Under the influence of climate change and human activities, water scarcity and uneven spatial distribution have become critical factors constraining societal development and threatening ecological ...security. Accurately assessing changes in blue and green water resources (BW and GW) caused by human activities can reveal the actual situation of water scarcity. However, previous research often overlooked the calibration of GW and human water usage, and it rarely delved into the primary human factors leading to water scarcity and potential impact mechanisms. Therefore, based on the PCR-GLOBWB model that considers human impacts, and with reasonable calibration of B/GW and human water usage, hydrological processes were simulated under both human-influenced and natural conditions. A comprehensive assessment of the impact of human activities on BW and GW was conducted. The results show that: (1) BW and GW exhibit a spatial pattern of increasing from northwest to southeast in the basin. From 1961 to 2020, the proportion of BW showed an upward trend, while GW was decreasing; (2) The impact of human activities on changes in water resources is mainly concentrated in the midstream and dowmstream of the basin. Due to human influences, the green water flow (GWF) increased by 3–24.4 mm, and the BW volume increased by 67.2–146.4 mm. However, the green water storage (GWS) decreased by 5.6–75.4 mm; (3) The impact of human activities on blue water scarcity (BWscarcity) is significantly greater than green water scarcity (GWscarcity). The worsening of GWscarcity does not exceed 0.2, while areas where BW reaches significant deterioration (BWscarcity > 1.5) account for 1.3 %, 9.8 %, and 17 % of the upstream, midstream and downstream, respectively. (4) Irrigation activities are the main factor causing water resource scarcity. In the future, it is important to reasonably develop the potential for GW utilization and optimize BW management measures to address water resource crises.
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•Analyzed human impact on blue-green water resource evolution & scarcity.•Human activities affect water resources with notable spatiotemporal variability.•Even in water- rich basin, human activities can lead to water scarcity.•Yangtze River Basin's water scarcity is mainly related to irrigation activities.
The development of methods to assess the potential environmental impact of green water consumption in life cycle assessment has lagged behind those for blue water use, which are now routinely applied ...in industrial and policy-related studies. This represents a critical gap in the assessment of land-based production systems and the ability to inform policy related to the bio-economy. Combining satellite remote sensing and meteorological data sets, this study develops two new sets of spatially-differentiated and globally applicable characterisation factors (CFs) to assess the environmental impact of green water flows in LCA.
One set of CFs addresses the impact of shifts in water vapour flow by evapotranspiration on blue water availability (CFWS) and the other set of CFs addresses moisture recycling within a basin (CFWA). Furthermore, as an additional and optional step, these two indicators are combined into an aggregated green water scarcity indicator, representing the global variability of green water scarcity. The values obtained for CFWA show that there are significant changes in green water flows that were returned to the atmosphere in Alaska (covered by open shrublands) and in some central regions of China (covered by grasslands and barren or sparsely vegetated land), where precipitation levels are lower than 10 mm/yr. The results obtained for CFWS indicate that severe perturbations in surface blue water production occur, particularly in central regions of China (covered by grasslands), the southeast of Australia (covered by evergreen broadleaf forest) and in some central regions of the USA (covered by grassland and evergreen needleleaf forest).
The application of the green water scarcity CFs enables the evaluation of the potential environmental impact due to green water consumption by agricultural and forestry products, informing both technical and non-technical audiences and decision-makers for the purpose of strategic planning of land use and to identify green water protection measures.
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•Development of global spatially differentiated green water scarcity CFs for LCA.•Potential impact of ET on blue water production and green water recycled into the basin.•CFWS and CFWA show high variability mostly in the northern hemisphere.•Uncertainty of CFWS and CFWA is high due to changes on green water availability to ET purposes.
An accurate estimate of global water uses with high spatial resolution is a key to assessing global water scarcity and to understanding human’s interference with the ecosystems. In spite of the ...progress made previously, there is a lack of spatially explicit assessment of both green and blue water uses in agriculture. In this paper, we estimated consumptive water use (CWU) in cropland on a global scale with a spatial resolution of 30
arc-minutes. A GIS-based version of the EPIC model, GEPIC, is used for the estimation. The results show that in crop growing periods, global CWU was 5938
km
3
a
−1 in cropland around the year 2000, of which green water contributed to 84%. On an annual basis, global CWU was 7323
km
3
a
−1 in cropland, of which green water contributed to 87%. We compared the simulated consumptive blue water use (CBWU) with the statistical CBWU at the national level among individual countries, and at the federal state or province level in the USA and China. The comparison indicates a good agreement between the simulated and statistical CBWU, suggesting a satisfactory performance of the GEPIC model and reliability of the estimation in irrigated cropland. The importance of green water in both crop production and food trade calls for a better management of green water, in addition to blue water.
