency of themes using the standardized Cronbach’s alpha was used to collect data. Descriptive statistics were generated using SPSS (version 20.0). Findings were that WCI was sometimes not readily available or was received late. Approximately 36% of the intermediate stakeholders (service providers) passed on WCI to farmers in its original form, from the main source the Meteorological Services Department. It was also unfortunate to discover that 36% of the respondents had challenges interpreting WCI. Impediments to the use of WCI by farmers included scientific information not aligning with indigenous information, which is better understood by farmers, and lack of trust in WCI. It is imperative to improve access to WCI and to train stakeholders on interpretation and dissemination of WCI. Significance Statement Weather and climate information—if accurate, accessible, provided in a timely manner, and well understood—can be helpful in the farm decision-making process. Its usefulness is becoming more important with increased climatic variability and change. This paper highlights the challenges and opportunities for service providers in communicating and disseminating WCI. We believe that findings from the study will give direction to efficient utilization of the information by the various end users, for which smallholder farmers are the majority in most developing countries.

Weather Data Management Using Hadoop MapReduce in Zimbabwe

The Meteorological Services Department (MSD) in Zimbabwe is experiencing huge costs in transferring data of over Gigabytes from its different models of automatic weather stations into centralized database at Head Quarters (HQ) Belvedere in Harare. However, surveys indicate that emerging technologies of big data analytics such as Hadoop MapReduce can be extended into weather data management offering multiplicity of functions that includes: prediction, management of transmission of data and also managing the range of weather elements to monitor at anytime and anywhere. This study therefore sought to design and develop an experimental set-up to understand how Hadoop MapReduce can be used to manage data files from various weather stations simulated as Application Programming Interface (APIs). The developed system was conducted entirely in a cloud environment and the results suggest that Hadoop MapReduce function is an appropriate big data tool to manage weather data and offers better options especially for cash strapped organizations such as Meteorological Services Department (MSD). Adoption of MapReduce is economic and elastic to accord changing weather data management requirements. The research used a small dataset of 100 records which might offer comprehensive model for use for practical purposes. Further studies with more realistic huge datasets might be pertinent.

Seasonal dynamics of agro-meteorological drought in Mberengwa and Zvishavane districts between 2017 and 2020, Zimbabwe

Drought severity is increasing in Southern Africa which is affecting rain-fed agriculture, the main source of livelihood in most countries in this region. The study assessed the seasonal spatio-temporal dynamics of agro-meteorological drought between 2017 and 2020 in Mberengwa and Zvishavane districts. An empirical research design supported by quantitative geographical information system techniques for data analysis was adopted in this study. Remote sensing data and precipitation records from the Meteorological Services Department were main data sources in this study. Microsoft excel 2013, SPI generator and ArcMap 10.5 software were used for data analysis in this study. Results showed that both Mberengwa and Zvishavane districts experienced an increasing trend in spatial coverage of drought from 2017 to 2019 before a slight decline in 2020. From 2017, drought severity increased in terms of spatial coverage with this spatial distribution increasing to almost over ¾ of the wards in both Mberengwa and Zvishavane districts between 2018 and 2020. Since 2017, on a ward level basis, both districts have been experiencing late onset and early cessation of the rain season as shown by increasingly dry October, November and March, months which determine the length of crop growing season in these two districts. Results indicated that the month of March was drier in Mberengwa whilst the month of December was drier in Zvishavane, an indication of more mid-season dry spells in Zvishavane and earlier rainfall cessation in Mberengwa. Drought is worsening in both Mberengwa and Zvishavane districts; hence, long-term drought resilience interventions are required to improve drought resilience of communities in these areas. The study recommends the Government of Zimbabwe and other stakeholders of drought resilience building like CARE International, World Vision among others to prioritise launching of resilience building initiatives in most vulnerable areas whilst guided by fine empirical information on spatial distribution of drought.

