The agricultural community has a challenge of increasing food production by more than 70% to meet demand from the global population increase by the mid-21st century. Sustainable food production involves the sustained availability of resources, such as water and energy, to agriculture. The key challenges to sustainable food production are population increase, increasing demands for food, climate change, and climate variability, decreasing per capita land and water resources. To discuss more details on (a) the challenges for sustainable food production and (b) mitigation options available, a special issue on “Water Management for Sustainable Food Production” was assembled. The special issue focused on issues such as irrigation using brackish water, virtual water trade, allocation of water resources, consequences of excess precipitation on crop yields, strategies to increase water productivity, rainwater harvesting, irrigation water management, deficit irrigation, and fertilization, environmental and socio-economic impacts, and irrigation water quality. Articles covered several water-related issues across the U.S., Asia, Middle-East, Africa, and Pakistan for sustainable food production. The articles in the special issue highlight the substantial impacts on agricultural production, water availability, and water quality in the face of increasing demands for food and energy.

In its annual report to Congress, the Council on Environmental Quality predicted that water shortage and pollution in the 1980's will be as big an international issue as energy was in the 1970's. With the majority of the earth's water supply found in the ocean or locked in ice caps and glaciers, only 65% is available for human and agricultural use, and agriculture consumes 80% of that supply. Continuing population growth and widespread population further tax this resource. Emphasizing this concern, the United Nations sponsored Water Conferences, stressing the importance of better "water management." Improving and expanding irrigated agriculture in developing countries was recommended as the primary method of conserving water supplies. Technological advances in irrigation would not only conserve resources, but would also improve food production capabilities.

Climate change is expected to considerably affect the water resources in the Indus River basin in Pakistan and thus agricultural production in the country. This article reports an analysis of the impacts of various climate scenarios on both water resources and food production out to 2050. While changes in water availability range from –12% to +24%, depending on the scenario, crop yield and production impacts are negative across all scenarios, and net food imports increase. We suggest a combination of accelerated investment in agricultural research and increased water-use efficiency in agriculture to reduce the adverse impacts of climate change on water and food.

Efficient use of water and nutrients in crop production are critical for sustainable water and crop production systems. Understanding the role of humans in ensuring water and nutrient use efficiency is therefore an important ingredient of sustainable development. Crop production functions are often defined either as functions of water and nutrient deficiency or are based on economic production theory that conceptualizes production as a result of economic activities that take in inputs such as water, capital and labor and produce crop biomass as output. This paper fills a gap by consistently treating water and nutrient use and human agency in crop production, thus providing a better understanding of the role humans play in crop production. Uptake of water and nutrients are two dominant biophysical processes of crop growth while human agency, including irrigation machine power, land-preparing machine power and human labor force, determine limits of water and nutrient resources that are accessible to crops. Two crops, i.e., winter wheat and rice, which account for the majority of food crop production are considered in a rapidly developing region of the world, Jiangsu Province, China, that is witnessing the phenomenon of rural to urban migration. Its production is modeled in two steps. First water and nutrient efficiencies, defined as the ratios of observed uptake to quantities applied, are modeled as functions of labor and machine power (representing human agency). In the second step, crop yields are modeled as functions of water and nutrient efficiencies multiplied by amounts of water and fertilizers applied. As a result, crop production is predicted by first simulating water and nutrient uptake efficiencies and then determining yield as a function of water and nutrients that are actually taken up by crops. Results show that modeled relationship between water use efficiency and human agency explains 68% of observed variance for wheat and 49% for rice. The modeled relationship between nutrient use efficiency and human agency explains 49% of the variance for wheat and 56% for rice. The modeled relationships between yields and actual uptakes in the second step explain even higher percentages of observed the variance: 73% for wheat and 84% for rice. Leave-one-out cross validation of yield predictions shows that relative errors are on average within 5% of the observed yields, reinforcing the robustness of the estimated relationship and of conceptualizing crop production as a composite function of bio-physical mechanism and human agency. Interpretations based on the model reveal that after 2005, mechanization gradually led to less labor being used relative to machinery to achieve same levels of water use efficiency. Labor and irrigation equipment, on the other hand, were found to be complimentary inputs to water use efficiency. While the results suggest interventions targeting machinery are most instrumental in increasing wheat productivity, they may exasperate rural – urban migration. Policy strategies for alleviating rural-urban migration while ensuring regional food security can nonetheless be devised where appropriate data are available.

