Green Water Footprint Research Articles

Spatio-temporal variability and trend of water footprints in the upper Awash basin, central Ethiopia

The water resources in the upper Awash basin in central Ethiopia are intensively utilized by the densely populated urban centers and extensive agricultural activities in the wide rift plains surrounding the major cities. The green, blue, grey and total water footprints of major crops dominantly cultivated in the sub-basin (teff, maize, sorghum and sugar cane) are characterized. The water footprints were analyzed for the period 2000 to 2010 using climatic as well as soil and crop yield data from the Debrezeit, Wonji, Melkassa and Metehara stations. The temporal and spatial variations of total water footprints (TWFs) in the basin were analyzed and mapped. The temporal trends of the Water Footprints (WFs) are interpreted using Mann-Kendall and Sen’s slope tests. The crop production in the sub-basin mainly depends on green water consumption. Teff and sorghum crops in the climatically similar Debrezeit and Melkassa areas had relatively higher TWFs (4205 m3/ton and 2539 m3/ton, respectively) compared to maize. Blue water requirement to supplement rainfed agriculture decreases from Metehara, Melkassa, Wonji to Debrezeit in that order. The TWF of irrigated sugarcane (117–212 m3/ton) is less than those of rainfed crops such as maize which has a minimum TWF of 1752 m3/ton. The spatial and temporal variations in WFs in the sub-basin are determined by both climatic (effective rainfall, evapotranspiration, length of wet spell and length of growing period) and non-climatic parameters (such as fertilizer consumption, soil types, crop yields and agricultural management practices). Our results suggest cultivating less water-intensive, high-yield crops can significantly decrease the TWFs in the sub-basin. The results could be used to develop well-informed regional and national freshwater resource management policies. More broadly, our novel approach of characterizing WFs at the sub-basin scale using limited amount of locally measured data sets could be a useful tool in other parts of the world where locally measured data sets are scarce.

Exploring the environmental impact of crop production in China using a comprehensive footprint approach

The carbon-nutrient-water cycles of farmland ecosystem not only provides support for crop production, but also has an impact on the environment. Comprehensively quantifying the impact of crop production on the environment can provide a basis for crop sustainable production. A series of environmental footprint approaches, including carbon footprint (CF), nitrogen footprint (NF) and water footprint (WF), were optimized to evaluate greenhouse gas (GHG) emissions, reactive nitrogen (Nr) loss and water resource consumption in crop production, and a comprehensive footprint method based on Endpoint modeling was proposed to evaluate the overall environmental impact of crop production in China. The CF, NF and WF of 28 forms of crop production varied from 1206.29 kg CO2 equivalent (CO2-eq) ha−1 of oil crops to 7326.37 kg CO2-eq ha−1 of fiber crops, 16.07 kg Nr-eq ha−1 of oil crops to 60.70 kg Nr-eq ha−1 of sugar crops, and 4032.04 m3 ha−1 oil crops to 12,476.28 m3 ha−1 of sugar crops, respectively. The contribution of each component to footprints varied greatly among different crops, and fertilizer manufacture, NH3 volatilization and green WF were generally the main contributors of CF, NF and WF, respectively. The total GHG emissions, Nr loss and water consumption were estimated to be 670.11 Tg CO2-eq, 5.50 Tg Nr-eq and 837.06 G m3 for all crop production of China. The greenhouse vegetable with the highest area-scaled comprehensive footprint was 4.5 times that of the oil crops which had the lowest one. The contribution of crop production to the corresponding environmental impact in China was as low as 3.7%, of which NH3 volatilization contributed 48% and grain production contributed 72%. Mineral N fertilization was the main driver of the variation of comprehensive footprint between provinces, with reduction of N fertilizer application as an important way to reduce the environmental impact of crop production.

