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Evapotranspiration over crop growth period, also referred to as the consumptive water footprint of crop production (WFCP), is an essential component of the hydrological cycle. However, the existing high-resolution consumptive WFCP datasets do not distinguish between soil evaporation and crop transpiration and disregard the impacts of different irrigation practices. This restricts the practical implementation of existing WFCP datasets for precise crop water productivity assessments, agricultural water-saving evaluations, the development of sustainable irrigation techniques, cropping structure optimization, and crop-related interregional virtual water trade analysis. This study establishes a 5-arcmin gridded dataset of monthly green and blue WFCP, evaporation, transpiration, and associated unit WFCP benchmarks for 21 crops grown in China during 2000–2018. The data simulation was based on calibrated AquaCrop modelling under furrow-, sprinkler-, and micro-irrigated as well as rainfed conditions. Data quality was validated by comparing the current results with multiple public datasets and remote sensing products. The improved gridded WFCP dataset is available at 10.5281/zenodo.7756013 (Wang et al., 2023) and effectively compensated for the gaps in the existing datasets through (i) revealing the intensity, structure, and spatiotemporal evolution of both productive and non-productive blue and green water consumption on a monthly scale, and (ii) including crop-by-crop unit WFCP benchmarks according to climatic zones. [ABSTRACT FROM AUTHOR]

Agriculture is the world's largest consumer of water resources, and accurate measurement of crop water footprint (CWF) can provide a scientific basis for evaluating the water use characteristics of agricultural production and guiding water management. The measurement of regional CWF requires large amounts of ground data, and remote sensing provides an effective means to scientifically measure the CWF on a large scale. In this study, we developed an effective means to estimate regional maize CWF based on global evapotranspiration (MOD16 and Global Land Data Assimilation System (GLDAS)‐Noah) products in China. And we also calculated the CWF based on the FAO Penman‐Monteith equation (FAO‐PM) on the site scale in China. We assessed the accuracy of these methods by comparing them against eight eddy‐covariance based flux tower measurements. Links and differences behind the results of the three water footprint calculations were analyzed in terms of the basic principles and characteristics of the calculations. The results showed that the CWF had a similar distribution based on the MOD16 and GLDAS‐Noah, reflecting the influence of regional soil moisture on the CWF. Computational rationale analysis of the three quantitative methods showed that the ETc‐based method from the FAO‐PM model was similar to the MOD16‐ and GLDAS‐Noah‐based CWF in the wetter areas, two remote sensing‐based methods considered the water constraints during soil evaporation and water dissipation during dry and wet canopy conditions, and were closer to reality than the ETc‐based methods in measuring the CWF in arid and semi‐arid regions. Key Points: An effective means based on MOD16 and Global Land Data Assimilation System (GLDAS)‐Noah was developed for simulating regional maize crop water footprint (CWF)The accuracy of the estimated CWF based on FAO‐PM was influenced by the soil moistureThe CWF estimated by MOD16 or GLDAS‐Noah was closer to the reality than that estimated by FAO‐PM, especially in arid and semi‐arid region [ABSTRACT FROM AUTHOR]

Adaptation to future climate change with limited water resources is a major global challenge to sustainable and sufficient crop production. However, the large-scale responses of the crop water footprint and its associated benchmarks under various irrigation regimes to future climate change scenarios remain unclear. The present study quantified the responses of the maize and wheat water footprint (WF) per unit yield (m 3 t -1) as well as the corresponding WF benchmarks under two Representative Concentration Pathway (RCP) scenarios, RCP2.6 and RCP8.5, in the 2030s, 2050s, and 2080s at a 5 arcmin grid level in China. The AquaCrop model with the outputs of six global climate models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) as its input data was used to simulate the WFs of maize and wheat. The differences among rain-fed wheat and maize and furrow-, micro-, and sprinkler-irrigated wheat and maize were identified. Compared with the baseline year (2013), the maize WF will increase under both RCP2.6 and RCP8.5 (by 17 % and 13 %, respectively) until the 2080s. The wheat WF will increase under RCP2.6 (by 12 % until the 2080s) and decrease (by 12 %) under RCP8.5 until the 2080s, with a higher increase in the wheat yield and a decrease in the wheat WF due to the higher CO 2 concentration in 2080s under RCP8.5. The WF will increase the most for rain-fed crops. Relative to rain-fed crops, micro-irrigation and sprinkler irrigation result in the smallest increases in the WF for maize and wheat, respectively. These water-saving management techniques will mitigate the negative impact of climate change more effectively. The WF benchmarks for maize and wheat in the humid zone (an approximate overall average of 680 m 3 t -1 for maize and 873 m 3 t -1 for wheat at the 20th percentile) are 13 %–32 % higher than those in the arid zone (which experiences an overall average of 601 m 3 t -1 for maize and 753 m 3 t -1 for wheat). The differences in the WF benchmarks among various irrigation regimes are more significant in the arid zone, where they can be as high as 57 % for the 20th percentile: WF benchmarks of 1020 m 3 t -1 for sprinkler-irrigated wheat and 648 m 3 t -1 for micro-irrigated wheat. Nevertheless, the WF benchmarks will not respond to climate changes as dramatically as the WF in the same area, especially in areas with limited agricultural development. The present study demonstrated that the observed different responses to climate change in terms of crop water consumption, water use efficiency, and WF benchmarks under different irrigation regimes cannot be ignored. It also lays the foundation for future investigations into the influences of irrigation methods, RCPs, and crop types on the WF and its benchmarks in response to climate change in all agricultural regions worldwide. [ABSTRACT FROM AUTHOR]