English

In this paper, the hypothesis that rainfall variability has an impact on wetland loss is tested. There is limited research in Zimbabwe that recognises the influence of rainfall variability on wetland loss. The purpose of this research is to determine the influence of rainfall variability on wetland size over time. Topographical maps, for the period 1972 to 2008, provided data on wetland locations and their changes in size with time. Rainfall data for Masvingo province for the 1980 to 2015 period was obtained from the Meteorological Services Department (MSD) of Zimbabwe. Statistical analysis shows that there is no relationship between rainfall variability and wetland loss. It can be concluded that there is no relationship between rainfall variability and wetland loss therefore. The research findings show that the rates of change in wetland size differ from one wetland to another. The implications on wetland management are that interventions should largely address human causal factors of wetland loss than rainfall variability. Therefore, it is vital to devise a wetland rehabilitation plan that enables management of water from the rivers and wetlands that the communities depend on.   Key words: Climate change, rainfall variability, standard precipitation index (SPI), wetland rehabilitation, Zimbabwe.

Women’s Vulnerability to Climate Change: Gender-skewed Implications on Agro-based Livelihoods in Rural Zvishavane, Zimbabwe

Climate change presents a considerable threat to human security, with notable gender disproportions. Women’s vulnerability to climate change has implications on agro-based livelihoods, especially the rural populace. The primary purpose of this study was to assess women’s vulnerability to climate change and the gender-skewed implications on agro-based livelihoods in rural Zvishavane, Zimbabwe. A qualitative approach that used purposive sampling techniques was adopted. Data was collected through 20 in-depth interviews with 11 de jure and 9 de facto small-scale female-headed farmer households. Two focus group discussions with mixed de facto and de jure small-scale female-headed farmer households were also conducted. Five key informant interviews were held with departmental heads of the Ministry of Women’s Affairs, Gender and Community Development; the Agriculture Technical Extension Service Department; the Livestock Production Department; the Runde Rural District Council and the Meteorological Services Department. Gendered effects were noted in terms of increased roles and responsibilities for women. Observations showed that there was an increase in distances travelled by women to fetch water owing to a depleted water table. Climate-induced migration of men due to depleted livelihoods in rural areas has also increased roles and responsibilities for women. The traditional male responsibilities assumed by women included cattle herding and ox-driven ploughing. This study concluded that adaptation strategies towards vulnerability to climate change have to be gender-sensitive and area-specific. This study also recommended that response programmes and policies meant to curb existing gendered vulnerabilities should be informed by evidence because climate-change effects are unique for different geographical areas. Moreover, adaptation activities should be mainstreamed in community processes so as to reduce the burden on women and increase sustainability opportunities.

The 03 April 2017 Botswana M6.5 earthquake: Preliminary results

An earthquake of magnitude Mw 6.5 occurred on the evening of 3 April 2017 in Central Botswana, southern Africa. The event was well recorded by the regional seismic networks. The location by the Council for Geoscience (CGS) placed it near the Central Kgalagadi Game Reserve. Its effects were felt widely in southern Africa and were pronounced for residents of Gauteng and the North West Province in South Africa. In response to this event, the CGS, together with the Botswana Geoscience Institute (BGI), embarked on two scientific projects. The first project involved a macroseismic survey to study the extent and nature of the effects of the event in southern Africa. This involved CGS and BGI scientists soliciting information from members of the public through questionnaire surveys. More information was collected through questionnaires submitted online by the public. In total, 181 questionnaires were obtained through interviews and 151 online from South Africa, Zimbabwe and Namibia through collaboration between the CGS, the Meteorological Services Department of Zimbabwe and the Geological Survey of Namibia. All collected data were analysed to produce 79 intensity data points (IDPs) located all over the region, with maximum intensity values of VI (according to the Modified Mercalli Intensity scale) observed near the epicentre. This is quite a low value of maximum intensity for such a large event, but was expected given that the epicentral region is in a national park which is sparsely populated. The second scientific project involved the rapid installation of a temporary network of six seismograph stations in and around the location of the main event with the purpose of detecting and recording its aftershocks over a period of three months. Data recorded in the first month of April 2017 were collected and delivered to both the CGS and BGI for processing. More than 500 aftershock events of magnitude ML ≥ 0.8 were recorded and analysed for this period. All the events were located at the eastern edge of the Central Kgalagadi Park near the location of the main event in two clear clusters. The observed clusters imply that a segmented fault is the source of these earthquakes and is oriented in a NW-SE direction, similar to the direction inferred from the fault plane solution of the main event.

