Agricultural Water Consumption Research Articles

Assessing the impact of agriculture, coal mining, and ecological restoration on water sustainability in the Mu Us Sandyland

Balancing water demand for socio–economic development and ecosystem stability presents a challenge for regional sustainable management, especially in drylands. Previous studies have indicated that large–scale ecological restoration projects (ERPs) lead to a decline in terrestrial water storage (TWS) in the Mu Us Sandyland (MUS). However, the effects of other human activities (e.g., cropland reclamation, coal mining) on water resources remain unclear, raising concerns regarding water crisis and human–natural system sustainability. Through the utilization of coal mine location data, we found that the impact of coal mass loss on the Gravity Recovery and Climate Experiment (GRACE) products cannot be ignored in MUS, especially in the coal–rich northeastern part. Combining these data with auxiliary datasets, we observed a significant (p < 0.05) decrease in TWS (−0.85 cm yr−1) and groundwater storage (GWS, −0.95 cm yr−1) in the MUS, with human activities accounting for 79.23 % of TWS and 90.45 % of GWS reductions, primarily due to increased agricultural and industrial water consumption. Agricultural water consumption increased 2.23 times from 2001 to 2020, attributed to enhanced water use intensity (62.6 %) and cropland expansion (37.4 %). Industrial water consumption in Shenmu, a representative coal county, experienced a 4.16–fold rise between 2001 and 2020. Despite these challenges, local governments have alleviated water stress, ensured food security, and increased household income by comprehensive management strategies, such as enhancing water–saving technology and enforcing stringent policies. Previous studies have overestimated the amount of water resources consumed by ERPs. However, ERPs has played a critical role in stabilizing the regional ecological environment and ensuring the region as a vital food and energy supplier. Our findings can guide for socio-economic development and water management policies in similar regions.

A Coupling Study of Agricultural Carbon Emission, Water Resources and Economic Development in Heilongjiang Province

Heilongjiang Province is a major agricultural province in China, and its agricultural water consumption will account for 88.6% of the province's water consumption in 2020.Based on the coupling effects of agricultural water resources, agricultural carbon emissions and agricultural economy, this paper calculates and finds the data of Heilongjiang Province from 2000 to 2019,and uses Kuznets model theory, literature reading method, systematic research method and geographical research as the theoretical basis. The negative problems of Heilongjiang Province's agriculture, such as weak level of sustainable development, unreasonable consumption of agricultural water resources, and poor sustainable and good development of environment and economy, are analyzed in depth. Finally, by analyzing the restrictive factors, the author puts forward the path and countermeasures of the corresponding coordinated economic development.

Research on optimal allocation of soil and water resources based on water–energy–food–carbon nexus

Current population growth and rapid urbanization in China have intensified the demand for water, energy, and food. This is threatening the intertwined global water, energy, and food security. Therefore, it is necessary to formulate interconnected and interdependent water, energy, food, and carbon policies. In this study, based on the theory of water–energy–food–carbon nexus, a soil and water resource optimization allocation model was developed by establishing an optimization modeling framework to achieve coordination between various sectors of water allocation. The model is an effective decision-making tool that fully considers the close relationship within the nexus system, and multiple uncertainty conditions. It was applied on the Fen River Basin in Shanxi Province as the study area, and a series of optimized allocation schemes were obtained. The results indicated that the current water allocation to each sector is meeting its minimum water demand. The planting structure optimization of two crops, wheat and corn, reduces the regional agricultural water consumption. For example, in dry years, the area of wheat cultivation (which needs more irrigation and has lower net economic benefits) is reduced and that of corn (which needs less irrigation and consumes less water) is increased in each subdistrict. The wheat plantation area in the midstream and downstream is decreased by 2.08% and 26.25%, respectively. The water use structure of crops indicated that precipitation and groundwater resources significantly contribute to the production of both crops throughout the entire growth process. This model can be applied in other regions; the model's economic and ecological benefits are combined so that decision makers can consider the stability of the water–energy–food–carbon system and provide optimal resource allocation under various scenarios, contributing to achieving the goal of sustainable development.