Multimodel quantification of green and blue water components and its error propagations through parameter transferability approach across input choices

A robust quantitative assessment of water security through efficient water accounting concepts like blue and green water footprints has gained a lot of attention for water resources management at river basin scale. However, such water accounting tools and models have dependencies to the choice of precipitation data used to drive the model, as the input bias propagate into simulated streamflow through interaction with different hydrological processes. This study performs a holistic investigation of sensitivity of water accounting fractions like blue water flow (BWF), green water flow (GWF), green water storage (GWS), and their dependencies on secondary precipitation datasets (SPDs) choices using a lumped conceptual rainfall-runoff model [Hydrological Simulation model (HYSIM)] and a physically based semi-distributed hydrological model [Soil and Water Assessment Tool (SWAT)] in the Damodar River basin, India. These models were driven by seven gridded precipitation datasets, including India Meteorological Department (IMD) data, Indian Monsoon Data Assimilation and Analysis (IMDAA) data, Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) data, Watch forcing ERA-Interim data, Climate Hazard Group Infrared Precipitation with Station data (CHIRPS), PRINCETON precipitation data and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Records (PERSIANN-CDR) data. The reference IMD based multimodel results revealed that the annual average blue and green water components of the Damoder River were in the range of 558–656 mm/year, 574–728 mm/year and 34–112 mm/year for BWF, GWF, and GWS respectively during 1994–2010 period. The results obtained after applying parameter transferability approach across the input space have revealed exact quantification of choice dependent annual variations in spatial and temporal characteristics of BWF, GWF, and GWS. A further evaluation based on error propagation ratios (γCC, γrRMSE, γB) has revealed a quantification of input choice induced dampening/magnification effects on flow estimations of both the HYSIM and SWAT and these quantifications were free from the compensation effects of recalibration. The findings in this study demonstrate that the change in annual average BWF varies between −46.97% to +41.38% in comparison to benchmark IMD simulations, and the corresponding changes for GWF is between −19.63% and +17.06% and for GWS is between −29.97% to +35.5% with different choices of SPD scenarios. The systematic (γB) and random (γrRMSE) error propagation factors during monsoon season are larger for SWAT model ([0.21–0.78], [0.69–0.89] respectively) than that of HYSIM model ([0.18–0.74], [0.66–0.81], respectively) and it is varying with choice of different SPDs.

Sustainability of the Water Footprint of Various Soil Types on Oil Palm Plantations

There are significant studies that have quantified oil palm water footprint as an indicator of environmental sustainability but an estimation of water footprint under varying soil types furthermore is still limited. The objectives of the study were to estimate whether annual variations of soil type and yields significantly effects for the oil palm water footprint. The data from three types of soil (spodosol, inceptisol, ultisol) were collected from an oil palm plantation in Pundu village, Central Kalimantan, Indonesia. To perform the water footprint analysis we utilize water balance accounting equations via application Cropwat 8.0. From that, we determine the crop irrigation scheduling to compute the blue, green, and grey water footprint of oil palm fresh fruit bunch in the area. Our analysis found that the actual evapotranspiration of spodosol and inceptisol have the same value: 1242 mm/year whilst ultisol is 1239 mm/year. The total water footprint of oil palm varied considerably with the largest value being 1310.04 m3/ton for ultisol. The actual evapotranspiration of spodosol and inceptisol have the same value of 1242 mm/year whilst ultisol is 1239 mm/year. The higher production resulted in a lower water footprint and vice versa. Moreover, the total water footprint from ultisol soil type has the highest value due to the lowest yields. The difference in evapotranspiration value resulted in the insignificant value of total water footprint. The lower water availability, the lower water use, and the higher actual irrigation requirement in oil palm plantation yet showed the unnotable impact on water footprint in different soil types for the oil palm plantation.

Explaining water security indicators using hydrologic and agricultural systems models

Water security plays an important role in socio-economic development, ecosystem management, and environmental sustainability. Over the last four decades, water security assessment has attracted much political and economic attention. An improved understanding of the relationships between water demand and supply is needed to mitigate the impacts of diminishing water resources. This study provides an overview of water security assessment by focusing on the various water security indicators and the concept of water footprint (blue, green, and grey water). The water security indicators based on the water footprint concept is currently receiving more attention because it accounts for the return flow from the total water withdrawn from a watershed. We also investigate the application of different physically-based hydrological models, such as Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC), on water security assessment at a regional to continental scale. However, hydrological/agricultural system models cannot quantify evapotranspiration from irrigation and rainwater separately. Therefore, independent quantification of blue and green water footprint from an irrigated field is challenging. For illustration purposes, we apply the fully distributed Agricultural Ecosystems Services (AgES) model in the Big Dry Creek Watershed (BDCW), an intensively managed and irrigated watershed located in semiarid Colorado. The results indicate that the blue water footprint is higher than the green water footprint in the watershed. In addition, the spatial distribution of grey water footprint is highly correlated with the amount of fertilizer application. The variation of grey water footprint among the irrigated fields is higher than blue and green water footprints. We conclude that applying a physically distributed model can provide useful insight into the impact of climate and anthropogenic activities on water security at different scales.