A core goal of sustainable agricultural water resources management is to implement a lower water footprint (WF), i.e. higher water productivity, and to maximize economic benefits in crop production. However, previous studies mostly focused on crop water productivity from a single physical perspective. Little attention is paid to synergies and trade-offs between water consumption and economic value creation of crop production. Distinguishing between blue and green water composition, grain and cash crops, and irrigation and rainfed production modes in China, this study calculates the production-based WF (PWF) and derives the economic value-based WF (EWF) of 14 major crops in 31 provinces for each year over 2001–2016. The synergy evaluation index (SI) of PWF and EWF is proposed to reveal the synergies and trade-offs of crop water productivity and its economic value from the WF perspective. Results show that both the PWF and EWF of most considered crops in China decreased with the increase in crop yield and prices. The high (low) values of both the PWF and EWF of grain crops tended to cluster obviously in space and there existed a huge difference between blue and green water in economic value creation. Moreover, the SI revealed a serious incongruity between PWFs and EWFs both in grain and cash crops. Negative SI values occurred mostly in north-west China for grain crops, and overall more often and with lower values for cash crops. Unreasonable regional planting structure and crop prices resulted in this incongruity, suggesting the need to promote regional coordinated development to adjust the planting structure according to local conditions and to regulate crop prices rationally. [ABSTRACT FROM AUTHOR]

Assessment of the water use efficiency is the key to effectively manage agricultural water resource. The water footprint is a new index for water use evaluation, and its quantification is a precondition for assessment of the agricultural water use efficiency. Due to the shortage of water footprint calculation methods and computational module defects, this study aims to establish a method for calculating the water footprint of crop production based on hydrological processes. In this study, the field-scale water footprints of wheat, corn and sunflower were calculated using the SWAT model in the Hetao irrigation district (HID), China. The results showed that the average total water footprints of wheat, corn and sunflower were 1.036 m 3 /kg, 0.774 m 3 /kg and 1.510 m 3 /kg, respectively. Additionally, the proportions of green water footprints in wheat, corn and sunflower were 22.3%, 26.1% and 29.4%, respectively. Water footprint calculations based on the SWAT model can reflect the spatial differences of water footprints during the process of crop production. The overall distribution pattern of the green, blue and total water footprints for the three crops demonstrated that high values were in the east part of the HID, followed by the west and the central areas. The SWAT-based water footprint offers high spatial resolution and is effective in exploring the spatial heterogeneity of crop water footprints. [ABSTRACT FROM AUTHOR]

Relay intercropping of spring wheat and maize is practiced on a large scale in northern China. In order to provide information on productivity and nitrogen use for spring wheat/maize intercropping, a two-year experiment under three N levels and three cropping systems (monocultured wheat, monocultured maize, and intercropped wheat and maize) was carried out in the Hetao Irrigation District of the Inner Mongolia Autonomous Region, to quantify and characterize the growth and yield of the wheat and maize and determine the uptake and use efficiency of nitrogen in two crops. The land equivalent ratio (LER) of the wheat/maize intercropping system ranged from 1.01 to 1.19, and thus land use efficiency was significantly enhanced by this intercropping system. The dry-matter yield and LAI (leaf area index) of wheat were higher in border rows than in inner rows and monocultured rows, indicating an effect of border rows in the intercropping system. The LAI was considerably lower for the intercropped than the monocultured maize, indicating that intercropping limited the vegetative growth of maize. The grain yield and nitrogen uptake of both wheat and maize in two cropping systems were significantly improved with increasing amounts of N application. The LER of intercropping system tended to increase at higher N levels. The patterns of maize growth in the monocultures and intercrops were characterized by fitting expolinear growth equations to periodic harvest data. Fitted parameters indicated a growth delay in the intercropped maize ranging from 2.39 to 8.24 d relative to the maize monoculture. The growth delays were shortest at the moderate N rate among three N levels (2.39 d in 2012 and 2.57 d in 2013). This result could be interpreted in terms of the competitive effect of wheat during the seedling phase of maize, which was weakest at the moderate N rate, causing a comparatively short growth delay. The estimated growth rate during the linear growth phase was highest in the intercrop in the high N treatment (417.5 kg ha −1 d −1 in 2012 and 376.7 kg ha −1 d −1 in 2013). The physiological nitrogen use efficiency (IE) was more favorable for monocultured wheat and intercropped maize and decreased as N rates increased. The efficiency of the use of N for the entire system was assessed by comparing the relative nitrogen yield total to the relative yield total. The relative nitrogen yield total ranged from 1.06 to 1.23, while the relative yield total ranged from 1.01 to 1.19, indicating that the intercrop used more nitrogen per unit production than did the monocultures. [ABSTRACT FROM AUTHOR]

Highlights: [•] The SD theory combined with DPSIR framework is established for designing indicators of AWLRU zoning. [•] The proposed framework can decipher the causal relationships at each of the levels in the system of AWLRU. [•] Water resources conditions play a key role on AWLRU in water-scarce area, such as Bayan Nur. [•] The supply level determines the degree and direction of water and land resource utilization and types of agricultural production. [Copyright &y& Elsevier]

Abstract: Irrigation plays an increasing important role in agriculture of China. The assessment of water resources utilization during agricultural production process will contribute to improving agricultural water management practices for the irrigation districts. The water footprint provides a new approach to assessing the agricultural water utilization. The present paper put forward a modified calculation method to quantify the water footprint of crop. On this basis, this paper calculated the water footprint of major crop in Hetao irrigation district, China. Then, it evaluated the influencing factors that caused the variability of crop water footprint during the study period. Results showed that: 1) the annual average water footprint of integrated-crop production in Hetao irrigation district was 3.91m3 kg−1 (90.91% blue water and 9.09% green water). The crop production in the Hetao irrigation district mainly relies on blue water; 2) under the integrated influences of interannual climate variability and variation of agricultural inputs, the water footprint of integrated-crop production displayed a decreasing trend; 3) the contribution rate of the climatic factors to the variation of water footprint was only −6.90%, while the total contribution rate of the agricultural inputs factors was −84.31%. The results suggest that the water footprint of crop mainly depends on agricultural management rather than the regional climate and its variation. The results indicated that the water footprint of a crop could be controlled at a reasonable level by better management of all agricultural inputs and the improvement of water use efficiency in agriculture. [Copyright &y& Elsevier]