Assessment of Crop Water Footprint and Actual Agricultural Water Consumption in Arid Inland Regions: A Case Study of Aksu Region

Water scarcity is a major issue in arid regions, and it is crucial to have an accurate understanding of water resource utilization for informed decision-making regarding water-related issues. However, due to various reasons such as inadequate measuring facilities, the actual agricultural water usage is often underestimated. The concept and methodology of the water footprint, based on a life-cycle perspective, provide a powerful tool for studying the actual water usage in agriculture. By utilizing the theories and models of water footprints, a method for reviewing the actual agricultural water usage in arid regions is proposed. Taking the Aksu region as an example, the evolution patterns and water consumption of 15 major crops over a 31-year period from 1990 to 2020 were calculated and analyzed. The research shows that the total water footprint of crops in the Aksu region has increased by nearly 3.13 times over the 31-year period, with significant accelerations in 2003 and 2016. The green water footprint accounts for an average of about 8% of the major crops, while the average water footprint of cotton accounts for over 57.2% of the total water footprint of major crops in the study area. Based on the calculation of the blue water footprint, the actual water usage in the Aksu region in 2020 was estimated to be 11.128 billion cubic meters, which is 1.30 times higher than the reported water usage, with groundwater extraction being 2.46 times higher than reported. This method of water footprint analysis for reviewing actual water usage and its application examples provide a methodological foundation and technical support for regional water resource management and policymaking.

Water Footprint Assessment of Agricultural Crop Productions in the Dry Farming Region, Shanxi Province, Northern China

Exploring the crop production water footprint and their driving factors is of significant importance for management of agricultural water resources. However, how do we effectively assess the total agricultural water consumption and explore the significance of their driving factors, i.e., population, economy, and agricultural production conditions, using a backpropagation neural network (BPNN)? It is still ambiguous. Water consumption for crops during the growing season is explicitly explored by way of water footprint indicators (green water footprint, WFPg, and blue water footprint, WFPb). This study provides new insights into the factors driving the changes in crop production water footprint in Taiyuan City over the period of 2005–2021. Simulations of crop evapotranspiration using the CROPWAT model were quantified. The results showed that Taiyuan City has a low crop yield level below the average level of China, with the highest crop yield in maize. The crop production water footprint in Taiyuan City showed a non-linearly decreasing trend over time. The average annual crop production water footprint was 187.09 × 103 m3/kg in Taiyuan City, with the blue water footprint and green water footprint accounting for 63.32% and 36.68%, respectively. The crop production water footprint in the west and north of Taiyuan City was significantly higher than those in other areas, accounting for 42.92% of the total crop production water footprint. Oilseed crops contributed most to the total crop production water footprint, accounting for 47.11%. The GDP and total sown area of crops were more important for the changes in WFPb. Agricultural machinery power and agriculture-to-non-agriculture ratio were more important for the changes in WFPg. Agricultural machinery power and GDP were more important for the changes in IWFP. In-depth analysis of the factors driving the changes in crop production water footprint is dramatically important for agricultural decision makers to mitigate water resource pressure in Taiyuan City.

Dynamic nexus between agricultural water consumption, economic growth and food security

ABSTRACT Water, energy and food (WEF) are important strategic resources for economic development in arid agriculture-based regions. Analyzing development indicators in the management of limited resources to achieve sustainability on a time scale is one of the basic goals of this research. Therefore, a system dynamics model was developed to analyze the WEF system resource flow relationship to achieve sustainable resource development. First, the subsystems of WEF resources were created and their dynamic relationship was formed in the form of a logical loop in a 10-year time frame. The evolution of 7 years (from 2015 to 2022) was taken into consideration to predict the 3-year period (from 2023 to 2025). The results showed that the reduction of water resources exploitation rate in China in interaction with agricultural productivity has automatically improved energy consumption and the nexus index. In China, a dynamic balance between WEF with a focus on water is recommended for planning.

