The difference of water footprint and availability as a physical metric for sustainable water use and management

Ecohydrology ◽  
2021 ◽  
Author(s):  
Mostafa Naderi ◽  
Samaneh Parsa
Keyword(s):  
Water Use ◽  
Water Footprint ◽  
Sustainable Water Use ◽  
The Difference

scholarly journals Water footprint

2019 ◽  
Vol 13 (2) ◽  
pp. 12-20
Author(s):  
Virág Nagypál ◽  
Edit Mikó ◽  
Imre Czupy ◽  
Cecilia Hodúr
Keyword(s):  
Fresh Water ◽  
Water Use ◽  
Efficient Solution ◽  
Water Footprint ◽  
Weather Conditions ◽  
Future Generations ◽  
Water Supplies ◽  
Meat Demand ◽  
Qualitative And Quantitative ◽  
Sustainable Water Use

Sustainability of water use has got into focus recently, as availability of fresh water resources is under depletion. Population growth, extreme weather conditions (drought), increasing global meat demand all results in higher water consumption of humanity and ecosystem. Water footprint is a promising indicator, which assesses both qualitative and quantitative deterioration of fresh water supplies. By identifying blue, green and grey water components, water use can be assessed in a more comprehensive way. Furthermore impact assessment of different components during production and processing let us identify crucial points of water use, where more efficient solution should be found. As a consequence of a more conscious and sustainable water use assessment considering water footprint, there is a chance, that future generations will inherit fresh water supplies at least in the same condition as we got it from our ancestors. 

Assessment of Water Footprint in Selected Crops: A State Level Appraisal

2017 ◽  
Vol 1 (1) ◽  
pp. 11-25
Author(s):  
Mohammad Suhail
Keyword(s):  
Water Use ◽  
Water Footprint ◽  
Large Fraction ◽  
State Level ◽  
Soil Survey ◽  
National Bureau ◽  
Blue Water ◽  
Total Water Consumption ◽  
Balanced Approach ◽  
Green Component

Every commodity or goods has intake of water i.e. either in processing or furnished stage. Thus, the present study propensities macro-level (states-level) water footprint (WFP) assessment of selected eight crops namely, Wheat, Barley, Maize, Millets, Rice, Sorghum, Soybeans and Tea. The aim of present research is to assess water use in selected crops at field level. In addition, the spatial evaluation at state level also considered as one of the significant objective to understand regional disparity and/or similarly. Methodology and approach of assessment was adopted from Water Footprint Assessment Manual (2011). Data was collected from state Agricultural Directorate, National Bureau of Soil Survey and landuse, published reports and online database such as FAOSTAT, WMO, WFN, and agriculture census. Results show that green component of WFP contributes large fraction as about 72 percent, while blue and grey component amounted of about 19 and 9 percent of the total water consumption, respectively. Moreover, spatial variability of blue, green and grey among the states assimilated by soil regime and climate barriers. Supply of blue water is high where the region imparted to semi-arid or arid land. Consequently, a balanced approach between green and blue water use has been recommended in the present study to address increasing water demand in the future.

scholarly journals The Water Footprint of Primary and Secondary Processing of Beef from Different Cattle Breeds: A Value Fraction Allocation Model

2021 ◽  
Vol 13 (12) ◽  
pp. 6914
Author(s):  
Frikkie Alberts Maré ◽  
Henry Jordaan
Keyword(s):  
Water Footprint ◽  
Negative Relationship ◽  
High Water ◽  
Allocation Model ◽  
Cattle Breeds ◽  
A Value ◽  
Average Production ◽  
High Water Intake ◽  
The Difference ◽  
By Products