Abstract: In this study, we analyzed the drought variation trends in six subregions of the Loess Plateau over the past four decades. To do this, we used a new method wherein we combined the Variable Infiltration Capacity (VIC) Model for simulating watershed hydrological processes and Palmer Drought Severity Index (PDSI) for drought assessment and analysis. A new classified calibration procedure of climate characteristic coefficient, K j , was introduced in the study to improve the traditional PDSI computation method. The results suggest that the total area affected by drought in subregions 1–3 located in the middle reaches of the Yellow River mainly exhibited downward trends during 1971–2010. As these domains are the principal sediment sources of the Yellow River, the decreasing trends in drought area could benefit to vegetation recover in these regions, which are key sites of “Grain for Green” project, and help to control the severe soil and water losses. However, subregions 4–6 located in the upper reaches of the Yellow River primarily experienced upward trends in the total drought area. These subregions are the main grain producing areas of the study region, and the increase in drought area may cause damage to agricultural production and regional food security. The spatial distribution of drought frequency increased from southeast to northwest on the Loess Plateau. Most areas of the subregions 4–6 of the plateau exhibited an upward trend in drought frequency as indicated by a Mann–Kendall test, and the upward trend will show persistent behavior in the future, according to a Hurst exponent analysis. Generally speaking, the drought hazard in the upper reaches of the Yellow River tended to be increasingly severe, while drought hazard in the middle reaches has relieved to certain extent over the past four decades. [Copyright &y& Elsevier]

Water and food safety are two major challenges which the world faces today. Traditional water management focuses on the reduction of water use through improvements in water saving technologies. However, quantitative research is needed to evaluate the effects of changing food consumption patterns on water resources. Here we report the water saving effects of changing diet pattern of the major crops and animal products in mainland China. By using the concepts of water footprint (WF) per weight unit and per calorie unit, provided by 13 primary crop and animal products, the WFs of the 13 agricultural products in each province are compared, and their water/energy conversion efficiencies are analyzed. Then, impacts of different scenarios of changing diet pattern on water consumption were explored. Results show that there are obvious differences between the WF per weight and calorie unit provided by crop and animal products due to the nutritional properties of the agricultural products. Promoting water savings from the food consumption side could give a positive feedback on water consumption. Scenario analysis of adjustments to the diet pattern proves that it is potentially feasible to reach the objective of alleviating stress on water resources while guaranteeing nutritional value of the residents. [ABSTRACT FROM AUTHOR]

Scarcity and competition for water are becoming matters of increasing concern around the world. The interdisciplinary nature of the problem requires that the technical, economic, environmental and social aspects of water usage are integrated into a coherent analytical framework. Therefore, a comprehensive evaluation of agricultural water use during crop production is a necessary prerequisite for agricultural water management. The present study provides an overview of water-accounting and water footprint assessment methods by analysing the performance, efficiency, economic profitability and environmental impact of the Hetao Irrigation District, China. The performance and efficiency results showed that the total volume of water consumed in the Hetao Irrigation District, during wheat production, was 872 Mm 3 , of which 116 Mm 3 was green water and 756 Mm 3 was blue water. Furthermore, 443 Mm 3 of the blue water was used effectively, while 313 Mm 3 was non-beneficial due to an inefficient irrigation system. The grey water footprint was 152 Mm 3 during wheat production, which accounted for 15.42% of the total available water in the district. The results indicated that the economic profit is higher relative to the national average due to the high yields in wheat production in the Hetao Irrigation District. However, efficient use of resources and environmental sustainability were relatively low due to high water consumption and pollution. This study highlighted the need for a comprehensive evaluation of water use in agricultural production and it provides insights by using water footprint and water accounting in water use assessment and is a reference for other related studies. [ABSTRACT FROM AUTHOR]

Revealing the characteristics of crop water use in arid and semi-arid areas and clarifying the differences in crop species and water use between provinces will help propose measures to promote sustainable agricultural development from the perspective of efficient crop water use, which is crucial for ensuring global food security. In this study, taking arid and semi-arid Northwest China as an example, the temporal and spatial evolution characteristics of the water footprint (WF) of major grain and economic crops were systematically analyzed using WF and comparative advantage theory and the differences in WF among different regions and crops were evaluated. The results showed that from 2000 to 2020, the WF of regional agricultural production decreased significantly (p <0.01). The blue WF of grain and cash crops decreased from 59.9 % and 48.0 % in 2000–54.0 % and 41.2 % in 2020, respectively. The WF of wheat, rice, soybeans, maize, potatoes, vegetables, cotton, oil and fruits decreased by 40.9 %, 46.3 %, 50.1 %, 43.4 %, 48.9 %, 40.7 %, 40.6 %, 50.1 %, and 39.7 % from 2000 to 2020, respectively. The WF of grain crop production in Inner Mongolia was 45.8 % lower than that in Qinghai. The WF of economic crop production in Gansu was 2.7 times that of Ningxia. The differences in WF of crop production among regions led to different comparative advantages for different crops in different regions. Shanxi, Shaanxi and Inner Mongolia had comparative advantages in wheat production WF, with indices of 0.91, 0.90 and 0.89, respectively. The regions with relative comparative advantage of maize were Inner Mongolia, Shaanxi and Qinghai. The research results can provide a reference for the systematic analysis of crop production characteristics in other arid and semi-arid regions around the world and propose remedial measures for inter-regional crop production differences to contribute to a reduction in the number of people experiencing hunger. [Display omitted] • Spatial and temporal characteristics of the water footprint of 9 crops are analyzed. • Comparative advantage theory assesses crop and regional differences in water use. • The crop structure between regions is unreasonable and has optimization potential. • Measures are proposed to promote sustainable regional crop production. [ABSTRACT FROM AUTHOR]