Water footprints and crop water use of 175 individual crops for 1990–2019 simulated with a global crop model

The water footprint of a crop (WF) is a common metric for assessing agricultural water consumption and productivity. To provide an update and methodological enhancement of existing WF datasets, we apply a global process-based crop model to quantify consumptive WFs of 175 individual crops at a 5 arcminute resolution over the 1990–2019 period. This model simulates the daily crop growth and vertical water balance considering local environmental conditions, crop characteristics, and farm management. We partition WFs into green (water from precipitation) and blue (from irrigation or capillary rise), and differentiate between rainfed and irrigated production systems. The outputs include gridded datasets and national averages for unit water footprints (expressed in m3 t−1 yr−1), water footprints of production (m3 yr−1), and crop water use (mm yr−1). We compare our estimates to other global studies covering different historical periods and methodological approaches. Provided outputs can offer insights into spatial and temporal patterns of agricultural water consumption and serve as inputs for further virtual water trade studies, life cycle and water footprint assessments.

Using Niche Model to Analyze Water Consumption Structure in Jinan City, Shandong

Water resources are essential for healthy economic growth. Based on data on water consumption and industrial structure, this paper analyzes the evolution trends of the regional water consumption structure and industrial structure in Jinan City, Shandong Province, with the theory of the niche and ecological entropy, which may provide guidance for water resource utilization and social economy development in Jinan City. By establishing a coupling coordination model of the niche and ecological entropy, the dynamic niche evolution of the water consumption structure and industrial structure in Jinan City is analyzed. The results show the following: (1) The niche of agricultural water consumption accounts for the largest portion of the niche of water consumption, with an overall decreasing trend year by year. On the contrary, those of industrial and domestic water consumption have shown slow and fluctuating upward trends, respectively. Similar characteristics and trends are also reflected in the ecological entropy of water consumption. (2) In terms of industrial structure, the niche of the secondary industry accounts for the largest proportion among the three main industries, and only the niche of the tertiary industry is fluctuating upward. (3) Over the years, the overall coupling and coordination degree between the water consumption structure and industrial structure in Jinan was classified as a low degree of imbalance–weak coupling coordination. Among them, the coupling and coordination degree of the tertiary industry is the highest, that of the primary industry is the lowest, and that of the secondary industry is increasing year by year. Thus, it is necessary for Jinan to develop efficient water-saving agriculture and high-tech industry, maintain the development momentum of the tertiary industry, and continue to improve its coupling and coordination status.

Response Study of Streamflow and Sediment Reduction in the Northeast Region of the Loess Plateau under Changing Environment

The Sanggan River Basin in the loess hill and gully area is the primary water source for the establishment of the capital water conservation function area and the ecological environment support zone. Against the backdrop of global warming, population growth, and accelerated urbanization, water consumption in the Sanggan River Basin has persistently increased in recent years, leading to a series of issues, such as river pollution, surface streamflow reduction, groundwater over-exploitation, soil erosion, and decreased vegetation coverage. In this research, we employed the DMC approach, SWAT model, InVEST model, and CA-Markov model to quantitatively analyze the correlation between alterations in streamflow and sediment within this area and three influential factors: climate variations, LUCC, and other human interventions. Furthermore, we clarified the relative contributions of climate factor elements, land-use types, and human activities to streamflow and sediment in this region. The findings indicate a decline in the annual streamflow and sediment quantities observed within this region from 1960 to 2020, with reduction rates of 1.27 × 108 m3/10 a and 129.07 × 104 t/10 a, respectively, and an abrupt change year in 1983 and 1982. Compared to the annual streamflow, the annual sediment volume demonstrates more substantial variation. Based on the constructed model, three scenario simulation periods: P0 (1962–1981/1982), P1 (1983/1982–1999), and P2 (2000–2020) were set. Compared with P0, the respective contribution rates of climatic variation, land use, and other human intervention to streamflow (sediment volume) were 15.247% (19.601%), −0.03% (−1.349%), and 84.783% (81.748%) in P1. In P2, the contribution rates of these three factors on streamflow (sediment volume) were 9.160% (9.128%), 0.211% (3.053%), and 90.629% (84.818%), respectively. Through a quantitative analysis of climatic factors on streamflow and sediment, we found a positive correlation between precipitation and both streamflow and sediment. Additionally, there is an inverse relationship between temperature and streamflow, but streamflow will increase when temperature rises by 10%. Under three different future land-use scenarios, the variations in streamflow and sediment exhibited as ecological protection scenario &lt; urban expansion scenario &lt; natural development scenario. Changes in streamflow in this region are primarily caused by human intervention that alters the underlying surface. The increase in check dams and silted land could lead the runoff and sediment to decrease. Moreover, compared with the increase in industrial and agricultural water consumption, the increase in urban water consumption is the main factor for human water consumption.