The high water intake and wastewater discharge of slaughterhouses have been a concern for many years. One neglected factor in previous research is allocating the water footprint (WF) to beef production’s different products and by-products. The objective of this article was to estimate the WF of different cattle breeds at a slaughterhouse and cutting plant and allocate it according to the different cuts (products) and by-products of beef based on the value fraction of each. The results indicated a negative relationship between the carcass weight and the processing WF when the different breeds were compared. Regarding a specific cut of beef, a kilogram of rib eye from the heaviest breed had a processing WF of 614.57 L/kg, compared to the 919.91 L/kg for the rib eye of the lightest breed. A comparison of the different cuts indicated that high-value cuts had higher WFs than low-value cuts. The difference between a kilogram of rib eye and flank was 426.26 L/kg for the heaviest breed and 637.86 L/kg for the lightest breed. An option to reduce the processing WF of beef is to lessen the WF by slaughtering heavier animals. This will require no extra investment from the slaughterhouse. At the same time, the returns should increase as the average production inputs per kilogram of output (carcass) should reduce, as the slaughterhouse will process more kilograms.

scholarly journals Assessing local impacts of water use on human health: evaluation of water footprint models in the Province Punjab, Pakistan

2021 ◽  
Author(s):  
Natalia Mikosch ◽  
Markus Berger ◽  
Elena Huber ◽  
Matthias Finkbeiner
Keyword(s):  
Human Health ◽  
Water Use ◽  
Water Deprivation ◽  
Water Footprint ◽  
Local Scale ◽  
Water Supply Systems ◽  
Domestic Water ◽  
Income Loss ◽  
Human Health Damage ◽  
Health Damage

Abstract Purpose The water footprint (WF) method is widely applied to quantify water use along the life cycle of products and organizations and to evaluate the resulting impacts on human health. This study analyzes the cause-effect chains for the human health damage related to the water use on a local scale in the Province Punjab of Pakistan, evaluates their consistency with existing WF models, and provides recommendations for future model development. Method Locally occurring cause-effect chains are analyzed based on site observations in Punjab and a literature review. Then, existing WF models are compared to the findings in the study area including their comprehensiveness (covered cause-effect chains), relevance (contribution of the modeled cause-effect chain to the total health damage), and representativeness (correspondence with the local cause-effect chain). Finally, recommendations for the development of new characterization models describing the local cause-effect chains are provided. Results and discussion The cause-effect chains for the agricultural water deprivation include malnutrition due to reduced food availability and income loss as well as diseases resulting from the use of wastewater for irrigation, out of which only the first one is addressed by existing WF models. The cause-effect chain for the infectious diseases due to domestic water deprivation is associated primarily with the absence of water supply systems, while the linkage to the water consumption of a product system was not identified. The cause-effect chains related to the water pollution include the exposure via agricultural products, fish, and drinking water, all of which are reflected in existing impact assessment models. Including the groundwater compartment may increase the relevance of the model for the study area. Conclusions Most cause-effect chains identified on the local scale are consistent with existing WF models. Modeling currently missing cause-effect chains for the impacts related to the income loss and wastewater usage for irrigation can enhance the assessment of the human health damage in water footprinting.

The Decomposition Analysis of Tourism Water Footprint in Taiwan: Revealing Decision-Relevant Information

2018 ◽  
Vol 58 (4) ◽  
pp. 695-708 ◽  
Author(s):  
Ya-Yen Sun ◽  
Ching-Mai Hsu
Keyword(s):  
Water Use ◽  
Water Consumption ◽  
Water Footprint ◽  
Decomposition Analysis ◽  
Economic Structure ◽  
Relevant Information ◽  
Structural Decomposition Analysis ◽  
Total Consumption ◽  
Economic Output ◽  
Input Structure

Tourism water consumption reflects the dynamics between the visitation volume, economic structure, and water use technology of a destination. This paper presents a structural decomposition analysis that attributes changes of Taiwan’s tourism water footprint into the demand factors of total consumption and purchasing patterns, and production factors of the industry input structure and water use technology. From 2006 to 2011, Taiwan experienced a 48% growth in visitor expenditures and a 74% surge in its water footprint. Diseconomies of scale were observed, with a 1% increase in consumption leading to a 1.5% increase in the tourism water footprint. A strong preference by visitors for water-intensive goods and services and a changing economic structure requiring more water input for tourism establishments and supply chain members contributed to this worrisome pattern. The water requirements received only a minimal offset effect with technological improvements. Decoupling tourism water consumption from economic output is currently unattainable.

