Evapotranspiration (ET) modeling plays a vital role in water resource management, agriculture, and climate adaptation. Accurate ET prediction is essential for effective irrigation planning and crop management. However, traditional methods often struggle to capture the complex relationships between environmental factors, resulting in less reliable forecasts. To address this, we implemented and optimized the Long Short-Term Memory (LSTM) network model to predict ET with improved accuracy of 98.8%, achieving a Mean Squared Error (MSE) of 0.12. Our approach incorporates SHapley Additive exPlanations (SHAP) to enhance model interpretability, offering insights into how key factors like solar radiation, wind speed, air temperature, and relative humidity impact ET predictions. The results showed that solar radiation had the highest impact on ET, followed by wind speed and air temperature. This improved understanding of key factors can help farmers and water managers make better decisions about irrigation, ensuring efficient water use and supporting sustainable agriculture. This provides a reliable and interpretable solution for ET prediction, aiding smarter irrigation strategies, improving resource efficiency, and supporting sustainable agricultural practices.

This study aimed to determine the perceived effects of climate change on the livelihoods of farming communities in the semi-arid regions of southwestern Zimbabwe. A qualitative approach was used to investigate smallholder farmers’ views and experiences regarding climate change and its impacts in two wards in the Tsholotsho district, Matabeleland North province, Zimbabwe. The primary data collection methods were key informant interviews and focus-group discussions. Participants were selected using purposive sampling from established farmer groups in the study area. Most focus group discussion participants agreed that they were aware of and experienced climate-related risks in their community. They observed climate variability, particularly in the occurrence of extreme events, such as drought and insufficient rainfall, including mid-season dry spells. The 2023/2024 season was marked by very low rainfall, mid-season dry spells, and challenges to crop sustainability. Smallholder farmers in the study area indicated that they were experiencing crop failure, livestock mortality, and reduced crop yields, all of which contribute to declining agricultural productivity. In response to drought, smallholder farmers primarily employed coping strategies, such as land management through Pfumvudza, a conservation land management coping strategy; crop diversification; the use of drought-tolerant crops that are early maturing; and seeking alternative non-farming income sources.

Body weight estimation accuracy is key to efficient sheep management and improved animal performance. This study investigated sex-based differences in the correlation between body weight (BWT) and linear body measurements (LBM) in indigenous Sabi sheep. A dataset comprising 173 Sabi sheep (112 ewes, 22 rams, and 39 wethers) from Zimbabwe’s Matopos Research Institute was analyzed, revealing significant positive correlations between body weight and linear measurements, particularly in ewes and rams. Heart girth exhibited the strongest positive correlation with body weight across sexes, with rams demonstrating higher correlation coefficients than ewes. Notably, body length in rams (r = 0.90) had a significantly higher correlation coefficient with body weight compared to ewes (r = 0.79). Conversely, weaker correlations were observed for Thurl width and pin bone width in wethers. The study identified sex-based differences in the relationships between body weight and linear measurements, indicating sexual dimorphism. Heart girth, body length, and chest depth emerged as key predictors of body weight in indigenous Sabi sheep. These findings underscore the importance of considering sex in understanding the relationship between body weight and linear body measurements in this breed, with implications for enhancing breeding programs and management practices for indigenous Sabi sheep. In conclusion, this study emphasizes the necessity of sex-specific data analysis when examining the correlation between body weight and linear body measurements in indigenous Sabi sheep to ensure accurate and reliable results.