A Study of Value Addition by Information Systems to a Service Providing Business at the Meteorological Services Department in Zimbabwe

Many companies are using only a portion of what is needed in terms of Information Technologies (IT) and this has caused the researcher to study how best MSD can effectively utilize Management Information Systems (MIS). The objective that directed the study was to investigate value addition by information systems to a service providing business with specific reference to the weather station in Zimbabwe (Meteorological Services Department). Knowing the value added by MIS to one’s business and working environment is key to cope with the ever increasing challenges such as the volume of information resources, nature and quality of information, user needs and expectations, information and communication technology competencies and infrastructure, inflated cost of information resources and staffing needs. The researcher studied how information systems add value to the daily business of Meteorological Services Department (MSD) in the following areas of the organisation processes: products, quality, management, problem solving and decision of the organisation. The study on value addition by management information systems will assist in the improvement of the MSD in Zimbabwe. The study used a multistage sampling process for drawing sample from the target population. Secondary and primary data collection methods were used for data collection purposes. The source for primary data was questionnaire. Five different types of Management Information Systems that add value to the MSD were identified; Management Information Systems, Office Automation Systems, Executive Support Systems, Expert Systems, Decision Support System and Transaction Processing System. From the findings it was concluded that management information systems add value by allowing valid decisions which provide accurate and up-to-date information and performing analytic functions. This study demonstrated the importance of information systems in an organisation and outlined the fundamental roles of Information Systems (IS) which are to support business processes and operation, support decision making by employees and managers and support strategies for competitive advantage.

Rainfall Seasons Analysis as a Guiding Tool to Small Holder Farmers in The Face of Climate Change in Midlands in Zimbabwe

A rigorous analysis of trends in rainfall season of an area over a lengthy period of time can be effectively used as a tool to guide small holder farmers in their activities. Climate change adaptation is important to ensure sustainability and survival in rainfed crop farming. In this study two districts (Chirumhanzu and Zvishavane) in the Midlands Province of Zimbabwe were selected and rainfall data for the areas was provided by Zimbabwe Meteorological Services Department. Rainfall characteristics that include onset times, cessation times, length of seasons, total amount of rainfall, number of rainy days, dry spell and risk of water logging were analysed to provide farmers with an indicative picture of possibilities in their respective areas in a bid to reduce risks of crop failure due to uncertainties brought about by climate change and variability. Time series analysis method together with risk analysis were the statistical methods employed to understand better the risk and measures that can be taken by farmers. For Chirumhanzu it was concluded there is a 41% risk of replanting if farmers plant with the first rains received. However, over the period this risk seems to be decreasing. Farmers are encouraged to stagger the planting to minimise risk. Risk analysis showed that for Zvishavane the mean number of rainy days for Zvishavane is 34 with a possibility of 45 days in good seasons and 23 days in poor seasons The tool guides meant for farmers require proper packaging and systematic channels to promote buy-in by the end users of the information.

Indigenous ways of disaster preparedness in Zimbabwe: Lessons from living Heritage

This paper argues that today’s communities have suffered considerably due to severe droughts, floods and storms occurring in what can best be described as coming out of season. These have led to loss of lives, livestock and property. It asserts that some of these disasters are avoidable if communities learn from the intangible cultural heritage that guided the pre-colonials and those of the pre independence period when most Blacks still respected and appreciated their beliefs and value systems. It notes that while it is important to rely on the Meteorological Services Department for weather forecasting, events over the past few years have shown this Department’s forecasts at times as unreliable. The paper therefore argues that Zimbabweans, especially those involved in crop and livestock production should also observe natural phenomena such as flora and fauna as was done by the people of old who got early warning signs from Mother Nature herself.

