Mean water footprint of national consumption per capita (1996-2005)

2017 ◽  
Author(s):  
Chloé Meyer
Keyword(s):  
Water Use ◽  
Industrial Production ◽  
Agricultural Production ◽  
Water Footprint ◽  
Domestic Water ◽  
The Mean ◽  
Per Capita ◽  
Annual Water ◽  
Table Data ◽  
National Consumption

This layer presents estimations of the mean annual water footprint of national consumption per capita for the period 1996-2005. The water footprint is a measure of human’s appropriation of freshwater resources; it has three components: green, blue and grey. Estimations are given in cubic meter per capita per year. In the table, data are also available disaggregated per sectors: agricultural production, industrial production and domestic water use. A detailed description of the methodology and results can be found in the main report available here: http://temp.waterfootprint.org/Reports/Report50-NationalWaterFootprints-Vol1.pdf . For more information, visit the Water Footprint Network website: http://temp.waterfootprint.org/?page=files/WaterStat Cost Use/Reuse

Mean annual blue water footprint of national consumption per capita (1996-2005)

2018 ◽  
Author(s):  
Najet Guefradj
Keyword(s):  
Water Use ◽  
Industrial Production ◽  
Agricultural Production ◽  
Water Footprint ◽  
Blue Water ◽  
Domestic Water ◽  
The Mean ◽  
Per Capita ◽  
Table Data ◽  
National Consumption

This layer represents estimation of the mean annual blue water footprint of national consumption for the period 1996-2005. The water footprint is a measure of human’s appropriation of freshwater resources. The blue water footprint refers to consumption of blue water resources (surface and ground water). Estimations are given in cubic meter per capita per year. In the table, data are also available disaggregated per sectors: agricultural production, industrial production and domestic water use. A detailed description of the methodology and results can be found in the main report available here: http://temp.waterfootprint.org/Reports/Report50-NationalWaterFootprints-Vol1.pdf . For more information, visit the Water Footprint Network website: http://temp.waterfootprint.org/?page=files/WaterStat Agriculture Supply Use/Reuse

Mean annual green water footprint of national consumption per capita (1996-2005)

2018 ◽  
Author(s):  
Najet Guefradj
Keyword(s):  
Industrial Production ◽  
Agricultural Production ◽  
Crop Production ◽  
Water Footprint ◽  
Green Water ◽  
Domestic Water ◽  
The Mean ◽  
Per Capita ◽  
Table Data ◽  
National Consumption

This layer represents estimation of the mean annual green water footprint of national consumption for the period 1996-2005. The water footprint is a measure of human’s appropriation of freshwater resources. The green water footprint is the volume of green water (rainwater) consumed, which is particularly relevant in crop production. Estimation are given in cubic meter per capita per year. In the table, data are also available disaggregated per sectors: agricultural production, industrial production and domestic water use. Methodology and results can be found in the main report: http://temp.waterfootprint.org/Reports/Report50-NationalWaterFootprints-Vol1.pdf . For more information, visit the Water Footprint Network website: http://temp.waterfootprint.org/?page=files/WaterStat Agriculture Supply Use/Reuse

scholarly journals The Water Footprint of Kathmandu Metropolitan City

2015 ◽  
Vol 28 ◽  
pp. 73-80
Author(s):  
Mohan Bikram Shrestha ◽  
Udhab Raj Khadka
Keyword(s):  
Water Use ◽  
Water Footprint ◽  
Industrial Water ◽  
Total Water ◽  
Domestic Water ◽  
Rapid Urbanization ◽  
Water Project ◽  
Metropolitan City ◽  
Industrial Water Use ◽  
Per Capita

The water footprint is consumption-based indicator of water use. Water footprint is defined as the total volume of both indirect and the direct freshwater used for producing goods and services consumed by individuals or inhabitants of community. There are many studies regarding the direct water use but studies incorporating both direct and indirect water use is deficient. This study tries to estimate total volume of water based on the consumption pattern of different commodities by individuals of Kathmandu Metropolitan city using extended water footprint calculator. The average water footprint of individuals appears to be 1145.52 m3/yr. The indirect and direct water footprint appears to be 1070.82 Mm3/yr and 46.59 Mm3/yr respectively which cumulatively give the total water footprint of Kathmandu Metropolitan City of 1117.40 Mm3/yr. This volume is equal to 2.27 times the annual flow the River Bagmati. The indirect water footprint includes food water footprint of 1055.60 Mm3/yr or 2.14 times the annual flow and industrial water use of 15.22 Mm3/yr or 0.03 times the annual flow while the direct water footprint includes domestic water use of 46.59 Mm3/yr or 0.09 times the annual flow. In food water footprint, cereals consumption shared the highest contribution of 34.82% followed by meat consumption with share of 32.62% in total water footprint. Per capita per day water use of inhabitants appears to be 3138 liters which includes water use in food items of 2965 liters, industrial water use of 43 liters and domestic water use of 131 liters. The per capita per day domestic water use is 90 liters more than supplement of 41 liters by the water operator of Kathmandu Valley. Per capita per day domestic water use is already 5 liters more than expected improvement in water supplement of 126 liters per capita per day in 2025 after accomplishment of Melamchi water project. And, it is expected to increase further observing the rapid urbanization of Kathmandu Metropolitan City. The study showed water footprint of individuals is directly related to food consumption behavior, life style and services used therefore it is necessary to initiate water offsetting measures at individual level and water operator to find environmentally sustainable alternatives along with ongoing water project to fulfill demand. J. Nat. Hist. Mus. Vol. 28, 2014: 73-80

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.