scholarly journals A spatially detailed blue water footprint of the United States economy

2018 ◽  
Vol 22 (5) ◽  
pp. 3007-3032 ◽  
Author(s):  
Richard R. Rushforth ◽  
Benjamin L. Ruddell
Keyword(s):  
United States ◽  
Water Use ◽  
Water Footprint ◽  
Virtual Water ◽  
The United States ◽  
Energy Information Administration ◽  
Blue Water ◽  
Consumptive Use ◽  
The Us ◽  
Per Capita

Abstract. This paper quantifies and maps a spatially detailed and economically complete blue water footprint for the United States, utilizing the National Water Economy Database version 1.1 (NWED). NWED utilizes multiple mesoscale (county-level) federal data resources from the United States Geological Survey (USGS), the United States Department of Agriculture (USDA), the US Energy Information Administration (EIA), the US Department of Transportation (USDOT), the US Department of Energy (USDOE), and the US Bureau of Labor Statistics (BLS) to quantify water use, economic trade, and commodity flows to construct this water footprint. Results corroborate previous studies in both the magnitude of the US water footprint (F) and in the observed pattern of virtual water flows. Four virtual water accounting scenarios were developed with minimum (Min), median (Med), and maximum (Max) consumptive use scenarios and a withdrawal-based scenario. The median water footprint (FCUMed) of the US is 181 966 Mm3 (FWithdrawal: 400 844 Mm3; FCUMax: 222 144 Mm3; FCUMin: 61 117 Mm3) and the median per capita water footprint (FCUMed′) of the US is 589 m3 per capita (FWithdrawal′: 1298 m3 per capita; FCUMax′: 720 m3 per capita; FCUMin′: 198 m3 per capita). The US hydroeconomic network is centered on cities. Approximately 58 % of US water consumption is for direct and indirect use by cities. Further, the water footprint of agriculture and livestock is 93 % of the total US blue water footprint, and is dominated by irrigated agriculture in the western US. The water footprint of the industrial, domestic, and power economic sectors is centered on population centers, while the water footprint of the mining sector is highly dependent on the location of mineral resources. Owing to uncertainty in consumptive use coefficients alone, the mesoscale blue water footprint uncertainty ranges from 63 to over 99 % depending on location. Harmonized region-specific, economic-sector-specific consumption coefficients are necessary to reduce water footprint uncertainties and to better understand the human economy's water use impact on the hydrosphere.

scholarly journals Burning Water, Overview of the Contribution of Arjen Hoekstra to the Water Energy Nexus

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2844
Author(s):  
Winnie Gerbens-Leenes ◽  
Santiago Vaca-Jiménez ◽  
Mesfin Mekonnen
Keyword(s):  
Energy Source ◽  
Water Use ◽  
Information Needs ◽  
Fossil Fuels ◽  
Water Footprint ◽  
Open Water ◽  
Oil Crops ◽  
Energy Relationships ◽  
Large Water ◽  
New Research

This paper gives an overview of the contribution of water footprint (WF) studies on water for energy relationships. It first explains why water is needed for energy, gives an overview of important water energy studies until 2009, shows the contribution of Hoekstra’s work on WF of energy generation, and indicates how this contribution has supported new research. Finally, it provides knowledge gaps that are relevant for future studies. Energy source categories are: 1. biofuels from sugar, starch and oil crops; 2. cellulosic feedstocks; 3. biofuels from algae; 4. firewood; 5. hydropower and 6. various sources of energy including electricity, heat and transport fuels. Especially category 1, 3, 4, 5 and to a lesser extent 2 have relatively large WFs. This is because the energy source derives from agriculture or forestry, which has a large water use (1,2,4), or has large water use due to evaporation from open water surfaces (3,5). WFs for these categories can be calculated using the WF tool. Category 6 includes fossil fuels and renewables, such as photovoltaics and wind energy and has relatively small WFs. However, information needs to be derived from industry.

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