A Study of Value Addition by Information Systems to a Service Providing Business at the Meteorological Services Department in Zimbabwe

Many companies are using only a portion of what is needed in terms of Information Technologies (IT) and this has caused the researcher to study how best MSD can effectively utilize Management Information Systems (MIS). The objective that directed the study was to investigate value addition by information systems to a service providing business with specific reference to the weather station in Zimbabwe (Meteorological Services Department). Knowing the value added by MIS to one’s business and working environment is key to cope with the ever increasing challenges such as the volume of information resources, nature and quality of information, user needs and expectations, information and communication technology competencies and infrastructure, inflated cost of information resources and staffing needs. The researcher studied how information systems add value to the daily business of Meteorological Services Department (MSD) in the following areas of the organisation processes: products, quality, management, problem solving and decision of the organisation. The study on value addition by management information systems will assist in the improvement of the MSD in Zimbabwe.
 The study used a multistage sampling process for drawing sample from the target population. Secondary and primary data collection methods were used for data collection purposes. The source for primary data was questionnaire. Five different types of Management Information Systems that add value to the MSD were identified; Management Information Systems, Office Automation Systems, Executive Support Systems, Expert Systems, Decision Support System and Transaction Processing System. From the findings it was concluded that management information systems add value by allowing valid decisions which provide accurate and up-to-date information and performing analytic functions.
 This study demonstrated the importance of information systems in an organisation and outlined the fundamental roles of Information Systems (IS) which are to support business processes and operation, support decision making by employees and managers and support strategies for competitive advantage.
 
 

Investigating the implications of meteorological indicators of seasonal rainfall performance on maize yield in a rain-fed agricultural system: case study of Mt. Darwin District in Zimbabwe

The study focuses on the impacts of climate variability and change on maize yield in Mt. Darwin District. The rainfall and temperature data for the period under study that is from 1992 to 2012 were obtained from Meteorological Services Department of Zimbabwe at daily resolution while crop yield data were obtained from Department of Agricultural, Technical and Extension Services (AGRITEX) and Zimbabwe Statistics Agency (ZIMSTAT) at seasonal/yearly resolution. In order to capture full rainfall seasons, a year was set to begin on 1 June and end on 31 July the next year. Yearly yield, temperature and rainfall data were used to compute time series analysis of rainfall, temperature and yield. The relationship between temperature, rainfall, quality of season (start, cessation, dry days, wet days and length) and yield was also investigated. The study also investigated the link between meteorological normal and maize yield. The study revealed that temperature is rising while rainfall is decreasing with time hence increasing risk of low maize yield in Mt. Darwin. Correlation between maize yield was higher using a non-linear (R2 = 0.630) than a linear regression model (R2 = 0.173). There was a very high correlation between maize yield and number of dry days (R = −0.905) as well as between maize yield and length of season (R = 0.777). We also observed a strong correlation between percentage normal rainfall and percentage normal maize yield (R2 = 0.753). This was also agreed between rainfall tessiles and maize yield tessiles as 50 % of the seasons had normal and above normal rainfall coinciding with normal and above normal maize yield. Of the 21 seasons considered, only one season had above normal rainfall while maize yield was below normal. The study concluded that there is a strong association between meteorological normal and maize yield in a rain-fed agricultural system. Climate information remains crucial to agricultural productivity hence the need to train farmers to access the information and use it for the benefit of their activities.