Assessing variation and driving factors of the county-scale water footprint for soybean production in China

Water scarcity and food security are major challenges facing the world in the 21st century. The water footprint provides a new and comprehensive approach for understanding the relationship between crop production and water utilization, and it has been used to estimate the water consumption of most crops at global and regional scales. However, the water footprint of soybean production (WFP) in China has not been extensively studied. Here, this study investigated firstly the components, spatial-temporal variation, as well as the driving factors of the county-scale WFP during the period of 1985–2015 in China. Annual WFP first increased and then decreased from 26.86 G m3 (109 m3) in 1985–24.62 G m3 in 2015. The WFP exhibited a clustered spatial distribution across the entire study area, and high-value areas for WFP were mainly distributed in the Northeast, North-central, and Middle and Lower Reaches of the Yangtze River Regions. The spatial distribution of WFP at the county level tends to be dispersed in studied period. The proportion of green water footprint (WFPgreen) reached as high as 70% of the WFP, whereas it decreased in the northern areas accompanied by the increased WFPblue proportion. Soybean yield was the major factor affecting WFP, and the increase in soybean yield contributed to the 32.80% decrease in the water footprint per ton soybean over the entire study period, further saved the 50.75 G m3 water resource for national soybean production in 2015. The results of this study provide new insights that could be used to improve agricultural water management, optimize regional water resource allocation, and alleviate water shortages in China.

An assessment of the urban water footprint and blue water scarcity: A case study for Van (Turkey).

Today, most of the world's population faces water scarcity, while global warming, urbanization, industrialization and population increases continue to increase the severity of the pressure on water resources. Management of water resources plays a key role in the sustainability of agricultural production. The water footprint (WF) is different in comparison to other water statistics because it takes direct and indirect water consumption into account, and helps in the management of water resources. Within this context, the WF of Van province, which is Turkey's most easterly located arid region, was calculated from 2004 to 2019. The study area covers lake Van, which is Turkey's largest lake, and the Van basin with an area of 23.334 km2 and a population of 1.136.757 (2019). In the calculations, crop (WFcrop), livestock (WFlivestock), and domestic and industrial water footprints (WFdomestic+industrial) were evaluated separately, and blue and green water footprints (WFblue and WFgreen) were analyzed in detail. According to the results, the average WF of Van province was found to be 8.73 billion m3 year-1. Throughout the province, 87.6% of the WF is composed of WFcrop, 4.9% is WFlivestock and 7.5% is WFdomestic+industrial. Of the WFcrop, 62.5% depends on WFblue, i.e., freshwater. Most of the WFlivestock consisted of dairy cattle (49%) and sheep (38%). The average WFdomestic+industrial for 2004 to 2019 was 0.64 billion m3 year-1. The average per capita water footprint of Van province was found to be 889.9 m3 year-1 capita-1. In addition, the province is classified as severe water scarcity (257%). This study is one of the first province-based calculations of WF in Turkey and is the first study to bring a different aspect to published literature by including residual soil moisture from the winter months. As a result of this study, the WFblue of the WFcrop is above the worldwide average and should be reduced by changing the crop pattern or synchronizing the planting and harvest dates of the crops to a period that benefits from precipitation. In addition, this study is expected to contribute to new studies for calculating the provincial scale WF and will have positive effects on agricultural planning, water allocation and the sustainability of water resources.

THE WATER FOOTPRINT IN CONTEXT OF CIRCULAR ECONOMY

Fresh water is the most used natural resource among the products we consume daily. Everything we eat or buy contains. But do we know how much water is needed to produce these goods? The concept of water footprint can help us find the answer to this question. Researcher at the University of Twente (Netherlands), Arjen Hoekstra, developed this concept in 2002. His goal was to show the impact on the amount of water that products in our lives contains. For a single product, the water footprint means the amount of water consumed and/or polluted at all stages of its production. It is measured in units of volume giving us an idea of the impact that a particular item has on the use of fresh water. Therefore, it takes into account the water used directly in production and the indirect part used in raw materials. The water footprint assessment method represents the volume of drinking water used either by a consumer or by a producer throughout the supply chain. By using this method, the volume of water is calculated by type of source, as well as the amount of water polluted, depending on the type of pollution, all these elements being specified spatially and temporally. The total water footprint of a product consists of three components: blue, green and gray water footprint. Assessing the water footprint of products and services is a good step towards evaluation of water circularity. The water footprint assessment must be integrated into the concepts of the circular economy by insisting on what happens to water after use and how circular and sustainable it is.

