Climate change and irrigation demand: Uncertainty and adaptation

Study region: The Kalamazoo River Watershed, southwest Michigan, USA. Study focus: Climate change is projected to have significant impacts on agricultural production. Therefore, understanding the regional impacts of climate change on irrigation demand for crop production is important for watershed managers and agricultural producers to understand for effective water resources management. In this study, the Soil and Water Assessment Tool was used to assess the impact of climate change on corn and soybean irrigation demand in the Kalamazoo River Watershed. Bias-corrected statistically downscaled climate change data from ten global climate models and four emissions scenarios were used in SWAT to develop projections of irrigation demand and yields for 2020–2039 and 2060–2079. Six adaptation scenarios were developed to shift the planting dates (planting earlier and later in the growing season) to take advantage of periods with greater rainfall or lower temperature increases. New hydrological insights for the region: Uncertainty in irrigation demand was found to increase moving from 2020–2039 to 2060–2079, with demand generally decreasing moving further into the future for corn and soybean. A shift in timing of peak irrigation demand and increases in temperature lead to corn yield reductions. However, soybean yield increased under these conditions. Finally, the adaptation strategy of planting earlier increased irrigation demand and water available for transpiration, while delaying planting resulted in demand decreases for both crops. Keywords: Irrigation demand, Climate change, SWAT, Crop yield, Adaptation, Uncertaint

Livestock and aquaculture farming in Bangladesh: Current and future challenges and opportunities

AbstractWe conducted a comprehensive review of livestock farming in Bangladesh to unveil current challenges and potential opportunities in this agriculture sector. Six challenges were selected as the major constraints to livestock farming in Bangladesh: climate change and natural hazards, poor veterinary care, breeding and management resources, marketing and international trade, and the SARS-CoV-2 pandemic. Solutions to these challenges (such as hazardous weather shelters, intensified surveillance of biosecurity for farms and markets, and non-government, government, and private organizations working together to educate and assist farmers) must target specific regions where the solutions would have the greatest effect

Climate change and livestock: Impacts, adaptation, and mitigation

Global demand for livestock products is expected to double by 2050, mainly due to improvement in the worldwide standard of living. Meanwhile, climate change is a threat to livestock production because of the impact on quality of feed crop and forage, water availability, animal and milk production, livestock diseases, animal reproduction, and biodiversity. This study reviews the global impacts of climate change on livestock production, the contribution of livestock production to climate change, and specific climate change adaptation and mitigation strategies in the livestock sector. Livestock production will be limited by climate variability as animal water consumption is expected to increase by a factor of three, demand for agricultural lands increase due to need for 70% growth in production, and food security concern since about one-third of the global cereal harvest is used for livestock feed. Meanwhile, the livestock sector contributes 14.5% of global greenhouse gas (GHG) emissions, driving further climate change. Consequently, the livestock sector will be a key player in the mitigation of GHG emissions and improving global food security. Therefore, in the transition to sustainable livestock production, there is a need for: a) assessments related to the use of adaptation and mitigation measures tailored to the location and livestock production system in use, and b) policies that support and facilitate the implementation of climate change adaptation and mitigation measures

Predicting the effect of weir management on the discharge of a controlled drainage system in a changing climate

Subsurface drainage in humid areas prevents field waterlogging but also transports nutrients to freshwater systems. Controlled drainage (CD) reduces drainage discharge and nutrient transport from fields. Some regions are expected to experience increased precipitation in the future, requiring CD to be evaluated under a changing climate. The objective of this study was to compare the performance of CD under two weir managements for a future period (2030–2059) and historical period (1992-2021) in southeast Michigan, USA. Climate projections were obtained for the shared socioeconomic pathway 245 emission scenario. Aggressive management involved maintaining the weir height at 40 cm during the growing season and 15 cm during the non-growing season, with a longer period of managed flow compared to common management, which maintained the weir height at 50 cm during the growing season and 30 cm during the non-growing season. It was predicted that the 30-year average annual precipitation would not change significantly in the future. The 30-year average mean monthly temperature would increase by 3.0°C in the future compared to the historical period. We performed simulations using the calibrated Root Zone Water Quality Model 2 (RZWQM2). The average drainage discharge in the future indicated a 20% increase in the 30-year average drainage discharge for a field with free drainage. The CD with common and aggressive managements reduced drainage discharge by 59% and 67% for the historical period, whereas the performance of CD was even better for the future period (63% and 72%, respectively). The improved future performance of CD can be attributed to a shift in precipitation patterns, with reduced precipitation during the growing season and increased precipitation during the non-growing season. As a result, the more aggressive weir management during this period created additional opportunities for reducing drainage discharge. In conclusion, aggressive management resulted in a slightly better flow-reducing performance than common management while indicating that both methods would effectively reduce drainage discharge in the likely future scenario

Multidimensional Aspects of Sustainable Biofuel Feedstock Production

Bioenergy is becoming increasingly relevant as an alternative to fossil fuels. Various bioenergy feedstocks are suggested as environmentally friendly solutions due to their positive impact on stream health and ability to sequester carbon, but most evaluations for bioenergy feedstocks have not evaluated the implications of bioenergy crop production holistically to date. Through the application of multi-objective optimization on 10 bioenergy feedstock rotations in a Michigan watershed, a Pareto front is searched to identify optimal trade-off solutions for three objective functions representing stream health, environmental emissions/carbon footprint, and economic feasibility. Various multi-criteria decision-making techniques are then applied to the resulting Pareto front to select a set of most-preferred trade-off solutions, which are compared to optimal solutions from each individual objective function. The most-preferred trade-off solutions indicate that a diverse mix of rotations are necessary to optimize all three objectives, whereas the individually optimal solutions do not consider a diverse range of feedstocks, thereby making the proposed multi-objective treatment an important and pragmatic strategy