Evaluation of AquaCrop’s Ability to Simulate Water Stress Based on 2-Year Case Study of Maize Crop

To apply AquaCrop to the study of agricultural soil moisture in the North China Plain, a water-treatment experiment on summer maize was carried out at the Fengqiu experimental station of the Chinese Academy of Sciences from 2017 to 2018. A water treatment was used to achieve field water capacities of 20 (W1), 40 (W2), and 60 (W3) cm soil layers under irrigation, and a rain-fed treatment (W0) was added. The model parameters were calibrated using the measured data in 2017. Then, they were applied to 2018 to verify the ability of the model to simulate water stress. The results showed that the variation trends for crop yield, canopy coverage, total soil water content, and the curve in the growth cycle simulated via AquaCrop were consistent with the actual observations; the results of a discrete analysis showed that the values of b (regression coefficient), R2 (determination coefficient), and EF (efficiency) were close to 1, and the values of the RMSE (root mean square error) were close to 0, which proved that the model could simulate dynamic changes in summer maize yield, canopy coverage, and total soil water content well. AquaCrop had good applicability in the North China Plain and could be applied to the study of agricultural water consumption and water-use efficiency in this area. The simulated values obtained can serve as an easily obtainable source of long-term experimental data in areas with frequent non-extreme weather events.

Climate-smart irrigation strategy can mitigate agricultural water consumption while ensuring food security under a changing climate

North China Plain suffers from the world’s most severe water scarcity and groundwater depletion due to intensive irrigation for agricultural production. It is imperative to reduce irrigation water consumption while safeguarding crop production and food security. This study conducted a quantitative analysis with deficit irrigation strategies for winter wheat using a water-driven AquaCrop model. After model calibration and validation with field experimental data, we analyzed the irrigation water demand, crop yield, and water productivity (WP) of winter wheat under various deficit irrigation scenarios. A set of optimal irrigation schedules were proposed for different climate years, which significantly mitigated irrigation water usage while sustaining high yields and WPs. The results indicated that despite the irrigation water demand of winter wheat under the future climate scenario was slightly higher than that in the historical period, their crop water sensitive periods (reviving, jointing, and flowering) remained the same. Therefore, we recommended adopting the same deficit irrigation schedules for the historical and future periods. In wet years, adopting a 50% deficit irrigation strategy only reduced crop yields by less than 5% compared with full irrigation, but it saved 1000–1100 m3 of water per hectare and contributed a WP higher than 1.88 kg/m3. While in normal and dry years, an optimal 25% deficit irrigation could sustain over 96% of the maximum yield, meanwhile it could save 650–800 m3/ha of water and achieve almost the same WP as full irrigation. These climate-smart irrigation strategies adapting to diverse climatic conditions largely mitigate agricultural water consumption while maximizing crop productivity and water use efficiency, which are essential for achieving precision irrigation and sustainable water management under a changing climate.