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 Analysis and Comprehensive Evaluation of Water Use Efficiency in China

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2620 ◽  
Author(s):  
Wenge Zhang ◽  
Xianzeng Du ◽  
Anqi Huang ◽  
Huijuan Yin
Keyword(s):  
Water Quality ◽  
Water Use Efficiency ◽  
Water Use ◽  
Water Consumption ◽  
Value Added ◽  
Domestic Water ◽  
Projection Direction ◽  
Domestic Water Consumption ◽  
Use Efficiency ◽  
Per Capita

Proper water use requires its monitoring and evaluation. An indexes system of overall water use efficiency is constructed here that covers water consumption per 10,000 yuan GDP, the coefficient of effective utilization of irrigation water, the water consumption per 10,000 yuan of industrial value added, domestic water consumption per capita of residents, and the proportion of water function zone in key rivers and lakes complying with water-quality standards and is applied to 31 provinces in China. Efficiency is first evaluated by a projection pursuit cluster model. Multidimensional efficiency data are transformed into a low-dimensional subspace, and the accelerating genetic algorithm then optimizes the projection direction, which determines the overall efficiency index. The index reveals great variety in regional water use, with Tianjin, Beijing, Hebei, and Shandong showing highest efficiency. Shanxi, Liaoning, Shanghai, Zhejiang, Henan, Shanxi, and Gansu also use water with high efficiency. Medium efficiency occurs in Inner Mongolia, Jilin, Heilongjiang, Jiangsu, Hainan, Qinghai, Ningxia, and Low efficiency is found for Anhui, Fujian, Jiangxi, Hubei, Hunan, Guangdong, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, and Xinjiang. Tibet is the least efficient. The optimal projection direction is a* = (0.3533, 0.7014, 0.4538, 0.3315, 0.1217), and the degree of influence of agricultural irrigation efficiency, water consumption per industrial profit, water used per gross domestic product (GDP), domestic water consumption per capita of residents, and environmental water quality on the result has decreased in turn. This may aid decision making to improve overall water use efficiency across China.

scholarly journals The Water Footprint of Diets: A Global Systematic Review and Meta-analysis

2019 ◽  
Author(s):  
Francesca Harris ◽  
Cami Moss ◽  
Edward J M Joy ◽  
Ruth Quinn ◽  
Pauline F D Scheelbeek ◽  
...  
Keyword(s):  
Water Use ◽  
Dietary Patterns ◽  
Water Footprint ◽  
Meta Analysis ◽  
Water Security ◽  
Population Level ◽  
Dietary Guidelines ◽  
Animal Origin ◽  
Agricultural Water ◽  
Per Capita

ABSTRACT Agricultural water requirements differ between foods. Population-level dietary preferences are therefore a major determinant of agricultural water use. The “water footprint” (WF) represents the volume of water consumed in the production of food items, separated by water source; blue WF represents ground and surface water use, and green WF represents rain water use. We systematically searched for published studies using the WF to assess the water use of diets. We used the available evidence to quantify the WF of diets in different countries, and grouped diets in patterns according to study definition. “Average” patterns equated to those currently consumed, whereas “healthy” patterns included those recommended in national dietary guidelines. We searched 7 online databases and identified 41 eligible studies that reported the dietary green WF, blue WF, or total WF (green plus blue) (1964 estimates for 176 countries). The available evidence suggests that, on average, European (170 estimates) and Oceanian (18 estimates) dietary patterns have the highest green WFs (median per capita: 2999 L/d and 2924 L/d, respectively), whereas Asian dietary patterns (98 estimates) have the highest blue WFs (median: 382 L/d per capita). Foods of animal origin are major contributors to the green WFs of diets, whereas cereals, fruits, nuts, and oils are major contributors to the blue WF of diets. “Healthy” dietary patterns (425 estimates) had green WFs that were 5.9% (95% CI: −7.7, −4.0) lower than those of “average” dietary patterns, but they did not differ in their blue WFs. Our review suggests that changes toward healthier diets could reduce total water use of agriculture, but would not affect blue water use. Rapid dietary change and increasing water security concerns underscore the need for a better understanding of the amount and type of water used in food production to make informed policy decisions.