Bayesian Regression and Neuro-Fuzzy Methods Reliability Assessment for Estimating Streamflow

Accurate and efficient estimation of streamflow in a watershed’s tributaries is prerequisite parameter for viable water resources management. This study couples process-driven and data-driven methods of streamflow forecasting as a more efficient and cost-effective approach to water resources planning and management. Two data-driven methods, Bayesian regression and adaptive neuro-fuzzy inference system (ANFIS), were tested separately as a faster alternative to a calibrated and validated Soil and Water Assessment Tool (SWAT) model to predict streamflow in the Saginaw River Watershed of Michigan. For the data-driven modeling process, four structures were assumed and tested: general, temporal, spatial, and spatiotemporal. Results showed that both Bayesian regression and ANFIS can replicate global (watershed) and local (subbasin) results similar to a calibrated SWAT model. At the global level, Bayesian regression and ANFIS model performance were satisfactory based on Nash-Sutcliffe efficiencies of 0.99 and 0.97, respectively. At the subbasin level, Bayesian regression and ANFIS models were satisfactory for 155 and 151 subbasins out of 155 subbasins, respectively. Overall, the most accurate method was a spatiotemporal Bayesian regression model that outperformed other models at global and local scales. However, all ANFIS models performed satisfactory at both scales

Groundwater-surface water interactions at wetland interface: advancement in catchment system modelling

Wetlands strongly interact with groundwater and surface water, influencing catchment hydrology and altering water quality. Meanwhile, catchment-scale models are typically unable to simulate groundwater-wetland interactions despite the fact that quantifying groundwater-wetland interactions can assist in better identifying locations for wetlands restoration/creation. We modified an integrated groundwater-surface water model (SWAT-MODFLOW-RT3D) to simulate water and nutrient exchange at the wetland interface. Several modifications were applied to the SWAT wetland module, and a spatial linkage was established between the module and the MODFLOW Drain Package to provide bidirectional water and nutrient exchange between groundwater and wetlands. We applied the modified model (SMR-W) to a tropical catchment in northeast Australia and quantified water and nitrate exchange between wetland, groundwater, and surface water for 28 potential locations. This study demonstrates that when groundwater heads are perched above wetlands bed, significant nitrate discharge from aquifers to wetlands occurs, which should be considered during wetland restoration planning

An improved calibration technique to address high dimensionality and non-linearity in integrated groundwater and surface water models

The calibration of integrated groundwater-surface water models is often associated with high dimensionality and stagnation around local optimum solutions. Since these models are computationally demanding and also non-linear, finding their global optimum solution requires efficient optimization techniques. Here, we introduce the Multi-Memory Particle Swarm Optimization (MMPSO) algorithm. The swarm cognitive capacity is enhanced to minimize the number of local optimums and calibrate the model based on sub-objective functions. We used the MMPSO to simultaneously calibrate groundwater head, streamflow, baseflow, and nitrate loads in the SWAT-MODFLOW-RT3D model with 78 sensitive parameters. The results demonstrate that enhancing the cognitive capacity led to a marked improvement in discovering the global optimum solution. Furthermore, we evaluated the calibrated model's performance to quantify groundwater nitrate loads to streams and characterize the shallow surficial aquifer under intensive fertilizer land use. The results show the effectiveness of the MMPSO algorithm for calibrating complex hydrogeochemical models for large-scale applications

Current and Future Challenges and Opportunities for Livestock Farming in West Africa: Perspectives from the Case of Senegal

Livestock farming is a livelihood activity and is critically important for the food and nutritional security of the majority of the population in West African countries, including Senegal. Nevertheless, livestock farming operates far below the optimum production potential, mainly due to demographical, biophysical, economic, environmental, and sociopolitical challenges. To address these issues, we conducted this review with an overall objective of characterizing different livestock farming systems and to identify challenges and opportunities to improve livestock production in West Africa through the broader perspectives from the case of Senegal. Pastoral, agropastoral, and off-land systems are the three major livestock production systems in this region, which are unique in terms of agroclimatology and degree of intensification and integration. The major challenges identified in livestock farming systems are lack of pasture and quality feed, scarcity of water resources, climate change, undeveloped breeding and management of livestock, poor marketing and trade, and socioeconomic constraints. Moreover, we contribute to the literature on crop-livestock farming in Senegal and West Africa by proposing plausible interventions to improve the productivity of the farming system to improve food and nutritional security. Concentrated efforts must be taken in co-designing effective management interventions for sustainable intensification of livestock sector in the region, considering site-specific approaches

Current and Future Challenges and Opportunities for Livestock Farming in West Africa: Perspectives from the Case of Senegal

Livestock farming is a livelihood activity and is critically important for the food and nutritional security of the majority of the population in West African countries, including Senegal. Nevertheless, livestock farming operates far below the optimum production potential, mainly due to demographical, biophysical, economic, environmental, and sociopolitical challenges. To address these issues, we conducted this review with an overall objective of characterizing different livestock farming systems and to identify challenges and opportunities to improve livestock production in West Africa through the broader perspectives from the case of Senegal. Pastoral, agropastoral, and off-land systems are the three major livestock production systems in this region, which are unique in terms of agroclimatology and degree of intensification and integration. The major challenges identified in livestock farming systems are lack of pasture and quality feed, scarcity of water resources, climate change, undeveloped breeding and management of livestock, poor marketing and trade, and socioeconomic constraints. Moreover, we contribute to the literature on crop-livestock farming in Senegal and West Africa by proposing plausible interventions to improve the productivity of the farming system to improve food and nutritional security. Concentrated efforts must be taken in co-designing effective management interventions for sustainable intensification of livestock sector in the region, considering site-specific approaches