Purpose: – The purpose of this paper is to identify, analyse and document local traditional indicators used in drought forecasting in the Mzingwane Catchment and to assess the possibility of integrating traditional rainfall forecasting, using the local traditional indicators, with meteorological forecasting methods.Design/methodology/approach: – Self-administered structured questionnaires were conducted on 101 respondents in four districts of the Mzingwane Catchment area, namely, Beitbridge, Mangwe, Esighodini and Mwenezi from February to August 2012. In addition, key informant interviews and focus group discussions were also used in data collection and the collected data were analysed for drought history and demographics; drought adaptation and the use of drought forecasting methods in the catchment using Statistical Package for Social Science.Findings: – The paper reveals the growing importance of precipitation forecasts among Mzingwane communities, particularly the amount, timing, duration and distribution of rainfall. Rainfall was cited as the major cause of drought by 98 per cent of the respondents in the catchment. Whilst meteorological rainfall forecasts are available through various channels, they are not readily accessible to rural communities. Furthermore, they are not very reliable at local level. The paper shows that communities in the Mzingwane Catchment still regard local traditional knowledge forecasting as their primary source of weather forecasts. The paper finds that plant phenology is widely used by the local communities in the four districts for drought forecasting. Early and significant flowering of Mopane trees (Colophospermum mopane) from September to December has been identified to be one of the signals of poor rainfall season in respect to quantity and distribution and subsequent drought. Late and less significant flowering of Umtopi trees (Boscia albitrunca) from September to December also signals a poor rainfall season.Originality/value: – The paper fulfils an identified need to study and document useful traditional drought indicators. Furthermore, the paper provides a platform for possible integration of traditional drought forecasting and meteorological forecasting and ensure sustainable rural livelihood development. The paper is useful to both meteorological researchers and resource-constrained communities in Mzingwane Catchment.

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.

The ability of smallholder farmers to utilise seasonal climate forecast (SCF) information in farm planning to reflect anticipated climate is a precursor to improved farm management. However, the integration of SCF by smallholder farmers into farm planning has been poor, partly because of the lack of forecast skill, lack of communication and inability to see the relevance of the SCFs for specific farming decisions. The relevance of seasonal climate forecasting in farming decisions can be enhanced through improved understanding of SCF from the smallholder farmers’ perspective. Studies that have been done of how smallholder farmers understand SCF and how the available SCFs influence smallholder farmers’ decisions are limited. Therefore, the objective of this paper was to review how smallholder farmers make decisions on farming practices based on SCFs and the challenges and opportunities thereof. The review shows that the majority of smallholder farmers in Africa make use of either scientific or indigenous knowledge climate forecasts and, in some cases, a combination of both. There are mixed results in the area of evaluating benefits of SCFs in decision-making and farm production. In some cases, the outcomes are positive, whereas in others they are difficult to quantify. Thus, the integration of SCFs into smallholder farmers’ decision-making is still a challenge. We recommend that significant work must be done to improve climate forecasts in terms of format, and spatial and temporal context in order for them to be more useful in influencing decision-making by smallholder farmers. Significance: At the farm level, making the right decisions at the right time is rendered even more difficult in light of the increasing frequency of extreme weather patterns. The threat of climate change makes accurate seasonal climate forecasting essential for African smallholder farmers. Technological, social and interdisciplinary issues, communication and scale are some key challenges which impact the utility and uptake of SCFs in rural smallholder farms. The integration of both scientific and indigenous knowledge forecasts is an opportunity for further exploration.

Despite extensive research on climate change impacts and adaptation strategies in Zimbabwe, their effectiveness from the perspective of smallholder farmers, particularly in the Gwayi catchment remains insufficiently understood. This study evaluated adaptation strategies in response to land use change and climate variability using a mixed-methods approach. Data were collected through a survey of 483 smallholder farmers, 10 focus group discussions (8–12 participants), and interviews with 25 key informants. Results show that despite farmers' awareness of improved practices, adaptation remains constrained by limited access to water, quality seeds, and technology (64%), financial constraints (46%), and knowledge gaps (19%). The most common adaptation strategies include soil water conservation (85%), drought-resistant crops (80%), early planting (55%), and diversification (49%), with soil water conservation and drought-tolerant crops being the most widely practiced and perceived as most effective. Regression analysis indicates that livestock ownership, participation in community climate-resilient programs, and recent drought experiences significantly (p < 0.05) influence both the choice and number of adaptation strategies adopted. These findings highlight the need for context-specific interventions to mitigate the impacts of climate and land use changes on food security. Strengthening resilience among smallholder farmers requires improved resource access, livestock support, community-based resilience programs, capacity building, financial aid, and enhanced drought preparedness. Implementing these measures will bolster adaptive capacity and promote sustainable agricultural practices in the face of climate uncertainty.

Profiling eco-environmentally vulnerable (EV) areas can contribute to the development of mechanisms for environmental protection and sustainable management of ecological resources. Land cover change, population density, annual precipitation, mean temperature, remotely sensed indices, actual evapotranspiration, land surface temperature (LST), and runoff for the catchment for 1990, 2000, 2011, and 2020 were used to assess spatiotemporal ecological vulnerability. Spatial principal component analysis (SPCA) was used to assess thematic vulnerability for each year. The analytical hierarchical process (AHP) was then used to determine the weighting of the thematic maps to produce the final ecological vulnerability maps. Our results showed that most of the sub-basin had low and moderate vulnerability in 1990, 2000, 2011, and 2020, with the combined proportion of these areas being 80.6%, 55.45%, 83.92%, and 85.1%, respectively. The areas classified as high vulnerability decreased steadily over the investigated years, except in 2000, where an increase was observed. Most areas in the southern parts of the sub-basin were classified as moderately vulnerable, while high vulnerability values were recorded in the northern areas. The southern parts of the Upper Mzingwane basin are drier and less populated than the northern parts. The spatial architecture of vulnerability presented will help inform decision makers in mitigation planning and overall disaster risk management initiatives in the basin.