The agricultural activities contribute to the largest share of water consumption in the arid and semi-arid basins. In this study, we demonstrate the application of Water Accounting Plus (WA+) for ...estimation of the green water consumption (ETGreen) and blue water consumption (ETBlue) for assessing the water productivity (WP) and land productivity (LP) to identify the bright-spots and hot-spots at the district administrative unit level for effectively managing the scarce water resources and sustaining food security in a highly non-resilient semi-arid basin of India. The WA+ framework uses satellite remote sensing datasets from different sources for this purpose and we used the data from 2003 to 2020. The long-term average of ETGreen and ETBlue in the Mahi basin is found to be 15.8 km3/year and 12.32 km3/year, respectively. The blue water index (BWI) and green water index (GWI) in the basin vary from 0.282 to 0.598 and 0.40–0.72. We found that the BWI is highest for the districts of Gujarat, whereas, the GWI is highest for the districts of Madhya Pradesh. The long-term average of the LP and WP for both the irrigated and rainfed cereals in the basin is found as 2287.71 kg/ha & 1713.62 kg/ha and 0.721 kg/m³ & 0.483 kg/m³ , respectively from 2003 to 2020. The WP (rainfed) of all the districts of the Gujarat is comparatively lower (varying from 0.34 kg/m³ to 0.5 kg/m³) than the districts of the Madhya Pradesh (varying from 0.59 kg/m3 to 0.70 kg/m³ ) and the Rajasthan (varying from 0.48 kg/m³ to 0.73 kg/m³ ). Based on the results, we found that the Ratlam district of the Madhya Pradesh has both highest LP and WP (irrigated) as 2573.96 kg/ha and 2.14 kg/m3, respectively among all the districts of the Mahi basin, and hence it is classified as the ‘Bright spot-district’. The Anand district is found to have the lowest WP and LP as 0.44 kg/m3 and 2467.51 kg/ha, respectively and hence it is classified as the ‘hot spot-district’. For rainfed cereals, we found that the Neemuch district of Madhya Pradesh has the highest WP and LP as 0.59 kg/m3 and 1948.13 kg /ha, respectively, and the Anand district with the lowest WP as 0.34 kg/m3 and LP of 1572.21 kg/ha, respectively. Therefore, we classified the Neemach district as the ‘Bright spot-district’ and the Anand district as the hot spot- district for rainfed cereals. These findings will help develop sustainable and actionable agricultural water management plans by the policymakers and stakeholders in the basin.
▪ET partitioning as per LULC classes and interactions.▪ETGreen and ETBlue quantification for irrigation water management.▪Spatio-temporal variability of WP and LP for irrigated and rainfed agriculture.▪Hot and bright spots for agricultural water management and food security.
We assessed the basin-scale crop water productivity (CWP) on staple grain crops, i.e. rice, wheat, maize, soybean, at major breadbasket basins of China over time periods of 1997–2004. The ...multiple-year average CWP was 1.06
kg
m
−3 for the selected basins (equivalents of 946
m
3 water consumption in producing 1 metric ton of crop economic yield), varying from 0.97
kg
m
−3 to 1.18
kg
m
−3. Of all the water consumed in crop production, irrigation water contributes 28–41%, while soil-stored precipitation contributes 59–72%, confirming the crucial yet hitherto under-estimated role played by green water in total crop yield formation. The blue water depletion rate ranges from 0.48 to 0.87, with most of the basins exceeding 0.50, while the green water depletion rate from 0.39 to 0.85, with the majority of basins being beyond 0.60. We conclude that both blue and green water shortage will contribute to water scarcity in grain crop production. The mission of ensuring China's food security will entail multiple trade-offs among water security, ecosystem conservation, environment protection, and human development with increasing challenges in the years to come. However, increasing water productivity through research innovation and technological upgrades at river basin scale is a key to mitigating water stress that may be caused by increasing food production in the coming decades.
•An integrated modeling framework is developed to better understand water scarcity using blue and green water concept.•Future land use transformation is projected using an Agent-based probabilistic ...model (ABPM)•Hydrology in the watershed is estimated using Soil and Water Assessment Tool (SWAT)•Future population projection is estimated based on zoning and projected land use.•Geospatial framework is developed to identify potential hotspots in the watershed.
Water security assessment based on the concept of blue versus green water is becoming widely accepted globally. Blue water is the combination of surface runoff and deep aquifer recharge while green water is the summation of evapotranspiration and soil water content (i.e. mediated by plants). Due to the tight coupling between land use and the partitioning of blue and green water within a watershed, an integrated geospatial modeling framework that links land use and watershed hydrological processes is needed to predict the consequences of future land use change on blue versus green water security. By loosely coupling an agent based probabilistic land use change model with a hydrologic model, we investigated the consequences of present trends of urban growth to identify potential future hotspots of hydrological change across a watershed in central New Jersey undergoing suburbanization. The agent based probabilistic model, working at the scale of land ownership parcels, predicted that future urban development would be the result of forest, rather than farm land conversion. Using existing zoning maps, the housing unit density and human population of the urban growth areas was estimated. A consequence of the loss of forest land and increasing impervious surface leading was higher blue water but lower green water. While no severe blue water scarcity was observed, an increasing green water scarcity was found in some study area sub-basins. Such information will aid watershed managers’ and policymakers’ effort in sustainably managing water resources under changing land use and climate.