Distribution of Water Footprint Components of University Students and Detecting the Factors that Affect Those Components

20% of world population face the risk of disease and death due to the lack of access to healthy drinking water. A certain portion of water resources can no longer be used because of being polluted while some other parts pose danger for public health because of substructure incapacity. Water footprint is a remarkably crucial concept in terms of sustainable water management. Within the context of this study, consumption habits of university students and related changes in water footprint values have been investigated. Water Footprint Survey has been administered to participant university students and water footprint profiles of the students have been designed based on water footprint values computed according to survey results. At the end of the conducted analyses in Istanbul University-Cerrahpasa Avcilar Campus, mean annual rate of water footprint per person has been computed as 1848.78 m3 for students. Components of this water footprint has been designated as; green water footprint 1329 m3/per person/year, blue water footprint 199 m3/per person/year, grey water footprint 320.78 m3/per person/year. In addition, by transferring the data attained from surveys to IBM SPSS environment, presence and/or absence of a significant relationship between variables has been analyzed. It was then observed that parallel to the rise in students' income level a corresponding climb emerged in general water footprint.

Identification of Suitable Sites for Jatropha curcas L. Bioenergy Plantation Using the AquaCrop Model

Jatropha curcas (JC), as a biofuel plant, has been reported to have various desired characteristics such as high oil content seeds (27–40%), fast-growth, easy cultivation, drought tolerance, and can be grown on marginal soil and wasteland, requiring fewer nutrients and management and does not interfere with existing food crops, insects, and pest resistance. This investigation was the first study of its type to use climatological data, blue/green water footprints, and JC seed production to identify suitable sites for JC bioenergy plantation using the AquaCrop FAO model across the Khyber Pakhtunkhwa province in northwest Pakistan. The JC seed yield (10 ton/ha) was at a maximum in the districts of Bannu, Karak, Hangu, Kurram, North Waziristan, Lakki Marwat, South Waziristan, and Dera Ismail Khan, in addition to its frontier regions, Tank, Peshawar, Mohmand, Orakzai, Khyber, Kohat, Charsadda, Mardan, Swabi, and Nowshera, respectively. Green water footprint (264 m3/ton of JC seed) and blue water footprint (825 m3/ton) was less in these areas. Furthermore, the results revealed that, depending on climatological circumstances, the southern part of the Khyber Pakhtunkhwa province is more appropriate for JC bioenergy plantation than the northern region. The districts of Bannu, Karak, Hangu, Kurram, North Waziristan, Lakki Marwat, South Waziristan, Dera Ismail Khan, and its frontier regions, Tank, Peshawar, Mohmand, Orakzai, Khyber, and Kohat, in Khyber Pakhtunkhwa province were identified to be the most ideal places for JC bioenergy plantation. As a result, under the Billion Tree Afforestation Project (BTAP) and the Green Pakistan Project, the Forest Department of Khyber Pakhtunkhwa should consider planting JC species in the province’s southern region. Furthermore, this research will provide scientific information to government and private sector officials for better management and optimum yield of the JC biofuel crop, as well as for the promotion of energy forestry in Pakistan.

A water stress perspective on the UK’s water footprint

ABSTRACT The global water requirements of economic activities have been studied through the concept of the water footprint, which can be captured in multinational Input–Output (IO) frameworks. While useful for looking at aggregate requirements, this paper links the UK’s blue and green water footprint with a country-level water stress index. We show that more than half of the UK’s blue water footprint was in areas of high water stress, while its green water footprint is more concentrated in areas of lower water stress. These findings show how water stress can be incorporated alongside measures of water footprint. This can be critical in evaluating the success of policies aimed to improve national and international water security and reduce water stress.