African rainforest moisture contribution to continental agricultural water consumption

Precipitation is essential for food production in Sub-Saharan Africa, where more than 80 % of agriculture is rainfed. Although ∼40 % of precipitation in certain regions is recycled moisture from Africa's tropical rainforest, there needs to be more knowledge about how this moisture supports the continent's agriculture. In this study, we quantify all moisture sources for agrarian precipitation (African agricultural precipitationshed), the estimates of African rainforest's moisture contribution to agricultural precipitation, and the evaporation from agricultural land across the continent. Applying a moisture tracking model (UTRACK) and a dynamic global vegetation model (LPJmL), we find that the Congo rainforest (>60 % tree cover) is a crucial moisture source for many agricultural regions. Although most of the rainforest acreage is in the DRC, many neighboring nations rely significantly on rainforest moisture for their rainfed agriculture, and even in remote places, rainforest moisture accounts for ∼10–20 % of agricultural water use. Given continuous deforestation and climate change, which impact rainforest areas and resilience, more robust governance for conserving the Congo rainforest is necessary to ensure future food production across multiple Sub-Saharan African countries.

Water Footprint of Animal Breeding Industry and Driving Forces at Provincial Level in China

Agriculture significantly contributes to the global water footprint (WF) with the animal breeding industry accounting for over 33% of agricultural water consumption. Since 2000, rapid development in animal breeding has intensified the pressure on water resources. Forecasts indicate a projected 70% increase in freshwater usage in the meat industry by 2025 compared to 2000, particularly in developing countries, such as China, yet comprehensive studies regarding China’s animal breeding industry WF remain limited. This study aimed to assess the variations in the green, blue, and gray WF of pork, beef, milk, eggs, and chicken meat across 31 provinces in China from 2000 to 2017. Additionally, a driving force analysis using the Kaya equation and LMDI method was conducted. Findings revealed that the total WF of animal products increased from 1049.67 Gm3 (in 2000) to 1385.05 Gm3 (in 2017) in China, and pork exhibited a significantly higher WF compared to other animal products, contributing 64.49% to China’s total animal product WF. The sharp rise in the green WF demonstrated regional disparities in water consumption efficiency within the animal breeding industry. The increase in the blue WF was associated with rising livestock numbers and China’s efforts to conserve water. The increase in the gray WF indicated that increased consumption of animal products heightened wastewater treatment pressures, particularly in economically developed provinces. The augmentation in China’s animal product WF was primarily influenced by policy and economic effects, with increased agricultural equipment funding and enhanced production efficiency identified as effective strategies for WF reduction. This study suggests that the promotion of technology, combined with scientific policies, can alleviate the pressure on water resources in the animal breeding industry in developing countries.

Temporal and Spatial Pattern Change in Evapotranspiration Over the High Plains: The Impact of and Guide on Extensive Groundwater‐Fed Irrigation

AbstractAquifer depletion due to extensive and intensive irrigation in the High Plains has threatened the environmental sustainability of the region. The change of crop evapotranspiration (ET), the major form of agriculture water consumption, presents a critical signature of hydrologic cycle change. This study evaluates the relative contributions of climate and groundwater‐fed irrigation to ET temporal and spatial pattern change over the High Plains Aquifer, one of the most severely depleted aquifers in the US. We developed a framework to extend the Budyko hypothesis to assess the impact of catchment storage change on long‐term ET. It is found that irrigation from groundwater pumping contributes more than half of the increase in ET (74.1 mm) from the period of 1940–1975 to 1976–2010, despite an increase of precipitation (35.0 mm) in the region. ET seasonal variance is decreased by the decline in precipitation variability (at −20.7 mm) and increase in irrigation (at +14.2 mm). As expected, irrigation decreases ET coefficient of variability (i.e., the ratio of standard deviation to mean). Spatially, we find that the human‐induced ET heterogeneity post‐1975 superimposes over the natural east‐to‐west gradient (in precipitation and ET) of this region. A correlation between the statistics (mean vs. coefficient of variation) on ET and crop yield provides promising signatures for understanding the coupled natural and human system of High Plains agriculture. Guides are discussed regarding how to handle the tradeoffs between agricultural development and natural resource sustainability under climate variability in the High Plains and other regions with similar conditions.