Crop Yield Sensitivity to Climatic Variability as the Basis for Creating Climate Resilient Agriculture

Climate change and variability are presenting challenges to the agricultural sector as well as agricultural sustainability in Zimbabwe. This paper was aimed at investigating the impacts of climate change and variability on maize, sorghum and groundnut production in the Buhera district of Zimbabwe. The paper specifically determined the climatic scenarios in Buhera and how crop production is sensitive to them. Temperature and rainfall data used were obtained from the Zimbabwe Meteorological Services Department. Crop yield data for maize, sorghum and groundnuts were obtained from the Department of Agriculture and Rural Extension Buhera District office. The Mann-Kendall Trend test was then used to determine if there were significant changes in the precipitation and temperature scenarios at Buhera weather station. Before performing the Mann-Kendall test, the time series data were first tested for auto-correlation. Finally the Spearman’s correlation coefficient was used to determine how precipitation and crop yields were related and the strength of their relationships. Mann-Kendall trend tests reviewed that only mean minimum temperatures show significant trends over time (p = 0.003, α = 0.05). Correlation analysis showed that only maize showed a significant correlation coefficient with the amount of rainfall (r = 0.79, r2 = 0.625 and p = 0.001, α = 0.05). The research showed that groundnuts were the least sensitive to climatic variations followed by sorghum; hence their production offers the best climatic resilience and must be encouraged to local subsistence farmers.

Assessment of the Reliability of World Weather Online Forecasts for Kadoma Community

In recent times weather related catastrophes have become a commonplace. Many weather forecasters have taken the lead in furnishing individuals, corporate and governments with information. Consequently, little has been done to verify the accuracy of the weather reports and forecasts. This study therefore, compared and assessed the accuracy of forecasts given by World Weather Online with those of Meteorological Services Department for the case of Kadoma in Zimbabwe. The study also investigated the extent to which people benefit from using weather information as well as the challenges faced in accessing this information. Both quantitative and qualitative methods were used to gather data. Internet data mining, questionnaire and interview were used. Temperature and rainfall data were statistically analyzed while benefits and challenges were qualitatively assessed. The WWO forecasts for minimum temperatures had an accuracy of 96% while those for maximum temperature had an accuracy of 91.4% (percentage error of 8.6%). Rainfall forecasts showed a percentage correct of 60% and 56.7% for MSD and 70% and 66.7% for WWO for one day and twoday lead times, respectively. The researcher therefore recommended that the MSD defragment its regions into smaller areas to increase accuracy of forecasts. Awareness campaigns by all stakeholders were also seen as necessary in fostering understanding of weather reports and forecasts by the all people.

Validation of local knowledge drought forecasting systems in the Limpopo River Basin in Southern Africa

Purpose – This research paper is informed by a study to assess performance of local knowledge drought forecasts (LKDFs) in the Mzingwane catchment which is located in the Limpopo River Basin in Zimbabwe. The purpose of this paper is to validate local traditional knowledge (LTK) indicators being applied in Mzingwane catchment and verify their accuracy and reliability in drought forecasting and early warning. Design/methodology/approach – LTK forecast data for 2012/2013 season were collected through structured questionnaires administered to 40 selected household heads and focus group discussions. Observations and key informant interviews with chiefs and the elderly (>55 years) were also used to collect additional LTK forecast data. Meteorological data on seasonal rainfall were collected from the meteorological Services Department of Zimbabwe (MSD). Two sets of comparisons were conducted namely the hind-cast comparison where the LKDF system results were evaluated against what the season turned out to be and forecast comparison where local LKDF system results were compared with downscaled meteorological forecasts. Findings – The results showed that the majority of the LTK indicators used were accurate in forecasting weather and drought conditions when compared to the observed data of what the season turned out to be. LTK forecasts were found to be more accurate than meteorological forecast at local scale. This study has shown that the reliability of LTKs is high as demonstrated by the fact that the predicted event occurs. Research limitations/implications – Further validation be carried out for a number of seasons, in order to standardise the LTK indicators per geographical area. Originality/value – The research creates platform for adoption of LTKs into formal forecasting systems. The research is useful to both meteorological researchers and resource constrained communities in Mzingwane catchment.