The water–climate-food security nexus is uniquely vulnerable in Central Asia, a region replete with transboundary water conflicts, shortages in land and water resources and high sensitivity to climate change. Using a water balance for the Amu Darya River Basin, we present a synthetic evaluation of future water use, crop yields, land and water productivities for the period 2016 to 2055 in Ahal, Dashoguz, Lebap, and Mary provinces in Turkmenistan. Modeled fut socio-economic scenarios include food security and diet change (FSD), export-oriented sustainable adaptation (ESA) and business as usual (BAU). Results show that water requirements and water deficits during growing seasons will exhibit a decreasing trend from 2016 to 2055 in most provinces under all three scenarios. Crop yields and land and water productivities will likely increase in the four provinces under both the FSD and ESA scenarios. Mary province had the highest mean income and losses of irrigated agriculture, with an annual average value of about 7 × 108 USD/year and 1.5 × 103 USD/year, respectively. Ahral province showed the largest annual mean land and irrigation water productivities for all three scenarios, up to about 800 USD/ha/year and 0.40 USD/m3/year respectively. Results obtained from this study provide tools to assist resource managers to identify vulnerabilities in the nexus of water, land and climate to ensure food security, water management, and sustainable development.

Climate change and variability will impact water availability and the food security of India. Trend analyses of historical data indicate an increase in temperature and changes in rainfall pattern in different parts of the country. The general circulation models (GCMs) also project increased warming and changes in precipitation patterns over India. This chapter presents examples of model applications in water management and crop yield simulation in India, focusing on climate change impact assessment. Simulation models have been successfully applied for rotational water allocation, deficit irrigation scheduling, etc. in different canal commands. Application of a universal soil loss equation in a distributed parametric modeling approach by partitioning watershed into erosion response units suggests that by treating only 14% of the watershed area, a 47% reduction in soil loss can be achieved. Simulation studies conducted using different hydrological models with different climate change projections and downscaling approaches showed varied hydrological responses of different river basins to the future climate change scenarios, depending on the hydrological model, climate change scenarios, and downscaling approaches used. Crop yield modeling showed decreases in irrigated and rainfed rice (Oryza sativa L.) yields under the future climate change scenarios, but the decrease is marginal for rainfed rice. Maize (Zea mays L.) yields in monsoon may be adversely affected by a rise in atmospheric temperature, but increased rain can partly offset those losses. Wheat (Triticum aestivum L.) yields are likely to be reduced by 6 to 23% and 15 to 25% during the 2050s and 2080s, respectively. A combined bottom-up participatory process and top-down integrated modeling tool could provide valuable information for locally relevant climate change adaptation planning.

Climate change and variability will impact water availability and the food security of India. Trend analyses of historical data indicate an increase in temperature and changes in rainfall pattern in different parts of the country. The general circulation models (GCMs) also project increased warming and changes in precipitation patterns over India. This chapter presents examples of model applications in water management and crop yield simulation in India, focusing on climate change impact assessment. Simulation models have been successfully applied for rotational water allocation, deficit irrigation scheduling, etc. in different canal commands. Application of a universal soil loss equation in a distributed parametric modeling approach by partitioning watershed into erosion response units suggests that by treating only 14% of the watershed area, a 47% reduction in soil loss can be achieved. Simulation studies conducted using different hydrological models with different climate change projections and downscaling approaches showed varied hydrological responses of different river basins to the future climate change scenarios, depending on the hydrological model, climate change scenarios, and downscaling approaches used. Crop yield modeling showed decreases in irrigated and rainfed rice (Oryza sativa L.) yields under the future climate change scenarios, but the decrease is marginal for rainfed rice. Maize (Zea mays L.) yields in monsoon may be adversely affected by a rise in atmospheric temperature, but increased rain can partly offset those losses. Wheat (Triticum aestivum L.) yields are likely to be reduced by 6 to 23% and 15 to 25% during the 2050s and 2080s, respectively. A combined bottom-up participatory process and top-down integrated modeling tool could provide valuable information for locally relevant climate change adaptation planning.

This article is devoted to the assessment of Tunisian agricultural production and food trade balance water-equivalent. A linear regression model relating annual rainfall to crop yields is developed to estimate the agricultural production water-equivalent. Its implementation is based on national data for crop and animal production, leading to food demand water-equivalent quantification. Results highlight the relationship between agricultural and water policies and provide a picture of food security in the country in relation to local agricultural production, and to virtual water fluxes related to foodstuffs trade balance.