Ground water tables in Punjab are declining at alarming rates in most districts of Punjab. One of the major causes of declining water tables is the increased cropping intensity. Whereas cropping intensity in Punjab was only 120% until about 50 years ago, it is now 190%. With one crop per year, a balance was maintained between water extraction and aquifer recharge. With two crops per year, this balance has been altered. Homogenization of crops in the state has also exacerbated the problem. Even more serious threat to nation’s agriculture is climate change. Himalayan glaciers, which are water towers for our rivers, are retreating. This will reduce the water flow in our rivers. While the climate-change impact on our water availability is several years away, we must address immediate problem of declining water tables in the state. Suggested interventions include crop diversification, precision agriculture, including water saving technologies, and developing crop varieties with improved water-use efficiency.

Recent research studies and policies about innovative solutions to reduce water and energy consumption in food production are briefly reviewed. Options to increase water use efficiency and productivity include soil mulching, drip irrigation, deficit irrigation, and precision agriculture. As for the energy–water nexus, attention is focused on energy audits of water distribution networks; improving of system performance –– network sectoring, use of variable speed drives, critical points control, electricity tariff — and reduction of wastewater treatment’s energy use. At a larger scale, other solutions emerge: diversification and rotation of crops, cultivation of drought-resistant crops, and optimization process of the spatial distribution of cropping patterns. The rebound effect that can be associated to these options is also considered.

Legacy phosphorus (P) that has accumulated in soils from past inputs of fertilizers and manures is a large secondary global source of P that could substitute manufactured fertilizers, help preserve critical reserves of finite phosphate rock to ensure future food and bioenergy supply, and gradually improve water quality. We explore the issues and management options to better utilize legacy soil P and conclude that it represents a valuable and largely accessible P resource. The future value and period over which legacy soil P can be accessed depends on the amount present and its distribution, its availability to crops and rates of drawdown determined by the cropping system. Full exploitation of legacy P requires a transition to a more holistic system approach to nutrient management based on technological advances in precision farming, plant breeding and microbial engineering together with a greater reliance on recovered and recycled P. We propose the term ‘agro-engineering’ to encompass this integrated approach. Smaller targeted applications of fertilizer P may still be needed to optimize crop yields where legacy soil P cannot fully meet crop demands. Farm profitability margins, the need to recycle animal manures and the extent of local eutrophication problems will dictate when, where and how quickly legacy P is best exploited. Based on our analysis, we outline the stages and drivers in a transition to the full utilization of legacy soil P as part of more sustainable regional and global nutrient management.

Using a multi-disciplinary approach, this paper integrated spatial analysis with agricultural and energy system modelling to assess the impacts of drought on crop water demand, water availability, crop yield, and electricity requirements for irrigation. This was done by a novel spatially-explicit and integrated water-food-energy nexus model, using the spatial climatic data generated by the mesoscale MESAN and STRÅNG models. In this study, the model was applied to quantify the effects of drought on the Swedish irrigation sector in 2013, a typical drought year, for a specific crop. The results show that drought can severely affect the crop yield if irrigation is not applied, with a peak yield reduction of 18 t/ha, about 50 % loss as compared to the potential yield in irrigated conditions. Accordingly, the water and energy requirements for irrigation to halt the negative drought effects and maintain high yields are significant, with the peaks up to 350 mm and 700 kWh per hectare. The developed model can be used to provide near real-time guidelines for a comprehensive drought management system. The model also has significant potentials for applications in precision agriculture, especially using high-resolution satellite data.

Greenhouse farming is essential in increasing domestic crop production in countries with limited resources and a harsh climate like Qatar. Smart greenhouse development is even more important to overcome these limitations and achieve high levels of food security. While the main aim of greenhouses is to offer an appropriate environment for high-yield production while protecting crops from adverse climate conditions, smart greenhouses provide precise regulation and control of the microclimate variables by utilizing the latest control techniques, advanced metering and communication infrastructures, and smart management systems thus providing the optimal environment for crop development. However, due to the development of information technology, greenhouses are undergoing a big transformation. In fact, the new generation of greenhouses has gone from simple constructions to sophisticated factories that drive agricultural production at the minimum possible cost. The main objective of this paper is to present a comprehensive understanding framework of the actual greenhouse development in Qatar, so as to be able to support the transition to sustainable precision agriculture. Qatar’s greenhouse market is a dynamic sector, and it is expected to mark double-digit growth by 2025. Thus, this study may offer effective supporting information to decision and policy makers, professionals, and end-users in introducing new technologies and taking advantage of monitoring techniques, artificial intelligence, and communication infrastructure in the agriculture sector by adopting smart greenhouses, consequently enhancing the Food-Energy-Water Nexus resilience and sustainable development. Furthermore, an analysis of the actual agriculture situation in Qatar is provided by examining its potential development regarding the existing drivers and barriers. Finally, the study presents the policy measures already implemented in Qatar and analyses the future development of the local greenhouse sector in terms of sustainability and resource-saving perspective and its penetration into Qatar’s economy. | Open Access funding provided by the Qatar National Library. The authors are grateful to Qatar National Research Fund (QNRF) for funding and supporting the M-NEX Project (Grant No. BFSUGI01-1120-170005) in Qatar. The M-NEX is a project of the Collaborative Research Area Belmont Forum (Grant No. 11314551).

The increase in world population and the resulting demand for food, water and energy are exerting increasing pressure on soil, water resources and ecosystems. Identification of tools to minimise the related environmental impacts within the food–energy–water nexus is, therefore, crucial. The purpose of the study is to carry out an analysis of the agri-food sector in order to improve the energy-environmental performance of four vegetable crops (beans, peas, sweet corn, tomato) through a combination of precision agriculture (PA) and life cycle assessment (LCA). Thus, PA strategies were identified and a full LCA was performed on actual and future scenarios for all crops in order to evaluate the benefits of a potential combination of these two tools. In the case study analysed, a life cycle approach was able to target water consumption as a key parameter for the reduced water availability of future climate scenarios and to set a multi-objective function combining also such environmental aspects to the original goal of yield maximisation. As a result, the combination of PA with the LCA perspective potentially allowed the path for an optimal trade-off of all the parameters involved and an overall reduction of the expected environmental impacts in future climate scenarios.