Intercropping can improve productivity per unit incident radiation by increasing the interception of solar radiation and/or maintaining higher radiation-use efficiency (RUE). This study examined the changes in radiation interception and RUE of spring wheat and spring maize after the initiation of intercropping. The field experiment comprised four treatments: wheat only, maize only, six rows of wheat alternated with two rows of maize (I62), and twelve rows of wheat alternated with four rows of maize (I124). The results demonstrated that per row, wheat in I62 and I124 intercepted 17% and 9% more radiation, respectively, than the wheat sole-cropping system and maize in I62 and I124 intercepted 28% and 26% more radiation, respectively, than the maize sole-cropping system. The RUE values were 3.10 and 3.19 g MJ −1 for maize in I62 and I124, respectively, lower than that for the maize sole-cropping system (3.51 g MJ −1 ). No significant difference was observed between the RUE values of intercropped and monoculture wheat. The harvest index of maize was identical in all systems, while that of the wheat was enhanced by intercropping. The grain yields of wheat in I62 and I124 were 29.2% and 10.8% higher, respectively, than that of sole wheat on per row basis and the grain yields of maize in I62 and I124 were 16.8% and 15.0% higher, respectively, than that of sole maize. Thus, increased radiation capture was the primary factor responsible for the high productivity of the wheat/maize intercropping systems. A simple model was developed to estimate radiation interception and partitioning in strip intercropping systems, considering the heterogeneity of leaf distribution in both the horizontal and vertical directions. The model may also be applicable to other strip intercropping systems. [ABSTRACT FROM AUTHOR]

The integration of water footprints and virtual water flows allows the mapping of the links between production, trade, and consumption and could potentially help to alleviate water scarcity and improve water management. We evaluated the water footprints and virtual water flows of crop production, consumption, and trade and their influencing factors in the Hetao irrigation district in China for 1960–2010. The water footprint of crop production and the export of virtual water fluctuated but tended to increase during this period and were influenced mainly by agricultural factors such as crop yield, irrigation efficiency, and area sown. The water footprint of crop consumption and the import of virtual water increased during 1960–1979 and decreased during 1980–2010 and were influenced by socio-economic factors such as total population, the retail-price index, and the proportion of the population in urban areas. Most of the water footprint of production was exported to other areas, which added to the pressure on local water systems. The import of virtual water led to a saving of water for the Hetao irrigation district, while its share of the water footprint of consumption has decreased significantly since 1977. An increase in irrigation efficiency can alleviate water scarcity, and its application should be coupled with measures that constrain the continued expansion of agriculture. Full-cost pricing of irrigation water was an effective policy tool for its management. Re-shaping regional water-production and water-trade nexuses by changing crop structures could provide alternative opportunities for addressing the problems of local water scarcity, but the trade-offs involved should first be assessed. [ABSTRACT FROM AUTHOR]

Agriculture is not only the basic guarantee for human survival, but also the basis for the economy development and ecology construction. Water use and carbon emissions in grain production will largely determine China's transition to "green". On the basis of finding out how much water is consumed and how much carbon is emitted by grain cultivation, and then finding out whether and what extent water use and carbon emissions affect economic-ecological development in China. This study uses the Tapio decoupling model to calculate the decoupling status of the grain water‑carbon footprint and economic-ecological development in mainland China from 1998 to 2020. Then the Logarithmic Mean Division Index (LMDI) model is used to analyze the drivers of the change of water-economy decoupling status. The results show that the grain water‑carbon footprint is well decoupled from economic development, most decoupling states are absolute decoupling (− 3 < e < 0) and relative decoupling ① (0 < e < 1). The grain water‑carbon footprint decoupled from ecological development is weak, and the decoupling coefficient has significant spatio-temporal differences. The agricultural production technology is the main positive driver for the decoupling between grain water footprint and economic development in mainland China (− 1 < e B < 0). And the economic development scale is the main restraining factor for the decoupling between grain water footprint and economic development (0 < e C < 1). All provinces in mainland China need to correctly handle the relationship between economy-ecology development and grain security, and take water conservation and carbon emission reduction as an important starting point for adjusting the industrial structure, so as to achieve "green" development. The grain water‑carbon footprint was calculated in an integrated manner, and then based on the calculation of the decoupling situation, the drivers of the decoupling situation were further assessed. [Display omitted] • Research from the perspective of the agriculture-economy-ecology coupling system. • Heilongjiang has the largest grain water footprint and Henan has the largest grain carbon footprint. • Grain water-carbon footprint is better decoupled from economy and is weaker decoupled from ecology. • Agricultural production technology is the main driver for the decoupling between grain water footprint and economy. [ABSTRACT FROM AUTHOR]

A comprehensive assessment of the regional water-saving potential (WSP) for crop production is the foundation for setting targets, formulating strategies, and implementing management measures for agriculture. Water footprint (WF) for crop production is a well-known indicator of blue and green water consumption and an effective tool for evaluating blue and green WSP in crop production. The WSP evaluations based on crop WF primarily rely on crop redistribution (CR) and the crop WF benchmark (WFB). The CR can be completed relatively quickly, but the WSP is limited. In contrast, reaching an area's maximum WSP is possible with WFB, but it requires long-term and multi-aspect inputs. However, existing evaluations of regional crop WSP are often based on a single methodology, and the results are various, which confuse the policymakers at times. This study estimated both blue and green WSP of wheat and maize based on two approaches—crop redistribution (CR) and crop water footprint benchmark (WFB)—at the county level in the Yellow River basin (YRB) in different hydrological years. The WSP was 7–11% based on CR, whereas 17–24% based on the crop WFB. The green WSPs were larger than blue WSPs. Over half of counties had larger WSP based on the WFB. These values vary with the crop, region, and hydrological year. The analysis emphasises the importance of considering both blue and green water, and quantitatively comparing different water-saving methods when evaluating regional crop WSP. [Display omitted] • Crop blue and green water-saving potentials (WSPs) were assessed via two methods. • The two approaches were crop redistribution and water footprint benchmarking. • The approach with most water-saving potential varied with crop, region, and year. • Combination of two approaches provided both water saving and crop yield increases. [ABSTRACT FROM AUTHOR]

