Evaluating the Impacts of Variable Irrigation Management Strategies on the Performance of Cotton and Grain Sorghum Using Monitoring and Modeling Techniques

Diminishing water resources have threatened irrigated agriculture in many semi-arid and arid regions across the globe. In these regions, both surface and groundwater resources have declined due to persistent droughts and severe groundwater abstractions. Resultantly, producers are finding it difficult to irrigate to meet full crop water needs. Hence, there is an immediate need to find irrigation management strategies that ensure efficient utilization and conservation of water resources while optimizing crop yields in these areas. To achieve these goals, monitoring tools and crop models can be used to evaluate various irrigation management scenarios, so that meaningful irrigation recommendations could be offered to producers. The main goal of this research was to investigate crop and irrigation management practices for improving water conservation in the southern Great Plains, using a combination of field monitoring and crop modeling techniques. The specific objectives were: (1) To investigate the impacts of irrigation termination date on cotton yield and irrigation requirement, (2) To calibrate and validate a crop model for cotton and to apply the model to study the impact of irrigation capacity and seasonal weather conditions on cotton performance, and (3) To calibrate and validate a crop model for variably irrigated grain sorghum and apply the model to evaluate the performance of key water management scenarios. Evaluation of the effects of irrigation termination revealed that early irrigation terminations of cotton resulted in significant reductions in irrigation requirement, but this water conservation caused considerable declines in cotton yield. The performance of the crop model showed that it could be used as an effective tool for evaluating the impacts of variable crop and irrigation managements on the production of cotton and grain sorghum in the southern Great Plains. In both modeling studies, the results revealed a significant impact of planting date on crop yield and irrigation requirements, and this information gives the producers an opportunity to carefully consider this variable to optimize irrigation utilization. Additionally, simulations revealed that equally high cotton yields could be obtained with low irrigation capacities in the Southern High Plains region and this presents an opportunity to prolong the life of the Ogallala aquifer

Does A Market Systems Approach Revitalize Smallholder Irrigation Schemes? Evidence from Zimbabwe

Smallholder irrigation schemes potentially improve the livelihoods of rural communities in developing countries. However, they face challenges such as infrastructural decline, lack of funding, lack of markets, shortage of water, underutilization of land, and inefficient irrigation systems. In Zimbabwe, the government carried out rehabilitation programs to address these problems but the performance of smallholder irrigation schemes remained poor. These chronic challenges triggered experts to adopt a market systems approach (MSA) to revitalize failing irrigation schemes. Using primary and secondary data sources collected in 2015, this study used a “before” and “after” descriptive assessment approach to determine the effectiveness of the MSA at revitalizing smallholder irrigation schemes in Zimbabwe. We used Mutema Irrigation Scheme as a case study. Results suggest that the MSA leads to improved efficiency of irrigation infrastructure, farm gross margins, willingness to pay irrigation fees and farmers’ standard of living. While this research does not econometrically establish causation of relations between variables involved, our results provide a foundation for future research on the application of the MSA to revitalize underperforming smallholder irrigation schemes in developing countries

Review and operational guidelines for portable ultrasonic flowmeters

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Does A Market Systems Approach Revitalize Smallholder Irrigation Schemes? Evidence from Zimbabwe

Smallholder irrigation schemes potentially improve the livelihoods of rural communities in developing countries. However, they face challenges such as infrastructural decline, lack of funding, lack of markets, shortage of water, underutilization of land, and inefficient irrigation systems. In Zimbabwe, the government carried out rehabilitation programs to address these problems but the performance of smallholder irrigation schemes remained poor. These chronic challenges triggered experts to adopt a market systems approach (MSA) to revitalize failing irrigation schemes. Using primary and secondary data sources collected in 2015, this study used a “before” and “after” descriptive assessment approach to determine the effectiveness of the MSA at revitalizing smallholder irrigation schemes in Zimbabwe. We used Mutema Irrigation Scheme as a case study. Results suggest that the MSA leads to improved efficiency of irrigation infrastructure, farm gross margins, willingness to pay irrigation fees and farmers’ standard of living. While this research does not econometrically establish causation of relations between variables involved, our results provide a foundation for future research on the application of the MSA to revitalize underperforming smallholder irrigation schemes in developing countries