Effects of agricultural activities on energy-carbon-water nexus of the Qinghai-Tibet Plateau

Energy, carbon, water and their interactions determine agricultural production efficiency and sustainability. On the Qinghai-Tibet Plateau (QTP), agricultural activities threaten the ecological security of the region, and agriculture itself is susceptible to climate change. In this study, we applied an energy-carbon-water nexus framework to assess the carbon emissions, water utilization, and energy flow, and their links with agricultural production on the QTP, using emergy analysis, footprint analysis (carbon footprint and water footprint) and a coupling model. The results showed that agricultural activities on the QTP released 2.17 × 1010 kgCO2-eq and absorbed 6.00 × 1010 kgCO2-eq, using 3.24 × 1022 sej of emergy and 8.19 × 109 m3 of water in 2018. Meanwhile, the energy-carbon-water nexus of agricultural production on the QTP was imbalanced, and the environmental footprint revealed large spatial heterogeneity at county scale. The coupling interaction among the energy-carbon-water nexus in agricultural production was investigated based on the coupling coordination model. Five categories of coupling interaction were identified by the degree of coordination. The largest emitter was agricultural input, especially electricity and nitrogen fertilizer, accounting for 24% and 7% of the total on average, respectively. With regard to emergy flows, renewable organic resources, accounted for 47%, making them the predominant in emergy inputs. The green water footprint (water from natural rainfall) at 51% was higher than the blue water footprint (water from irrigation) at 49%. More measurements to reduce carbon emission and improve the efficiency of energy usage and water usage are needed, such as optimizing planting patterns and structures, promoting cleaner energy, improving the efficiency of agrochemical use and proposing reasonable spatial planning for regional ecological development. Our findings provide a systematic reference for energy-carbon-water nexus analysis and sustainable agricultural development policy for decision-makers on the QTP.

Spatiotemporal variations of agricultural water footprint and its economic benefits in Xinjiang, northwestern China

Agriculture is the largest water user and is the main driving force behind water stress in Xinjiang, northwestern China. In this study, the water footprint (WF) (blue, green and gray WF) of main crop production and their temporal and spatial characteristics in Xinjiang were estimated in 2006, 2010, 2014 and 2018. The blue water footprint deficit (BWFd) was conducted and food productivity and economic benefits of WF were also analyzed via the water consumption per output value (food productivity and economic benefits). The results reveal that the WF increased from 22.75 to 44.16 billion m3 during 2006–2018 in Xinjiang, of which cotton, corn and wheat are main contributors of WF. In terms of different regions, corn has the largest WF in north Xinjiang and cotton has the largest WF in south and east Xinjiang. The BWFd broadened from − 11.51 to + 13.26 billion m3 in Xinjiang with the largest increased BWFd in Kashgar (from − 3.35 to 1.40 billion m3) and Aksu (from − 2.92 to 2.23 billion m3) of south Xinjiang and in Shihezi (from − 0.11 to 2.90 billion m3) of north Xinjiang. In addition, the water footprint food productivity does not well correspond with the water footprint economic benefits in prefectures of Xinjiang. It means we should consider the food yields priority and economic benefits priority to formulate a scientific and effective supervisor mode to realize the sustainable management of agricultural water in prefectures of Xinjiang.

Blue, green, and grey water footprints assessment for paddy irrigation-drainage system

Water footprint (WF) quantifies the impact of paddy field evapotranspiration (ET) and non-point source pollution on water resources and is an evaluation index for water sustainability. However, it is difficult to measure accurately using the existing method, which is based on parameter assumption without considering the field water conditions. In this study, a generic and physically based method for blue, green, and grey water accounting in paddy rice cultivation is introduced. We conducted field experiments using the common flood irrigation (CFI) and water-saving irrigation (SWI) modes in Nanjing, East China. By tracing the sources of ET and the migration process of multiple pollutants (TN, TP, NH4+-N, and NO3−-N), the characteristics of blue-green water consumption and the actual amount of water required to dilute pollutants at different growth stages of rice under CFI and SWI were analyzed. The WF of paddy rice was 1000 m3/t (49% WFgreen, 17% WFblue, 34% WFgrey) and 910 m3/t (50% WFgreen, 10% WFblue, 40% WFgrey) for CFI and SWI, respectively. The WF for paddy rice production was reduced by approximately 9% under SWI compared to CFI, with declines of 47% for WFblue and 8% for WFgreen. The SWI mode changed the ratio of blue to green water fluxes in field water by reducing irrigation during non-critical periods, and green water was used preferentially to enhance its utility. This conceptual method is the first to describe the formation mechanism of blue, green, and grey WFs in paddy systems. It can be extended to different scales and agro-ecosystems that show the influence of crop cultivation on water resources.