Application of Gini, Theil and concentration indices for assessing water use inequality

2017 ◽  
Vol 44 (10) ◽  
pp. 1335-1347 ◽  
Author(s):  
Krishna Malakar ◽  
Trupti Mishra
Keyword(s):  
Water Use ◽  
National Income ◽  
Theil Index ◽  
Water Usage ◽  
Domestic Water ◽  
Content Type ◽  
Gini Coefficients ◽  
Management And Development ◽  
Per Capita ◽  
Concentration Indices

Purpose The purpose of this paper is to propose the application of Gini, Theil and concentration indices for measuring inequality in water usage. Design/methodology/approach Gini coefficients and Theil indices have been used to estimate the overall inequality in domestic water use in a sample of 30 countries around the world. Along with Theil’s L (unweighted) index, liters per capita per day and gross national income weighted Theil index have also been estimated. Theil indices have been further disintegrated into within- and between-group inequalities. Concentration curve is also constructed to study the inequality in water use in accordance to the countries’ economic standing. Findings Domestic water use is high among the well-off countries considered in the study. Also, the Theil indices indicate that between group inequality contributes more to the overall inequality. It is observed that Theil indices, which consider only per capita water usage and can be decomposed, give a better insight into the existing inequality. Practical implications Different approaches were used to quantify inequality. The choice of index depends on the context of the study. The proposed approaches can contribute to planning of sustainable water management and development policies. Originality/value There is a dearth of metrics for quantifying inequality in water access or use. The study presents the application of indices, widely used in quantifying inequality in access to other resources such as income and energy, in assessing water inequality.

scholarly journals A Survey of Household Water Use and Groundwater Quality Index Assessment in a Rural Community of Cambodia

2021 ◽  
Vol 13 (18) ◽  
pp. 10071
Author(s):  
Saret Bun ◽  
Sreymao Sek ◽  
Chantha Oeurng ◽  
Manabu Fujii ◽  
Phaly Ham ◽  
...  
Keyword(s):  
Groundwater Quality ◽  
Water Use ◽  
Rural Community ◽  
Water Consumption ◽  
Quality Index ◽  
Clean Water ◽  
Domestic Water ◽  
Household Water ◽  
Per Capita ◽  
Groundwater Wells

To propose an efficient system for addressing water scarcity in a rural area through groundwater use, the information on water consumption and interpretation of groundwater quality are essential for estimating the optimal preparation of the comprehensive water system. Hence, this study aimed to estimate the current household domestic water consumption and groundwater quality index of currently accessed wells in a small rural community of Preyveng province, Cambodia as a practical and beneficial as well as a model for the water resource sector in rural areas. The questionnaire survey was designed as the main instrument for collecting the household water use as face-to-face interviews. The result showed that the average daily water consumption in the Preal commune is about 71 L per capita, which is almost two times lower than the minimum water quantity recommended by the World Health Organization (WHO), 150 L/day per capita. Moreover, 100% of the households in this commune heavily rely on groundwater wells for domestic water use and more than 50% confirmed that they used raw groundwater as drinking water without a proposer treatment system. Approximately 70% of the people in Preal wishes to have a clean water supply and more than 80% of the household had a positive willingness to pay for clean water supply. In terms of groundwater quality in the Preal commune, it is mainly contaminated by iron, arsenic, fluoride, and manganese, which are mainly associated with human health effects from daily consumption. About 75% of groundwater wells are presented in poor conditions and were unsuitable for drinking purposes. Lastly, the suitable water treatment and supply should be considered in order to reduce the effects on people’s health as well as to improve living conditions.

scholarly journals Water footprints of cities – indicators for sustainable consumption and production

2014 ◽  
Vol 18 (1) ◽  
pp. 213-226 ◽  
Author(s):  
H. Hoff ◽  
P. Döll ◽  
M. Fader ◽  
D. Gerten ◽  
S. Hauser ◽  
...  
Keyword(s):  
Water Use ◽  
Water Footprint ◽  
Sustainable Consumption ◽  
Virtual Water ◽  
External Source ◽  
Trade Integration ◽  
Domestic Water ◽  
Export Production ◽  
Source Regions ◽  
Water Imports

Abstract. Water footprints have been proposed as sustainability indicators, relating the consumption of goods like food to the amount of water necessary for their production and the impacts of that water use in the source regions. We further developed the existing water footprint methodology, by globally resolving virtual water flows from production to consumption regions for major food crops at 5 arcmin spatial resolution. We distinguished domestic and international flows, and assessed local impacts of export production. Applying this method to three exemplary cities, Berlin, Delhi and Lagos, we find major differences in amounts, composition, and origin of green and blue virtual water imports, due to differences in diets, trade integration and crop water productivities in the source regions. While almost all of Delhi's and Lagos' virtual water imports are of domestic origin, Berlin on average imports from more than 4000 km distance, in particular soy (livestock feed), coffee and cocoa. While 42% of Delhi's virtual water imports are blue water based, the fractions for Berlin and Lagos are 2 and 0.5%, respectively, roughly equal to the water volumes abstracted in these two cities for domestic water use. Some of the external source regions of Berlin's virtual water imports appear to be critically water scarce and/or food insecure. However, for deriving recommendations on sustainable consumption and trade, further analysis of context-specific costs and benefits associated with export production will be required.

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