• Intercropped wheat had higher water use efficiency than sole wheat. • Wheat outcompeted maize for soil water during the co-growth period. • Transpiration was higher in wheat border rows than sole wheat, especially during the dry period. • A method for evapotranspiration partitioning in wheat/maize strips was proposed. Climate change will likely intensify water shortages, so more attention should be given to the efficient use of agricultural water in agricultural production, especially under rainfed conditions. Therefore, studying and understanding crop water consumption amounts and patterns is of great importance. However, the amount of water consumed by the component crops in strip intercropping systems has received little attention. To close this knowledge gap, a two-year field experiment of sole wheat (Triticum aestivum L.), sole maize (Zea mays L.), and wheat/maize strip intercropping was carried out under rainfed conditions. Soil water content, sap flow, soil water evaporation, and evaporation of canopy interception were measured both in intercrops and sole crops. Soil water movement between strips, evapotranspiration components, and water use efficiency were calculated. Compared with corresponding sole crops, intercropping increased water consumption of wheat and maize during the growing period of each crop. Intercropped wheat obtained soil water from the adjacent maize strip during the co-growth period, while intercropped maize obtained soil water from the adjacent wheat strip after wheat harvest. The amount of water obtained by maize was much less than the amount of water obtained by wheat. The transpiration of intercropped wheat was greater than that of sole wheat, but the transpiration of intercropped maize was lower than that of sole maize. Compared with sole cropping, intercropping increased the sap flow rate of wheat in border rows but reduced sap flow rate of maize in border rows, and this phenomenon was pronounced in the case of drought. After wheat harvest, soil water evaporation from the intercropped wheat strip was less than that from sole wheat, and evaporation from the intercropped maize strip was significantly higher than that of sole maize. The two-year average water use efficiency of intercropped wheat was 32% more than that of sole wheat, and water use efficiency of intercropped maize was 10% less than that of sole maize. These results can improve the understanding of water consumption in wheat and maize of intercropping from the point of evapotranspiration partitioning, and provide implications for water management of intercropping system under rainfed conditions. [ABSTRACT FROM AUTHOR]

• Machine learning models of crop water footprint are evaluated in time and space. • Optimal model types differ by crops, water supply scenarios and spatial scales. • The feature variables of spatial and temporal categories are more important. Crop water footprint (WF) calculation via physical process-based crop or hydrological models has basic requirements in terms of cost, time, and knowledge threshold. It is unsuitable for laypersons such as policymakers or cross-disciplinary researchers. Here, machine learning (ML) is an effective solution owing to low cost, high speed, and low processing difficulty. However, the feasibility and applicability of ML modeling for crop WFs at multiple spatial scales remain unverified. Here, we quantitatively evaluated the applicability, optimal model parameters and importance of the feature variables of four ML methods, including random forest (RF), light gradient boosting machine (LightGBM), generalized additive model (GAM), and artificial neural network (ANN), for constructing WF models for crop production at site and provincial scales. The models were tested through the case study for major grain crops (wheat, maize, soybean, and rice) in China over 2000–2019, distinguishing between irrigated and rainfed crops and between different irrigation methods. The findings show that the WF simulation accuracy for the irrigated scenario was higher than that for the rainfed scenario. The type of feasible ML model varied with crop types, variable combinations, water supply scenarios, and spatial scales. At the site scale, the RF model was generally suitable for simulating WF of maize, soybean, and rice, with R2 values ranging from 0.7 to 0.78 under different irrigation scenarios; the LightGBM was more suitable for simulating wheat with R2 values ranging from 0.76 to 0.82. The LightGBM was deemed to be the best model at the provincial scale, with some regions presenting a 50% lower root mean square error in the crop WF simulation than in RF. Variables related to spatio-temporal class feature were found to be the most important in both the RF and LightGBM simulations. This study provides a global methodological reference for different countries or regions to establish methods for rapid WF assessments in crop production with cross-disciplinary researchers or macro policymakers as the target users. [ABSTRACT FROM AUTHOR]

Blue water (irrigation water) and green water (soil moisture), as natural bases in crop production, are vulnerable to natural and socioeconomic disturbances. However, quantitative resilience assessments of blue and green water for crop production are still lacking. Here we constructed a social-ecological based general water resilience assessment framework that distinguishes blue and green water for crop production in four dimensions, including resistance, absorptive capacity, adaptive capacity and transformative capacity. The framework was applied to quantify the spatiotemporal characteristics of water resource resilience for three staple crops (rice, wheat, and maize) at provincial level in mainland China over 2000–2017. Results indicate that water resilience related to crop production of China as a whole was at the lower-middle level over the study period. The green water resilience had higher initial performance, while the blue water resilience had a faster growth rate (>50%). The performance of adaptive and transformative capacity was 8.9∼153.7% better than resistance and absorptive capacity. There were significant heterogeneities in the water resilience score among crops and in time and space. Wheat had the highest resilience of green water, while its blue water resilience was the lowest among the three crops. The water resilience for crop production varied by up to 2.4-fold across provinces. Synergies and trade-offs among the four dimensions of water resilience were further evaluated. The current study provides an effective approach for assessing the state and progress of resilience of regional water resources for crop production. [Display omitted] • Spatiotemporal resilience of blue and green water for crop production was evaluated. • Crop-related water resilience in China was at the lower-middle level. • Blue water resilience increased by over 50% over 2000–2017. • Adaptive and transformative capacity exceeded resistance and absorptive capacity. [ABSTRACT FROM AUTHOR]