Water footprint of lemon production in Argentina

This work comes to fill a knowledge gap regarding the sustainability of the lemon industry. The motivation is the prominent role of the citrus sector in the economy of the northwest of Argentina and in the world: Argentina is the eighth largest producer of fresh citrus fruits, one of the four leading lemon-producing countries and the world's first lemon processor. A water footprint study is conducted to obtain relevant information on the water consumption and degradation associated with citrus production, according to the Water Footprint Network guidelines. A remarkable aspect is that most data used come mainly from actual practices and sources considering daily weather data of seven weather stations from 2012 to 2018. The green, blue and grey water footprints linked to the primary production of lemons are evaluated every year. The water footprint is distributed approximately in 69% (234 m3t−1) green, 8% (30 m3t−1) blue and 23% (82 m3t−1) grey. In addition, the Available Water Remaining (AWARE) indicator is used for outlining the blue water sustainability, resulting in a potential for blue water deprivation of 102 m3 world eq. per tonne of harvested lemons. This work is expected to serve as a baseline to provide diagnosis and improvement opportunities in the lemon sector for public and private stakeholders.

Estimation of the rice water footprint based on machine learning algorithms

It is essential to investigate the impact of climate change on the water footprint (WF) of rice from both historical simulation and future projections. In this study, four machine learning (ML) models, including random tree (RT), random forest (RF), additive regression (AR) and reduced error pruning tree (REPT) were used to model blue and green water footprint (BWFP and GWFP) for the present and future stages in the Yunnan Province, southwest China. Climate variables of daily precipitation, temperature, solar radiation, sunshine hours, wind speed, relative humidity and vapor pressure deficit data, yield and sown areas of rice were collected form 16 districts from 1990 to 2018. Six different scenarios (Sc1-Sc6) with different combinations of climate variables, crop coefficient and sown areas were used as inputs of the ML models for each of blue and green water footprint. Also, future climate projections of maximum (Tmax) and minimum (Tmin) temperatures, precipitation and sunshine were adopted for two different emission scenarios, RCP 4.5 and 8.5 from 2021to 2050, based on Geophysical Fluid Dynamics Laboratory (GFDL-ESM2M) model. For BWFP, the RT model in Sc1 with inputs of solar radiation, humidity, and vapor pressure deficit, was superior to the other scenarios with root mean square error (RMSE) and mean average percentage error (MAPE) values of 11.82 (m3 ton-1) and 0.5%, respectively. Sc4 (sown area, Tmin, sunshine hours) and Sc5 (sown area, Tmin, Tmax, crop coefficient) were the best two scenarios for all models applied for BWFP, while addition of precipitation to these two scenarios were the best for GWFP. Further, GWFP was highly negative anomaly in 2011 by 46%, 34% and 32% for the districts 5, 1 and 2 respectively, followed by 2010. Predictions of variable trends in the future showed that crop evapotranspiration during the growing season would increase in all the districts, although effective precipitation (Peff) would have both decreasing and increasing trends. Furthermore, BWFP and GWFP will have an upward trend in the future based on RCP4.5 in Sc4. This investigation addresses water footprint prediction which may assist in mitigation plans such as policies for sustainable water-use and development plans for food security.

An assessment of water footprint for irrigated rice in Punjab


 Water scarcity has become one of the highest risks for environmental and economic security worldwide. The water footprint for rice production, i.e., the total volume of freshwater consumed to produce a unit quantity rice has been estimated for three different agroclimatic zones of Punjab for the years 2000 to 2017. The results revealed that effective rainfall (Peff) improved in later years due to a change in crop calendar,legally enforced by an Act prohibiting the transplanting of paddy before a specified date. During the period of study, minimum crop evapotranspiration (ETc) was 4645 and maximum was ETc of 9511 m3ha-1 during 2014 and 2011, respectively. The green water footprint (WFgreen) for rice varied from 646litreskg-1of rice during low rainfall years (2012) to 1149 litre kg-1 of rice during heavy rainfall (1192 mm) during 2011.Out of a total water footprint (WFtotal) of 2650 litre kg-1, the share of blue water footprint (WFblue) was higher 1804 litre kg-1 (68%), indicating a need to improve on-farm irrigation management to conserve water resources.