The wave-piercing tumblehome (WPTH) vessel has special geometric characteristics, its hull is inclined to suffer significant green water and corresponding hydrodynamic loads. The motions of a WPTH ...vessel in heading waves are simulated using commercial computational fluid dynamics (CFD) software. It is found that the typical green water process consists three stages: water collision above the bulbous, green water convergence, and green water jet flow impact. In stage 1, collision of two streams above the bulbous bow causes a high pressure area like a butterfly. The convergence of green water induces high pressure in stage 2, and the green water jet flow in stage 3 results high impact pressure on the superstructure. The vertical bending moments are calculated by introducing a field function. The green water and bow slamming have less effects on the vertical bending moment but cause considerable local hydrodynamic loads.
•Typical green water of the wave-piercing tumblehome vessel consists three stages.•Collision of streams over the bulbous results a butterfly-shaped pressure zone.•Green water from broadsides converges and high pressure is induced on the deck.•An accelerated water jet impacts on the superstructure and causes high pressure.
The paper makes a global assessment of the green, blue and grey water footprint of rice, using a higher spatial resolution and local data on actual irrigation. The national water footprint of rice ...production and consumption is estimated using international trade and domestic production data. The global water footprint of rice production is 784
km
3/year with an average of 1325
m
3/t which is 48% green, 44% blue, and 8% grey. There is also 1025
m
3/t of percolation in rice production. The ratio of green to blue water varies greatly over time and space. In India, Indonesia, Vietnam, Thailand, Myanmar and the Philippines, the green water fraction is substantially larger than the blue one, whereas in the USA and Pakistan the blue water footprint is 4 times more than the green component. The virtual water flows related to international rice trade was 31
km
3/year. The consumption of rice products in the EU27 is responsible for the annual evaporation of 2279
Mm
3 of water and polluted return flows of 178
Mm
3 around the globe, mainly in India, Thailand, the USA and Pakistan. The water footprint of rice consumption creates relatively low stress on the water resources in India compared to that in the USA and Pakistan.
► It is a global assessment of the green, blue and grey water footprint of rice. ► The global water footprint of rice is 784
km
3/year with an average of 1325
m
3/t. ► There is an average additional 1025
m
3/t of percolation in rice production. ►The shares of green, blue and grey water footprint are 48%, 44% and 8%. ► The virtual water flows related to international rice trade is 31
km
3/year.
•AWSI based on blue-green water and water footprint (WF) framework is established.•Blue water dominates in water resources while blue WF accounts for 12.7% of the total.•Water scarcity was aggravated ...from 1999 to 2014 in agricultural production of China.•The AWSI is suitable for water scarcity evaluations, particularly in arid area.
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An indicator, agricultural water stress index (AWSI), was established based blue-green water resources and water footprint framework for regional water scarcity in agricultural production industry evaluation. AWSI is defined as the ratio of the total agricultural water footprint (AWF) to water resources availability (AWR) in a single year. Then, the temporal and spatial patterns of AWSI in China during 1999–2014 were analyzed based on the provincial AWR and AWF quantification. The results show that the annual AWR in China has been maintained at approximately 2540Gm3, of which blue water accounted for >70%. The national annual AWF was approximately 1040Gm3 during the study period and comprised 65.6% green, 12.7% blue and 21.7% grey WFs The space difference in both the AWF for per unit arable land (AWFI) and its composition was significant. National AWSI was calculated as 0.413 and showed an increasing trend in the observed period. This index increased from 0.320 (mid-water stress level) in 2000 to 0.490 (high water stress level) in the present due to the expansion of the agricultural production scale. The Northern provinces, autonomous regions and municipalities (PAMs) have been facing high water stress, particularly the Huang-Huai-Hai Plain, which was at a very high water stress level (AWSI>0.800). Humid South China faces increasingly severe water scarcity, and most of the PAMs in the region have converted from low water stress level (AWSI=0.100–0.200) to mid water stress level (AWSI=0.200–0.400). The AWSI is more appropriate for reflecting the regional water scarcity than the existing water stress index (WSI) or the blue water scarcity (BWS) indicator, particularly for the arid agricultural production regions due to the revealed environmental impacts of agricultural production. China should guarantee the sustainable use of agricultural water resources by reducing its crop water footprint.