The water footprint (WF) of crop production is a measure of the volumes of blue water (irrigation water) and green water (effective precipitation) consumed during crop growth. Setting the WF benchmarks of crop production in an irrigation district, exploring the optimal tillage practices, and clearly specifying blue and green water-saving potentials (WSPs) are essential for efficient utilization and reasonable allocation of agricultural water resources. However, related studies disregarded the WF benchmark setting according to tillage practices and the corresponding WSPs at the irrigation district scale. Meanwhile, the evaluation of WSP is limited to blue water. Considering summer maize and winter wheat grown in Baojixia Irrigation District (BID) of Shaanxi Province in China as the study case, this study aims to evaluate the gross irrigation WSP, actual blue and green WSPs based on crop WF simulation and WF benchmark setting for the "best" tillage practice. Eighteen water-saving tillage practice scenarios were set considering three irrigation techniques, three irrigation strategies, and two mulching practices. Results show that crop responses to different tillage practices differ. Maize WF has low sensitivity whereas wheat WF shows a significant difference following a change in irrigation techniques. In the practice under 40% deficit irrigation with no mulching, there is the highest actual WSPs, but at the cost of at least 57% reduction in crop yield. Whereas the practice of 20% deficit irrigation, furrow irrigation, and mulching has no yield reduction and relatively low WF, which can save 20% blue water and 8–12% green water in the BID, which is the optimal balance point between the yield and water consumption of the two crops. From the perspective of crop WF, this study quantified the agricultural WSPs of different water resources, and formulated a method for evaluating agricultural WSPs based on set WF benchmarks, to provide reference for building a water-saving culture, and sustainable development. [Display omitted] • Crop water footprint benchmark is set by 18 tillage practices for an irrigation district. • Responses of crop water footprint to the same tillage practice is diverse by crop. • Maximize the water-saving potential could be at the cost of production reduction. • The set water footprint benchmarks should balance yield with water-savings. [ABSTRACT FROM AUTHOR]

Crop water productivity is an important indicator of agricultural water use. Understanding the impacts of climatic and agricultural factors variation on crop water productivity will provide a theoretical basis for regional crop productivity improvement. In this study, crop productivities at two scales were estimated based on the analysis of the agricultural water use in Hetao irrigation district, China. The sensitivity analysis was used to explore the sensitivity of crop water productivity to the variation of climatic and agricultural factors. Contribution rate analysis method was adopted to quantitatively evaluate the driving force of water productivity changes due to the variation of climatic and agricultural factors during the study period. Results show that crop water productivity of wheat had an average of 0.85 kg/m 3 over the study period at the field scale, and it had an average of 0.46 kg/m 3 at the regional scale. Both displayed an obvious upward during the study period. Among the climatic factors, water productivity of wheat at both the field and regional scales had higher sensitivity to relative humidity and wind speed, and had a lower sensitivity to sunshine hours. Among the agricultural variables, the crop water productivity had a higher sensitivity to irrigation efficiency, and is less sensitive to the amount of fertilizer used. The increase of agricultural inputs and irrigation efficiency were the main factors contributing to water productivity increases in Hetao Irrigation district. Climatic variations within the study period had less impact on the water productivity of wheat. [ABSTRACT FROM AUTHOR]

[Display omitted] • Urbanisation was a core driver of staple crop WFSS in water scarce provinces. • Population and social urbanisation enhanced China's staple crop WFSS. • Economic and spatial urbanisation reduced crop WFSS. • This work challenged the conventionally urbanisation-water relationship. Rapid urbanisation in developing countries has exerted ever-increasing pressure on food and water resource systems. Existing studies mostly focus on impacts of population urbanisation on agricultural water use, disregarding the multidimensional characteristics of urbanisation. Accounting for four dimensions of urbanisation: population, economy, spatial distribution, and society, we assessed the impact of multidimensional urbanisation on the water footprint self-sufficiency rate (WFSS) of three staple crops, that is, the ratio of the water footprint (WF) of crop production to the WF of crop-related consumption, through the case for China over 2000–2017. The socio-economic driving factors and spatial heterogeneity of crop WFSS were further tested. Results show that <30% of high-crop WFSS provinces supplied more than 70% of low-crop WFSS provinces. Social urbanisation and economic urbanisation were the governing positive and negative driving factors of the rice WFSS, respectively. Population urbanisation was the dominant factor attenuating wheat WFSS during the study period, while playing a reverse role in maize WFSS. Impacts of different dimensions of urbanisation on crop WFSS were heterogeneous and even contradictory depending on the crop type, the different processes of urbanisation, and the water endowment and economic level of the provinces. The quantile regression results further indicate that population urbanisation, spatial urbanisation and social urbanisation had greater impact on the higher WFSS (i.e., resulted in virtual water export) of rice and wheat. The current analysis challenges the conventionally monotonous urbanisation-water relationships, and suggests that additional dimensions of urbanisation should be considered when assessing the effects of urbanisation on agricultural water use. [ABSTRACT FROM AUTHOR]

• The rising trend of yield was in most regions of China caused by climate change. • The decreasing trend of water footprint was more obvious in RCP8.5 scenario. • Full irrigation could mitigate the reduction in yield caused by climate change. • Increasing irrigation cannot greatly reduce the water footprint in humid regions. Agriculture is the sector most sensitive to climate change. It is of great significance to explore the response characteristics of crop water footprint (WF) in rain-fed and irrigation agriculture to climate change for guiding agricultural production. This study coupled and downscaled the meteorological data from 31 global climate models (GCMs) under two Representative Concentration Pathways (RCPs) in China, and used crop growth model AquaCrop in large scale to quantify the changes in yield and WF of maize in China from the 2030s to the 2090s. The Monte Carlo Method was used to calibrate the crop parameters in AquaCrop model, which improved the accuracy and spatiotemporal resolution of the crop model. Results showed that precipitation and temperature would increase in most regions in China, which was more obvious in the RCP8.5 scenario. Meanwhile, climate change resulted in larger crop evapotranspiration (ET c) for maize in the north than south. In the future, the increase of ET c in Southwest China would be relatively larger, while that in Northwest China would decrease. Maize yield would generally increase in most regions except for central China, where illustrated that increases in the north was greater than in the south. In terms of irrigation strategies, full irrigation could mitigate the reduction in maize yield caused by climate change. However, increasing irrigation would have fewer benefits to maize yield in humid regions compared with arid and semiarid regions in China. In addition, increasing irrigation could not greatly reduce the WF of maize in humid regions. Due to different climatic and hydraulic soil characteristics in each region, the effects of climate change and irrigation strategies on WF of maize would vary in different regions. This study provided irrigation strategies guidance to mitigate the adverse effects of climate change on agricultural production and its water use. [ABSTRACT FROM AUTHOR]