Satellite-Based Monitoring of Growing Agricultural Water Consumption in Hyper-Arid Regions

Land-use change has a key role in hydrologic processes and biodiversity. Although many satellite-based studies have been conducted to reveal the interaction between land-use changes in hydrological processes worldwide, the land-use change impact on agricultural water consumption in hyper-arid regions is poorly understood. Here, we investigate increased agricultural water consumption in the Qom province, a hyper-arid region in Iran, using derived imageries from Landsat 5 Tm and Landsat 8 OLI during the last three decades. We used maximum likelihood classification (MLC) and decision tree classification (DTC) to analyze the satellite images. The MLC method showed that croplands have increased from 30,547 ha in 1989 to 39,255 ha in 2019 (i.e., a 29% increase). In this period, the total orchard area increased from 3904 ha to 6307 ha, revealing a growth of 61%. In the DTC method, the increases in the cropland and orchard areas were, respectively, 34% and 60%. Although both MLC and DTC satisfied the accuracy criteria, the former was more consistent than the latter concerning ground data and documented statistics. Satellite-based and MLC results showed an increase in agricultural water consumption from 152 million cubic meters (MCM) in 1989 to 209 MCM in 2019, showing a 38% increase (i.e., 1.27% annually). Our findings send an alarming message for policymakers to reduce the water demand through sustainable agricultural practices in the Qom province, where the agricultural sector uses approximately 90% of annual water demand.

Water resource utilization efficiency and driving factors in northern Anhui (China) based on the DEA-Malmquist model

Abstract Based on the DEA-Malmquist method, this study analyzes water resource utilization efficiency in six cities of the northern Anhui region. The input indicators covered per capita water resources, industrial water consumption, agricultural water consumption, domestic water consumption, fixed assets investment, and number of employees. The output indicator was per capita GDP of each city. The findings of the study revealed that only Huaibei achieved efficiency according to the DEA model, while the other cities in the northern Anhui region did not exhibit the same level of efficiency. The overall water resource utilization efficiency in the region was low, with significant variations among the cities (p ≤ 0.05; ANOVA test). The order of water resource utilization efficiency from high to low was Huaibei, Huainan, Bengbu, Bozhou, Suzhou, and Fuyang. An analysis of investment redundancy revealed that a large number of employees and an unreasonable water use structure were key factors that restricted the efficiency of water resource utilization in the region. The overall TFP index of water resource utilization efficiency in the region showed an upward trend, with a value of 1.02. By addressing them, decision-makers can work toward promoting sustainable economic development and effective water resource management in the region.

Environmental assessment of anaerobic digestion and biological methanation in power-to-methane systems

Biomethane can play a crucial role in achieving European climate goals and replacing natural gas. One way to increase biomethane production is through biological methanation, converting the remaining CO2 from biogas with hydrogen into methane. The required hydrogen is produced via electrolysis, making this technology also a valuable storage and balance solution for the energy grid. This study determines the ecological development potentials of biological methanation. For this purpose, different feedstock for anaerobic digestion are investigated as carbon source, effects of technological advances in electrolysis and biological methanation are determined and optimal modes of operation are evaluated. Results indicate that the biological methanation with an anaerobic digestion using manure as feedstock has the lowest greenhouse gas emissions. However, the biological methanation achieves the greatest reduction in emissions compared to traditional biomethane production (biogas upgrading with high pressurized water scrubbing) when using energy crops and reducing emissions from feedstock production. In the base scenario which represents the current state of technology, biogas from maize without additional methanation step produces 151.8 kgCO2eq/MWhCH4. In combination with biological methanation, biomethane can be produced in the future with CO2eq emissions of 121.4 kgCO2eq/MWhCH4. Other factors such as agricultural land occupation or water consumption show even more significant improvements. The main drivers of emissions are the electricity demand for the electrolysis and fugitive methane emissions. The study shows that there is great ecological potential in biological methanation, especially in the future with prognosed technological advances in electrolysis and biological methanation.