Green water appropriation of the cropland ecosystem in China

Despite the awareness that green water is the main source of water to produce food, studies on green water use in cropland ecosystems are still rather limited, and almost no research has so far explored the relationship between green water utilization and socioeconomic development. In this study, with the help of CropWat 8.0, the green water footprint (GWF) of main crops in China was estimated from 1979 to 2016. On this basis, a novel concept, i.e., green water appropriation rate (GWar), was introduced to reveal the relationship between GWF and precipitation. Then, for the first time, the center of gravity trajectory of the GWar and the correlation between GWar and socioeconomic factors were further investigated. The results show that the provinces with the largest increases of GWF were Inner Mongolia (223%), Xinjiang (127%), and Ningxia (123%), while the GWF of 11 provinces has decreased, and 9 of them were municipalities or coastal areas. Generally, the GWar in the eastern and central provinces was higher than that in the western provinces. The center of gravity of the GWar has always been in Henan Province, but it has moved westward from Kaifeng City in 1979 to Sanmenxia City in 2016 and may further move to Shanxi Province soon. The total power of agricultural machinery and the effective irrigation rate had a positive correlation with the GWar, while the agricultural GDP was negatively correlated with the GWar. It is expected that the results will explicitly provide a scientific basis for the development of water-appropriate agriculture and the full utilization of rainwater.

Irrigation Scheme Selection Based on Water Footprint Analysis of Winter Wheat Production in Piedmont Plains of Hebei Province under Future Climate Scenarios

The statistical downscaling tool of a statistical downscaling model (SDSM) to generate the future climate of the piedmont plain area in Hebei Province for a 30-year period. The Xinji city was selected as a typical example of this area. The crop growth model of the decision support system for agrotechnology transfer (DSSAT) was adopted to estimate the changing trends of the water footprint of winter wheat production in this area under future climate conditions, and to obtain the optimal irrigation scheme of winter wheat for an ‘acceptable yield’. According to the test results, all the temperature indices of the piedmont plain area increased in the two selected future climate scenarios. In addition, the effective precipitation exhibited a slight decrease in scenario A2 and a remarkable increase in scenario B2. Both the total water footprint and green water footprint increased. A yield of 500 kg per mu was taken as the acceptable yield. In scenario A2, to achieve this acceptable yield, it was required to irrigate once in the jointing period with an irrigation rate of 105 mm. In scenario B2, one-time irrigation with an amount of 85 mm was sufficient to reach the acceptable yield.

Modeling climate change impacts on blue, green, and grey water footprints and crop yields in the Texas High Plains, USA

Simulating the impacts of future climate change on water footprints and crop production allows for selecting alternative crops for mitigating climate change effects. In this study, climate change impacts on irrigated grain corn, grain sorghum, winter wheat, and dryland (rainfed) winter wheat in the Palo Duro watershed of the Texas High Plains were assessed using an improved Soil and Water Assessment Tool (SWAT) model with an enhanced irrigation representation of management allowed depletion (MAD) irrigation scheduling. Climate change analyses in this study used the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections of 11 General Circulation Models (GCMs) under four Representative Concentration Pathway (RCP) emission scenarios of RCP2.6, 4.5, 6.0, and 8.5 during two 30-year periods of the middle (2040-2069) and end (2070-2099) of the 21st century to compare to a baseline period of 1970-1999. For the irrigated summer crops of corn and sorghum, all 11 GCMs predicted the reductions of future irrigation, crop evapotranspiration (ETc), and yields compared to the baseline period. According to an ensemble of 11 GCMs, the simulated reductions in average annual irrigation, ETc, and yield for the irrigated corn were 63%, 34%, and 13%, respectively, at the end of the 21st century under the severe emission scenario of RCP8.5. Those values were 80%, 34%, and 34% under the irrigated sorghum land use. As for the irrigated winter wheat, the decreases in future irrigation and ETc were also identified in all GCMs relative to the baseline period. However, irrigated wheat yields were increased in the future climate. The changes in dryland wheat ETc were consistent with the rainfall variation under all climate change scenarios. Generally, the future climate could benefit the dryland wheat yields. A large uncertainty was found for the surface runoff simulations under both irrigated and dryland wheat according to various GCMs.