Owing to increasingly limited water resources, evaluating large-scale regional crop water footprints (WFs) within acceptable errors is the basis for efficiency and productivity improvements for sustainable agriculture. However, quantitative sensitivity analysis of outputs to inputs and parameters of advanced and widely used crop WF accounting models are still lacking. In this study, we evaluated the spatial and temporal sensitivity of the blue and green WFs of crops to key input variables based on year-by-year simulations for wheat, rice, maize, and soybean production in China from 2010 to 2019. We employed one of the most widely used AquaCrop models to test different water supply and irrigation scenarios. Nine input variables or model parameters were selected, including reference evapotranspiration (ET o), crop transpiration coefficient (Kc Tr), soil evaporation coefficient (K E), maximum canopy cover (MCC), precipitation (PR), canopy decline coefficient (CDC), planting density of the crop (DC), reference harvest index (HI 0), and normalised water productivity (WP*). The results showed that crop WFs are generally more sensitive to ET o among the input variables and Kc Tr and K E among the model parameters. We also found that the blue WF was more sensitive than the green WF. In most cases, WFs in rainfed scenarios were more sensitive to changes in input variables compared to WFs of irrigated crops. Of the four studied crops, the WFs of maize and wheat were more sensitive than the WFs of rice and soybean. Wheat, maize, and soybean also showed a visible spatial variation in the sensitivity of the WF to each input variable. Overall, the WF sensitivity was influenced by crop type, water supply, irrigation method, and regional climate features. The current analysis provides a feasible approach to comprehensively identify the key inputs and parameters to be calibrated for accurate crop WF accounting. [Display omitted] • Sensitivities were tested for crop water footprint simulation by AquaCrop model. • Water footprints were generally most sensitive to reference evapotranspiration. • Sensitivities of water footprints differ by crop types and by irrigation methods. • Sensitivities of water footprints of a same crop varied in time and space. [ABSTRACT FROM AUTHOR]

• System boundary of crop water (WF) and carbon footprint (CF) accounting is extended. • Production and consumption of agricultural inputs are accounted in crop WF and CF. • Agricultural inputs constitute up to 24% of WF and 89% of CF in a Chinese province. • Agricultural inputs define the overlooked environmental burden shifts in food system. Crop production is the biggest water user and key contributor to anthropogenic greenhouse gas emissions. Increasing crop yields to ensure adequate food supply under water and land scarcity is excessively dependents on intensive agricultural inputs (such as fertilizers, pesticides, agri-films, or energy), resulting in unintended environmental consequences. Supply chains bringing environmental-intensive inputs from their place of production to the croplands. However, most food-related environmental assessments ignore the environmental burden of agricultural input production, trade, and consumption. Here, we estimate spatially-detailed water (WF) and carbon footprints (CF) of wheat, maize, and rice production in China with extended system boundary from upstream raw material mining to the field. The agricultural inputs account for up to 24% and 89% of a crop's WF and CF, respectively, at the provincial level. The total local generated WF in Chinese northern provinces and CF in Shanxi and Inner Mongolia provinces for producing crops and agricultural inputs transgresses the corresponding downscaled blue water and carbon planetary boundaries. The study broadens the scope of traditional environmental impact assessments in agricultural production and sheds light on the significances to manage the linkages between the crop production and the agricultural inputs' upstream supply chains towards more efficient water use and less greenhouse gas emissions in food system. [Display omitted] [ABSTRACT FROM AUTHOR]

• Values of green water used in crop production are estimated accounting for costs. • Values of crop-related blue and green virtual water flows are compared. • Visible trade-offs between volume and value of water for crop production are observed. • Regional values of water are more sensitive than volume of water to future changes. Blue water (irrigation water) and green water (rainwater) constitute the indispensable inputs in crop production, and they virtually flow through crop trade. The valuation of water for crops is becoming essential for providing not only guidance in measuring both the biophysical and economic sustainability of agricultural water resources but also crucial information for investors and authorities engaged in water allocations. However, valuation of green water has been severely disregarded. Here, taking the Yellow River Basin as the study case, we show the feasibility of estimating the value of green water for crop production considering the costs in production processes in addition to blue water valuation. Thus, the volume versus value of blue and green water consumed in crop production as well as that of corresponding virtual water (VW) flows related to crop transfers within the basin are comparable. Fourteen major crops in current three typical years and four scenarios for the year 2050 under climate-socio-economic changes are examined. Results show that value of blue water was approximately 3 times that of green water for irrigated crops, whereas at similar level to the value of green water for rain-fed crops. Visible trade-offs between the regional volume and value of water used in crop production and that of the intra-national VW flows exist in terms of magnitude in time and space, as well as the structure by crops. The total volumes of the water footprint (WF), i.e., water consumption, in crop production and VW exports changed little over years, however the corresponding total water values was tripled and seven-folded, respectively, due to apple production expansions. Wheat was the biggest contributor in volume of VW export while apple accounted the most in value of VW export of the basin. The considered scenarios for 2050 suggested that the reduced values of crop-related WF and VW flows were more sensitive than the corresponding water quantity. This study implies the importance of managing the internal trade-offs or mutual effects between water resources and economic returns. [ABSTRACT FROM AUTHOR]