Towards Sustainable Water Resources Management Considering Climate Change in the Case of Saudi Arabia

Saudi Arabia is one of the most water-scarce nations in the world, with a huge demand-supply gap, and the situation is expected to worsen due to climate change. Conventional surface water resources are limited, while nonrenewable groundwater sources are depleted. To build a more resilient and sustainable water sector, the production of non-conventional water resources, specifically desalinated seawater and treated domestic wastewater, has steadily increased in recent years. As the country lacks perennial water resources, such as rivers or water bodies, it relies mainly on nonrenewable groundwater and desalinated water to meet its daily requirements. Although the government is attempting to regulate the agricultural sector, water consumption in agriculture remains relatively high. It presents an environmental challenge due to its heavy reliance on non-renewable groundwater resources. The anticipated increase in temperature and highly uncertain changes in the rainfall patterns in Saudi Arabia could lead to greater uncertainty when attempting to develop effective water resource management plans. In this work, we review the status of the present and future of water resources and the challenges local authorities face in managing water resources amidst a changing climate in Saudi Arabia. This study employed a narrative research methodology, utilizing various databases, including Scopus, Web of Science, and Science Direct, to extract relevant articles within the subject area. This study proposes a number of recommendations and conclusions aimed at improving decision-makers’ ability to adapt to and mitigate the anticipated adverse impacts of climate change to manage scarce water resources sustainably.

Optimal allocation of agricultural water and land resources integrated with virtual water trade: A perspective on spatial virtual water coordination

Agricultural production consumes the majority of global freshwater resources. The worsening water scarcity has imposed significant stress on agricultural production when regions seek food self-sufficiency. To seek optimal allocation of spatial agricultural water and land resources in each water function zone of the objective region, a multi-objective optimization model was developed to tackle the trade-offs between the water-saving objective and the economic benefit objective considering virtual water trade (VWT). The cultivated area of each crop in each water function zone was taken into account as the decision variable, while a set of strong constraints were used to restrict land resources and water availability. Then, a decomposition-simplex method aggregation algorithm (DSMA) was proposed to solve this nonlinear, bounding-constrained, and multi-objective optimization model. Based on the quantitative analysis of the spatial blue and green virtual water in each agricultural product, the proposed methodology was applied to a real-world, provincial-scale region in China (i.e., Jiangsu Province). The optimized results provided 18 Pareto solutions to reallocate the land resources in the 21 IV-level water function zones of Jiangsu Province, considering four major rainy-season crops and two dry-season crops. Compared to the actual scenario, the superior scheme increased by 7.95% (5.6 × 109 RMB) for economic trade and decreased by 1.77% (2.0 × 109 m3) for agricultural water consumption. It was mainly because the potential of spatial blue and green virtual water in Jiangsu was fully exploited by improving spatial land resource allocation. The food security of Jiangsu could be guaranteed by achieving self-sufficiency in the superior scheme, and the total VWT in the optimal scheme was 2.2 times more than the actual scenario. The results provided a systematic decision-support methodology from the perspective of spatial virtual water coordination, yet, the methodology is widely applicable.

Assessing the effects of drought on rainfed maize water footprints based on remote sensing approaches.

Drought affects the characteristics of water use during crop production and so quantitatively evaluating the impacts is important. However, it remains unclear how crop water use responds to drought. To address this gap, water footprint (WF) and standardized precipitation evapotranspiration index (SPEI) were calculated by remote sensing approaches to assess the effects of drought on crop water use. Rainfed maize is the most important crop in Jilin Province, and its growth and water use are more susceptible to drought. The present study explored not only the impact of growing season drought on the maize WF values in Jilin Province, but also the response of WF values to drought at different time scales. Spatially, 72.94% of the WFblue pixels showed a non-significant increase, and the WFgreen in 68% pixels decreased significantly, being mainly concentrated in the middle region. Furthermore, the pixels affected by monthly time scale drought were mainly in the middle region, whereas the pixels affected by annual time scale drought were mainly in the western region. Drought not only affected on the source and structure of agricultural water consumption, but also had different effects on WF values at different time scale. These effects had obvious spatial differences. The present study systematically explored the effects of drought on the WF values for rainfed maize in different climate regions and a consideration of these effects could provide valuable information on rainfed maize growth and the agricultural water use response to a changing climate. © 2023 Society of Chemical Industry.