Indigenous Weather Forecasting Systems: A Case Study of the Abiotic Weather Forecasting Indicators for Wards 12 and 13 in Mberengwa District Zimbabwe

Residents of wards 12 and 13 in Mberengwa depend on agriculture as a source of livelihood. They have since developed their own indigenous weather forecasting systems which they have been using in conjunction with meteorological weather forecasts in the planning and execution of their agricultural activities. These systems are used singularly or are complimented with the conventional meteorological forecast from the Meteorological Services Department. The main objective of this research was to identify the abiotic weather forecasting indicators as well as to acquire information on how they are used. Questionnaires, focus group discussions and interviews with key informants were used to collect the data. Key informants were those whose time of residence in the wards was more than 50 years. Investigations revealed that the residents rely mostly on environmental indicators for planning agricultural activities. Results showed that of the two categories of indigenous abiotic weather forecasting indicators, weather forecasts derived from weather indicators were the mostly used followed by forecasts derived from celestial indicators. There were however differences on the interpretations of the behavioural signs or indicators which were used in the production of the forecasts from these abiotic factors.The study recommends that further research should be carried out on the application and on the statistical evaluation of the precision of the indigenous forecasts. Attempts should also be made to document the abiotic weather indicators and the behavioural signs from which these forecasts are derived. The establishment of an effective indigenous weather forecasting system as part of a decision support system would go a long way in improving food security for this area.

Uptake Of Seasonal Rainfall Forecasts In Zimbabwe.

Agriculture is mainly rain-fed in Zimbabwe and the provision of accurate rainfall information by the Meteorological Services Department is crucial to agricultural productivity in the country. The seasonal rainfall forecasts are used as an early warning tool produced with a lead time of at least 3 months such that it is important for the users to know their accuracy. Rainfall data and seasonal forecasts from the Meteorological Services Department were used to create 3 by 3 contingency tables for each homogeneous rainfall region which were then used to compute statistics which indicate the accuracy of the forecasts in the country. The study observed that national seasonal climate forecasts are finer and more accurate than regional (SARCOF) ones. In Zimbabwe, the forecasts were found to be 55 and 60% accurate for the rainfall region 3, 64 and 90% for region 2 and 73 and 80% for region 1 for the JFM and OND seasons, respectively. In all the regions the accuracy was found to be higher during the OND season than the JFM season. Limited uptake by farmers (Manatsa et al., 2012) was therefore, attributed to limited access and knowledge of the science (Patt, 2001) than to the accuracy of the forecasts. The study encourages the climate experts to reach out to the farmers to train them as well as to train all partners involved in distributing the forecasts to the users such as the Agricultural extension officers. The study also developed a new forecast interpretation tool which is handy for any user of climate data. Further research leading to forecasting of extremes such as dry spells ahead of a season and inclusion of other indicators such as the Indian Ocean Dipole could improve the accuracy of seasonal forecasts. The binary system which indicates whether there will be drought or not should be adopted into the national climate forecasting system replacing the current one which uses probabilities and three categories of possible outcomes.

Climate Change and Variability in Southeast Zimbabwe: Scenarios and Societal Opportunities

A lot of researches have been done on the negative impacts and challenges caused by extreme weather conditions due to climate change and variability. Not many researches have been focused on the positive side in form of opportunities presented due to climate change. The study aimed to show the climate change scenarios and explore possible opportunities that could be derived from such scenarios in the southeastern region of Zimbabwe. The research used climate data records from three Zimbabwe Meteorological Services Department run weather stations in the region. The time series data were analyzed to show trends of rainfall and temperature over time. A questionnaire survey was also carried out to enquire from the farmers if they perceived climate change to have any opportunities. The rainfall trend analysis showed that rainfall amounts have declined at two of the three stations used. Rainfall total was also shown to be variable from year to year at all the stations. Ambient temperatures at all the stations were shown to have increased for both winter and summer. Opportunities that could be derived from climate change in the region were identified as the hydrological, agricultural and industrial. The research concludes that taking advantages of opportunities offered by climate change and variability provides the quickest way of embracing climate change adaptation.