Water consumption in grain production consists of blue (i.e., surface water and groundwater) and green water (i.e., rainwater), however, is rarely distinguished in existing emergy analysis. Taking four major grain crop production systems (rice, wheat, maize, and soybean) by provinces in mainland China over the period 2001–2016 as the study case, in this study the blue and green water were differentiated, for the first time, in the emergy analysis for crop production systems based on water footprint assessment. Three indicators were estimated per crop per province per year: water resource emergy input (WEI), water resource emergy contribution ratio (WECR), and water resource emergy use efficiency (WEUE). Results show that during the study period, the total WEI into the major grain crop production systems increased by 16.61%; blue and green WEI accounted for 52.64% and 47.36%, respectively, by 2016. Although the blue WECR was higher than green WECR, it decreased significantly over the study period. The annual average green WEUE was 10.99 sej sej−1, 7.7 times the blue; moreover, it increased by 27.28% over the study period. The annual average total WECRs in nine provinces were higher than the national average, but the corresponding total WEUEs were lower than the national average; of these, four were distributed in arid and rainwater-deficient areas of northwest China. The emergy analysis of blue and green water separately provides information for a more precise and efficient water allocation as well as better cropping structures given corresponding water endowments. [Display omitted] • Blue and green water were distinguished in water emergy analysis for crop production. • Three emergy based indicators were estimated to measure the water use efficiencies. • Visible spatial and temporal heterogeneities were shown in crop-related water emergy. • Blue water and green water have different emergy in crop production systems. [ABSTRACT FROM AUTHOR]

The water footprint (WF) of crop production indicates the water consumption for crop growth in a specific area over a certain time, enabling comprehensive water use efficiency assessments to be achieved for different types of water in an irrigation district. Daily and monthly blue (irrigation water) and green (rainfall) water resources are unevenly distributed in monsoon climate areas. However, the intra-annual evolution of the WF of crop production for a monsoon irrigation district is lacking. In the current study, maize and wheat production in the Baojixia Irrigation District (BID) of Shaanxi in China selected as the case study for the period 2008–2017, where the WF of crop production was analyzed based on a regional distributed hydrological model and the associated meteorological driving factors on daily, monthly, and yearly scales were identified. Results reveal that the method of WF of crop production established in the study can be applied to hydrological simulation of irrigated areas without drainage system. The blue WFs of maize and wheat production accounted for 34% and 36% of the irrigation water supplies, respectively. On a yearly scale, precipitation had the greatest impact on the green and blue WFs of maize, while sunshine hours and temperature had the greatest impact on those of wheat, respectively. On daily and monthly scales, different meteorological factors played key roles in the WF of crop production in different typical years. The time scale effect existed in the impact of meteorological driving factors on the WF of crop production, reaching its maximum on a monthly scale. Both water shortages and water waste coexist in BID. The irrigated area should rationally allocate blue water and effectively utilize green water resource to improve crop yield. Meanwhile, the time scale effect in the WF assessment of crop production and driving factors cannot be neglected. The irrigation strategy should be adjusted to cope with the impact of meteorological conditions according to the results and actual situation. [Display omitted] • Daily and monthly water footprint of irrigated crops were analyzed. • Precipitation had the largest effect on the water footprint of maize. • Sunshine hours and temperature effected largest on the water footprint of wheat. • Monthly time scale effect of meteorological factors on water footprint was larger. [ABSTRACT FROM AUTHOR]

Here we identified and evaluated the strengths and spatio-temporal heterogeneities in 12 main socio-economic driving factors of water footprints and inter-provincial virtual water flows related to three staple crops (rice, wheat, and maize) within mainland China for 2000–2017, in consideration of the infrastructure related to irrigation, agricultural electricity and road for the first time. The irrigation, agricultural electricity, and road infrastructures in China expanded by 33.8, 4.5, and 2.4 folds, respectively, throughout the course of this study. The results show that irrigation infrastructure in water-scarce regions was the most critical driver for the effective reduction of the water footprint per unit mass of crops, particularly the blue water footprints (i.e. increasing water efficiency). As the irrigation infrastructure per unit area doubled for 2000–2008, blue water use efficiency and total blue water consumption decreased by 58% and 71%, respectively. However, the development of irrigation infrastructure has led to a larger total water footprint in crop production. Agricultural electricity and road infrastructures had increasing effects on provincial virtual water export, with varied corresponding driving strengths across spaces. The visible effects of agricultural infrastructure on regional water productivity, water consumption, and virtual water patterns should not be neglected. This analysis suggests that investments in agricultural infrastructure should consider the spatio-temporal heterogeneity of these infrastructures on local water productivity and water consumption in addition to the economic benefits. [Display omitted] • Agricultural infrastructure is core driver for water in crop production and trade. • Irrigation infrastructure lowers water per crop but enlarges regional water consumed. • Spatiotemporal heterogeneities are in driving forces for crop water consumption. [ABSTRACT FROM AUTHOR]

• Quantification of water footprint for three crops during 2002–2018 were reviewed. • Approaches to water footprint quantification were divided into five types. • Results are affected by spatial scale and the type of approach. The water footprint (WF) of crop production has been widely accepted as a comprehensive indicator of agricultural water consumption. Rationality and accuracy in crop WF accounting are thus prerequisites for implementation of WF assessments that yield sustainable regional agricultural water management. However, few studies have focused on the rationality of multiple quantitative approaches and the associated differences in crop WF accounting among different studies. Here we, focusing on maize, wheat and rice, review quantitatively the effects of different quantification approaches and scales on the results of crop WF accounting and simulations in relevant published research during 2002–2018 worldwide. Results show that (i) The number of studies on crop WF accounting has increased by 17 times since 2002 (~the year of creation of WF concepts); the research direction is focused on improvement of quantification and resolution in both time and space. (ii) The current approaches to WF calculation can be divided into five main types: the field crop water requirement (FCWR) approach, field soil water balance (FSWB) approach, regional water balance (RWB) approach, remote sensing (RS) approach and field measured water balance (FMWB) approach. The FCWR and FSWB approaches are more widely adopted than the other three. (iii) There were non-negligible differences in the WF accounting results among approaches and scales. At the global level, the deviations in WF for maize, wheat, and rice were relatively low among different studies, with the world average values of 0.73 m3 kg−1 ± 14.9%, 1.136 m3 kg−1 ± 13.5%, and 1.269 m3 kg−1 ± 27%, respectively. The ranges of uncertainty varied significantly when downscaling to specific countries and provinces. The maximum coefficients of variation (CV) of WF for maize, wheat, and rice in different regions were up to 40%, 49%, and 50%, respectively. (iv) The WF simulations showed very reasonable agreement and lower deviation between the FCWR and FSWB approaches. [ABSTRACT FROM AUTHOR]