“Are They Aware, and Why?” Bayesian Analysis of Predictors of Smallholder Farmers’ Awareness of Climate Change and Its Risks to Agriculture

While climate change threatens global food security, health, and nutrition outcomes, Africa is more vulnerable because its economies largely depend on rain-fed agriculture. Thus, there is need for agricultural producers in Africa to employ robust adaptive measures that withstand the risks of climate change. However, the success of adaptation measures to climate change primarily depends on the communities’ knowledge or awareness of climate change and its risks. Nonetheless, existing empirical research is still limited to illuminate farmers’ awareness of the climate change problem. This study employs a Bayesian hierarchical logistic model, estimated using Hamiltonian Monte Carlo (HMC) methods, to empirically determine drivers of smallholder farmers’ awareness of climate change and its risks to agriculture in Zambia. The results suggest that on average, 77% of farmers in Zambia are aware of climate change and its risks to agriculture. We find socio-demographics, climate change information sources, climate change adaptive factors, and climate change impact-related shocks as predictors of the expression of climate change awareness. We suggest that farmers should be given all the necessary information about climate change and its risks to agriculture. Most importantly, the drivers identified can assist policymakers to provide the effective extension and advisory services that would enhance the understanding of climate change among farmers in synergy with appropriate farm-level climate-smart agricultural practices

Impacts of Irrigation Termination Date on Cotton Yield and Irrigation Requirement

Optimization of cotton irrigation termination (IT) can lead to more efficient utilization and conservation of limited water resources in many cotton production areas across the U.S. This study evaluated the effects of three IT timings on yield, fiber quality, and irrigation requirements of irrigated cotton in southwest Oklahoma during three growing seasons. The results showed cotton yield increased with later IT dates, but this response was highly dependent on the amount and timing of late-season precipitation events. Only a few fiber quality parameters were significantly different among treatments, suggesting a more limited impact of IT on fiber quality. When averaged over the three study years, the lint yield was significantly different amongst all treatments, with an average increase of 347 kg ha−1 from the earliest to the latest IT. Additionally, the seed yield and the micronaire were similar for the two earlier IT treatments and significantly smaller than the values under the latest IT treatment. The differences in fiber uniformity and strength were also significant amongst IT treatments. Strong positive relationships were found between yield components and average late-season water content in the root zone. Lint and seed yields plateaued at an average late-season soil matric potential of about −30 kPa and had a quadratic decline as soil moisture depleted. When benchmarked against the latest IT treatment, the earlier IT treatments achieved average reductions of 16⁻28% in irrigation requirement. However, this water conservation was accompanied with considerable declines in yield components and micronaire and smaller declines in fiber length, uniformity, and strength

Technical Efficiency and Technological Gaps of Rice Production in Anambra State, Nigeria

The traditional approach to modeling productive efficiency assumes that technology is constant across the sample. However, farms in different regions may face different production opportunities, and the technologies they employ may differ due to environmental factors. Therefore, rather than using a traditional stochastic frontier model in such cases, a stochastic meta-frontier (SMF) analysis is recommended to account for environmental factors between regions. It follows that differences in environmental factors between the upland and lowland regions in Anambra State, Nigeria, may result in farmers producing rice under different production and environmental conditions. Using the SMF model, this study, for the first time, determines technical efficiency (TE) and technological gap ratios (TGRs) of rice production from the upland and lowland regions in the Awka North Local Government Area of Anambra State, Nigeria. Our data are from a cross-section sample of randomly selected rice farmers. Results reveal that lowland regional rice producers are on average, significantly more technically efficient (91.7%) than their upland counterparts (84.2%). Additionally, mean TGRs associated with lowland rice farmers are higher (92.1%) than their corresponding upland producers (84.7%). While the upland rice producers are less technically efficient and further away from their full potential, results indicate that both sets of farmers do not use advanced technologies to match the industry’s potential. We suggest that agricultural policy should focus on providing regionally specific technologies, such as improved rice varieties that fit the working environment of the lagging area, to help rice farmers improve their resource efficiency and minimize technological gaps